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Patel B, Soundarajan S, Ménager H, Hu Z. Making Biomedical Research Software FAIR: Actionable Step-by-step Guidelines with a User-support Tool. Sci Data 2023; 10:557. [PMID: 37612312 PMCID: PMC10447492 DOI: 10.1038/s41597-023-02463-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 08/10/2023] [Indexed: 08/25/2023] Open
Abstract
Findable, Accessible, Interoperable, and Reusable (FAIR) guiding principles tailored for research software have been proposed by the FAIR for Research Software (FAIR4RS) Working Group. They provide a foundation for optimizing the reuse of research software. The FAIR4RS principles are, however, aspirational and do not provide practical instructions to the researchers. To fill this gap, we propose in this work the first actionable step-by-step guidelines for biomedical researchers to make their research software compliant with the FAIR4RS principles. We designate them as the FAIR Biomedical Research Software (FAIR-BioRS) guidelines. Our process for developing these guidelines, presented here, is based on an in-depth study of the FAIR4RS principles and a thorough review of current practices in the field. To support researchers, we have also developed a workflow that streamlines the process of implementing these guidelines. This workflow is incorporated in FAIRshare, a free and open-source software application aimed at simplifying the curation and sharing of FAIR biomedical data and software through user-friendly interfaces and automation. Details about this tool are also presented.
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Affiliation(s)
- Bhavesh Patel
- FAIR Data Innovations Hub, California Medical Innovations Institute, San Diego, CA, 92121, USA.
| | - Sanjay Soundarajan
- FAIR Data Innovations Hub, California Medical Innovations Institute, San Diego, CA, 92121, USA
| | - Hervé Ménager
- Institut Pasteur, Université Paris Cité, Bioinformatics and Biostatistics Hub, 75015, Paris, France
| | - Zicheng Hu
- Computational Health Science, University of California San Francisco, San Francisco, CA, 94158, USA
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2
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Chourdakis G, Davis K, Rodenberg B, Schulte M, Simonis F, Uekermann B, Abrams G, Bungartz HJ, Cheung Yau L, Desai I, Eder K, Hertrich R, Lindner F, Rusch A, Sashko D, Schneider D, Totounferoush A, Volland D, Vollmer P, Koseomur OZ. preCICE v2: A sustainable and user-friendly coupling library. OPEN RESEARCH EUROPE 2022; 2:51. [PMID: 37645328 PMCID: PMC10446068 DOI: 10.12688/openreseurope.14445.1] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 09/15/2022] [Indexed: 04/04/2024]
Abstract
preCICE is a free/open-source coupling library. It enables creating partitioned multi-physics simulations by gluing together separate software packages. This paper summarizes the development efforts in preCICE of the past five years. During this time span, we have turned the software from a working prototype -- sophisticated numerical coupling methods and scalability on ten thousands of compute cores -- to a sustainable and user-friendly software project with a steadily-growing community. Today, we know through forum discussions, conferences, workshops, and publications of more than 100 research groups using preCICE. We cover the fundamentals of the software alongside a performance and accuracy analysis of different data mapping methods. Afterwards, we describe ready-to-use integration with widely-used external simulation software packages, tests, and continuous integration from unit to system level, and community building measures, drawing an overview of the current preCICE ecosystem.
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Affiliation(s)
- Gerasimos Chourdakis
- Scientific Computing in Computer Science, Department of Informatics, Technical University of Munich, Garching, 85748, Germany
| | - Kyle Davis
- Simulation of Large Systems, Institute for Parallel and Distributed Systems, University of Stuttgart, Stuttgart, 70569, Germany
| | - Benjamin Rodenberg
- Scientific Computing in Computer Science, Department of Informatics, Technical University of Munich, Garching, 85748, Germany
| | - Miriam Schulte
- Simulation of Large Systems, Institute for Parallel and Distributed Systems, University of Stuttgart, Stuttgart, 70569, Germany
| | - Frédéric Simonis
- Scientific Computing in Computer Science, Department of Informatics, Technical University of Munich, Garching, 85748, Germany
| | - Benjamin Uekermann
- Usability and Sustainability of Simulation Software, Institute for Parallel and Distributed Systems, University of Stuttgart, Stuttgart, 70569, Germany
| | - Georg Abrams
- Simulation of Large Systems, Institute for Parallel and Distributed Systems, University of Stuttgart, Stuttgart, 70569, Germany
| | - Hans-Joachim Bungartz
- Scientific Computing in Computer Science, Department of Informatics, Technical University of Munich, Garching, 85748, Germany
| | - Lucia Cheung Yau
- Scientific Computing in Computer Science, Department of Informatics, Technical University of Munich, Garching, 85748, Germany
| | - Ishaan Desai
- Usability and Sustainability of Simulation Software, Institute for Parallel and Distributed Systems, University of Stuttgart, Stuttgart, 70569, Germany
| | - Konrad Eder
- Scientific Computing in Computer Science, Department of Informatics, Technical University of Munich, Garching, 85748, Germany
| | - Richard Hertrich
- Scientific Computing in Computer Science, Department of Informatics, Technical University of Munich, Garching, 85748, Germany
| | - Florian Lindner
- Simulation of Large Systems, Institute for Parallel and Distributed Systems, University of Stuttgart, Stuttgart, 70569, Germany
| | - Alexander Rusch
- Scientific Computing in Computer Science, Department of Informatics, Technical University of Munich, Garching, 85748, Germany
| | - Dmytro Sashko
- Scientific Computing in Computer Science, Department of Informatics, Technical University of Munich, Garching, 85748, Germany
| | - David Schneider
- Usability and Sustainability of Simulation Software, Institute for Parallel and Distributed Systems, University of Stuttgart, Stuttgart, 70569, Germany
| | - Amin Totounferoush
- Simulation of Large Systems, Institute for Parallel and Distributed Systems, University of Stuttgart, Stuttgart, 70569, Germany
| | - Dominik Volland
- Scientific Computing in Computer Science, Department of Informatics, Technical University of Munich, Garching, 85748, Germany
| | - Peter Vollmer
- Simulation of Large Systems, Institute for Parallel and Distributed Systems, University of Stuttgart, Stuttgart, 70569, Germany
| | - Oguz Ziya Koseomur
- Scientific Computing in Computer Science, Department of Informatics, Technical University of Munich, Garching, 85748, Germany
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3
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Chourdakis G, Davis K, Rodenberg B, Schulte M, Simonis F, Uekermann B, Abrams G, Bungartz HJ, Cheung Yau L, Desai I, Eder K, Hertrich R, Lindner F, Rusch A, Sashko D, Schneider D, Totounferoush A, Volland D, Vollmer P, Koseomur OZ. preCICE v2: A sustainable and user-friendly coupling library. OPEN RESEARCH EUROPE 2022; 2:51. [PMID: 37645328 PMCID: PMC10446068 DOI: 10.12688/openreseurope.14445.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 09/15/2022] [Indexed: 08/31/2023]
Abstract
preCICE is a free/open-source coupling library. It enables creating partitioned multi-physics simulations by gluing together separate software packages. This paper summarizes the development efforts in preCICE of the past five years. During this time span, we have turned the software from a working prototype -- sophisticated numerical coupling methods and scalability on ten thousands of compute cores -- to a sustainable and user-friendly software project with a steadily-growing community. Today, we know through forum discussions, conferences, workshops, and publications of more than 100 research groups using preCICE. We cover the fundamentals of the software alongside a performance and accuracy analysis of different data mapping methods. Afterwards, we describe ready-to-use integration with widely-used external simulation software packages, tests, and continuous integration from unit to system level, and community building measures, drawing an overview of the current preCICE ecosystem.
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Affiliation(s)
- Gerasimos Chourdakis
- Scientific Computing in Computer Science, Department of Informatics, Technical University of Munich, Garching, 85748, Germany
| | - Kyle Davis
- Simulation of Large Systems, Institute for Parallel and Distributed Systems, University of Stuttgart, Stuttgart, 70569, Germany
| | - Benjamin Rodenberg
- Scientific Computing in Computer Science, Department of Informatics, Technical University of Munich, Garching, 85748, Germany
| | - Miriam Schulte
- Simulation of Large Systems, Institute for Parallel and Distributed Systems, University of Stuttgart, Stuttgart, 70569, Germany
| | - Frédéric Simonis
- Scientific Computing in Computer Science, Department of Informatics, Technical University of Munich, Garching, 85748, Germany
| | - Benjamin Uekermann
- Usability and Sustainability of Simulation Software, Institute for Parallel and Distributed Systems, University of Stuttgart, Stuttgart, 70569, Germany
| | - Georg Abrams
- Simulation of Large Systems, Institute for Parallel and Distributed Systems, University of Stuttgart, Stuttgart, 70569, Germany
| | - Hans-Joachim Bungartz
- Scientific Computing in Computer Science, Department of Informatics, Technical University of Munich, Garching, 85748, Germany
| | - Lucia Cheung Yau
- Scientific Computing in Computer Science, Department of Informatics, Technical University of Munich, Garching, 85748, Germany
| | - Ishaan Desai
- Usability and Sustainability of Simulation Software, Institute for Parallel and Distributed Systems, University of Stuttgart, Stuttgart, 70569, Germany
| | - Konrad Eder
- Scientific Computing in Computer Science, Department of Informatics, Technical University of Munich, Garching, 85748, Germany
| | - Richard Hertrich
- Scientific Computing in Computer Science, Department of Informatics, Technical University of Munich, Garching, 85748, Germany
| | - Florian Lindner
- Simulation of Large Systems, Institute for Parallel and Distributed Systems, University of Stuttgart, Stuttgart, 70569, Germany
| | - Alexander Rusch
- Scientific Computing in Computer Science, Department of Informatics, Technical University of Munich, Garching, 85748, Germany
| | - Dmytro Sashko
- Scientific Computing in Computer Science, Department of Informatics, Technical University of Munich, Garching, 85748, Germany
| | - David Schneider
- Usability and Sustainability of Simulation Software, Institute for Parallel and Distributed Systems, University of Stuttgart, Stuttgart, 70569, Germany
| | - Amin Totounferoush
- Simulation of Large Systems, Institute for Parallel and Distributed Systems, University of Stuttgart, Stuttgart, 70569, Germany
| | - Dominik Volland
- Scientific Computing in Computer Science, Department of Informatics, Technical University of Munich, Garching, 85748, Germany
| | - Peter Vollmer
- Simulation of Large Systems, Institute for Parallel and Distributed Systems, University of Stuttgart, Stuttgart, 70569, Germany
| | - Oguz Ziya Koseomur
- Scientific Computing in Computer Science, Department of Informatics, Technical University of Munich, Garching, 85748, Germany
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4
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Carver JC, Weber N, Ram K, Gesing S, Katz DS. A survey of the state of the practice for research software in the United States. PeerJ Comput Sci 2022; 8:e963. [PMID: 35634111 PMCID: PMC9138129 DOI: 10.7717/peerj-cs.963] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 04/06/2022] [Indexed: 06/15/2023]
Abstract
Research software is a critical component of contemporary scholarship. Yet, most research software is developed and managed in ways that are at odds with its long-term sustainability. This paper presents findings from a survey of 1,149 researchers, primarily from the United States, about sustainability challenges they face in developing and using research software. Some of our key findings include a repeated need for more opportunities and time for developers of research software to receive training. These training needs cross the software lifecycle and various types of tools. We also identified the recurring need for better models of funding research software and for providing credit to those who develop the software so they can advance in their careers. The results of this survey will help inform future infrastructure and service support for software developers and users, as well as national research policy aimed at increasing the sustainability of research software.
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Affiliation(s)
- Jeffrey C. Carver
- Computer Science, University of Alabama, Tuscaloosa, AL, United States of America
| | - Nic Weber
- Information School, University of Washington, Seattle, WA, United States of America
| | - Karthik Ram
- Berkeley Institute for Data Science, University of California, Berkeley, Berkeley, CA, United States of America
| | - Sandra Gesing
- Discovery Partners Institute, Chicago, IL, United States of America
| | - Daniel S. Katz
- NCSA & CS & ECE & iSchool, University of Illinois at Urbana-Champaign, Urbana, IL, United States of America
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5
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Leipzig J, Nüst D, Hoyt CT, Ram K, Greenberg J. The role of metadata in reproducible computational research. PATTERNS (NEW YORK, N.Y.) 2021; 2:100322. [PMID: 34553169 PMCID: PMC8441584 DOI: 10.1016/j.patter.2021.100322] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Reproducible computational research (RCR) is the keystone of the scientific method for in silico analyses, packaging the transformation of raw data to published results. In addition to its role in research integrity, improving the reproducibility of scientific studies can accelerate evaluation and reuse. This potential and wide support for the FAIR principles have motivated interest in metadata standards supporting reproducibility. Metadata provide context and provenance to raw data and methods and are essential to both discovery and validation. Despite this shared connection with scientific data, few studies have explicitly described how metadata enable reproducible computational research. This review employs a functional content analysis to identify metadata standards that support reproducibility across an analytic stack consisting of input data, tools, notebooks, pipelines, and publications. Our review provides background context, explores gaps, and discovers component trends of embeddedness and methodology weight from which we derive recommendations for future work.
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Affiliation(s)
- Jeremy Leipzig
- Metadata Research Center, College of Computing and Informatics, Drexel University, Philadelphia, PA, USA
| | - Daniel Nüst
- Institute for Geoinformatics, University of Münster, Münster, Germany
| | | | - Karthik Ram
- Berkeley Institute for Data Science, University of California, Berkeley, Berkeley, CA, USA
| | - Jane Greenberg
- Metadata Research Center, College of Computing and Informatics, Drexel University, Philadelphia, PA, USA
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6
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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] [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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Darras KF, Pérez N, - M, Dilong L, Hanf-Dressler T, Markolf M, Wanger TC. ecoSound-web: an open-source, online platform for ecoacoustics. F1000Res 2020; 9:1224. [PMID: 33274051 PMCID: PMC7682500 DOI: 10.12688/f1000research.26369.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/10/2023] [Indexed: 03/04/2023] Open
Abstract
Passive acoustic monitoring of soundscapes and biodiversity produces vast amounts of audio recordings, but the management and analyses of these raw data present technical challenges. A multitude of software solutions exist, but none can fulfil all purposes required for the management, processing, navigation, analysis, and dissemination of acoustic data. The field of ecoacoustics needs a software tool that is free, evolving, and accessible. We take a step in that direction and present ecoSound-web: an open-source, online platform for ecoacoustics designed and built by ecologists and software engineers. ecoSound-web can be used for storing, organising, and sharing soundscape projects, manually creating and peer-reviewing annotations of soniferous animals and phonies, analysing audio in time and frequency, computing alpha acoustic indices, and providing reference sound libraries for different taxa. We present ecoSound-web's features, structure, and compare it with similar software. We describe its operation mode and the workflow for typical use cases such as the sampling of bird and bat communities, the use of a primate call library, and the analysis of phonies and acoustic indices. ecoSound-web is available from: https://github.com/ecomontec/ecoSound-web.
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Affiliation(s)
- Kevin F.A. Darras
- Computational Landscape Ecology, TU Dresden, Dresden, Sachsen, 01737, Germany
- Agroecology, University of Göttingen, Göttingen, Niedersachsen, 37077, Germany
- Sustainable Agricultural Systems & Engineering Laboratory, School of Engineering, Westlake University, Hangzhou, 310030, China
| | - Noemí Pérez
- Agroecology, University of Göttingen, Göttingen, Niedersachsen, 37077, Germany
| | - Mauladi -
- Department of Information Systems, Universitas Jambi, Jambi, Jambi, 36122, Indonesia
| | - Liu Dilong
- Quality Technology Centre, Nanjing Julong Steel Pipe Co., Ltd., Nanjing, 211800,, China
| | - Tara Hanf-Dressler
- Agroecology, University of Göttingen, Göttingen, Niedersachsen, 37077, Germany
| | - Matthias Markolf
- Behavioral Ecology & Sociobiology Unit, German Primate Centre,, Göttingen, Niedersachsen, 37077, Germany
| | - Thomas C Wanger
- Sustainable Agricultural Systems & Engineering Laboratory, School of Engineering, Westlake University, Hangzhou, 310030, China
- Key Laboratory of Coastal Environment and Resources of Zhejiang Province, Westlake University, Hangzhou, China
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