1
|
Meyer R, Davies N, Pitz KJ, Meyer C, Samuel R, Anderson J, Appeltans W, Barker K, Chavez FP, Duffy JE, Goodwin KD, Hudson M, Hunter ME, Karstensen J, Laney CM, Leinen M, Mabee P, Macklin JA, Muller-Karger F, Pade N, Pearlman J, Phillips L, Provoost P, Santi I, Schigel D, Schriml LM, Soccodato A, Suominen S, Thibault KM, Ung V, van de Kamp J, Wallis E, Walls R, Buttigieg PL. The founding charter of the Omic Biodiversity Observation Network (Omic BON). Gigascience 2022; 12:giad068. [PMID: 37632753 PMCID: PMC10460158 DOI: 10.1093/gigascience/giad068] [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: 06/29/2023] [Revised: 07/31/2023] [Accepted: 07/31/2023] [Indexed: 08/28/2023] Open
Abstract
Omic BON is a thematic Biodiversity Observation Network under the Group on Earth Observations Biodiversity Observation Network (GEO BON), focused on coordinating the observation of biomolecules in organisms and the environment. Our founding partners include representatives from national, regional, and global observing systems; standards organizations; and data and sample management infrastructures. By coordinating observing strategies, methods, and data flows, Omic BON will facilitate the co-creation of a global omics meta-observatory to generate actionable knowledge. Here, we present key elements of Omic BON's founding charter and first activities.
Collapse
Affiliation(s)
- Raïssa Meyer
- HGF MPG Joint Research Group for Deep-Sea Ecology and Technology, Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven 27570, Germany
- Faculty of Geosciences, University of Bremen, Bremen 28359, Germany
- HGF MPG Joint Research Group for Deep-Sea Ecology and Technology, Max Planck Institute for Marine Microbiology, Bremen 28359, Germany
| | - Neil Davies
- Gump South Pacific Research Station, University of California Berkeley, Moorea 98728, French Polynesia
- Berkeley Institute for Data Science, University of California, Berkeley, CA 94720, USA
| | - Kathleen J Pitz
- Science Department, Monterey Bay Aquarium Research Institute, Moss Landing, CA 95039, USA
| | - Chris Meyer
- Department of Invertebrate Zoology, National Museum of Natural History, Smithsonian Institution, Washington, DC 20560, USA
| | - Robyn Samuel
- School of Ocean and Earth Science, University of Southampton, Southampton SO17 1BJ, UK
- Ocean Technology and Engineering Group, National Oceanography Center, Southampton SO14 3ZH, UK
| | - Jane Anderson
- Department of Anthropology, New York University, New York City, NY 10012, USA
| | - Ward Appeltans
- Intergovernmental Oceanographic Commission of UNESCO, Ocean Biodiversity Information System, Oostende 8400, Begium
| | - Katharine Barker
- Global Genome Biodiversity Network Secretariat Office, National Museum of Natural History, Smithsonian Institution, Washington, DC 20560, USA
| | - Francisco P Chavez
- Science Department, Monterey Bay Aquarium Research Institute, Moss Landing, CA 95039, USA
| | - J Emmett Duffy
- Tennenbaum Marine Observatories Network and MarineGEO Program, Smithsonian Environmental Research Center, Edgewater, MD 21037, USA
| | - Kelly D Goodwin
- National Oceanic & Atmospheric Administration, NOAA Ocean Exploration, La Jolla, CA 92037, USA
| | - Maui Hudson
- Te Kotahi Research Institute, University of Waikato, Hamilton 3240, New Zealand
| | - Margaret E Hunter
- Wetland and Aquatic Research Center, U.S. Geological Survey, Gainesville, FL 32653, USA
| | - Johannes Karstensen
- Department of Physical Oceanography, GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel 24105, Germany
| | - Christine M Laney
- Science department, National Ecological Observatory Network, Boulder, CO 80301, USA
| | - Margaret Leinen
- Geosciences Research Division, Scripps Institution of Oceanography, La Jolla, CA 92093, USA
| | - Paula Mabee
- Observatory Leadership department, National Ecological Observatory Network, Boulder, CO 80301, USA
| | - James A Macklin
- Botany and Biodiversity Informatics, Agriculture and Agri-Food Canada (AAFC), Ottawa, Ontario K1A 0C6, Canada
| | - Frank Muller-Karger
- College of Marine Science, University of South Florida, St. Petersburg, FL 33701, USA
| | - Nicolas Pade
- European Marine Biological Resource Centre (EMBRC-ERIC), Paris 75252, France
| | | | - Lori Phillips
- Agriculture and Agri-Food Canada (AAFC), Harrow N0R 1G0, Ontario, Canada
| | - Pieter Provoost
- Intergovernmental Oceanographic Commission of UNESCO, Ocean Biodiversity Information System, Oostende 8400, Begium
| | - Ioulia Santi
- European Marine Biological Resource Centre (EMBRC-ERIC), Paris 75252, France
- Hellenic Centre for Marine Research (HCMR), Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Heraklion GR71003, Greece
| | - Dmitry Schigel
- GBIF | Global Biodiversity Information Facility, Copenhagen DK-2100, Denmark
| | - Lynn M Schriml
- Epidemiology & Public Health, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Alice Soccodato
- European Marine Biological Resource Centre (EMBRC-ERIC), Paris 75252, France
| | - Saara Suominen
- Intergovernmental Oceanographic Commission of UNESCO, Ocean Biodiversity Information System, Oostende 8400, Begium
| | - Katherine M Thibault
- Science department, National Ecological Observatory Network, Boulder, CO 80301, USA
| | | | | | | | - Ramona Walls
- Data Science department, Critical Path Institute, Tucson, AZ 85718, USA
| | - Pier Luigi Buttigieg
- HGF MPG Joint Research Group for Deep-Sea Ecology and Technology, Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven 27570, Germany
- Information, Data and Computer Center, Helmholtz Metadata Collaboration/GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel 24105, Germany
| |
Collapse
|
2
|
Hardisty AR, Ellwood ER, Nelson G, Zimkus B, Buschbom J, Addink W, Rabeler RK, Bates J, Bentley A, Fortes JAB, Hansen S, Macklin JA, Mast AR, Miller JT, Monfils AK, Paul DL, Wallis E, Webster M. Digital Extended Specimens: Enabling an Extensible Network of Biodiversity Data Records as Integrated Digital Objects on the Internet. Bioscience 2022; 72:978-987. [PMID: 36196222 PMCID: PMC9525127 DOI: 10.1093/biosci/biac060] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The early twenty-first century has witnessed massive expansions in availability and accessibility of digital data in virtually all domains of the biodiversity sciences. Led by an array of asynchronous digitization activities spanning ecological, environmental, climatological, and biological collections data, these initiatives have resulted in a plethora of mostly disconnected and siloed data, leaving to researchers the tedious and time-consuming manual task of finding and connecting them in usable ways, integrating them into coherent data sets, and making them interoperable. The focus to date has been on elevating analog and physical records to digital replicas in local databases prior to elevating them to ever-growing aggregations of essentially disconnected discipline-specific information. In the present article, we propose a new interconnected network of digital objects on the Internet—the Digital Extended Specimen (DES) network—that transcends existing aggregator technology, augments the DES with third-party data through machine algorithms, and provides a platform for more efficient research and robust interdisciplinary discovery.
Collapse
Affiliation(s)
| | | | - Gil Nelson
- Florida Museum of Natural History , Gainesville, Florida, United States
| | - Breda Zimkus
- Museum of Comparative Zoology , Cambridge, Massachusetts, United States
| | | | | | - Richard K Rabeler
- University of Michigan Herbarium , Ann Arbor, Michigan, United States
| | - John Bates
- Field Museum of Natural History , Chicago, Illinois, United States
| | - Andrew Bentley
- Biodiversity Institute, University of Kansas , Lawrence, Kansas, United States
| | | | - Sara Hansen
- Central Michigan University Herbarium, Central Michigan University , Mt. Pleasant, Michigan, United States
| | | | - Austin R Mast
- Department of Biological Science, Florida State University , Tallahassee, Florida, United States
| | - Joseph T Miller
- Global Biodiversity Information Facility Secretariat , Copenhagen, Denmark
| | - Anna K Monfils
- Central Michigan University Herbarium, Central Michigan University , Mt. Pleasant, Michigan, United States
| | - Deborah L Paul
- University of Illinois Urbana Champaign , Champaign, Illinois, United States
| | - Elycia Wallis
- Atlas of Living Australia, CSIRO , Melbourne, Australia
| | - Michael Webster
- Macaulay Library, Cornell Lab of Ornithology , Ithaca, New York, United States
| |
Collapse
|
3
|
Cui H, Ford B, Starr J, Reznicek A, Zhang L, Macklin JA. Authors’ attitude toward adopting a new workflow to improve the computability of phenotype publications. Database (Oxford) 2022; 2022:6519872. [PMID: 35106535 PMCID: PMC9278328 DOI: 10.1093/database/baac001] [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] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 11/24/2021] [Accepted: 01/10/2022] [Indexed: 11/13/2022]
Abstract
Critical to answering large-scale questions in biology is the integration of knowledge from different disciplines into a coherent, computable whole. Controlled vocabularies such as ontologies represent a clear path toward this goal. Using survey questionnaires, we examined the attitudes of biologists toward adopting controlled vocabularies in phenotype publications. Our questions cover current experience and overall attitude with controlled vocabularies, the awareness of the issues around ambiguity and inconsistency in phenotype descriptions and post-publication professional data curation, the preferred solutions and the effort and desired rewards for adopting a new authoring workflow. Results suggest that although the existence of controlled vocabularies is widespread, their use is not common. A majority of respondents (74%) are frustrated with ambiguity in phenotypic descriptions, and there is a strong agreement (mean agreement score 4.21 out of 5) that author curation would better reflect the original meaning of phenotype data. Moreover, the vast majority (85%) of researchers would try a new authoring workflow if resultant data were more consistent and less ambiguous. Even more respondents (93%) suggested that they would try and possibly adopt a new authoring workflow if it required 5% additional effort as compared to normal, but higher rates resulted in a steep decline in likely adoption rates. Among the four different types of rewards, two types of citations were the most desired incentives for authors to produce computable data. Overall, our results suggest the adoption of a new authoring workflow would be accelerated by a user-friendly and efficient software-authoring tool, an increased awareness of the challenges text ambiguity creates for external curators and an elevated appreciation of the benefits of controlled vocabularies.
Collapse
Affiliation(s)
- Hong Cui
- School of Information, University of Arizona , 1103 E. Second Street, Tucson, AZ 85705, USA
| | - Bruce Ford
- Department of Biological Sciences, University of Manitoba , 50 Sifton Road, Winnipeg, MB R3T 2N2, Canada
| | - Julian Starr
- Department of Biology, University of Ottawa , 30 Marie Curie Road, Ottawa, ON K1N 6N5, Canada
| | - Anton Reznicek
- SLA Herbarium, University of Michigan , 3600 Varsity Drive #1046, Ann Arbor, MI 48019, USA
| | - Limin Zhang
- School of Information, University of Arizona , 1103 E. Second Street, Tucson, AZ 85705, USA
| | - James A Macklin
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada , 960 Carling Avenue, Ottawa, ON K1A 0C6, Canada
| |
Collapse
|
4
|
Zhang L, Yang X, Cota Z, Cui H, Ford B, Chen HL, Macklin JA, Reznicek A, Starr J. Which methods are the most effective in enabling novice users to participate in ontology creation? A usability study. Database (Oxford) 2021; 2021:baab035. [PMID: 34156445 PMCID: PMC8218699 DOI: 10.1093/database/baab035] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Revised: 04/02/2021] [Accepted: 05/22/2021] [Indexed: 11/14/2022]
Abstract
Producing findable, accessible, interoperable and reusable (FAIR) data cannot be accomplished solely by data curators in all disciplines. In biology, we have shown that phenotypic data curation is not only costly, but it is burdened with inter-curator variation. We intend to propose a software platform that would enable all data producers, including authors of scientific publications, to produce ontologized data at the time of publication. Working toward this goal, we need to identify ontology construction methods that are preferred by end users. Here, we employ two usability studies to evaluate effectiveness, efficiency and user satisfaction with a set of four methods that allow an end user to add terms and their relations to an ontology. Thirty-three participants took part in a controlled experiment where they evaluated the four methods (Quick Form, Wizard, WebProtégé and Wikidata) after watching demonstration videos and completing a hands-on task. Another think-aloud study was conducted with three professional botanists. The efficiency effectiveness and user confidence in the methods are clearly revealed through statistical and content analyses of participants' comments. Quick Form, Wizard and WebProtégé offer distinct strengths that would benefit our author-driven FAIR data generation system. Features preferred by the participants will guide the design of future iterations.
Collapse
Affiliation(s)
- Limin Zhang
- School of Information, University of Arizona, 1103 E. Second Street, Tucson, AZ 85705, USA
| | - Xingyi Yang
- School of Information, University of Arizona, 1103 E. Second Street, Tucson, AZ 85705, USA
| | - Zuleima Cota
- School of Information, University of Arizona, 1103 E. Second Street, Tucson, AZ 85705, USA
| | - Hong Cui
- School of Information, University of Arizona, 1103 E. Second Street, Tucson, AZ 85705, USA
| | - Bruce Ford
- Department of Biological Sciences, University of Manitoba, 50 Sifton Road, Winnipeg, MB R3T 2N2, Canada
| | - Hsin-liang Chen
- Curtis Laws Wilson Library, Missouri University of Science and Technology, 400 W. 14th Street, Rolla, MO 65409, USA
| | - James A Macklin
- Information protected by Canada government, Agriculture and Agri-Food Canada, Ottawa, ON K1A 0C6, Canada
| | - Anton Reznicek
- SLA Herbarium, University of Michigan, 3600 Varsity Drive, Ann Arbor, MI 48019, USA
| | - Julian Starr
- Department of Biology, University of Ottawa, 30 Marie Curie Road, Ottawa, ON K1N 6N5, Canada
| |
Collapse
|
5
|
Francis A, Lujan-Toro BE, Warwick SI, Macklin JA, Martin SL. Update on the Brassicaceae species checklist. Biodivers Data J 2021; 9:e58773. [PMID: 33716543 PMCID: PMC7952366 DOI: 10.3897/bdj.9.e58773] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [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: 09/18/2020] [Accepted: 01/13/2021] [Indexed: 11/16/2022] Open
Abstract
Background Here we present a revised species checklist for the Brassicaceae, updated from Warwick SI, Francis, A, Al-Shehbaz IA (2006), Brassicaceae: Species checklist and database on CD-ROM, Plant Systematics and Evolution 259: 249─25. This update of the checklist was initiated, based on recent taxonomic and molecular studies on the Brassicaceae that have resulted in new species names, combinations and associated synonyms. New information New data have been added indicating tribal affiliations within the family and where type specimens have been designated. In addition, information from many early publications has been checked and added to the database. The database now includes information on 14983 taxa, 4636 of which are currently accepted and divided into 340 genera and 52 tribes. A selected bibliography of recent publications on the Brassicaceae is included.
Collapse
Affiliation(s)
- Ardath Francis
- Agriculture and Agri-Food Canada, Ottawa, Canada Agriculture and Agri-Food Canada Ottawa Canada
| | - Beatriz E Lujan-Toro
- Agriculture and Agri-Food Canada, Ottawa, Canada Agriculture and Agri-Food Canada Ottawa Canada
| | - Suzanne I Warwick
- Agriculture and Agri-Food Canada, Ottawa, Canada Agriculture and Agri-Food Canada Ottawa Canada
| | - James A Macklin
- Agriculture and Agri-Food Canada, Ottawa, Canada Agriculture and Agri-Food Canada Ottawa Canada
| | - Sara L Martin
- Agriculture and Agri-Food Canada, Ottawa, Canada Agriculture and Agri-Food Canada Ottawa Canada
| |
Collapse
|
6
|
Ryan MJ, Schloter M, Berg G, Kostic T, Kinkel LL, Eversole K, Macklin JA, Schelkle B, Kazou M, Sarand I, Singh BK, Fischer D, Maguin E, Ferrocino I, Lima N, McClure RS, Charles TC, de Souza RSC, Kiran GS, Krug HL, Taffner J, Roume H, Selvin J, Smith D, Rybakova D, Sessitsch A. Development of Microbiome Biobanks - Challenges and Opportunities: (Trends in Microbiology 29, 89-92; 2021). Trends Microbiol 2021; 29:378. [PMID: 33573876 DOI: 10.1016/j.tim.2021.01.009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
|
7
|
Ryan MJ, Schloter M, Berg G, Kinkel LL, Eversole K, Macklin JA, Rybakova D, Sessitsch A. Towards a unified data infrastructure to support European and global microbiome research: a call to action. Environ Microbiol 2020; 23:372-375. [PMID: 33196130 PMCID: PMC7898335 DOI: 10.1111/1462-2920.15323] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Accepted: 11/12/2020] [Indexed: 11/30/2022]
Abstract
High‐quality microbiome research relies on the integrity, management and quality of supporting data. Currently biobanks and culture collections have different formats and approaches to data management. This necessitates a standard data format to underpin research, particularly in line with the FAIR data standards of findability, accessibility, interoperability and reusability. We address the importance of a unified, coordinated approach that ensures compatibility of data between that needed by biobanks and culture collections, but also to ensure linkage between bioinformatic databases and the wider research community.
Collapse
Affiliation(s)
| | - Michael Schloter
- Helmholtz Zentrum München, National Research Center for Environmental Health, Research Unit for Comparative Microbiome Analysis, Oberschleissheim, Germany
| | - Gabriele Berg
- Institute of Environmental Biotechnology, Graz University of Technology, Graz, Austria
| | - Linda L Kinkel
- Department of Plant Pathology, University of Minnesota, Saint Paul, MN, USA
| | - Kellye Eversole
- International Alliance for Phytobiomes Research, Lee's Summit, MO, USA.,Eversole Associates, Bethesda, MD, USA
| | - James A Macklin
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON, Canada
| | - Daria Rybakova
- Institute of Environmental Biotechnology, Graz University of Technology, Graz, Austria
| | - Angela Sessitsch
- AIT Austrian Institute of Technology, Center for Health and Bioresources, Bioresources Unit, Tulln, Austria
| |
Collapse
|
8
|
Cui H, Zhang L, Ford B, Cheng HL, Macklin JA, Reznicek A, Starr J. Measurement Recorder: developing a useful tool for making species descriptions that produces computable phenotypes. Database (Oxford) 2020; 2020:5995854. [PMID: 33216896 PMCID: PMC7678789 DOI: 10.1093/database/baaa079] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 08/24/2020] [Accepted: 08/27/2020] [Indexed: 12/31/2022]
Abstract
To use published phenotype information in computational analyses, there have been efforts to convert descriptions of phenotype characters from human languages to ontologized statements. This postpublication curation process is not only slow and costly, it is also burdened with significant intercurator variation (including curator-author variation), due to different interpretations of a character by various individuals. This problem is inherent in any human-based intellectual activity. To address this problem, making scientific publications semantically clear (i.e. computable) by the authors at the time of publication is a critical step if we are to avoid postpublication curation. To help authors efficiently produce species phenotypes while producing computable data, we are experimenting with an author-driven ontology development approach and developing and evaluating a series of ontology-aware software modules that would create publishable species descriptions that are readily useable in scientific computations. The first software module prototype called Measurement Recorder has been developed to assist authors in defining continuous measurements and reported in this paper. Two usability studies of the software were conducted with 22 undergraduate students majoring in information science and 32 in biology. Results suggest that participants can use Measurement Recorder without training and they find it easy to use after limited practice. Participants also appreciate the semantic enhancement features. Measurement Recorder's character reuse features facilitate character convergence among participants by 48% and have the potential to further reduce user errors in defining characters. A set of software design issues have also been identified and then corrected. Measurement Recorder enables authors to record measurements in a semantically clear manner and enriches phenotype ontology along the way. Future work includes representing the semantic data as Resource Description Framework (RDF) knowledge graphs and characterizing the division of work between authors as domain knowledge providers and ontology engineers as knowledge formalizers in this new author-driven ontology development approach.
Collapse
Affiliation(s)
- Hong Cui
- School of Information, University of Arizona, Tucson, AZ 85705, USA
| | - Limin Zhang
- School of Information, University of Arizona, Tucson, AZ 85705, USA
| | - Bruce Ford
- Department of Biological sciences, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
| | - Hsin-Liang Cheng
- Curtis Laws Wilson Library, Missouri University of Science and Technology, Rolla, MO 65409, USA
| | - James A Macklin
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON K1A 0C6, Canada
| | - Anton Reznicek
- LSA Herbarium, University of Michigan, Ann Arbor, MI 48019, USA
| | - Julian Starr
- Department of Biology, University of Ottawa, Ottawa, ON K1N 6N5, Canada
| |
Collapse
|
9
|
Berg G, Rybakova D, Fischer D, Cernava T, Vergès MCC, Charles T, Chen X, Cocolin L, Eversole K, Corral GH, Kazou M, Kinkel L, Lange L, Lima N, Loy A, Macklin JA, Maguin E, Mauchline T, McClure R, Mitter B, Ryan M, Sarand I, Smidt H, Schelkle B, Roume H, Kiran GS, Selvin J, de Souza RSC, van Overbeek L, Singh BK, Wagner M, Walsh A, Sessitsch A, Schloter M. Correction to: Microbiome definition re-visited: old concepts and new challenges. Microbiome 2020; 8:119. [PMID: 32819450 PMCID: PMC7441691 DOI: 10.1186/s40168-020-00905-x] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/28/2023]
Abstract
An amendment to this paper has been published and can be accessed via the original article.
Collapse
Affiliation(s)
- Gabriele Berg
- Institute of Environmental Biotechnology, Graz University of Technology, Graz, Austria.
| | - Daria Rybakova
- Institute of Environmental Biotechnology, Graz University of Technology, Graz, Austria
| | | | - Tomislav Cernava
- Institute of Environmental Biotechnology, Graz University of Technology, Graz, Austria
| | | | - Trevor Charles
- Waterloo Centre for Microbial Research, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L 3G1, Canada
- Metagenom Bio, 550 Parkside Drive, Unit A9, Waterloo, ON, N2L 5 V4, Canada
| | - Xiaoyulong Chen
- Guizhou Provincial Key Laboratory for Agricultural Pest Management of the Mountainous Region, Guizhou University, Guiyang, 550025, Guizhou, China
| | - Luca Cocolin
- Department of Agricultural, Forest and Food Sciences, University of Turin, Turin, Italy
| | - Kellye Eversole
- International Alliance for Phytobiomes Research, Lee's Summit, MO, USA
| | | | - Maria Kazou
- Laboratory of Dairy Research, Department of Food Science and Human Nutrition, Agricultural University of Athens, Athens, Greece
| | - Linda Kinkel
- Department of Plant Pathology, University of Minnesota, St. Paul, MN, 55108, USA
| | - Lene Lange
- BioEconomy, Research, & Advisory, Valby, Denmark
| | - Nelson Lima
- CEB-Centre of Biological Engineering, University of Minho, Campus de Gualtar, 4710-057, Braga, Portugal
| | - Alexander Loy
- Department of Microbial Ecology and Ecosystem Science, University of Vienna, Vienna, Austria
| | | | - Emmanuelle Maguin
- MICALIS, INRA, AgroParisTech, Université Paris-Saclay, 78350, Jouy-en-Josas, France
| | - Tim Mauchline
- Sustainable Agriculture Sciences, Rothamsted Research, Harpenden, UK
| | - Ryan McClure
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Birgit Mitter
- Bioresources Unit, AIT Austrian Institute of Technology, Tulln, Austria
| | | | - Inga Sarand
- Department of Chemistry and Biotechnology, Tallinn University of Technology, Tallinn, Estonia
| | - Hauke Smidt
- Laboratory of Microbiology, Wageningen University & Research, Wageningen, the Netherlands
| | - Bettina Schelkle
- Department of Agricultural, Forest and Food Sciences, University of Turin, Turin, Italy
| | | | - G Seghal Kiran
- Dept of Food Science and Technology, Pondicherry University, Puducherry, India
| | - Joseph Selvin
- Department of Microbiology, Pondicherry University, Puducherry, India
| | - Rafael Soares Correa de Souza
- Genomics for Climate Change Research Center (GCCRC), Universidade Estadual de Campinas (UNICAMP), Campinas, SP, Brazil
| | - Leo van Overbeek
- Laboratory of Microbiology, Wageningen University & Research, Wageningen, the Netherlands
| | - Brajesh K Singh
- Hawkesbury Institute for the Environment, Western Sydney University, Penrith, NSW, Australia
- Global Centre for Land-Based Innovation, Western Sydney University, Penrith, NSW, Australia
| | - Michael Wagner
- Department of Microbial Ecology and Ecosystem Science, University of Vienna, Vienna, Austria
| | - Aaron Walsh
- Teagasc Food Research Centre, Moorepark, Fermoy, Co. Cork, Ireland
| | - Angela Sessitsch
- Bioresources Unit, AIT Austrian Institute of Technology, Tulln, Austria
| | | |
Collapse
|
10
|
Ryan MJ, Schloter M, Berg G, Kostic T, Kinkel LL, Eversole K, Macklin JA, Schelkle B, Kazou M, Sarand I, Singh BK, Fischer D, Maguin E, Ferrocino I, Lima N, McClure RS, Charles TC, de Souza RSC, Kiran GS, Krug HL, Taffner J, Roume H, Selvin J, Smith D, Rybakova D, Sessitsch A. Development of Microbiome Biobanks - Challenges and Opportunities. Trends Microbiol 2020; 29:89-92. [PMID: 32800611 DOI: 10.1016/j.tim.2020.06.009] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 06/20/2020] [Accepted: 06/25/2020] [Indexed: 12/16/2022]
Abstract
The microbiome research field is rapidly evolving, but the required biobanking infrastructure is currently fragmented and not prepared for the biobanking of microbiomes. The rapid advancement of technologies requires an urgent assessment of how biobanks can underpin research by preserving microbiome samples and their functional potential.
Collapse
Affiliation(s)
| | - M Schloter
- Helmholtz Zentrum München, National Research Center for Environmental Health, Research Unit for Comparative Microbiome Analysis, Oberschleissheim, Germany
| | - G Berg
- Institute of Environmental Biotechnology, Graz University of Technology, Graz, Austria
| | - T Kostic
- AIT Austrian Institute of Technology, Center for Health and Bioresources, Bioresources Unit, Tulln, Austria
| | - L L Kinkel
- Department of Plant Pathology, University of Minnesota, Saint Paul, MN, USA
| | - K Eversole
- International Alliance for Phytobiomes Research, Lee's Summit, MO, USA; Eversole Associates, Bethesda, MD, USA
| | - J A Macklin
- Agriculture and Agri-Food Canada, Ottawa, ON, Canada
| | - B Schelkle
- European Food Information Council, Brussels, Belgium
| | - M Kazou
- Laboratory of Dairy Research, Department of Food Science and Human Nutrition, Agricultural University of Athens, Athens, Greece
| | - I Sarand
- Department of Chemistry and Biotechnology, Tallinn University of Technology, Tallinn, Estonia
| | - B K Singh
- Global Centre for Land Based Innovation, Hawkesbury Institute for the Environment, Western Sydney University, Penrith, Australia
| | - D Fischer
- Helmholtz Zentrum München, National Research Center for Environmental Health, Research Unit for Comparative Microbiome Analysis, Oberschleissheim, Germany
| | - E Maguin
- INRAE, MICALIS Institute, Metagenopolis, Jouy-en-Josas, France
| | - I Ferrocino
- Department of Agricultural, Forest and Food Science, University of Turin, Grugliasco, Italy
| | - N Lima
- Biological Engineering Centre, University of Minho, Braga, Portugal
| | - R S McClure
- Pacific Northwest National Laboratory, Richland, WA, USA
| | - T C Charles
- Waterloo Centre for Microbial Research, University of Waterloo, Waterloo, ON, Canada
| | - R S C de Souza
- Genomics for Climate Change Research Center, Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil
| | - G S Kiran
- Department of Food Science and Technology, Pondicherry University, Puducherry, India
| | - H L Krug
- Institute of Environmental Biotechnology, Graz University of Technology, Graz, Austria
| | - J Taffner
- Institute of Environmental Biotechnology, Graz University of Technology, Graz, Austria
| | - H Roume
- INRAE, MICALIS Institute, Metagenopolis, Jouy-en-Josas, France
| | - J Selvin
- Department of Microbiology, Pondicherry University, Puducherry, India
| | | | - D Rybakova
- Institute of Environmental Biotechnology, Graz University of Technology, Graz, Austria
| | - A Sessitsch
- AIT Austrian Institute of Technology, Center for Health and Bioresources, Bioresources Unit, Tulln, Austria
| |
Collapse
|
11
|
Berg G, Rybakova D, Fischer D, Cernava T, Vergès MCC, Charles T, Chen X, Cocolin L, Eversole K, Corral GH, Kazou M, Kinkel L, Lange L, Lima N, Loy A, Macklin JA, Maguin E, Mauchline T, McClure R, Mitter B, Ryan M, Sarand I, Smidt H, Schelkle B, Roume H, Kiran GS, Selvin J, Souza RSCD, van Overbeek L, Singh BK, Wagner M, Walsh A, Sessitsch A, Schloter M. Microbiome definition re-visited: old concepts and new challenges. Microbiome 2020; 8:103. [PMID: 32605663 PMCID: PMC7329523 DOI: 10.1186/s40168-020-00875-0] [Citation(s) in RCA: 645] [Impact Index Per Article: 161.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Accepted: 05/22/2020] [Indexed: 05/03/2023]
Abstract
The field of microbiome research has evolved rapidly over the past few decades and has become a topic of great scientific and public interest. As a result of this rapid growth in interest covering different fields, we are lacking a clear commonly agreed definition of the term "microbiome." Moreover, a consensus on best practices in microbiome research is missing. Recently, a panel of international experts discussed the current gaps in the frame of the European-funded MicrobiomeSupport project. The meeting brought together about 40 leaders from diverse microbiome areas, while more than a hundred experts from all over the world took part in an online survey accompanying the workshop. This article excerpts the outcomes of the workshop and the corresponding online survey embedded in a short historical introduction and future outlook. We propose a definition of microbiome based on the compact, clear, and comprehensive description of the term provided by Whipps et al. in 1988, amended with a set of novel recommendations considering the latest technological developments and research findings. We clearly separate the terms microbiome and microbiota and provide a comprehensive discussion considering the composition of microbiota, the heterogeneity and dynamics of microbiomes in time and space, the stability and resilience of microbial networks, the definition of core microbiomes, and functionally relevant keystone species as well as co-evolutionary principles of microbe-host and inter-species interactions within the microbiome. These broad definitions together with the suggested unifying concepts will help to improve standardization of microbiome studies in the future, and could be the starting point for an integrated assessment of data resulting in a more rapid transfer of knowledge from basic science into practice. Furthermore, microbiome standards are important for solving new challenges associated with anthropogenic-driven changes in the field of planetary health, for which the understanding of microbiomes might play a key role. Video Abstract.
Collapse
Affiliation(s)
- Gabriele Berg
- Environmental Biotechnology, Graz University of Technology, Graz, Austria.
| | - Daria Rybakova
- Environmental Biotechnology, Graz University of Technology, Graz, Austria
| | | | - Tomislav Cernava
- Environmental Biotechnology, Graz University of Technology, Graz, Austria
| | | | - Trevor Charles
- Waterloo Centre for Microbial Research, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L 3G1, Canada
- Metagenom Bio, 550 Parkside Drive, Unit A9, Waterloo, ON, N2L 5 V4, Canada
| | - Xiaoyulong Chen
- Guizhou Provincial Key Laboratory for Agricultural Pest Management of the Mountainous Region, Guizhou University, Guiyang, 550025, Guizhou, China
| | - Luca Cocolin
- European Food Information Council, Brussels, Belgium
| | - Kellye Eversole
- International Alliance for Phytobiomes Research, Summit, Lee, MO, 's, USA
| | | | - Maria Kazou
- Laboratory of Dairy Research, Department of Food Science and Human Nutrition, Agricultural University of Athens, Athens, Greece
| | - Linda Kinkel
- Department of Plant Pathology, University of Minnesota, St. Paul, MN, 55108, USA
| | - Lene Lange
- BioEconomy, Research, & Advisory, Valby, Denmark
| | - Nelson Lima
- CEB-Centre of Biological Engineering, University of Minho, Campus de Gualtar, 4710-057, Braga, Portugal
| | - Alexander Loy
- Department of Microbial Ecology and Ecosystem Science, University of Vienna, Vienna, Austria
| | | | - Emmanuelle Maguin
- MICALIS, INRA, AgroParisTech, Université Paris-Saclay, 78350, Jouy-en-Josas, France
| | - Tim Mauchline
- Sustainable Agriculture Sciences, Rothamsted Research, Harpenden, UK
| | - Ryan McClure
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Birgit Mitter
- Bioresources Unit, AIT Austrian Institute of Technology, Tulln, Austria
| | | | - Inga Sarand
- Department of Chemistry and Biotechnology, Tallinn University of Technology, Tallinn, Estonia
| | - Hauke Smidt
- Laboratory of Microbiology, Wageningen University & Research, Wageningen, the Netherlands
| | | | | | - G Seghal Kiran
- Dept of Food Science and Technology, Pondicherry University, Puducherry, India
| | - Joseph Selvin
- Department of Microbiology, Pondicherry University, Puducherry, India
| | - Rafael Soares Correa de Souza
- Genomics for Climate Change Research Center (GCCRC), Universidade Estadual de Campinas (UNICAMP), Campinas, SP, Brazil
| | - Leo van Overbeek
- Laboratory of Microbiology, Wageningen University & Research, Wageningen, the Netherlands
| | - Brajesh K Singh
- Hawkesbury Institute for the Environment, Western Sydney University, Penrith, NSW, Australia
- Global Centre for Land-Based Innovation, Western Sydney University, Penrith, NSW, Australia
| | - Michael Wagner
- Department of Microbial Ecology and Ecosystem Science, University of Vienna, Vienna, Austria
| | - Aaron Walsh
- Teagasc Food Research Centre, Moorepark, Fermoy, Co. Cork, Ireland
| | - Angela Sessitsch
- Bioresources Unit, AIT Austrian Institute of Technology, Tulln, Austria
| | | |
Collapse
|
12
|
Cui H, Macklin JA, Sachs J, Reznicek A, Starr J, Ford B, Penev L, Chen HL. Incentivising use of structured language in biological descriptions: Author-driven phenotype data and ontology production. Biodivers Data J 2018; 6:e29616. [PMID: 30473620 PMCID: PMC6235995 DOI: 10.3897/bdj.6.e29616] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [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: 09/07/2018] [Accepted: 10/23/2018] [Indexed: 01/17/2023] Open
Abstract
Phenotypes are used for a multitude of purposes such as defining species, reconstructing phylogenies, diagnosing diseases or improving crop and animal productivity, but most of this phenotypic data is published in free-text narratives that are not computable. This means that the complex relationship between the genome, the environment and phenotypes is largely inaccessible to analysis and important questions related to the evolution of organisms, their diseases or their response to climate change cannot be fully addressed. It takes great effort to manually convert free-text narratives to a computable format before they can be used in large-scale analyses. We argue that this manual curation approach is not a sustainable solution to produce computable phenotypic data for three reasons: 1) it does not scale to all of biodiversity; 2) it does not stop the publication of free-text phenotypes that will continue to need manual curation in the future and, most importantly, 3) It does not solve the problem of inter-curator variation (curators interpret/convert a phenotype differently from each other). Our empirical studies have shown that inter-curator variation is as high as 40% even within a single project. With this level of variation, it is difficult to imagine that data integrated from multiple curation projects can be of high quality. The key causes of this variation have been identified as semantic vagueness in original phenotype descriptions and difficulties in using standardised vocabularies (ontologies). We argue that the authors describing phenotypes are the key to the solution. Given the right tools and appropriate attribution, the authors should be in charge of developing a project's semantics and ontology. This will speed up ontology development and improve the semantic clarity of phenotype descriptions from the moment of publication. A proof of concept project on this idea was funded by NSF ABI in July 2017. We seek readers input or critique of the proposed approaches to help achieve community-based computable phenotype data production in the near future. Results from this project will be accessible through https://biosemantics.github.io/author-driven-production.
Collapse
Affiliation(s)
- Hong Cui
- University of Arizona, TUCSON, United States of AmericaUniversity of ArizonaTUCSONUnited States of America
| | - James A. Macklin
- Agriculture and Agri-Food Canada, Ottawa, CanadaAgriculture and Agri-Food CanadaOttawaCanada
| | - Joel Sachs
- Agriculture and Agri-Food Canada, Ottawa, CanadaAgriculture and Agri-Food CanadaOttawaCanada
| | - Anton Reznicek
- University of Michigan, Ann Arbor, United States of AmericaUniversity of MichiganAnn ArborUnited States of America
| | - Julian Starr
- University of Ottawa, Ottawa, CanadaUniversity of OttawaOttawaCanada
| | - Bruce Ford
- University of Manitoba, Winnipeg, CanadaUniversity of ManitobaWinnipegCanada
| | - Lyubomir Penev
- Pensoft Publishers & Bulgarian Academy of Sciences, Sofia, BulgariaPensoft Publishers & Bulgarian Academy of SciencesSofiaBulgaria
| | - Hsin-Liang Chen
- University of Massachusetts at Boston, Boston, United States of AmericaUniversity of Massachusetts at BostonBostonUnited States of America
| |
Collapse
|
13
|
Cui H, Xu D, Chong SS, Ramirez M, Rodenhausen T, Macklin JA, Ludäscher B, Morris RA, Soto EM, Koch NM. Introducing Explorer of Taxon Concepts with a case study on spider measurement matrix building. BMC Bioinformatics 2016; 17:471. [PMID: 27855645 PMCID: PMC5114841 DOI: 10.1186/s12859-016-1352-7] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [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: 04/01/2016] [Accepted: 11/11/2016] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Taxonomic descriptions are traditionally composed in natural language and published in a format that cannot be directly used by computers. The Exploring Taxon Concepts (ETC) project has been developing a set of web-based software tools that convert morphological descriptions published in telegraphic style to character data that can be reused and repurposed. This paper introduces the first semi-automated pipeline, to our knowledge, that converts morphological descriptions into taxon-character matrices to support systematics and evolutionary biology research. We then demonstrate and evaluate the use of the ETC Input Creation - Text Capture - Matrix Generation pipeline to generate body part measurement matrices from a set of 188 spider morphological descriptions and report the findings. RESULTS From the given set of spider taxonomic publications, two versions of input (original and normalized) were generated and used by the ETC Text Capture and ETC Matrix Generation tools. The tools produced two corresponding spider body part measurement matrices, and the matrix from the normalized input was found to be much more similar to a gold standard matrix hand-curated by the scientist co-authors. Special conventions utilized in the original descriptions (e.g., the omission of measurement units) were attributed to the lower performance of using the original input. The results show that simple normalization of the description text greatly increased the quality of the machine-generated matrix and reduced edit effort. The machine-generated matrix also helped identify issues in the gold standard matrix. CONCLUSIONS ETC Text Capture and ETC Matrix Generation are low-barrier and effective tools for extracting measurement values from spider taxonomic descriptions and are more effective when the descriptions are self-contained. Special conventions that make the description text less self-contained challenge automated extraction of data from biodiversity descriptions and hinder the automated reuse of the published knowledge. The tools will be updated to support new requirements revealed in this case study.
Collapse
Affiliation(s)
- Hong Cui
- University of Arizona, Tucson, AZ USA
| | | | | | - Martin Ramirez
- Museo Argentino de Ciencias, Naturales, CONICET, Buenos Aires, Argentina
| | | | | | | | - Robert A. Morris
- University of Massachusetts at Boston and Harvard University Herbaria, Massachusetts, USA
| | - Eduardo M. Soto
- Department of Geology & Geophysics, Yale University, New Haven, Connecticut USA
| | | |
Collapse
|
14
|
McPhillips T, Song T, Kolisnik T, Aulenbach S, Belhajjame K, Bocinsky RK, Cao Y, Cheney J, Chirigati F, Dey S, Freire J, Jones C, Hanken J, Kintigh KW, Kohler TA, Koop D, Macklin JA, Missier P, Schildhauer M, Schwalm C, Wei Y, Bieda M, Ludäscher B. YesWorkflow: A User-Oriented, Language-Independent Tool for Recovering Workflow Information from Scripts. IJDC 2015. [DOI: 10.2218/ijdc.v10i1.370] [Citation(s) in RCA: 48] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Scientific workflow management systems offer features for composing complex computational pipelines from modular building blocks, executing the resulting automated workflows, and recording the provenance of data products resulting from workflow runs. Despite the advantages such features provide, many automated workflows continue to be implemented and executed outside of scientific workflow systems due to the convenience and familiarity of scripting languages (such as Perl, Python, R, and MATLAB), and to the high productivity many scientists experience when using these languages. YesWorkflow is a set of software tools that aim to provide such users of scripting languages with many of the benefits of scientific workflow systems. YesWorkflow requires neither the use of a workflow engine nor the overhead of adapting code to run effectively in such a system. Instead, YesWorkflow enables scientists to annotate existing scripts with special comments that reveal the computational modules and dataflows otherwise implicit in these scripts. YesWorkflow tools extract and analyze these comments, represent the scripts in terms of entities based on the typical scientific workflow model, and provide graphical renderings of this workflow-like view of the scripts. Future version of YesWorkflow will also allow the prospective provenance of the data products of these scripts to be queried in ways similar to those available to users of scientific workflow systems.
Collapse
|
15
|
Abstract
Background The need to create controlled vocabularies such as ontologies for knowledge organization and access has been widely recognized in various domains. Despite the indispensable need of thorough domain knowledge in ontology construction, most software tools for ontology construction are designed for knowledge engineers and not for domain experts to use. The differences in the opinions of different domain experts and in the terminology usages in source literature are rarely addressed by existing software. Methods OTO software was developed based on the Agile principles. Through iterations of software release and user feedback, new features are added and existing features modified to make the tool more intuitive and efficient to use for small and large data sets. The software is open source and built in Java. Results Ontology Term Organizer (OTO; http://biosemantics.arizona.edu/OTO/) is a user-friendly, web-based, consensus-promoting, open source application for organizing domain terms by dragging and dropping terms to appropriate locations. The application is designed for users with specific domain knowledge such as biology but not in-depth ontology construction skills. Specifically OTO can be used to establish is_a, part_of, synonym, and order relationships among terms in any domain that reflects the terminology usage in source literature and based on multiple experts’ opinions. The organized terms may be fed into formal ontologies to boost their coverage. All datasets organized on OTO are publicly available. Conclusion OTO has been used to organize the terms extracted from thirty volumes of Flora of North America and Flora of China combined, in addition to some smaller datasets of different taxon groups. User feedback indicates that the tool is efficient and user friendly. Being open source software, the application can be modified to fit varied term organization needs for different domains.
Collapse
Affiliation(s)
- Fengqiong Huang
- School of Information Resources and Library Science, University of Arizona, Tucson, USA.
| | | | - Hong Cui
- School of Information Resources and Library Science, University of Arizona, Tucson, USA.
| | | | - Lorena Endara
- Department of Biology, University of Florida, Gainesville, USA.
| |
Collapse
|
16
|
Song T, Köhler S, Ludäscher B, Hanken J, Kelly M, Lowery D, Macklin JA, Morris PJ, Morris RA. Towards Automated Design, Analysis and Optimization of Declarative Curation Workflows. IJDC 2014. [DOI: 10.2218/ijdc.v9i2.337] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Data curation is increasingly important. Our previous work on a Kepler curation package has demonstrated advantages that come from automating data curation pipelines by using workflow systems. However, manually designed curation workflows can be error-prone and inefficient due to a lack of user understanding of the workflow system, misuse of actors, or human error. Correcting problematic workflows is often very time-consuming. A more proactive workflow system can help users avoid such pitfalls. For example, static analysis before execution can be used to detect the potential problems in a workflow and help the user to improve workflow design. In this paper, we propose a declarative workflow approach that supports semi-automated workflow design, analysis and optimization. We show how the workflow design engine helps users to construct data curation workflows, how the workflow analysis engine detects different design problems of workflows and how workflows can be optimized by exploiting parallelism.
Collapse
|
17
|
Abstract
Electronic annotation of scientific data is very similar to annotation of documents. Both types of annotation amplify the original object, add related knowledge to it, and dispute or support assertions in it. In each case, annotation is a framework for discourse about the original object, and, in each case, an annotation needs to clearly identify its scope and its own terminology. However, electronic annotation of data differs from annotation of documents: the content of the annotations, including expectations and supporting evidence, is more often shared among members of networks. Any consequent actions taken by the holders of the annotated data could be shared as well. But even those current annotation systems that admit data as their subject often make it difficult or impossible to annotate at fine-enough granularity to use the results in this way for data quality control. We address these kinds of issues by offering simple extensions to an existing annotation ontology and describe how the results support an interest-based distribution of annotations. We are using the result to design and deploy a platform that supports annotation services overlaid on networks of distributed data, with particular application to data quality control. Our initial instance supports a set of natural science collection metadata services. An important application is the support for data quality control and provision of missing data. A previous proof of concept demonstrated such use based on data annotations modeled with XML-Schema.
Collapse
Affiliation(s)
- Robert A. Morris
- Harvard University Herbaria, Cambridge, Massachusetts, United States of America
- Computer Science Department, University of Massachusetts, Boston, Massachusetts, United States of America
- * E-mail:
| | - Lei Dou
- UC Davis Genome Center, University of California, Davis, California, United States of America
| | - James Hanken
- Museum of Comparative Zoology, Harvard University, Cambridge, Massachusetts, United States of America
| | - Maureen Kelly
- Harvard University Herbaria, Cambridge, Massachusetts, United States of America
| | - David B. Lowery
- Harvard University Herbaria, Cambridge, Massachusetts, United States of America
- Computer Science Department, University of Massachusetts, Boston, Massachusetts, United States of America
| | - Bertram Ludäscher
- UC Davis Genome Center, University of California, Davis, California, United States of America
| | | | - Paul J. Morris
- Harvard University Herbaria, Cambridge, Massachusetts, United States of America
- Museum of Comparative Zoology, Harvard University, Cambridge, Massachusetts, United States of America
| |
Collapse
|
18
|
Lendemer JC, Macklin JA. Type Specimens of Pandanaceae in the Herbarium of the Academy of Natural Sciences of Philadelphia. Proceedings of the Academy of Natural Sciences of Philadelphia 2003. [DOI: 10.1635/0097-3157(2003)153[0167:tsopit]2.0.co;2] [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] [Indexed: 11/11/2022]
|