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Jeanson F, Gibson SJ, Alper P, Bernier A, Woolley JP, Mietchen D, Strug A, Becker R, Kamerling P, Sanchez Gonzalez MDC, Mah N, Novakowski A, Wilkinson MD, Benhamed OM, Landi A, Krog GP, Müller H, Riaz U, Veal C, Holub P, van Enckevort E, Brookes AJ. Getting your DUCs in a row - standardising the representation of Digital Use Conditions. Sci Data 2024; 11:464. [PMID: 38719839 PMCID: PMC11078994 DOI: 10.1038/s41597-024-03280-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 04/18/2024] [Indexed: 05/12/2024] Open
Abstract
Improving patient care and advancing scientific discovery requires responsible sharing of research data, healthcare records, biosamples, and biomedical resources that must also respect applicable use conditions. Defining a standard to structure and manage these use conditions is a complex and challenging task. This is exemplified by a near unlimited range of asset types, a high variability of applicable conditions, and differing applications at the individual or collective level. Furthermore, the specifics and granularity required are likely to vary depending on the ultimate contexts of use. All these factors confound alignment of institutional missions, funding objectives, regulatory and technical requirements to facilitate effective sharing. The presented work highlights the complexity and diversity of the problem, reviews the current state of the art, and emphasises the need for a flexible and adaptable approach. We propose Digital Use Conditions (DUC) as a framework that addresses these needs by leveraging existing standards, striking a balance between expressiveness versus ambiguity, and considering the breadth of applicable information with their context of use.
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Grants
- 825575 EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Societal Challenges | H2020 Health (H2020 Societal Challenges - Health, Demographic Change and Well-being)
- 825575 EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Societal Challenges | H2020 Health (H2020 Societal Challenges - Health, Demographic Change and Well-being)
- 825575 EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Societal Challenges | H2020 Health (H2020 Societal Challenges - Health, Demographic Change and Well-being)
- 825575 EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Societal Challenges | H2020 Health (H2020 Societal Challenges - Health, Demographic Change and Well-being)
- 825575 EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Societal Challenges | H2020 Health (H2020 Societal Challenges - Health, Demographic Change and Well-being)
- 825575 EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Societal Challenges | H2020 Health (H2020 Societal Challenges - Health, Demographic Change and Well-being)
- 825575 EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Societal Challenges | H2020 Health (H2020 Societal Challenges - Health, Demographic Change and Well-being)
- 825575 EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Societal Challenges | H2020 Health (H2020 Societal Challenges - Health, Demographic Change and Well-being)
- 825575 EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Societal Challenges | H2020 Health (H2020 Societal Challenges - Health, Demographic Change and Well-being)
- 825575 EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Societal Challenges | H2020 Health (H2020 Societal Challenges - Health, Demographic Change and Well-being)
- 825575 EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Societal Challenges | H2020 Health (H2020 Societal Challenges - Health, Demographic Change and Well-being)
- 825575 EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Societal Challenges | H2020 Health (H2020 Societal Challenges - Health, Demographic Change and Well-being)
- 825575 EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Societal Challenges | H2020 Health (H2020 Societal Challenges - Health, Demographic Change and Well-being)
- Algerian Ministry of Higher Education and Scientific Research
- The European Reference Network on Rare Multisystemic Vascular Diseases (VASCERN), which is partly co-funded by the European Union within the framework of the EU4Health programme – “VASCERN Action Grant".
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Affiliation(s)
- Francis Jeanson
- Centre for Analytics, Ontario Brain Institute, Toronto, Canada.
| | - Spencer J Gibson
- Genetics and Genome Biology, University of Leicester, Leicester, UK
| | - Pinar Alper
- Luxembourg National Data Service, Esch-sur-Alzette, Luxembourg
| | - Alexander Bernier
- Faculty of Medicine and Health Sciences, McGill University, Montreal, Canada
| | - J Patrick Woolley
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | | | - Andrzej Strug
- Medical Laboratory Diagnostics Department, Medical University of Gdańsk, Gdańsk, Poland
| | - Regina Becker
- University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Pim Kamerling
- Center for Radiology and Nuclear Medicine, VASCERN ERN /Radboud University Medical Center, Nijmegen, Netherlands
| | | | - Nancy Mah
- Biomedical Data & Bioethics Group, Fraunhofer Institute for Biomedical Engineering, Sulzbach/Saar, Germany
| | | | - Mark D Wilkinson
- Departamento de Biotecnología-Biología Vegetal, ETSI Agronómica, Alimentaria y de Biosistemas, Centro de Biotecnología y Genómica de Plantas (CBGP, UPM-INIA/CSIC), Universidad Politécnica de Madrid, Madrid, Spain
| | - Oussama Mohammed Benhamed
- Departamento de Biotecnología-Biología Vegetal, ETSI Agronómica, Alimentaria y de Biosistemas, Centro de Biotecnología y Genómica de Plantas (CBGP, UPM-INIA/CSIC), Universidad Politécnica de Madrid, Madrid, Spain
| | - Annalisa Landi
- Research, Fondazione per la Ricerca Farmacologica Gianni Benzi Onlus, Bari, Italy
| | | | | | - Umar Riaz
- Genetics and Genome Biology, University of Leicester, Leicester, UK
| | - Colin Veal
- Genetics and Genome Biology, University of Leicester, Leicester, UK
| | - Petr Holub
- BBMRI-ERIC, Graz, Austria
- Institute of Computer Science, Masaryk University, Brno, Czechia
| | - Esther van Enckevort
- University of Groningen, Groningen, Netherlands
- Department of Genetics, University Medical Center Groningen, Groningen, Netherlands
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2
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Samuel S, Mietchen D. Computational reproducibility of Jupyter notebooks from biomedical publications. Gigascience 2024; 13:giad113. [PMID: 38206590 PMCID: PMC10783158 DOI: 10.1093/gigascience/giad113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 08/09/2023] [Accepted: 12/08/2023] [Indexed: 01/12/2024] Open
Abstract
BACKGROUND Jupyter notebooks facilitate the bundling of executable code with its documentation and output in one interactive environment, and they represent a popular mechanism to document and share computational workflows, including for research publications. The reproducibility of computational aspects of research is a key component of scientific reproducibility but has not yet been assessed at scale for Jupyter notebooks associated with biomedical publications. APPROACH We address computational reproducibility at 2 levels: (i) using fully automated workflows, we analyzed the computational reproducibility of Jupyter notebooks associated with publications indexed in the biomedical literature repository PubMed Central. We identified such notebooks by mining the article's full text, trying to locate them on GitHub, and attempting to rerun them in an environment as close to the original as possible. We documented reproduction success and exceptions and explored relationships between notebook reproducibility and variables related to the notebooks or publications. (ii) This study represents a reproducibility attempt in and of itself, using essentially the same methodology twice on PubMed Central over the course of 2 years, during which the corpus of Jupyter notebooks from articles indexed in PubMed Central has grown in a highly dynamic fashion. RESULTS Out of 27,271 Jupyter notebooks from 2,660 GitHub repositories associated with 3,467 publications, 22,578 notebooks were written in Python, including 15,817 that had their dependencies declared in standard requirement files and that we attempted to rerun automatically. For 10,388 of these, all declared dependencies could be installed successfully, and we reran them to assess reproducibility. Of these, 1,203 notebooks ran through without any errors, including 879 that produced results identical to those reported in the original notebook and 324 for which our results differed from the originally reported ones. Running the other notebooks resulted in exceptions. CONCLUSIONS We zoom in on common problems and practices, highlight trends, and discuss potential improvements to Jupyter-related workflows associated with biomedical publications.
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Affiliation(s)
- Sheeba Samuel
- Heinz-Nixdorf Chair for Distributed Information Systems, Friedrich Schiller University Jena, Jena 07743, Germany
- Michael Stifel Center Jena, Jena 07743, Germany
| | - Daniel Mietchen
- Ronin Institute, Montclair 07043-2314, NJ, United States
- Institute for Globally Distributed Open Research and Education (IGDORE)
- FIZ Karlsruhe—Leibniz Institute for Information Infrastructure, Berlin 76344, Germany
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3
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Lokatis S, Jeschke JM, Bernard-Verdier M, Buchholz S, Grossart HP, Havemann F, Hölker F, Itescu Y, Kowarik I, Kramer-Schadt S, Mietchen D, Musseau CL, Planillo A, Schittko C, Straka TM, Heger T. Hypotheses in urban ecology: building a common knowledge base. Biol Rev Camb Philos Soc 2023; 98:1530-1547. [PMID: 37072921 DOI: 10.1111/brv.12964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 03/31/2023] [Accepted: 04/04/2023] [Indexed: 04/20/2023]
Abstract
Urban ecology is a rapidly growing research field that has to keep pace with the pressing need to tackle the sustainability crisis. As an inherently multi-disciplinary field with close ties to practitioners and administrators, research synthesis and knowledge transfer between those different stakeholders is crucial. Knowledge maps can enhance knowledge transfer and provide orientation to researchers as well as practitioners. A promising option for developing such knowledge maps is to create hypothesis networks, which structure existing hypotheses and aggregate them according to topics and research aims. Combining expert knowledge with information from the literature, we here identify 62 research hypotheses used in urban ecology and link them in such a network. Our network clusters hypotheses into four distinct themes: (i) Urban species traits & evolution, (ii) Urban biotic communities, (iii) Urban habitats and (iv) Urban ecosystems. We discuss the potentials and limitations of this approach. All information is openly provided as part of an extendable Wikidata project, and we invite researchers, practitioners and others interested in urban ecology to contribute additional hypotheses, as well as comment and add to the existing ones. The hypothesis network and Wikidata project form a first step towards a knowledge base for urban ecology, which can be expanded and curated to benefit both practitioners and researchers.
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Affiliation(s)
- Sophie Lokatis
- Institute of Biology, Freie Universität Berlin, Königin-Luise-Str. 1-3, Berlin, 14195, Germany
- Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB), Müggelseedamm 310, Berlin, 12587, Germany
- Berlin-Brandenburg Institute of Advanced Biodiversity Research, Königin-Luise-Str. 2-4, Berlin, 14195, Germany
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Puschstr. 4, Leipzig, 04103, Germany
| | - Jonathan M Jeschke
- Institute of Biology, Freie Universität Berlin, Königin-Luise-Str. 1-3, Berlin, 14195, Germany
- Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB), Müggelseedamm 310, Berlin, 12587, Germany
- Berlin-Brandenburg Institute of Advanced Biodiversity Research, Königin-Luise-Str. 2-4, Berlin, 14195, Germany
| | - Maud Bernard-Verdier
- Institute of Biology, Freie Universität Berlin, Königin-Luise-Str. 1-3, Berlin, 14195, Germany
- Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB), Müggelseedamm 310, Berlin, 12587, Germany
- Berlin-Brandenburg Institute of Advanced Biodiversity Research, Königin-Luise-Str. 2-4, Berlin, 14195, Germany
| | - Sascha Buchholz
- Institute of Landscape Ecology, University of Münster, Heisenbergstr. 2, Münster, 48149, Germany
| | - Hans-Peter Grossart
- Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB), Müggelseedamm 310, Berlin, 12587, Germany
- Institute of Biochemistry and Biology, Potsdam University, Maulbeerallee 2, Potsdam, 14469, Germany
| | - Frank Havemann
- Institut für Bibliotheks- und Informationswissenschaft, Humboldt-Universität zu Berlin, Dorotheenstraße 26, Berlin, 10117, Germany
| | - Franz Hölker
- Institute of Biology, Freie Universität Berlin, Königin-Luise-Str. 1-3, Berlin, 14195, Germany
- Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB), Müggelseedamm 310, Berlin, 12587, Germany
- Berlin-Brandenburg Institute of Advanced Biodiversity Research, Königin-Luise-Str. 2-4, Berlin, 14195, Germany
| | - Yuval Itescu
- Institute of Biology, Freie Universität Berlin, Königin-Luise-Str. 1-3, Berlin, 14195, Germany
- Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB), Müggelseedamm 310, Berlin, 12587, Germany
- Berlin-Brandenburg Institute of Advanced Biodiversity Research, Königin-Luise-Str. 2-4, Berlin, 14195, Germany
| | - Ingo Kowarik
- Berlin-Brandenburg Institute of Advanced Biodiversity Research, Königin-Luise-Str. 2-4, Berlin, 14195, Germany
- Institute of Ecology, Technische Universität Berlin, Rothenburgstr. 12, Berlin, 12165, Germany
| | - Stephanie Kramer-Schadt
- Berlin-Brandenburg Institute of Advanced Biodiversity Research, Königin-Luise-Str. 2-4, Berlin, 14195, Germany
- Institute of Ecology, Technische Universität Berlin, Rothenburgstr. 12, Berlin, 12165, Germany
- Leibniz Institute for Zoo and Wildlife Research (IZW), Alfred-Kowalke-Str. 17, Berlin, 10315, Germany
| | - Daniel Mietchen
- Institute of Biology, Freie Universität Berlin, Königin-Luise-Str. 1-3, Berlin, 14195, Germany
- Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB), Müggelseedamm 310, Berlin, 12587, Germany
- Berlin-Brandenburg Institute of Advanced Biodiversity Research, Königin-Luise-Str. 2-4, Berlin, 14195, Germany
- Institute for Globally Distributed Open Research and Education (IGDORE), Gothenburg, Sweden
| | - Camille L Musseau
- Institute of Biology, Freie Universität Berlin, Königin-Luise-Str. 1-3, Berlin, 14195, Germany
- Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB), Müggelseedamm 310, Berlin, 12587, Germany
- Berlin-Brandenburg Institute of Advanced Biodiversity Research, Königin-Luise-Str. 2-4, Berlin, 14195, Germany
| | - Aimara Planillo
- Berlin-Brandenburg Institute of Advanced Biodiversity Research, Königin-Luise-Str. 2-4, Berlin, 14195, Germany
- Leibniz Institute for Zoo and Wildlife Research (IZW), Alfred-Kowalke-Str. 17, Berlin, 10315, Germany
| | - Conrad Schittko
- Berlin-Brandenburg Institute of Advanced Biodiversity Research, Königin-Luise-Str. 2-4, Berlin, 14195, Germany
- Institute of Ecology, Technische Universität Berlin, Rothenburgstr. 12, Berlin, 12165, Germany
| | - Tanja M Straka
- Berlin-Brandenburg Institute of Advanced Biodiversity Research, Königin-Luise-Str. 2-4, Berlin, 14195, Germany
- Institute of Ecology, Technische Universität Berlin, Rothenburgstr. 12, Berlin, 12165, Germany
| | - Tina Heger
- Institute of Biology, Freie Universität Berlin, Königin-Luise-Str. 1-3, Berlin, 14195, Germany
- Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB), Müggelseedamm 310, Berlin, 12587, Germany
- Berlin-Brandenburg Institute of Advanced Biodiversity Research, Königin-Luise-Str. 2-4, Berlin, 14195, Germany
- Technical University of Munich, Restoration Ecology, Emil-Ramann-Str. 6, Freising, 85350, Germany
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4
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Affiliation(s)
- Thomas Shafee
- Swinburne University of Technology, Melbourne, Australia
| | - Daniel Mietchen
- Ronin Institute, Montclair, New Jersey, United States of America
- Institute for Globally Distributed Open Research and Education (IGDORE), Gothenburg, Sweden
- Leibniz Institute for Freshwater Ecology and Inland Fisheries (IGB), Berlin, Germany
- FIZ Karlsruhe–Leibniz Institute for Information Infrastructure, Berlin, Germany
| | - Tiago Lubiana
- Ronin Institute, Montclair, New Jersey, United States of America
- University of São Paulo, São Paulo, Brazil
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Hegde S, Garg A, Murray-Rust P, Mietchen D. Mining the literature for ethics statements: A step towards standardizing research ethics. RIO 2022. [DOI: 10.3897/rio.8.e94685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Ethical aspects of research continue to gain attention, be that in the process of proposing and planning research or performing, documenting or publishing it. One of the ways in which this trend manifests itself is the increasingly common addition of ethics statements to publications in fields like biomedicine, psychology or ethnography. Such ethics statements in publications provide the reader with a window into some of the practical yet typically hidden aspects of research ethics. As more and more publications are becoming available in full text and in machine readable formats through repositories like Europe PubMed Central, we propose to mine the literature for ethics statements and to extract information about the various aspects of research ethics that they address. The more standardized these statements are, the better the mined materials can be converted into structured and queryable information that can in turn be used to inform efforts towards higher levels of standardization in research ethics. This paper sketches out the motivation for such mining and outlines some methodological approaches that could be leveraged towards this end.
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Agosti D, Benichou L, Addink W, Arvanitidis C, Catapano T, Cochrane G, Dillen M, Döring M, Georgiev T, Gérard I, Groom Q, Kishor P, Kroh A, Kvaček J, Mergen P, Mietchen D, Pauperio J, Sautter G, Penev L. Recommendations for use of annotations and persistent identifiers in taxonomy and biodiversity publishing. RIO 2022. [DOI: 10.3897/rio.8.e97374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The paper summarises many years of discussions and experience of biodiversity publishers, organisations, research projects and individual researchers, and proposes recommendations for implementation of persistent identifiers for article metadata, structural elements (sections, subsections, figures, tables, references, supplementary materials and others) and data specific to biodiversity (taxonomic treatments, treatment citations, taxon names, material citations, gene sequences, specimens, scientific collections) in taxonomy and biodiversity publishing. The paper proposes best practices on how identifiers should be used in the different cases and on how they can be minted, cited, and expressed in the backend article XML to facilitate conversion to and further re-use of the article content as FAIR data. The paper also discusses several specific routes for post-publication re-use of semantically enhanced content through large biodiversity data aggregators such as the Global Biodiversity Information Facility (GBIF), the International Nucleotide Sequence Database Collaboration (INSDC) and others, and proposes specifications of both identifiers and XML tags to be used for that purpose. A summary table provides an account and overview of the recommendations. The guidelines are supported with examples from the existing publishing practices.
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7
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Turki H, Rasberry L, Ali Hadj Taieb M, Mietchen D, Ben Aouicha M, Pouris A, Bousrih Y. Letter to the Editor: FHIR RDF - Why the world needs structured electronic health records. J Biomed Inform 2022; 136:104253. [DOI: 10.1016/j.jbi.2022.104253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2022] [Revised: 11/15/2022] [Accepted: 11/16/2022] [Indexed: 11/21/2022]
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8
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Meeus S, Addink W, Agosti D, Arvanitidis C, Balech B, Dillen M, Dimitrova M, González-Aranda JM, Holetschek J, Islam S, Jeppesen T, Mietchen D, Nicolson N, Penev L, Robertson T, Ruch P, Trekels M, Groom Q. Recommendations for interoperability among infrastructures. RIO 2022. [DOI: 10.3897/rio.8.e96180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The BiCIKL project is born from a vision that biodiversity data are most useful if they are presented as a network of data that can be integrated and viewed from different starting points. BiCIKL’s goal is to realise that vision by linking biodiversity data infrastructures, particularly for literature, molecular sequences, specimens, nomenclature and analytics. To make those links we need to better understand the existing infrastructures, their limitations, the nature of the data they hold, the services they provide and particularly how they can interoperate. In light of those aims, in the autumn of 2021, 74 people from the biodiversity data community engaged in a total of twelve hackathon topics with the aim to assess the current state of interoperability between infrastructures holding biodiversity data. These topics examined interoperability from several angles. Some were research subjects that required interoperability to get results, some examined modalities of access and the use and implementation of standards, while others tested technologies and workflows to improve linkage of different data types.
These topics and the issues in regard to interoperability uncovered by the hackathon participants inspired the formulation of the following recommendations for infrastructures related to (1) the use of data brokers, (2) building communities and trust, (3) cloud computing as a collaborative tool, (4) standards and (5) multiple modalities of access:
If direct linking cannot be supported between infrastructures, explore using data brokers to store links
Cooperate with open linkage brokers to provide a simple way to allow two-way links between infrastructures, without having to co-organize between many different organisations
Facilitate and encourage the external reporting of issues related to their infrastructure and its interoperability.
Facilitate and encourage requests for new features related to their infrastructure and its interoperability.
Provide development roadmaps openly
Provide a mechanism for anyone to ask for help
Discuss issues in an open forum
Provide cloud-based environments to allow external participants to contribute and test changes to features
Consider the opportunities that cloud computing brings as a means to enable shared management of the infrastructure.
Promote the sharing of knowledge around big data technologies amongst partners, using cloud computing as a training environment
Invest in standards compliance and work with standards organisations to develop new, and extend existing standards
Report on and review standards compliance within an infrastructure with metrics that give credit for work on standard compliance and development
Provide as many different modalities of access as possible
Avoid requiring personal contacts to download data
Provide a full description of an API and the data it serves
If direct linking cannot be supported between infrastructures, explore using data brokers to store links
Cooperate with open linkage brokers to provide a simple way to allow two-way links between infrastructures, without having to co-organize between many different organisations
Facilitate and encourage the external reporting of issues related to their infrastructure and its interoperability.
Facilitate and encourage requests for new features related to their infrastructure and its interoperability.
Provide development roadmaps openly
Provide a mechanism for anyone to ask for help
Discuss issues in an open forum
Provide cloud-based environments to allow external participants to contribute and test changes to features
Consider the opportunities that cloud computing brings as a means to enable shared management of the infrastructure.
Promote the sharing of knowledge around big data technologies amongst partners, using cloud computing as a training environment
Invest in standards compliance and work with standards organisations to develop new, and extend existing standards
Report on and review standards compliance within an infrastructure with metrics that give credit for work on standard compliance and development
Provide as many different modalities of access as possible
Avoid requiring personal contacts to download data
Provide a full description of an API and the data it serves
Finally, the hackathons were an ideal meeting opportunity to build, diversify and extend the BiCIKL community further, and to ensure the alignment of the community with a common vision on how best to link data from specimens, samples, sequences, taxonomic names and taxonomic literature.
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Mietchen D. FAIRifying the dependencies of FAIR Digital Objects within and beyond the research ecosystem. RIO 2022. [DOI: 10.3897/rio.8.e96118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
As the FAIR Principles about findability, accessiblity, interoperability and reusability of research (Wilkinson et al. 2016) reach further and deeper into the research ecosystem, they are increasingly reflected in research policies, research infrastructures, data management plans and other elements of the research landscape. Yet many of these elements are themselves limited in their FAIRness, which hinders the FAIRification - adaptation to the FAIR Principles - of elements that depend on them, e.g. datasets, software, reviews, replication attempts or research evaluation. This can cause friction in alignment with current practices, thereby leading to missed educational and community engagement opportunities and hampering efficient monitoring of compliance or systematic identification of potential improvements.
This poster looks at how the FAIRness of FAIR Digital Objects is affected by the FAIRness of their dependencies, focusing on two types of examples - research data policies and research ethics workflows.
In the first part, the poster explores how the role of research data-related policies and regulations would change if theiy would increasingly involve FAIR Digital Objects, e.g. if policies and their key stipulations would have persistable identifiers linked to well-defined and machine-actionable schemas. These explorations will touch upon both technical and social aspects: what mechanisms are available and already used to increase the FAIRness of policies? Does it help or hinder if certain aspects of the transition to a FAIRer ecosystem are shared in a more or less FAIR way or with shorter or longer delays? Does having more FAIR policies themselves provide funders, institutions, publishers or other organizations with more of an edge or a handicap in terms of assisting their respective communities in the transition towards more FAIRness in their respective corner of the research ecosystem? How can the design of FAIR policy elements be tailored to optimize learning opportunities for specific stakeholder groups pertaining to specific types of collections of FAIR Digital Objects?
In the second part, the poster explores what the benefits and risks would be of making more use of FAIR Digital Objects in research ethics workflows (Hegde et al. 2022). The components considered include the circumstances suggesting or even requiring an ethical review, the types of information that need to be exchanged during the process, the types of communications set up to convey said information, the stakeholders involved in any part of the process, the ways in which metadata about the process is stored and shared, and rules that govern any of these aspects and related matters. These questions will be discussed from the perspectives of several stakeholder groups, e.g. researchers, research subjects, research administrators, reviewers (on ethics committees or during manuscript or grant proposal review), data stewards, tool developers, science journalists, ethics educators and others. Another aspect considered is the potential of a more FAIR ethics process to reduce the burden on the stakeholders involved and to make their participation more meaningful, while raising compliance with applicable regulations, increasing the speed and transparency of the process and improving documentation and standardization.
Generalizing based on these two examples, the poster concludes with a depiction of how to include dependencies of research-related FAIR Digital Objects in FAIR Digital workflows and assessments or reuses thereof.
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10
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Mietchen D. The ecology of FAIR Digital Objects, with special attention to roundtripping and benchmarking across the research ecosystem. RIO 2022. [DOI: 10.3897/rio.8.e96117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The more findable, accessible, interoperable and reusable (i.e. aligned with the FAIR Principles outlined by Wilkinson et al. 2016) a Digital Object is, the more likely it is to interact with other entities in the research ecosystem and beyond. As long as the interoperability of these entities is not perfect (and it rarely is), a variety of interactions with a given Digital Object (e.g. split, merge, aggregation, transformation, backup, upload, download, or updates of content, metadata, storage or permissions) will mean a variety of representations of it, with some closer to the original than others. This has consequences for how the information about Digital Objects or contained in them can move around the research ecosystem. In some contexts, multiple representations of a given original (or aspects of it) might exist, creating the need to assess similarities, differences and relationships and to include them in curation, management, education, dissemination and preservation workflows. In other contetxts, the sole copy of a Digital Object might exist on a legacy system with limited alignment to the FAIR Principles, which creates the need for generating more readily accessible backup copies and to adapt some of them for inclusion in contemporary workflows.
In this presentation, we will look at the suitability of sets of FAIR Digital Objects to serve as indicators for several aspects of FAIRness across different elements of the research ecosystem. These sets could involve existing FAIR Digital Objects (e.g. data management plans, as per Mietchen 2021) as well as new or hypothetical ones, and inclusion or exclusion with respect to a given set could be defined using a wide range of criteria pertaining to the ecosystem elements of interest. Taking inspiration from tracing, monitoring, benchmarking and roundtripping activities in various research fields, we will then explore how far, how well and how quickly such sets - or their content - can travel through multiple elements of the research ecosystem (e.g. different databases or software pipelines or different stages of the research cycle) and what this means in terms of potential improvements to the FAIR Digital Objects themselves, to the sets and their contents, to the way the FAIR assessments are implemented or to relevant elements of the research ecosystem.
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Mietchen D. Connecting research-related FAIR Digital Objects with communities of stakeholders. RIO 2022. [DOI: 10.3897/rio.8.e96119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The last few years have seen considerable progress in terms of integrating individual elements of the research ecosystem with the so-called FAIR Principles (Wilkinson et al. 2016), a set of guidelines to make research-related resources more findable, accessible, interoperable and reusable (FAIR). This integration process has lots of technical as well as social components and ramifications, some of which resulted in dedicated terms like that of a FAIR Digital Object (FDO) which stands for research objects (e.g. datasets, software, specimens, publications) having at least a minimum level of compliance with the FAIR Principles.
As the volume, breadth and depth of FAIR data and the variety of FAIR Digital Objects as well as their use and reuse continue to grow, there is ample opportunity for multi-dimensional interactions between generators, managers, curators, users and reusers of data, and the scope of data quality issues is diversifying accordingly.
This poster looks at two ways in which individual collections of FAIR Digital Objects interact with the wider FAIR research landscape. First, it considers communities that curate, generate or use data, metadata or other resources pertaining to individual collections of FAIR Digital Objects. Specifically, which of these community activities are affected by higher or lower compliance of a collection's FDOs with the FAIR Principles? Second, we will consider the case of communities that overlap across FAIR collections - i.e. when some community members are engaged with several collections, possibly through multiple platforms - and what this means in terms of challenges and opportunities for enhancing findability, accessibility, interoperability and reusability between and across FAIR silos.
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Turki H, Jemielniak D, Hadj Taieb MA, Labra Gayo JE, Ben Aouicha M, Banat M, Shafee T, Prud’hommeaux E, Lubiana T, Das D, Mietchen D. Using logical constraints to validate statistical information about disease outbreaks in collaborative knowledge graphs: the case of COVID-19 epidemiology in Wikidata. PeerJ Comput Sci 2022; 8:e1085. [PMID: 36262159 PMCID: PMC9575845 DOI: 10.7717/peerj-cs.1085] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 08/15/2022] [Indexed: 06/16/2023]
Abstract
Urgent global research demands real-time dissemination of precise data. Wikidata, a collaborative and openly licensed knowledge graph available in RDF format, provides an ideal forum for exchanging structured data that can be verified and consolidated using validation schemas and bot edits. In this research article, we catalog an automatable task set necessary to assess and validate the portion of Wikidata relating to the COVID-19 epidemiology. These tasks assess statistical data and are implemented in SPARQL, a query language for semantic databases. We demonstrate the efficiency of our methods for evaluating structured non-relational information on COVID-19 in Wikidata, and its applicability in collaborative ontologies and knowledge graphs more broadly. We show the advantages and limitations of our proposed approach by comparing it to the features of other methods for the validation of linked web data as revealed by previous research.
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Affiliation(s)
- Houcemeddine Turki
- Data Engineering and Semantics Research Unit, Faculty of Sciences of Sfax, University of Sfax, Sfax, Tunisia
| | - Dariusz Jemielniak
- Department of Management in Networked and Digital Societies, Kozminski University, Warsaw, Masovia, Poland
| | - Mohamed A. Hadj Taieb
- Data Engineering and Semantics Research Unit, Faculty of Sciences of Sfax, University of Sfax, Sfax, Tunisia
| | - Jose E. Labra Gayo
- Web Semantics Oviedo (WESO) Research Group, University of Oviedo, Oviedo, Asturias, Spain
| | - Mohamed Ben Aouicha
- Data Engineering and Semantics Research Unit, Faculty of Sciences of Sfax, University of Sfax, Sfax, Tunisia
| | - Mus’ab Banat
- Faculty of Medicine, Hashemite University, Zarqa, Jordan
| | - Thomas Shafee
- La Trobe University, Melbourne, Victoria, Australia
- Swinburne University of Technology, Melbourne, Victoria, Australia
| | - Eric Prud’hommeaux
- World Wide Web Consortium, Cambridge, Massachusetts, United States of America
| | - Tiago Lubiana
- Computational Systems Biology Laboratory, University of São Paulo, São Paulo, Brazil
| | - Diptanshu Das
- Institute of Child Health (ICH), Kolkata, West Bengal, India
- Medica Superspecialty Hospital, Kolkata, West Bengal, India
| | - Daniel Mietchen
- Ronin Institute, Montclair, New Jersey, United States of America
- Department of Evolutionary and Integrative Ecology, Leibniz Institute of Freshwater Ecology and Inland Fisheries, Berlin, Germany
- School of Data Science, University of Virginia, Charlottesville, Virginia, United States
- Institute for Globally Distributed Open Research and Education (IGDORE), Jena, Germany
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Rasberry L, Mietchen D. Scholia for Software. RIO 2022. [DOI: 10.3897/rio.8.e94771] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Scholia for Software is a project to add software profiling features to Scholia, which is a scholarly profiling service from the Wikimedia ecosystem and integrated with Wikipedia and Wikidata. This document is an adaptation of the funded grant proposal. We are sharing it for several reasons, including research transparency, our wish to encourage the sharing of research proposals for reuse and remixing in general, to assist others specifically in making proposals that would complement our activities, and because sharing this proposal helps us to tell the story of the project to community stakeholders.
A "scholarly profiling service" is a tool which assists the user in accessing data on some aspect of scholarship, usually in relation to research. Typical features of such services include returning the biography of academic publications for any given researcher, or providing a list of publications by topic. Scholia already exists as a Wikimedia platform tool built upon Wikidata and capable of serving these functions. This project will additionally add software-related data to Wikidata, develop Scholia's own code, and address some ethical issues in diversity and representation around these activities. The end result will be that Scholia will have the ability to report what software a given researcher has described using in their publications, what software is most used among authors publishing on a given topic or in a given journal, what papers describe projects which use some given software, and what software is most often co-used in projects which use a given software.
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Rutz A, Sorokina M, Galgonek J, Mietchen D, Willighagen E, Gaudry A, Graham JG, Stephan R, Page R, Vondrášek J, Steinbeck C, Pauli GF, Wolfender JL, Bisson J, Allard PM. The LOTUS initiative for open knowledge management in natural products research. eLife 2022; 11:e70780. [PMID: 35616633 PMCID: PMC9135406 DOI: 10.7554/elife.70780] [Citation(s) in RCA: 62] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Accepted: 03/22/2022] [Indexed: 12/17/2022] Open
Abstract
Contemporary bioinformatic and chemoinformatic capabilities hold promise to reshape knowledge management, analysis and interpretation of data in natural products research. Currently, reliance on a disparate set of non-standardized, insular, and specialized databases presents a series of challenges for data access, both within the discipline and for integration and interoperability between related fields. The fundamental elements of exchange are referenced structure-organism pairs that establish relationships between distinct molecular structures and the living organisms from which they were identified. Consolidating and sharing such information via an open platform has strong transformative potential for natural products research and beyond. This is the ultimate goal of the newly established LOTUS initiative, which has now completed the first steps toward the harmonization, curation, validation and open dissemination of 750,000+ referenced structure-organism pairs. LOTUS data is hosted on Wikidata and regularly mirrored on https://lotus.naturalproducts.net. Data sharing within the Wikidata framework broadens data access and interoperability, opening new possibilities for community curation and evolving publication models. Furthermore, embedding LOTUS data into the vast Wikidata knowledge graph will facilitate new biological and chemical insights. The LOTUS initiative represents an important advancement in the design and deployment of a comprehensive and collaborative natural products knowledge base.
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Affiliation(s)
- Adriano Rutz
- School of Pharmaceutical Sciences, University of GenevaGenevaSwitzerland
- Institute of Pharmaceutical Sciences of Western Switzerland, University of GenevaGenevaSwitzerland
| | - Maria Sorokina
- Institute for Inorganic and Analytical Chemistry, Friedrich-Schiller-University JenaJenaGermany
| | - Jakub Galgonek
- Institute of Organic Chemistry and Biochemistry of the CASPragueCzech Republic
| | - Daniel Mietchen
- Ronin InstituteMontclairUnited States
- Leibniz Institute of Freshwater Ecology and Inland FisheriesBerlinGermany
- School of Data Science, University of VirginiaCharlottesvilleUnited States
| | - Egon Willighagen
- Department of Bioinformatics-BiGCaT, Maastricht UniversityMaastrichtNetherlands
| | - Arnaud Gaudry
- School of Pharmaceutical Sciences, University of GenevaGenevaSwitzerland
- Institute of Pharmaceutical Sciences of Western Switzerland, University of GenevaGenevaSwitzerland
| | - James G Graham
- Center for Natural Product Technologies and WHO Collaborating Centre for Traditional Medicine (WHO CC/TRM), Pharmacognosy Institute; College of Pharmacy, University of Illinois at ChicagoChicagoUnited States
- Department of Pharmaceutical Sciences, College of Pharmacy, University of Illinois at ChicagoChicagoUnited States
| | - Ralf Stephan
- Ontario Institute for Cancer Research (OICR), University Ave SuiteTorontoCanada
| | | | - Jiří Vondrášek
- Institute of Organic Chemistry and Biochemistry of the CASPragueCzech Republic
| | - Christoph Steinbeck
- Institute for Inorganic and Analytical Chemistry, Friedrich-Schiller-University JenaJenaGermany
| | - Guido F Pauli
- Center for Natural Product Technologies and WHO Collaborating Centre for Traditional Medicine (WHO CC/TRM), Pharmacognosy Institute; College of Pharmacy, University of Illinois at ChicagoChicagoUnited States
- Department of Pharmaceutical Sciences, College of Pharmacy, University of Illinois at ChicagoChicagoUnited States
| | - Jean-Luc Wolfender
- School of Pharmaceutical Sciences, University of GenevaGenevaSwitzerland
- Institute of Pharmaceutical Sciences of Western Switzerland, University of GenevaGenevaSwitzerland
| | - Jonathan Bisson
- Center for Natural Product Technologies and WHO Collaborating Centre for Traditional Medicine (WHO CC/TRM), Pharmacognosy Institute; College of Pharmacy, University of Illinois at ChicagoChicagoUnited States
- Department of Pharmaceutical Sciences, College of Pharmacy, University of Illinois at ChicagoChicagoUnited States
| | - Pierre-Marie Allard
- School of Pharmaceutical Sciences, University of GenevaGenevaSwitzerland
- Institute of Pharmaceutical Sciences of Western Switzerland, University of GenevaGenevaSwitzerland
- Department of Biology, University of FribourgFribourgSwitzerland
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Stocker M, Heger T, Schweidtmann A, Ćwiek-Kupczyńska H, Penev L, Dojchinovski M, Willighagen E, Vidal ME, Turki H, Balliet D, Tiddi I, Kuhn T, Mietchen D, Karras O, Vogt L, Hellmann S, Jeschke J, Krajewski P, Auer S. SKG4EOSC - Scholarly Knowledge Graphs for EOSC: Establishing a backbone of knowledge graphs for FAIR Scholarly Information in EOSC. RIO 2022. [DOI: 10.3897/rio.8.e83789] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
In the age of advanced information systems powering fast-paced knowledge economies that face global societal challenges, it is no longer adequate to express scholarly information - an essential resource for modern economies - primarily as article narratives in document form. Despite being a well-established tradition in scholarly communication, PDF-based text publishing is hindering scientific progress as it buries scholarly information into non-machine-readable formats. The key objective of SKG4EOSC is to improve science productivity through development and implementation of services for text and data conversion, and production, curation, and re-use of FAIR scholarly information. This will be achieved by (1) establishing the Open Research Knowledge Graph (ORKG, orkg.org), a service operated by the SKG4EOSC coordinator, as a Hub for access to FAIR scholarly information in the EOSC; (2) lifting to EOSC of numerous and heterogeneous domain-specific research infrastructures through the ORKG Hub’s harmonized access facilities; and (3) leverage the Hub to support cross-disciplinary research and policy decisions addressing societal challenges. SKG4EOSC will pilot the devised approaches and technologies in four research domains: biodiversity crisis, precision oncology, circular processes, and human cooperation. With the aim to improve machine-based scholarly information use, SKG4EOSC addresses an important current and future need of researchers. It extends the application of the FAIR data principles to scholarly communication practices, hence a more comprehensive coverage of the entire research lifecycle. Through explicit, machine actionable provenance links between FAIR scholarly information, primary data and contextual entities, it will substantially contribute to reproducibility, validation and trust in science. The resulting advanced machine support will catalyse new discoveries in basic research and solutions in key application areas.
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Abstract
Biological invasions are on the rise, and their global impacts on ecosystems, economies and human health are a major challenge. Invasion science is critical to mitigate invader impacts, yet due to the strong increase of data and information in this area, it has become difficult to acquire and maintain an overview of the field. As a result, existing evidence is often not found, knowledge is too rarely transferred to practice, and research is sometimes conducted in pursuit of dead ends. We propose to address these challenges by developing an interactive atlas of invasion science that can be extended to other disciplines in the future. This online portal, which we aim to create in the course of the project described here, will be an evolving knowledge resource and open for anyone to use, including researchers, citizen scientists, practitioners and policy makers. Users will be able to zoom into the major research questions and hypotheses of invasion science, which are connected to the relevant studies published in the field and, if available, the underlying raw data. The portal will apply cutting-edge visualization techniques, artificial intelligence and novel methods for knowledge synthesis.
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Rasberry L, Mietchen D. Wikipedia for multilingual COVID-19 vaccine education at scale. RIO 2021. [DOI: 10.3897/rio.7.e70042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
We present the design of a project to develop Wikipedia content on general vaccine safety and the COVID-19 vaccines, specifically. This proposal describes what a team would need to distribute public health information in Wikipedia in multiple languages in response to a disaster or crisis, and to measure and report the communication impact of the same. Researchers at the School of Data Science at the University of Virginia made this proposal in response to a February 2021 call from a sponsor which was seeking to share public health information to respond globally to vaccine hesitancy related to the COVID-19 vaccines. This proposal was not selected for funding, and now the research team is sharing the proposal here with an open copyright license for anyone to reuse and remix. Most of the text here is from the original proposal, but there are modifications to remove the names of the funder, named partners, and for other details to make this text more reusable. The budget in this proposal has been converted from a dollar amount to equivalent descriptions in terms of labor hours, and the timeline was adapted from absolute to relative months.
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Pickering B, Biro T, Austin CC, Bernier A, Bezuidenhout L, Casorrán C, Crawley FP, David R, Engelhardt C, Mitrea G, Mochmann IC, Nagrani R, O'Brien-Uhlmansiek M, Parker S, Wang M, Castro LJ, Cournia Z, Dharmawardena K, Diallo G, Dillo I, Gonzalez-Beltran A, Gururaj A, Gutam S, Harrower N, Jonnagaddala J, McNeill K, Mietchen D, Pienta A, Polydoratou P, Tovani-Palone MR. Radical collaboration during a global health emergency: development of the RDA COVID-19 data sharing recommendations and guidelines. Open Res Eur 2021; 1:69. [PMID: 37645170 PMCID: PMC10446077 DOI: 10.12688/openreseurope.13369.1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 04/09/2021] [Indexed: 08/31/2023]
Abstract
Background: The coronavirus disease 2019 (COVID-19) global pandemic required a rapid and effective response. This included ethical and legally appropriate sharing of data. The European Commission (EC) called upon the Research Data Alliance (RDA) to recruit experts worldwide to quickly develop recommendations and guidelines for COVID-related data sharing. Purpose: The purpose of the present work was to explore how the RDA succeeded in engaging the participation of its community of scientists in a rapid response to the EC request. Methods: A survey questionnaire was developed and distributed among RDA COVID-19 work group members. A mixed-methods approach was used for analysis of the survey data. Results: The three constructs of radical collaboration (inclusiveness, distributed digital practices, productive and sustainable collaboration) were found to be well supported in both the quantitative and qualitative analyses of the survey data. Other social factors, such as motivation and group identity were also found to be important to the success of this extreme collaborative effort. Conclusions: Recommendations and suggestions for future work were formulated for consideration by the RDA to strengthen effective expert collaboration and interdisciplinary efforts.
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Affiliation(s)
| | - Timea Biro
- Digital Repository of Ireland / Royal Irish Academy, Dublin, Ireland
| | | | | | | | | | - Francis P. Crawley
- Good Clinical Practice Alliance - Europe (GCPA) / Strategic Initiative for Developing Capacity in Ethical Review (SIDCER), Leuven, Belgium
| | - Romain David
- European Research Infrastructure on Highly Pathogenic Agents, Paris, France
| | | | - Geta Mitrea
- Carol I National Defence University, Bucharest, Romania
| | | | - Rajini Nagrani
- Leibniz Institute for Prevention Research and Epidemiology (BIPS), Bremen, Germany
| | | | - Simon Parker
- The German Cancer Research Center (Deutsches Krebsforschungszentrum, DKFZ), Heidelberg, Germany
| | | | | | - Zoe Cournia
- Biomedical Research Foundation, Academy of Athens, Athens, Greece
| | | | | | - Ingrid Dillo
- Data Archiving and Networked Services (DANS), The Hague, The Netherlands
| | | | - Anupama Gururaj
- National Institute of Allergy and Infectious Disease, National Institutes of Health, Fairfax, USA
| | - Sridhar Gutam
- ICAR-Indian Institute of Horticultural Research, Bengaluru, India
| | - Natalie Harrower
- Digital Repository of Ireland / Royal Irish Academy, Dublin, Ireland
| | | | | | - Daniel Mietchen
- School of Data Science, University of Virginia, Charlottesville, USA
| | - Amy Pienta
- ICPSR-University of Michigan, Ann Arbor, USA
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Mietchen D, Rasberry L, Morata T, Sadowski J, Novakovich J, Heilman J. Developing a scalable framework for partnerships between health agencies and the Wikimedia ecosystem. RIO 2021. [DOI: 10.3897/rio.7.e68121] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
In this era of information overload and misinformation, it is a challenge to rapidly translate evidence-based health information to the public. Wikipedia is a prominent global source of health information with high traffic, multilingual coverage, and acceptable quality control practices. Viewership data following the Ebola crisis and during the COVID-19 pandemic reveals that a significant number of web users located health guidance through Wikipedia and related projects, including its media repository Wikimedia Commons and structured data complement, Wikidata.
The basic idea discussed in this paper is to increase and expedite health institutions' global reach to the general public, by developing a specific strategy to maximize the availability of focused content into Wikimedia’s public digital knowledge archives. It was conceptualized from the experiences of leading health organizations such as Cochrane, the World Health Organization (WHO) and other United Nations Organizations, Cancer Research UK, National Network of Libraries of Medicine, and Centers for Disease Control and Prevention (CDC)'s National Institute for Occupational Safety and Health (NIOSH). Each has customized strategies to integrate content in Wikipedia and evaluate responses.
We propose the development of an interactive guide on the Wikipedia and Wikidata platforms to support health agencies, health professionals and communicators in quickly distributing key messages during crisis situations. The guide aims to cover basic features of Wikipedia, including adding key health messages to Wikipedia articles, citing expert sources to facilitate fact-checking, staging text for translation into multiple languages; automating metrics reporting; sharing non-text media; anticipating offline reuse of Wikipedia content in apps or virtual assistants; structuring data for querying and reuse through Wikidata, and profiling other flagship projects from major health organizations.
In the first phase, we propose the development of a curriculum for the guide using information from prior case studies. In the second phase, the guide would be tested on select health-related topics as new case studies. In its third phase, the guide would be finalized and disseminated.
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Austin CC, Bernier A, Bezuidenhout L, Bicarregui J, Biro T, Cambon-Thomsen A, Carroll SR, Cournia Z, Dabrowski PW, Diallo G, Duflot T, Garcia L, Gesing S, Gonzalez-Beltran A, Gururaj A, Harrower N, Lin D, Medeiros C, Méndez E, Meyers N, Mietchen D, Nagrani R, Nilsonne G, Parker S, Pickering B, Pienta A, Polydoratou P, Psomopoulos F, Rennes S, Rowe R, Sansone SA, Shanahan H, Sitz L, Stocks J, Tovani-Palone MR, Uhlmansiek M. Fostering global data sharing: highlighting the recommendations of the Research Data Alliance COVID-19 working group. Wellcome Open Res 2021; 5:267. [PMID: 33501381 PMCID: PMC7808050 DOI: 10.12688/wellcomeopenres.16378.2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/08/2021] [Indexed: 11/20/2022] Open
Abstract
The systemic challenges of the COVID-19 pandemic require cross-disciplinary collaboration in a global and timely fashion. Such collaboration needs open research practices and the sharing of research outputs, such as data and code, thereby facilitating research and research reproducibility and timely collaboration beyond borders. The Research Data Alliance COVID-19 Working Group recently published a set of recommendations and guidelines on data sharing and related best practices for COVID-19 research. These guidelines include recommendations for clinicians, researchers, policy- and decision-makers, funders, publishers, public health experts, disaster preparedness and response experts, infrastructure providers from the perspective of different domains (Clinical Medicine, Omics, Epidemiology, Social Sciences, Community Participation, Indigenous Peoples, Research Software, Legal and Ethical Considerations), and other potential users. These guidelines include recommendations for researchers, policymakers, funders, publishers and infrastructure providers from the perspective of different domains (Clinical Medicine, Omics, Epidemiology, Social Sciences, Community Participation, Indigenous Peoples, Research Software, Legal and Ethical Considerations). Several overarching themes have emerged from this document such as the need to balance the creation of data adherent to FAIR principles (findable, accessible, interoperable and reusable), with the need for quick data release; the use of trustworthy research data repositories; the use of well-annotated data with meaningful metadata; and practices of documenting methods and software. The resulting document marks an unprecedented cross-disciplinary, cross-sectoral, and cross-jurisdictional effort authored by over 160 experts from around the globe. This letter summarises key points of the Recommendations and Guidelines, highlights the relevant findings, shines a spotlight on the process, and suggests how these developments can be leveraged by the wider scientific community.
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Affiliation(s)
- Claire C. Austin
- Environment and Climate Change Canada, 351 boul. St-Joseph, Gatineau, Quebec, K1A 0H3, Canada
| | - Alexander Bernier
- Centre of Genomics and Policy, McGill University, 740, avenue Dr. Penfield, suite 5200, Montreal, Quebec, Canada
| | - Louise Bezuidenhout
- Institute for Science, Innovation and Society, University of Oxford, 64 Banbury Road, Oxford, OX2 6PN, UK
| | - Juan Bicarregui
- UKRI-STFC Rutherford Appleton Laboratory, Harwell Campus, Didcot, OX11 0QX, UK
| | - Timea Biro
- Digital Repository of Ireland, Royal Irish Academy, 19 Dawson St, Dublin 2, D02 HH58, Ireland
| | | | - Stephanie Russo Carroll
- Native Nations Institute at the Udall Center for Studies in Public Policy and the College of Public Health, University of Arizona, 803 E First ST, Tucson, AZ, 85719, USA
| | - Zoe Cournia
- Biomedical Research Foundation, Academy of Athens, 4 Soranou Ephessiou, Athens, 11527, Greece
| | | | - Gayo Diallo
- BPH INSERM1219 & LaBRI, Univ. Bordeaux, 146 rue Léo Saignat, F-33000, Bordeaux, France
| | - Thomas Duflot
- Normandie Univ, UNIROUEN, CHU Rouen, Department of Clinical Research, Rouen University Hospital, 1 Rue de Germont, Rouen Cedex, 76031, France
| | - Leyla Garcia
- ZB MED Information Centre for Life Sciences, Gleueler Str 60, Cologne, 50931, Germany
| | - Sandra Gesing
- University of Notre Dame Center for Research Computing, 814 Flanner Hall, Notre Dame, IN, 46556, USA
| | | | - Anupama Gururaj
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, 5601 Fishers Lane, Rockville, MD, 20852, USA
| | - Natalie Harrower
- Digital Repository of Ireland, Royal Irish Academy, 19 Dawson St, Dublin 2, D02 HH58, Ireland
| | - Dawei Lin
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, 5601 Fishers Lane, Rockville, MD, 20852, USA
| | - Claudia Medeiros
- Institute of Computing, University of Campinas, Av Albert Einstein 1251, Campinas, São Paulo, 13082-853, Brazil
| | - Eva Méndez
- Universidad Carlos III de Madrid, C/ Madrid, 128, Getafe (Madrid), 28903, Spain
| | - Natalie Meyers
- 250D Navari Center for Digital Scholarship, Hesburgh Library, University of Notre Dame, Notre Dame, IN, 46556, USA
| | - Daniel Mietchen
- School of Data Science, University of Virginia, P.O. Box 400249, Charlottesville, VA, 22904, USA
| | - Rajini Nagrani
- Leibniz Institute for Prevention Research and Epidemiology, Achterstrasse 30, Bremen, 28359, Germany
| | - Gustav Nilsonne
- Karolinska Institutet & Swedish National Data Service, Nobels väg 9, Stockholm, 17177, Sweden
| | - Simon Parker
- Cancer Research UK, 2 Redman Place, London, E20 1JQ, UK
| | - Brian Pickering
- University of Southampton, University Road, Southampton, SO17 1BJ, UK
| | - Amy Pienta
- ICPSR, University of Michigan, P.O. Box 1248, Ann Arbor, MI, 48106-1248, USA
| | - Panayiota Polydoratou
- OpenEdition/Department of Library Science, Archives and Information Systems, International Hellenic University, P.O. Box 141, Thessaloniki, 57400, Greece
| | - Fotis Psomopoulos
- Institute of Applied Biosciences (INAB), Centre for Research and Technology Hellas (CERTH), Thessaloniki, 57001, Greece
| | - Stephanie Rennes
- INRAE National Research Institute for Agriculture, Food and Environment, 147 Rue de l'Université, Paris, 75007, France
| | - Robyn Rowe
- Laurentian University, Ontario, P3E 2C6, Canada
| | - Susanna-Assunta Sansone
- Oxford e-Research Centre, Department of Engineering Science, University of Oxford, 7 Keble Road, Oxford, OX1 3QG, UK
| | - Hugh Shanahan
- Department of Computer Science, Royal Holloway, University of London, Bedford Building, Egham, TW20 0EX, UK
| | - Lina Sitz
- Indepedent Researcher, Strada Costiera, Trieste, 34151, Italy
| | - Joanne Stocks
- Division of Rheumatology, Orthopedics and Dermatology, School of Medicine, University of Nottingham, Queens Medical Centre, Nottingham, NG7 2UH, UK
| | | | - Mary Uhlmansiek
- Research Data Alliance - US Region (RDA-US), c/o Ronin Institute, 127 Haddon Place, Montclair, NJ, 07043, USA
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Mietchen D, Penev L, Georgiev T, Ovcharova B, Kostadinova I. Open science in practice: 300 published research ideas and outcomes illustrate how RIO Journal facilitates engagement with the research process. RIO 2021. [DOI: 10.3897/rio.7.e68595] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Since Research Ideas and Outcomes was launched in late 2015, it has stimulated experimentation around the publication of and engagement with research processes, especially those with a strong open science component. Here, we zoom in on the first 300 RIO articles that have been published and elucidate how they relate to the different stages and variants of the research cycle, how they help address societal challenges and what forms of engagement have evolved around these resources, most of which have a nature and scope that would prevent them from entering the scholarly record via more traditional journals. Building on these observations, we describe some changes we recently introduced in the policies and peer review process at RIO to further facilitate engagement with the research process, including the establishment of an article collections feature that allows us to bring together research ideas and outcomes from within one research cycle or across multiple ones, irrespective of where they have been published.
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Abstract
This project seeks to conduct language translation on metadata labels for research publications, attribution data, and clinical trials information to make data about medical research queriable in underserved languages through Wikidata and the Linked Open Web. This project has the benefit of distributing content through Wikipedia and Wikidata, which already have an annual userbase of a billion users and which already have established actionable standards to practice diversity, inclusion, openness, FAIRness, and transparency about program development. The impact will be localized access to basic research information in various Global South languages to integrate with existing community efforts for establishing the same. Although Wikidata development in this direction seems inevitable, the cultural and social exchange required to establish global multilingual research partnerships could begin now with support rather than later as a second phase effort for including the developing world. Wikipedia and Wikidata are established forums with an existing active userbase for multilingual research collaboration, but the research practices there still are immature. By applying metadata expertise through this project, we will elevate the current amateur development with more stable Linked Open Data compatibility to English language databases. Using the wiki distribution and discussion platform to develop the global conversation about data sharing will set good precedents for the trend of global research collaboration.
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Austin CC, Bernier A, Bezuidenhout L, Bicarregui J, Biro T, Cambon-Thomsen A, Carroll SR, Cournia Z, Dabrowski PW, Diallo G, Duflot T, Garcia L, Gesing S, Gonzalez-Beltran A, Gururaj A, Harrower N, Lin D, Medeiros C, Méndez E, Meyers N, Mietchen D, Nagrani R, Nilsonne G, Parker S, Pickering B, Pienta A, Polydoratou P, Psomopoulos F, Rennes S, Rowe R, Sansone SA, Shanahan H, Sitz L, Stocks J, Tovani-Palone MR, Uhlmansiek M. Fostering global data sharing: highlighting the recommendations of the Research Data Alliance COVID-19 working group. Wellcome Open Res 2020; 5:267. [PMID: 33501381 PMCID: PMC7808050 DOI: 10.12688/wellcomeopenres.16378.1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/21/2020] [Indexed: 08/31/2023] Open
Abstract
The systemic challenges of the COVID-19 pandemic require cross-disciplinary collaboration in a global and timely fashion. Such collaboration needs open research practices and the sharing of research outputs, such as data and code, thereby facilitating research and research reproducibility and timely collaboration beyond borders. The Research Data Alliance COVID-19 Working Group recently published a set of recommendations and guidelines on data sharing and related best practices for COVID-19 research. These guidelines include recommendations for researchers, policymakers, funders, publishers and infrastructure providers from the perspective of different domains (Clinical Medicine, Omics, Epidemiology, Social Sciences, Community Participation, Indigenous Peoples, Research Software, Legal and Ethical Considerations). Several overarching themes have emerged from this document such as the need to balance the creation of data adherent to FAIR principles (findable, accessible, interoperable and reusable), with the need for quick data release; the use of trustworthy research data repositories; the use of well-annotated data with meaningful metadata; and practices of documenting methods and software. The resulting document marks an unprecedented cross-disciplinary, cross-sectoral, and cross-jurisdictional effort authored by over 160 experts from around the globe. This letter summarises key points of the Recommendations and Guidelines, highlights the relevant findings, shines a spotlight on the process, and suggests how these developments can be leveraged by the wider scientific community.
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Affiliation(s)
- Claire C. Austin
- Environment and Climate Change Canada, 351 boul. St-Joseph, Gatineau, Quebec, K1A 0H3, Canada
| | - Alexander Bernier
- Centre of Genomics and Policy, McGill University, 740, avenue Dr. Penfield, suite 5200, Montreal, Quebec, Canada
| | - Louise Bezuidenhout
- Institute for Science, Innovation and Society, University of Oxford, 64 Banbury Road, Oxford, OX2 6PN, UK
| | - Juan Bicarregui
- UKRI-STFC Rutherford Appleton Laboratory, Harwell Campus, Didcot, OX11 0QX, UK
| | - Timea Biro
- Digital Repository of Ireland, Royal Irish Academy, 19 Dawson St, Dublin 2, D02 HH58, Ireland
| | | | - Stephanie Russo Carroll
- Native Nations Institute at the Udall Center for Studies in Public Policy and the College of Public Health, University of Arizona, 803 E First ST, Tucson, AZ, 85719, USA
| | - Zoe Cournia
- Biomedical Research Foundation, Academy of Athens, 4 Soranou Ephessiou, Athens, 11527, Greece
| | | | - Gayo Diallo
- BPH INSERM1219 & LaBRI, Univ. Bordeaux, 146 rue Léo Saignat, F-33000, Bordeaux, France
| | - Thomas Duflot
- Normandie Univ, UNIROUEN, CHU Rouen, Department of Clinical Research, Rouen University Hospital, 1 Rue de Germont, Rouen Cedex, 76031, France
| | - Leyla Garcia
- ZB MED Information Centre for Life Sciences, Gleueler Str 60, Cologne, 50931, Germany
| | - Sandra Gesing
- University of Notre Dame Center for Research Computing, 814 Flanner Hall, Notre Dame, IN, 46556, USA
| | | | - Anupama Gururaj
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, 5601 Fishers Lane, Rockville, MD, 20852, USA
| | - Natalie Harrower
- Digital Repository of Ireland, Royal Irish Academy, 19 Dawson St, Dublin 2, D02 HH58, Ireland
| | - Dawei Lin
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, 5601 Fishers Lane, Rockville, MD, 20852, USA
| | - Claudia Medeiros
- Institute of Computing, University of Campinas, Av Albert Einstein 1251, Campinas, São Paulo, 13082-853, Brazil
| | - Eva Méndez
- Universidad Carlos III de Madrid, C/ Madrid, 128, Getafe (Madrid), 28903, Spain
| | - Natalie Meyers
- 250D Navari Center for Digital Scholarship, Hesburgh Library, University of Notre Dame, Notre Dame, IN, 46556, USA
| | - Daniel Mietchen
- School of Data Science, University of Virginia, P.O. Box 400249, Charlottesville, VA, 22904, USA
| | - Rajini Nagrani
- Leibniz Institute for Prevention Research and Epidemiology, Achterstrasse 30, Bremen, 28359, Germany
| | - Gustav Nilsonne
- Karolinska Institutet & Swedish National Data Service, Nobels väg 9, Stockholm, 17177, Sweden
| | - Simon Parker
- Cancer Research UK, 2 Redman Place, London, E20 1JQ, UK
| | - Brian Pickering
- University of Southampton, University Road, Southampton, SO17 1BJ, UK
| | - Amy Pienta
- ICPSR, University of Michigan, P.O. Box 1248, Ann Arbor, MI, 48106-1248, USA
| | - Panayiota Polydoratou
- OpenEdition/Department of Library Science, Archives and Information Systems, International Hellenic University, P.O. Box 141, Thessaloniki, 57400, Greece
| | - Fotis Psomopoulos
- Institute of Applied Biosciences (INAB), Centre for Research and Technology Hellas (CERTH), Thessaloniki, 57001, Greece
| | - Stephanie Rennes
- INRAE National Research Institute for Agriculture, Food and Environment, 147 Rue de l'Université, Paris, 75007, France
| | - Robyn Rowe
- Laurentian University, Ontario, P3E 2C6, Canada
| | - Susanna-Assunta Sansone
- Oxford e-Research Centre, Department of Engineering Science, University of Oxford, 7 Keble Road, Oxford, OX1 3QG, UK
| | - Hugh Shanahan
- Department of Computer Science, Royal Holloway, University of London, Bedford Building, Egham, TW20 0EX, UK
| | - Lina Sitz
- Indepedent Researcher, Strada Costiera, Trieste, 34151, Italy
| | - Joanne Stocks
- Division of Rheumatology, Orthopedics and Dermatology, School of Medicine, University of Nottingham, Queens Medical Centre, Nottingham, NG7 2UH, UK
| | | | - Mary Uhlmansiek
- Research Data Alliance - US Region (RDA-US), c/o Ronin Institute, 127 Haddon Place, Montclair, NJ, 07043, USA
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Abstract
In this project, we will explore the range of data-related decisions made during public health emergencies like the ongoing COVID-19 pandemic and analyze the flow of information, data, and metadata within networks of such decisions.
Data sharing is now considered a key component of addressing present, future, and even past public health emergencies, from local to global levels. Researchers, research institutions, journals and others have taken steps towards increasing the sharing of data around the ongoing COVID-19 pandemic and in preparation for future pandemics.
We will quantify the effects of data flow modifications to identify parameter sets under which specific modes of sharing or withholding information have the largest effects on outbreak dynamics. For these high-impact parameter sets, we will then assess the current and past availability of corresponding data, metadata, and misinformation, and estimate the effects on outbreak mitigation and preparedness efforts.
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25
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Waagmeester A, Stupp G, Burgstaller-Muehlbacher S, Good BM, Griffith M, Griffith OL, Hanspers K, Hermjakob H, Hudson TS, Hybiske K, Keating SM, Manske M, Mayers M, Mietchen D, Mitraka E, Pico AR, Putman T, Riutta A, Queralt-Rosinach N, Schriml LM, Shafee T, Slenter D, Stephan R, Thornton K, Tsueng G, Tu R, Ul-Hasan S, Willighagen E, Wu C, Su AI. Wikidata as a knowledge graph for the life sciences. eLife 2020; 9:e52614. [PMID: 32180547 PMCID: PMC7077981 DOI: 10.7554/elife.52614] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Accepted: 02/28/2020] [Indexed: 12/22/2022] Open
Abstract
Wikidata is a community-maintained knowledge base that has been assembled from repositories in the fields of genomics, proteomics, genetic variants, pathways, chemical compounds, and diseases, and that adheres to the FAIR principles of findability, accessibility, interoperability and reusability. Here we describe the breadth and depth of the biomedical knowledge contained within Wikidata, and discuss the open-source tools we have built to add information to Wikidata and to synchronize it with source databases. We also demonstrate several use cases for Wikidata, including the crowdsourced curation of biomedical ontologies, phenotype-based diagnosis of disease, and drug repurposing.
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Affiliation(s)
| | - Gregory Stupp
- Department of Integrative Structural and Computational Biology, The Scripps Research InstituteLa JollaUnited States
| | - Sebastian Burgstaller-Muehlbacher
- Center for Integrative Bioinformatics Vienna, Max Perutz Laboratories, University of Vienna and Medical University of ViennaViennaAustria
| | - Benjamin M Good
- Department of Integrative Structural and Computational Biology, The Scripps Research InstituteLa JollaUnited States
| | - Malachi Griffith
- McDonnell Genome Institute, Washington University School of MedicineSt. LouisUnited States
| | - Obi L Griffith
- McDonnell Genome Institute, Washington University School of MedicineSt. LouisUnited States
| | - Kristina Hanspers
- Institute of Data Science and Biotechnology, Gladstone InstitutesSan FranciscoUnited States
| | | | - Toby S Hudson
- School of Chemistry, The University of SydneySydneyAustralia
| | - Kevin Hybiske
- Division of Allergy and Infectious Diseases, Department of Medicine, University of WashingtonSeattleUnited States
| | - Sarah M Keating
- European Bioinformatics Institute (EMBL-EBI)HinxtonUnited Kingdom
| | - Magnus Manske
- Wellcome Trust Sanger InstituteCambridgeUnited Kingdom
| | - Michael Mayers
- Department of Integrative Structural and Computational Biology, The Scripps Research InstituteLa JollaUnited States
| | - Daniel Mietchen
- School of Data Science, University of VirginiaCharlottesvilleUnited States
| | - Elvira Mitraka
- University of Maryland School of MedicineBaltimoreUnited States
| | - Alexander R Pico
- Institute of Data Science and Biotechnology, Gladstone InstitutesSan FranciscoUnited States
| | - Timothy Putman
- Department of Integrative Structural and Computational Biology, The Scripps Research InstituteLa JollaUnited States
| | - Anders Riutta
- Institute of Data Science and Biotechnology, Gladstone InstitutesSan FranciscoUnited States
| | - Nuria Queralt-Rosinach
- Department of Integrative Structural and Computational Biology, The Scripps Research InstituteLa JollaUnited States
| | - Lynn M Schriml
- University of Maryland School of MedicineBaltimoreUnited States
| | - Thomas Shafee
- Department of Animal Plant and Soil Sciences, La Trobe UniversityMelbourneAustralia
| | - Denise Slenter
- Department of Bioinformatics-BiGCaT, NUTRIM, Maastricht UniversityMaastrichtNetherlands
| | | | | | - Ginger Tsueng
- Department of Integrative Structural and Computational Biology, The Scripps Research InstituteLa JollaUnited States
| | - Roger Tu
- Department of Integrative Structural and Computational Biology, The Scripps Research InstituteLa JollaUnited States
| | - Sabah Ul-Hasan
- Department of Integrative Structural and Computational Biology, The Scripps Research InstituteLa JollaUnited States
| | - Egon Willighagen
- Department of Bioinformatics-BiGCaT, NUTRIM, Maastricht UniversityMaastrichtNetherlands
| | - Chunlei Wu
- Department of Integrative Structural and Computational Biology, The Scripps Research InstituteLa JollaUnited States
| | - Andrew I Su
- Department of Integrative Structural and Computational Biology, The Scripps Research InstituteLa JollaUnited States
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26
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Rasberry L, Willighagen E, Nielsen F, Mietchen D. Robustifying Scholia: paving the way for knowledge discovery and research assessment through Wikidata. RIO 2019. [DOI: 10.3897/rio.5.e35820] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Knowledge workers like researchers, students, journalists, research evaluators or funders need tools to explore what is known, how it was discovered, who made which contributions, and where the scholarly record has gaps. Existing tools and services of this kind are not available as Linked Open Data, but Wikidata is. It has the technology, active contributor base, and content to build a large-scale knowledge graph for scholarship, also known as WikiCite. Scholia visualizes this graph in an exploratory interface with profiles and links to the literature. However, it is just a working prototype. This project aims to "robustify Scholia" with back-end development and testing based on pilot corpora. The main objective at this stage is to attain stability in challenging cases such as server throttling and handling of large or incomplete datasets. Further goals include integrating Scholia with data curation and manuscript writing workflows, serving more languages, generating usage stats, and documentation.
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27
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Gold ER, Ali-Khan SE, Allen L, Ballell L, Barral-Netto M, Carr D, Chalaud D, Chaplin S, Clancy MS, Clarke P, Cook-Deegan R, Dinsmore AP, Doerr M, Federer L, Hill SA, Jacobs N, Jean A, Jefferson OA, Jones C, Kahl LJ, Kariuki TM, Kassel SN, Kiley R, Kittrie ER, Kramer B, Lee WH, MacDonald E, Mangravite LM, Marincola E, Mietchen D, Molloy JC, Namchuk M, Nosek BA, Paquet S, Pirmez C, Seyller A, Skingle M, Spadotto SN, Staniszewska S, Thelwall M. An open toolkit for tracking open science partnership implementation and impact. Gates Open Res 2019. [DOI: 10.12688/gatesopenres.12958.1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Serious concerns about the way research is organized collectively are increasingly being raised. They include the escalating costs of research and lower research productivity, low public trust in researchers to report the truth, lack of diversity, poor community engagement, ethical concerns over research practices, and irreproducibility. Open science (OS) collaborations comprise of a set of practices including open access publication, open data sharing and the absence of restrictive intellectual property rights with which institutions, firms, governments and communities are experimenting in order to overcome these concerns. We gathered two groups of international representatives from a large variety of stakeholders to construct a toolkit to guide and facilitate data collection about OS and non-OS collaborations. Ultimately, the toolkit will be used to assess and study the impact of OS collaborations on research and innovation. The toolkit contains the following four elements: 1) an annual report form of quantitative data to be completed by OS partnership administrators; 2) a series of semi-structured interview guides of stakeholders; 3) a survey form of participants in OS collaborations; and 4) a set of other quantitative measures best collected by other organizations, such as research foundations and governmental or intergovernmental agencies. We opened our toolkit to community comment and input. We present the resulting toolkit for use by government and philanthropic grantors, institutions, researchers and community organizations with the aim of measuring the implementation and impact of OS partnership across these organizations. We invite these and other stakeholders to not only measure, but to share the resulting data so that social scientists and policy makers can analyse the data across projects.
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28
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Gold ER, Ali-Khan SE, Allen L, Ballell L, Barral-Netto M, Carr D, Chalaud D, Chaplin S, Clancy MS, Clarke P, Cook-Deegan R, Dinsmore AP, Doerr M, Federer L, Hill SA, Jacobs N, Jean A, Jefferson OA, Jones C, Kahl LJ, Kariuki TM, Kassel SN, Kiley R, Kittrie ER, Kramer B, Lee WH, MacDonald E, Mangravite LM, Marincola E, Mietchen D, Molloy JC, Namchuk M, Nosek BA, Paquet S, Pirmez C, Seyller A, Skingle M, Spadotto SN, Staniszewska S, Thelwall M. An open toolkit for tracking open science partnership implementation and impact. Gates Open Res 2019; 3:1442. [PMID: 31850398 PMCID: PMC6904887 DOI: 10.12688/gatesopenres.12958.2] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/08/2019] [Indexed: 12/26/2022] Open
Abstract
Serious concerns about the way research is organized collectively are increasingly being raised. They include the escalating costs of research and lower research productivity, low public trust in researchers to report the truth, lack of diversity, poor community engagement, ethical concerns over research practices, and irreproducibility. Open science (OS) collaborations comprise of a set of practices including open access publication, open data sharing and the absence of restrictive intellectual property rights with which institutions, firms, governments and communities are experimenting in order to overcome these concerns. We gathered two groups of international representatives from a large variety of stakeholders to construct a toolkit to guide and facilitate data collection about OS and non-OS collaborations. Ultimately, the toolkit will be used to assess and study the impact of OS collaborations on research and innovation. The toolkit contains the following four elements: 1) an annual report form of quantitative data to be completed by OS partnership administrators; 2) a series of semi-structured interview guides of stakeholders; 3) a survey form of participants in OS collaborations; and 4) a set of other quantitative measures best collected by other organizations, such as research foundations and governmental or intergovernmental agencies. We opened our toolkit to community comment and input. We present the resulting toolkit for use by government and philanthropic grantors, institutions, researchers and community organizations with the aim of measuring the implementation and impact of OS partnership across these organizations. We invite these and other stakeholders to not only measure, but to share the resulting data so that social scientists and policy makers can analyse the data across projects.
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Affiliation(s)
- E. Richard Gold
- Centre for Intellectual Property and Policy (CIPP), Faculty of Law, McGill University, Montreal, QC, H3A 1W9, Canada
- Department of Human Genetics, Faculty of Medicine, McGill University, Montreal, QC, H3A 0C7, Canada
| | - Sarah E. Ali-Khan
- Centre for Intellectual Property and Policy (CIPP), Faculty of Law, McGill University, Montreal, QC, H3A 1W9, Canada
- Tanenbaum Open Science Institute (TOSI), Montreal Neurological Institute and Hospital, Montreal, QC, H3A 2B4, Canada
| | | | - Lluis Ballell
- Diseases of the Developing World, Global Health R&D, GlaxoSmithKline, Madrid, Spain
| | | | | | - Damien Chalaud
- Montreal Neurological Institute and Hospital, Montreal, QC, H3A 2B4, Canada
| | | | - Matthew S. Clancy
- US Department of Agriculture Economic Research Service, Washington, DC, 20024, USA
| | | | | | | | | | - Lisa Federer
- US National Library of Medicine, Bethesda, MD, 20894, USA
| | - Steven A. Hill
- Research England, UK Research and Innovation, Bristol, BS34 8SR, UK
| | | | - Antoine Jean
- Centre for Intellectual Property and Policy (CIPP), Faculty of Law, McGill University, Montreal, QC, H3A 1W9, Canada
| | - Osmat Azzam Jefferson
- Queensland University of Technology, Brisbane, QLD, 4000, Australia
- The Lens, Canberra, ACT, 2601, Australia
| | | | | | | | - Sophie N. Kassel
- Centre for Intellectual Property and Policy (CIPP), Faculty of Law, McGill University, Montreal, QC, H3A 1W9, Canada
| | | | | | - Bianca Kramer
- Utrecht University Library, Utrecht, CX, 3584, The Netherlands
| | - Wen Hwa Lee
- Structural Genomics Consortium (SGC), University of Oxford, Oxford, OX3 7DQ, UK
| | - Emily MacDonald
- Centre for Intellectual Property and Policy (CIPP), Faculty of Law, McGill University, Montreal, QC, H3A 1W9, Canada
| | | | | | - Daniel Mietchen
- Data Science Institute, University of Virginia, Charlottesville, VA, 22904, USA
| | | | | | - Brian A. Nosek
- Department of Psychology, University of Virginia, Charlottesville, VA, 22904-4400, USA
- Center for Open Science, Charlottesville, VA, 22903-5083, USA
| | | | - Claude Pirmez
- Fundação Oswaldo Cruz - Fiocruz, Rio de Janeiro, RJ, 21040-900, Brazil
| | - Annabel Seyller
- Montreal Neurological Institute and Hospital, Montreal, QC, H3A 2B4, Canada
| | | | - S. Nicole Spadotto
- Centre for Intellectual Property and Policy (CIPP), Faculty of Law, McGill University, Montreal, QC, H3A 1W9, Canada
| | - Sophie Staniszewska
- Warwick Research in Nursing, University of Warwick Medical School, Coventry, CV4 7AL, UK
| | - Mike Thelwall
- University of Wolverhampton, Wolverhampton, WV1 1LY, UK
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30
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Affiliation(s)
- Daniel Mietchen
- Data Science Institute, University of Virginia, Charlottesville, Virginia, United States of America
- * E-mail:
| | - Shoshana Wodak
- Vlaams Instituut voor Biotechnologie-Vrije Universiteit Brussel Centre for Structural Biology, Brussels, Belgium
| | - Szymon Wasik
- Institute of Computing Science, Poznan University of Technology, Poznan, Poland
- European Centre for Bioinformatics and Genomics, Poznan University of Technology, Poznan, Poland
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland
| | - Natalia Szostak
- Institute of Computing Science, Poznan University of Technology, Poznan, Poland
- European Centre for Bioinformatics and Genomics, Poznan University of Technology, Poznan, Poland
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland
| | - Christophe Dessimoz
- University College London, London, United Kingdom
- University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
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31
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Maggio LA, Willinsky JM, Steinberg RM, Mietchen D, Wass JL, Dong T. Wikipedia as a gateway to biomedical research: The relative distribution and use of citations in the English Wikipedia. PLoS One 2017; 12:e0190046. [PMID: 29267345 PMCID: PMC5739466 DOI: 10.1371/journal.pone.0190046] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2017] [Accepted: 12/07/2017] [Indexed: 11/18/2022] Open
Abstract
Wikipedia is a gateway to knowledge. However, the extent to which this gateway ends at Wikipedia or continues via supporting citations is unknown. Wikipedia's gateway functionality has implications for information design and education, notably in medicine. This study aims to establish benchmarks for the relative distribution and referral (click) rate of citations-as indicated by presence of a Digital Object Identifier (DOI)-from Wikipedia, with a focus on medical citations. DOIs referred from the English Wikipedia in August 2016 were obtained from Crossref.org. Next, based on a DOI's presence on a WikiProject Medicine page, all DOIs in Wikipedia were categorized as medical (WP:MED) or non-medical (non-WP:MED). Using this categorization, referred DOIs were classified as WP:MED, non-WP:MED, or BOTH, meaning the DOI may have been referred from either category. Data were analyzed using descriptive and inferential statistics. Out of 5.2 million Wikipedia pages, 4.42% (n = 229,857) included at least one DOI. 68,870 were identified as WP:MED, with 22.14% (n = 15,250) featuring one or more DOIs. WP:MED pages featured on average 8.88 DOI citations per page, whereas non-WP:MED pages had on average 4.28 DOI citations. For DOIs only on WP:MED pages, a DOI was referred every 2,283 pageviews and for non-WP:MED pages every 2,467 pageviews. DOIs from BOTH pages accounted for 12% (n = 58,475). The referral of DOI citations found in BOTH could not be assigned to WP:MED or non-WP:MED, as the page from which the referral was made was not provided with the data. While these results cannot provide evidence of greater citation referral from WP:MED than non-WP:MED, they do provide benchmarks to assess strategies for changing referral patterns. These changes might include editors adopting new methods for designing and presenting citations or the introduction of teaching strategies that address the value of consulting citations as a tool for extending learning.
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Affiliation(s)
- Lauren A. Maggio
- Department of Medicine, Uniformed Services University of the Health Sciences. Bethesda, Maryland, United States of America
- * E-mail:
| | - John M. Willinsky
- Graduate School of Education, Stanford University, Stanford, California, United States of America
| | - Ryan M. Steinberg
- Lane Medical Library, Stanford Medicine, Stanford, California, United States of America
| | - Daniel Mietchen
- Data Science Institute, University of Virginia, Charlottesville, Virginia, United States of America
| | | | - Ting Dong
- Department of Medicine, Uniformed Services University of the Health Sciences. Bethesda, Maryland, United States of America
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Kittrie E, Atienza AA, Kiley R, Carr D, MacFarlane A, Pai V, Couch J, Bajkowski J, Bonner JF, Mietchen D, Bourne PE. Developing international open science collaborations: Funder reflections on the Open Science Prize. PLoS Biol 2017; 15:e2002617. [PMID: 28763440 PMCID: PMC5538631 DOI: 10.1371/journal.pbio.2002617] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
The Open Science Prize was established with the following objectives: first, to encourage the crowdsourcing of open data to make breakthroughs that are of biomedical significance; second, to illustrate that funders can indeed work together when scientific interests are aligned; and finally, to encourage international collaboration between investigators with the intent of achieving important innovations that would not be possible otherwise. The process for running the competition and the successes and challenges that arose are presented.
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Affiliation(s)
- Elizabeth Kittrie
- National Institutes of Health, Bethesda, Maryland, United States of America
- * E-mail: (EK); (PEB)
| | | | | | - David Carr
- Wellcome Trust, London, England, United Kingdom
| | | | - Vinay Pai
- National Institutes of Health, Bethesda, Maryland, United States of America
| | - Jennifer Couch
- National Institutes of Health, Bethesda, Maryland, United States of America
| | - Jared Bajkowski
- Howard Hughes Medical Institute, Bethesda, Maryland, United States of America
| | - Joseph F. Bonner
- National Institutes of Health, Bethesda, Maryland, United States of America
| | - Daniel Mietchen
- University of Virginia, Charlottesville, Virginia, United States of America
| | - Philip E. Bourne
- University of Virginia, Charlottesville, Virginia, United States of America
- * E-mail: (EK); (PEB)
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Tennant JP, Dugan JM, Graziotin D, Jacques DC, Waldner F, Mietchen D, Elkhatib Y, B. Collister L, Pikas CK, Crick T, Masuzzo P, Caravaggi A, Berg DR, Niemeyer KE, Ross-Hellauer T, Mannheimer S, Rigling L, Katz DS, Greshake Tzovaras B, Pacheco-Mendoza J, Fatima N, Poblet M, Isaakidis M, Irawan DE, Renaut S, Madan CR, Matthias L, Nørgaard Kjær J, O'Donnell DP, Neylon C, Kearns S, Selvaraju M, Colomb J. A multi-disciplinary perspective on emergent and future innovations in peer review. F1000Res 2017; 6:1151. [PMID: 29188015 PMCID: PMC5686505 DOI: 10.12688/f1000research.12037.3] [Citation(s) in RCA: 92] [Impact Index Per Article: 13.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/24/2017] [Indexed: 11/20/2022] Open
Abstract
Peer review of research articles is a core part of our scholarly communication system. In spite of its importance, the status and purpose of peer review is often contested. What is its role in our modern digital research and communications infrastructure? Does it perform to the high standards with which it is generally regarded? Studies of peer review have shown that it is prone to bias and abuse in numerous dimensions, frequently unreliable, and can fail to detect even fraudulent research. With the advent of web technologies, we are now witnessing a phase of innovation and experimentation in our approaches to peer review. These developments prompted us to examine emerging models of peer review from a range of disciplines and venues, and to ask how they might address some of the issues with our current systems of peer review. We examine the functionality of a range of social Web platforms, and compare these with the traits underlying a viable peer review system: quality control, quantified performance metrics as engagement incentives, and certification and reputation. Ideally, any new systems will demonstrate that they out-perform and reduce the biases of existing models as much as possible. We conclude that there is considerable scope for new peer review initiatives to be developed, each with their own potential issues and advantages. We also propose a novel hybrid platform model that could, at least partially, resolve many of the socio-technical issues associated with peer review, and potentially disrupt the entire scholarly communication system. Success for any such development relies on reaching a critical threshold of research community engagement with both the process and the platform, and therefore cannot be achieved without a significant change of incentives in research environments.
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Affiliation(s)
| | - Jonathan M. Dugan
- Berkeley Institute for Data Science, University of California, Berkeley, CA, USA
| | - Daniel Graziotin
- Institute of Software Technology, University of Stuttgart, Stuttgart, Germany
| | - Damien C. Jacques
- Earth and Life Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium
| | - François Waldner
- Earth and Life Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium
| | - Daniel Mietchen
- Data Science Institute, University of Virginia, Charlottesville, VA, USA
| | - Yehia Elkhatib
- School of Computing and Communications, Lancaster University, Lancaster, UK
| | | | | | - Tom Crick
- Cardiff Metropolitan University, Cardiff, UK
| | - Paola Masuzzo
- Department of Biochemistry, Ghent University, Ghent, Belgium
- VIB-UGent Center for Medical Biotechnology, Ghent, Belgium
| | - Anthony Caravaggi
- School of Biological, Earth and Environmental Sciences, University College Cork, Cork, Ireland
| | - Devin R. Berg
- Engineering & Technology Department, University of Wisconsin-Stout, Menomonie, WI, USA
| | - Kyle E. Niemeyer
- School of Mechanical, Industrial, and Manufacturing Engineering, Oregon State University, Corvallis, OR, USA
| | - Tony Ross-Hellauer
- State and University Library, University of Göttingen, Göttingen, Germany
| | | | | | - Daniel S. Katz
- School of Information Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL, USA
- Department of Computer Science, University of Illinois Urbana-Champaign, Urbana, IL, USA
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | | | | | - Nazeefa Fatima
- Department of Biology, Faculty of Science, Lund University, Lund, Sweden
| | - Marta Poblet
- Graduate School of Business and Law, RMIT University, Melbourne, Australia
| | - Marios Isaakidis
- Department of Computer Science, University College London, London, UK
| | - Dasapta Erwin Irawan
- Department of Groundwater Engineering, Faculty of Earth Sciences and Technology, Institut Teknologi Bandung, Bandung, Indonesia
| | - Sébastien Renaut
- Département de Sciences Biologiques, Institut de Recherche en Biologie Végétale, Université de Montréal, Montreal, QC, Canada
| | | | - Lisa Matthias
- OpenAIRE, University of Göttingen, Göttingen, Germany
| | - Jesper Nørgaard Kjær
- Department of Affective Disorders, Psychiatric Research Academy, Aarhus University Hospital, Risskov, Denmark
| | - Daniel Paul O'Donnell
- Department of English and Centre for the Study of Scholarly Communications, University of Lethbridge, Lethbridge, AB, Canada
| | - Cameron Neylon
- Centre for Culture and Technology, Curtin University, Perth, Australia
| | - Sarah Kearns
- Department of Chemical Biology, University of Michigan, Ann Arbor, MI, USA
| | - Manojkumar Selvaraju
- Integrated Gulf Biosystems, Riyadh, Saudi Arabia
- Saudi Human Genome Program, King Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia
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Tennant JP, Dugan JM, Graziotin D, Jacques DC, Waldner F, Mietchen D, Elkhatib Y, B. Collister L, Pikas CK, Crick T, Masuzzo P, Caravaggi A, Berg DR, Niemeyer KE, Ross-Hellauer T, Mannheimer S, Rigling L, Katz DS, Greshake Tzovaras B, Pacheco-Mendoza J, Fatima N, Poblet M, Isaakidis M, Irawan DE, Renaut S, Madan CR, Matthias L, Nørgaard Kjær J, O'Donnell DP, Neylon C, Kearns S, Selvaraju M, Colomb J. A multi-disciplinary perspective on emergent and future innovations in peer review. F1000Res 2017; 6:1151. [PMID: 29188015 PMCID: PMC5686505 DOI: 10.12688/f1000research.12037.1] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/13/2017] [Indexed: 11/20/2022] Open
Abstract
Peer review of research articles is a core part of our scholarly communication system. In spite of its importance, the status and purpose of peer review is often contested. What is its role in our modern digital research and communications infrastructure? Does it perform to the high standards with which it is generally regarded? Studies of peer review have shown that it is prone to bias and abuse in numerous dimensions, frequently unreliable, and can fail to detect even fraudulent research. With the advent of Web technologies, we are now witnessing a phase of innovation and experimentation in our approaches to peer review. These developments prompted us to examine emerging models of peer review from a range of disciplines and venues, and to ask how they might address some of the issues with our current systems of peer review. We examine the functionality of a range of social Web platforms, and compare these with the traits underlying a viable peer review system: quality control, quantified performance metrics as engagement incentives, and certification and reputation. Ideally, any new systems will demonstrate that they out-perform current models while avoiding as many of the biases of existing systems as possible. We conclude that there is considerable scope for new peer review initiatives to be developed, each with their own potential issues and advantages. We also propose a novel hybrid platform model that, at least partially, resolves many of the technical and social issues associated with peer review, and can potentially disrupt the entire scholarly communication system. Success for any such development relies on reaching a critical threshold of research community engagement with both the process and the platform, and therefore cannot be achieved without a significant change of incentives in research environments.
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Affiliation(s)
| | - Jonathan M. Dugan
- Berkeley Institute for Data Science, University of California, Berkeley, CA, USA
| | - Daniel Graziotin
- Institute of Software Technology, University of Stuttgart, Stuttgart, Germany
| | - Damien C. Jacques
- Earth and Life Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium
| | - François Waldner
- Earth and Life Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium
| | - Daniel Mietchen
- Data Science Institute, University of Virginia, Charlottesville, VA, USA
| | - Yehia Elkhatib
- School of Computing and Communications, Lancaster University, Lancaster, UK
| | | | | | - Tom Crick
- Cardiff Metropolitan University, Cardiff, UK
| | - Paola Masuzzo
- Department of Biochemistry, Ghent University, Ghent, Belgium
- VIB-UGent Center for Medical Biotechnology, Ghent, Belgium
| | - Anthony Caravaggi
- School of Biological, Earth and Environmental Sciences, University College Cork, Cork, Ireland
| | - Devin R. Berg
- Engineering & Technology Department, University of Wisconsin-Stout, Menomonie, WI, USA
| | - Kyle E. Niemeyer
- School of Mechanical, Industrial, and Manufacturing Engineering, Oregon State University, Corvallis, OR, USA
| | - Tony Ross-Hellauer
- State and University Library, University of Göttingen, Göttingen, Germany
| | | | | | - Daniel S. Katz
- School of Information Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL, USA
- Department of Computer Science, University of Illinois Urbana-Champaign, Urbana, IL, USA
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | | | | | - Nazeefa Fatima
- Department of Biology, Faculty of Science, Lund University, Lund, Sweden
| | - Marta Poblet
- Graduate School of Business and Law, RMIT University, Melbourne, Australia
| | - Marios Isaakidis
- Department of Computer Science, University College London, London, UK
| | - Dasapta Erwin Irawan
- Department of Groundwater Engineering, Faculty of Earth Sciences and Technology, Institut Teknologi Bandung, Bandung, Indonesia
| | - Sébastien Renaut
- Département de Sciences Biologiques, Institut de Recherche en Biologie Végétale, Université de Montréal, Montreal, QC, Canada
| | | | - Lisa Matthias
- OpenAIRE, University of Göttingen, Göttingen, Germany
| | - Jesper Nørgaard Kjær
- Department of Affective Disorders, Psychiatric Research Academy, Aarhus University Hospital, Risskov, Denmark
| | - Daniel Paul O'Donnell
- Department of English and Centre for the Study of Scholarly Communications, University of Lethbridge, Lethbridge, AB, Canada
| | - Cameron Neylon
- Centre for Culture and Technology, Curtin University, Perth, Australia
| | - Sarah Kearns
- Department of Chemical Biology, University of Michigan, Ann Arbor, MI, USA
| | - Manojkumar Selvaraju
- Integrated Gulf Biosystems, Riyadh, Saudi Arabia
- Saudi Human Genome Program, King Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia
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Tennant JP, Dugan JM, Graziotin D, Jacques DC, Waldner F, Mietchen D, Elkhatib Y, B. Collister L, Pikas CK, Crick T, Masuzzo P, Caravaggi A, Berg DR, Niemeyer KE, Ross-Hellauer T, Mannheimer S, Rigling L, Katz DS, Greshake Tzovaras B, Pacheco-Mendoza J, Fatima N, Poblet M, Isaakidis M, Irawan DE, Renaut S, Madan CR, Matthias L, Nørgaard Kjær J, O'Donnell DP, Neylon C, Kearns S, Selvaraju M, Colomb J. A multi-disciplinary perspective on emergent and future innovations in peer review. F1000Res 2017; 6:1151. [PMID: 29188015 PMCID: PMC5686505 DOI: 10.12688/f1000research.12037.2] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/14/2017] [Indexed: 12/22/2022] Open
Abstract
Peer review of research articles is a core part of our scholarly communication system. In spite of its importance, the status and purpose of peer review is often contested. What is its role in our modern digital research and communications infrastructure? Does it perform to the high standards with which it is generally regarded? Studies of peer review have shown that it is prone to bias and abuse in numerous dimensions, frequently unreliable, and can fail to detect even fraudulent research. With the advent of web technologies, we are now witnessing a phase of innovation and experimentation in our approaches to peer review. These developments prompted us to examine emerging models of peer review from a range of disciplines and venues, and to ask how they might address some of the issues with our current systems of peer review. We examine the functionality of a range of social Web platforms, and compare these with the traits underlying a viable peer review system: quality control, quantified performance metrics as engagement incentives, and certification and reputation. Ideally, any new systems will demonstrate that they out-perform and reduce the biases of existing models as much as possible. We conclude that there is considerable scope for new peer review initiatives to be developed, each with their own potential issues and advantages. We also propose a novel hybrid platform model that could, at least partially, resolve many of the socio-technical issues associated with peer review, and potentially disrupt the entire scholarly communication system. Success for any such development relies on reaching a critical threshold of research community engagement with both the process and the platform, and therefore cannot be achieved without a significant change of incentives in research environments.
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Affiliation(s)
| | - Jonathan M. Dugan
- Berkeley Institute for Data Science, University of California, Berkeley, CA, USA
| | - Daniel Graziotin
- Institute of Software Technology, University of Stuttgart, Stuttgart, Germany
| | - Damien C. Jacques
- Earth and Life Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium
| | - François Waldner
- Earth and Life Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium
| | - Daniel Mietchen
- Data Science Institute, University of Virginia, Charlottesville, VA, USA
| | - Yehia Elkhatib
- School of Computing and Communications, Lancaster University, Lancaster, UK
| | | | | | - Tom Crick
- Cardiff Metropolitan University, Cardiff, UK
| | - Paola Masuzzo
- Department of Biochemistry, Ghent University, Ghent, Belgium
- VIB-UGent Center for Medical Biotechnology, Ghent, Belgium
| | - Anthony Caravaggi
- School of Biological, Earth and Environmental Sciences, University College Cork, Cork, Ireland
| | - Devin R. Berg
- Engineering & Technology Department, University of Wisconsin-Stout, Menomonie, WI, USA
| | - Kyle E. Niemeyer
- School of Mechanical, Industrial, and Manufacturing Engineering, Oregon State University, Corvallis, OR, USA
| | - Tony Ross-Hellauer
- State and University Library, University of Göttingen, Göttingen, Germany
| | | | | | - Daniel S. Katz
- School of Information Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL, USA
- Department of Computer Science, University of Illinois Urbana-Champaign, Urbana, IL, USA
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | | | | | - Nazeefa Fatima
- Department of Biology, Faculty of Science, Lund University, Lund, Sweden
| | - Marta Poblet
- Graduate School of Business and Law, RMIT University, Melbourne, Australia
| | - Marios Isaakidis
- Department of Computer Science, University College London, London, UK
| | - Dasapta Erwin Irawan
- Department of Groundwater Engineering, Faculty of Earth Sciences and Technology, Institut Teknologi Bandung, Bandung, Indonesia
| | - Sébastien Renaut
- Département de Sciences Biologiques, Institut de Recherche en Biologie Végétale, Université de Montréal, Montreal, QC, Canada
| | | | - Lisa Matthias
- OpenAIRE, University of Göttingen, Göttingen, Germany
| | - Jesper Nørgaard Kjær
- Department of Affective Disorders, Psychiatric Research Academy, Aarhus University Hospital, Risskov, Denmark
| | - Daniel Paul O'Donnell
- Department of English and Centre for the Study of Scholarly Communications, University of Lethbridge, Lethbridge, AB, Canada
| | - Cameron Neylon
- Centre for Culture and Technology, Curtin University, Perth, Australia
| | - Sarah Kearns
- Department of Chemical Biology, University of Michigan, Ann Arbor, MI, USA
| | - Manojkumar Selvaraju
- Integrated Gulf Biosystems, Riyadh, Saudi Arabia
- Saudi Human Genome Program, King Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia
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Littler K, Boon WM, Carson G, Depoortere E, Mathewson S, Mietchen D, Moorthy VS, O'Connor D, Roth C, Segovia C. Progress in promoting data sharing in public health emergencies. Bull World Health Organ 2017; 95:243. [PMID: 28479616 PMCID: PMC5407259 DOI: 10.2471/blt.17.192096] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
Affiliation(s)
- Katherine Littler
- Wellcome Trust, Gibbs Building, 215 Euston Road, London NW1 2BE, England
| | - Wee-Ming Boon
- Research Policy and Translation, National Health and Medical Research Council, Melbourne, Australia
| | - Gail Carson
- Nuffield Department of Medicine, University of Oxford, Oxford, England
| | - Evelyn Depoortere
- Directorate-General for Research and Innovation, European Commission, Brussels, Belgium
| | - Sophie Mathewson
- Wellcome Trust, Gibbs Building, 215 Euston Road, London NW1 2BE, England
| | - Daniel Mietchen
- National Library of Medicine, National Institutes of Health, Bethesda, United States of America
| | - Vasee S Moorthy
- Information, Evidence and Research, World Health Organization, Geneva, Switzerland
| | - Denise O'Connor
- Directorate-General for Research and Innovation, European Commission, Brussels, Belgium
| | - Cathy Roth
- Department for International Development, the Government of the United Kingdom of Great Britain and Northern Ireland, London, England
| | - Carlos Segovia
- Directorate for Research Evaluation and Promotion, Instituto de Salud Carlos III, Madrid, Spain
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Penev L, Mietchen D, Chavan V, Hagedorn G, Smith V, Shotton D, Ó Tuama É, Senderov V, Georgiev T, Stoev P, Groom Q, Remsen D, Edmunds S. Strategies and guidelines for scholarly publishing of biodiversity data. RIO 2017. [DOI: 10.3897/rio.3.e12431] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
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Chodacki J, Lemberger T, Lin J, Martone M, Mietchen D, Polka J, Sever R, Strasser C. Technical aspects of preprint services in the life sciences: a workshop report. RIO 2017. [DOI: 10.3897/rio.3.e11825] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
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Koureas D, Arvanitidis C, Belbin L, Berendsohn W, Damgaard C, Groom Q, Güntsch A, Hagedorn G, Hardisty A, Hobern D, Marcer A, Mietchen D, Morse D, Obst M, Penev L, Pettersson L, Sierra S, Smith V, Vos R. Community engagement: The ‘last mile’ challenge for European research e-infrastructures. RIO 2016. [DOI: 10.3897/rio.2.e9933] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
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Welch L, Brooksbank C, Schwartz R, Morgan SL, Gaeta B, Kilpatrick AM, Mietchen D, Moore BL, Mulder N, Pauley M, Pearson W, Radivojac P, Rosenberg N, Rosenwald A, Rustici G, Warnow T. Applying, Evaluating and Refining Bioinformatics Core Competencies (An Update from the Curriculum Task Force of ISCB's Education Committee). PLoS Comput Biol 2016; 12:e1004943. [PMID: 27175996 PMCID: PMC4866758 DOI: 10.1371/journal.pcbi.1004943] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Affiliation(s)
- Lonnie Welch
- School of Electrical Engineering and Computer Science, Ohio University, Athens, Ohio, United States of America
- * E-mail:
| | - Cath Brooksbank
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Russell Schwartz
- Department of Biological Sciences and Computational Biology Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
| | - Sarah L. Morgan
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Bruno Gaeta
- School of Computer Science and Engineering, UNSW, Sydney, New South Wales, Australia
| | - Alastair M. Kilpatrick
- Department of Pediatrics, University of California San Diego, La Jolla, California, United States of America
| | - Daniel Mietchen
- National Institutes of Health, Bethesda, Maryland, United States of America
| | - Benjamin L. Moore
- MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Nicola Mulder
- Computational Biology group, Department of Integrative Biomedical Sciences, IDM, University of Cape Town, Cape Town, South Africa
| | - Mark Pauley
- School of Interdisciplinary Informatics, University of Nebraska at Omaha, Omaha, Nebraska, United States of America
| | - William Pearson
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, Virginia, United States of America
| | - Predrag Radivojac
- School of Informatics and Computing, Indiana University, Bloomington, Indiana, United States of America
| | - Naomi Rosenberg
- Tufts University School of Medicine, Boston, Massachusetts, United States of America
| | - Anne Rosenwald
- Department of Biology, Georgetown University, Washington, D.C., United States of America
| | - Gabriella Rustici
- School of the Biological Sciences, University of Cambridge, Cambridge Systems Biology Centre, Cambridge, United Kingdom
| | - Tandy Warnow
- Departments of Computer Science and Bioengineering, University of Illinois, Urbana, Illinois, United States of America
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Egloff W, Agosti D, Patterson D, Hoffmann A, Mietchen D, Kishor P, Penev L. Data Policy Recommendations for Biodiversity Data. EU BON Project Report. RIO 2016. [DOI: 10.3897/rio.2.e8458] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
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Ekins S, Mietchen D, Coffee M, Stratton TP, Freundlich JS, Freitas-Junior L, Muratov E, Siqueira-Neto J, Williams AJ, Andrade C. Open drug discovery for the Zika virus. F1000Res 2016; 5:150. [PMID: 27134728 PMCID: PMC4841202 DOI: 10.12688/f1000research.8013.1] [Citation(s) in RCA: 44] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/08/2016] [Indexed: 01/20/2023] Open
Abstract
The Zika virus (ZIKV) outbreak in the Americas has caused global concern that we may be on the brink of a healthcare crisis. The lack of research on ZIKV in the over 60 years that we have known about it has left us with little in the way of starting points for drug discovery. Our response can build on previous efforts with virus outbreaks and lean heavily on work done on other flaviviruses such as dengue virus. We provide some suggestions of what might be possible and propose an open drug discovery effort that mobilizes global science efforts and provides leadership, which thus far has been lacking. We also provide a listing of potential resources and molecules that could be prioritized for testing as
in vitro assays for ZIKV are developed. We propose also that in order to incentivize drug discovery, a neglected disease priority review voucher should be available to those who successfully develop an FDA approved treatment. Learning from the response to the ZIKV, the approaches to drug discovery used and the success and failures will be critical for future infectious disease outbreaks.
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Affiliation(s)
- Sean Ekins
- Collaborations in Chemistry Inc, Fuquay-Varina, NC, USA; Collaborations Pharmaceuticals Inc., Fuquay-Varina, NC, USA; Collaborative Drug Discovery Inc., Burlingame, CA, USA
| | | | - Megan Coffee
- The International Rescue Committee , NY, NY, USA
| | - Thomas P Stratton
- Department of Pharmacology, Physiology and Neuroscience, Rutgers University-New Jersey Medical School, Newark, NJ, USA
| | - Joel S Freundlich
- Department of Pharmacology, Physiology and Neuroscience, Rutgers University-New Jersey Medical School, Newark, NJ, USA; Division of Infectious Diseases, Department of Medicine, and the Ruy V. Lourenço Center for the Study of Emerging and Re-emerging Pathogens, Rutgers University-New Jersey Medical School, Newark, NJ, USA
| | - Lucio Freitas-Junior
- Chemical Biology and Screening Platform, Brazilian Laboratory of Biosciences (LNBio), CNPEM, Campinas, Brazil
| | - Eugene Muratov
- Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA
| | - Jair Siqueira-Neto
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, San Diego, CA, USA
| | | | - Carolina Andrade
- LabMol - Laboratory for Molecular Modeling and Drug Design, Faculty of Pharmacy, Federal University of Goias, Goiânia, Brazil
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Mietchen D, Hagedorn G, Willighagen E, Rico M, Gómez-Pérez A, Aibar E, Rafes K, Germain C, Dunning A, Pintscher L, Kinzler D. Enabling Open Science: Wikidata for Research (Wiki4R). RIO 2015. [DOI: 10.3897/rio.1.e7573] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
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Abstract
This Perspective extends an ongoing debate on transparency in research funding, advocating the exploration of more radical approaches. Central to research funding are grant proposals that researchers send in to potential funders for review, in the hope of approval. A survey of policies at major research funders found that there is room for more transparency in the process of grant review, which would strengthen the case for the efficiency of public spending on research. On that basis, debate was invited on which transparency measures should be implemented and how, with some concrete suggestions at hand. The present article adds to this discussion by providing further context from the literature, along with considerations on the effect size of the proposed measures. The article then explores the option of opening to the public key components of the process, makes the case for pilot projects in this area, and sketches out the potential that such measures might have to transform the research landscape in those areas in which they are implemented.
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Affiliation(s)
- Daniel Mietchen
- Museum für Naturkunde Berlin, Leibniz-Institut für Evolutions- und Biodiversitätsforschung, Berlin, Germany
- * E-mail:
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Vos RA, Biserkov JV, Balech B, Beard N, Blissett M, Brenninkmeijer C, van Dooren T, Eades D, Gosline G, Groom QJ, Hamann TD, Hettling H, Hoehndorf R, Holleman A, Hovenkamp P, Kelbert P, King D, Kirkup D, Lammers Y, DeMeulemeester T, Mietchen D, Miller JA, Mounce R, Nicolson N, Page R, Pawlik A, Pereira S, Penev L, Richards K, Sautter G, Shorthouse DP, Tähtinen M, Weiland C, Williams AR, Sierra S. Enriched biodiversity data as a resource and service. Biodivers Data J 2014:e1125. [PMID: 25057255 PMCID: PMC4092319 DOI: 10.3897/bdj.2.e1125] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2014] [Accepted: 06/11/2014] [Indexed: 11/28/2022] Open
Abstract
Background: Recent years have seen a surge in projects that produce large volumes of structured, machine-readable biodiversity data. To make these data amenable to processing by generic, open source “data enrichment” workflows, they are increasingly being represented in a variety of standards-compliant interchange formats. Here, we report on an initiative in which software developers and taxonomists came together to address the challenges and highlight the opportunities in the enrichment of such biodiversity data by engaging in intensive, collaborative software development: The Biodiversity Data Enrichment Hackathon. Results: The hackathon brought together 37 participants (including developers and taxonomists, i.e. scientific professionals that gather, identify, name and classify species) from 10 countries: Belgium, Bulgaria, Canada, Finland, Germany, Italy, the Netherlands, New Zealand, the UK, and the US. The participants brought expertise in processing structured data, text mining, development of ontologies, digital identification keys, geographic information systems, niche modeling, natural language processing, provenance annotation, semantic integration, taxonomic name resolution, web service interfaces, workflow tools and visualisation. Most use cases and exemplar data were provided by taxonomists. One goal of the meeting was to facilitate re-use and enhancement of biodiversity knowledge by a broad range of stakeholders, such as taxonomists, systematists, ecologists, niche modelers, informaticians and ontologists. The suggested use cases resulted in nine breakout groups addressing three main themes: i) mobilising heritage biodiversity knowledge; ii) formalising and linking concepts; and iii) addressing interoperability between service platforms. Another goal was to further foster a community of experts in biodiversity informatics and to build human links between research projects and institutions, in response to recent calls to further such integration in this research domain. Conclusions: Beyond deriving prototype solutions for each use case, areas of inadequacy were discussed and are being pursued further. It was striking how many possible applications for biodiversity data there were and how quickly solutions could be put together when the normal constraints to collaboration were broken down for a week. Conversely, mobilising biodiversity knowledge from their silos in heritage literature and natural history collections will continue to require formalisation of the concepts (and the links between them) that define the research domain, as well as increased interoperability between the software platforms that operate on these concepts.
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Affiliation(s)
| | | | - Bachir Balech
- Institute of Biomembranes and Bioenergetics, National Research Council, Bari, Italy
| | - Niall Beard
- University of Manchester, Manchester, United Kingdom
| | | | | | | | - David Eades
- The Illinois Natural History Survey, Champaign, United States of America
| | | | | | | | | | | | | | | | - Patricia Kelbert
- Botanic Garden and Botanical Museum Berlin-Dahlem, Freie Universität Berlin, Berlin, Germany
| | - David King
- The Open University, Milton Keynes, United Kingdom
| | - Don Kirkup
- Royal Botanic Gardens, Kew, United Kingdom
| | | | | | | | | | | | | | - Rod Page
- University Of Glasgow, Glasgow, United Kingdom
| | | | | | | | - Kevin Richards
- Biodiversity Informatics Consultant, Christchurch, New Zealand
| | | | | | | | - Claus Weiland
- Biodiversity and Climate Research Centre, Senckenberg Gesellschaft für Naturforschung, Frankfurt, Germany
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Stoev P, Komerički A, Akkari N, Liu S, Zhou X, Weigand AM, Hostens J, Hunter CI, Edmunds SC, Porco D, Zapparoli M, Georgiev T, Mietchen D, Roberts D, Faulwetter S, Smith V, Penev L. Eupolybothrus cavernicolus Komerički & Stoev sp. n. (Chilopoda: Lithobiomorpha: Lithobiidae): the first eukaryotic species description combining transcriptomic, DNA barcoding and micro-CT imaging data. Biodivers Data J 2013; 1:e1013. [PMID: 24723752 PMCID: PMC3964625 DOI: 10.3897/bdj.1.e1013] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2013] [Accepted: 10/23/2013] [Indexed: 12/29/2022] Open
Abstract
We demonstrate how a classical taxonomic description of a new species can be enhanced by applying new generation molecular methods, and novel computing and imaging technologies. A cave-dwelling centipede, Eupolybothrus cavernicolus Komerički & Stoev sp. n. (Chilopoda: Lithobiomorpha: Lithobiidae), found in a remote karst region in Knin, Croatia, is the first eukaryotic species for which, in addition to the traditional morphological description, we provide a fully sequenced transcriptome, a DNA barcode, detailed anatomical X-ray microtomography (micro-CT) scans, and a movie of the living specimen to document important traits of its ex-situ behaviour. By employing micro-CT scanning in a new species for the first time, we create a high-resolution morphological and anatomical dataset that allows virtual reconstructions of the specimen and subsequent interactive manipulation to test the recently introduced 'cybertype' notion. In addition, the transcriptome was recorded with a total of 67,785 scaffolds, having an average length of 812 bp and N50 of 1,448 bp (see GigaDB). Subsequent annotation of 22,866 scaffolds was conducted by tracing homologs against current available databases, including Nr, SwissProt and COG. This pilot project illustrates a workflow of producing, storing, publishing and disseminating large data sets associated with a description of a new taxon. All data have been deposited in publicly accessible repositories, such as GigaScience GigaDB, NCBI, BOLD, Morphbank and Morphosource, and the respective open licenses used ensure their accessibility and re-usability.
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Affiliation(s)
- Pavel Stoev
- National Museum of Natural History, Sofia, Bulgaria
- Pensoft Publishers, Sofia, Bulgaria
| | | | - Nesrine Akkari
- Natural History Museum of Denmark, University of Copenhagen, Copenhagen, Denmark
| | - Shanlin Liu
- China National GeneBank, BGI-Shenzhen, Shenzhen, China
| | - Xin Zhou
- China National GeneBank, BGI-Shenzhen, Shenzhen, China
| | - Alexander M. Weigand
- Croatian Biospeleological Society, Zagreb, Croatia
- Goethe-University, Institute for Ecology, Evolution and Diversity, Frankfurt am Main, Germany
| | | | | | | | - David Porco
- Université de Rouen - Laboratoire ECODIV, Mont Saint Aignan Cedex, France
| | - Marzio Zapparoli
- Università degli Studi della Tuscia, Department for Innovation in Biological, Agro-food and Forest systems (DIBAF), Viterbo, Italy
| | | | - Daniel Mietchen
- Pensoft Publishers, Sofia, Bulgaria
- Museum für Naturkunde – Leibniz-Institut für Evolutions- und Biodiversitätsforschung, Berlin, Germany
| | | | - Sarah Faulwetter
- National and Kapodestrian University of Athens, Athens, Greece
- Hellenic Centre for Marine Research, Heraklion, Greece
| | | | - Lyubomir Penev
- Institute of Biodiversity & Ecosystem Research - Bulgarian Academy of Sciences and Pensoft Publishers, Sofia, Bulgaria
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