Related literature#
Content relating to Data and Metadata standards#
Peer-Reviewed Articles#
Russell A. Poldrack, Christopher J. Markiewicz, Stefan Appelhoff, Yoni K. Ashar, Tibor Auer, Sylvain Baillet, Shashank Bansal, Leandro Beltrachini, Christian G. Benar, Giacomo Bertazzoli, Suyash Bhogawar, Ross W. Blair, Marta Bortoletto, Mathieu Boudreau, Teon L. Brooks, Vince D. Calhoun, Filippo Maria Castelli, Patricia Clement, Alexander L. Cohen, Julien Cohen-Adad, Sasha D’Ambrosio, Gilles de Hollander, María de la Iglesia-Vayá, Alejandro de la Vega, Arnaud Delorme, Orrin Devinsky, Dejan Draschkow, Eugene Paul Duff, Elizabeth DuPre, Eric Earl, Oscar Esteban, Franklin W. Feingold, Guillaume Flandin, Anthony Galassi, Giuseppe Gallitto, Melanie Ganz, Rémi Gau, James Gholam, Satrajit S. Ghosh, Alessio Giacomel, Ashley G. Gillman, Padraig Gleeson, Alexandre Gramfort, Samuel Guay, Giacomo Guidali, Yaroslav O. Halchenko, Daniel A. Handwerker, Nell Hardcastle, Peer Herholz, Dora Hermes, Christopher J. Honey, Robert B. Innis, Horea-Ioan Ioanas, Andrew Jahn, Agah Karakuzu, David B. Keator, Gregory Kiar, Balint Kincses, Angela R. Laird, Jonathan C. Lau, Alberto Lazari, Jon Haitz Legarreta, Adam Li, Xiangrui Li, Bradley C. Love, Hanzhang Lu, Eleonora Marcantoni, Camille Maumet, Giacomo Mazzamuto, Steven L. Meisler, Mark Mikkelsen, Henk Mutsaerts, Thomas E. Nichols, Aki Nikolaidis, Gustav Nilsonne, Guiomar Niso, Martin Norgaard, Thomas W. Okell, Robert Oostenveld, Eduard Ort, Patrick J. Park, Mateusz Pawlik, Cyril R. Pernet, Franco Pestilli, Jan Petr, Christophe Phillips, Jean-Baptiste Poline, Luca Pollonini, Pradeep Reddy Raamana, Petra Ritter, Gaia Rizzo, Kay A. Robbins, Alexander P. Rockhill, Christine Rogers, Ariel Rokem, Chris Rorden, Alexandre Routier, Jose Manuel Saborit-Torres, Taylor Salo, Michael Schirner, Robert E. Smith, Tamas Spisak, Julia Sprenger, Nicole C. Swann, Martin Szinte, Sylvain Takerkart, Bertrand Thirion, Adam G. Thomas, Sajjad Torabian, Gael Varoquaux, Bradley Voytek, Julius Welzel, Martin Wilson, Tal Yarkoni, Krzysztof J. Gorgolewski. The past, present, and future of the brain imaging data structure (BIDS). Imaging Neuroscience (2024). URL: https://direct.mit.edu/imag/article/doi/10.1162/imag_a_00103/119672. DOI: https://doi.org/10.1162/imag_a_00103
Christopher J Markiewicz, Krzysztof J Gorgolewski, Franklin Feingold, Ross Blair, Yaroslav O Halchenko, Eric Miller, Nell Hardcastle, Joe Wexler, Oscar Esteban, Mathias Goncavles, Anita Jwa, and Russell Poldrack. The OpenNeuro resource for sharing of neuroscience data. Elife, October 2021. URL: https://elifesciences.org/articles/71774. DOI: https://doi.org/10.7554/eLife.71774
Russell A Poldrack, Franklin Feingold, Michael J Frank, Padraig Gleeson, Gilles de Hollander, Quentin J. M. Huys, Bradley C. Love, Christopher J. Markiewicz, Rosalyn Moran, Petra Ritter, Timothy T. Rogers, Brandon M. Turner, Tal Yarkoni, Ming Zhan, and Jonathan D. Cohen. The importance of standards for sharing of computational models and data. Computational Brain & Behavior 2 (2019): 229-232. URL: https://link.springer.com/article/10.1007/s42113-019-00062-x. DOI: https://doi.org/10.1007/s42113-019-00062-x
Yarkoni, Tal, Dean Eckles, James AJ Heathers, Margaret C. Levenstein, Paul E. Smaldino, and Julia I. Lane. Enhancing and accelerating social science via automation: Challenges and opportunities. Harvard Data Science Review 3, no. 2 (2021). URL:https://hdsr.mitpress.mit.edu/pub/nu90ngsc/release/4. DOI: https://doi.org/10.1162/99608f92.df2262f5
Krzysztof J Gorgolewski, Tibor Auer, Vince D Calhoun, R Cameron Craddock, Samir Das, Eugene P Duff, Guillaume Flandin, Satrajit S Ghosh, Tristan Glatard, Yaroslav O Halchenko, Daniel A Handwerker, Michael Hanke, David Keator, Xiangrui Li, Zachary Michael, Camille Maumet, B Nolan Nichols, Thomas E Nichols, John Pellman, Jean-Baptiste Poline, Ariel Rokem, Gunnar Schaefer, Vanessa Sochat, William Triplett, Jessica A Turner, Gaël Varoquaux, and Russell A Poldrack. The Brain Imaging Data Structure, a format for organizing and describing outputs of neuroimaging experiments. Sci Data, 3:160044, June 2016. URL: https://www.nature.com/articles/sdata201644. DOI: https://doi.org/10.1038/sdata.2016.44.
Non-Peer-Reviewed Documents & Articles#
Title: Working in Public: The Making and Maintenance of Open Source Software
Type: Book
Author: Eghbal, Nadia
Year: 2020
Identifier: 0578675862
Abstract / Summary: In this book Eghbal presents an overview of the socio-technical nuances of Open source development. Of particular relation to the topic of Open Source Ecosystems, Eghbal dedicates a portion of discussion to the issue(s) of Open Source communities and organizations. Through this exploration she reveals many of the challenges associated with the coordination and sustenance of a coherent and aligned Open Source endeavor.
Title: The relationship between open source software and standard setting
Type: Report
Author: Blind, Knut; Thumm, Nikolaus; Böhm, Mirko
Year: 2019
Identifier: 978-92-76-11593-9; 10.2760/163594
Abstract / Summary: In this 2019 European Commission, Joint Research Centre (JRC) report, the interactions and relationships between the socio-technical processes of Open Source Software (OSS) development communities and Standards Development Organizations (SDOs) is analyzed. Of particular interest to the report are issues of incentive structures/systems, Intellectual Property Rights/regimes (IPR), and collaboration (within SDOs/OSS communities and between SDOs and OSS communities). The report includes a consideration of 20 case studies and the provision of recommendations to a broad range of stakeholders, in fulfillment of the inciting charge issued by the European Commission on this subject.
Of particular salience and interest to the current workshop endeavor is the overarching conceptual framework provided by the analysis, which can be understood to subsume the (sub)-domain of Open Source Ecosystems for data and metadata standard development and promulgation.
Title: Research Data File Formats and Digital Preservation — Final Report
Type: Report
Author: Digital preservation services development group; The Open Science and Research Initiative (ATT)
Year: 2017
Identifier: URN:NBN:fi-fe2017121855906; 10.2760/163594
Abstract / Summary: “This report is part of designing the digital preservation ensemble. It focuses on research data file formats, whose understandability, prevalence and software support are important for data reuse. The report is based on international sources and interviews with Finnish researchers. Additionally, the report presents preliminary requirements for accepting research datasets for digital preservation.”[source]
Policy & Policy-related Documents#
Title: Request for Information (RFI): Proposed Use of Common Data Elements (CDEs) for NIH-Funded Clinical Research and Trials
Organization: National Institutes of Health (NIH), Office of Data Science Strategy (ODSS)
Link: https://grants.nih.gov/grants/guide/notice-files/NOT-OD-24-063.html
Abstract / Summary: “The purpose of the Request for Information (RFI) is to solicit public input on 1) a set of minimum core common data elements (CDEs) that would be used across all NIH funded/conducted clinical studies/trials and community-based research involving human participants; 2) additional CDEs for social determinants of health (SDoH) and clinical domains including autoimmune diseases and immune-mediated diseases; and 3) technologies, tools and policies that could facilitate the use of NIH CDEs. NIH CDEs are defined as CDEs “recommended” or “required” by an NIH body, and/or found in the NIH CDE Repository. These RFI responses will be used to inform NIH’s continuing guidance on CDE use and assist in the planning for adequate resources for CDE implementation.” [source]
Title: Desirable Characteristics of Data Repositories for Federally Funded Research
Organization: The National Science and Technology Council (NSTC), Subcommittee on Open Science (SOS)
Link: https://www.whitehouse.gov/wp-content/uploads/2022/05/05-2022-Desirable-Characteristics-of-Data-Repositories.pdf, https://doi.org/10.5479/10088/113528
Abstract / Summary: A Guidance document produced by the NSTC SOS (against the backdrop of executive mandates from 2013 and 2022 on public access to federally funded science products) regarding the desired characteristics of data repositories. Includes (brief) guidance on both issues of metadata and format.
Title: USDA Fiscal Year 2024-2026 Data Strategy
Organization: United States Department of Agriculture (USDA)
Link: https://www.usda.gov/sites/default/files/documents/fy-2024-2026-usda-data-strategy.pdf, https://doi.org/10.5479/10088/113528
Abstract / Summary: The visioning document for the USDA’s data strategy for 2024 to 2026. Goal 4 of this roadmap is broadly dedicated towards efforts to the enhance the “Openness” of the USDA’s Data Catalog, while objective 4.1 is specifically dedicated to enhance and standardize metadata.
Media#
Resources#
Resource Title: Fairshairing.org Standards Database
Organization: Fairsharing.org
Link: https://fairsharing.org/search?fairsharingRegistry=Standard
Description / Summary: “A registry of terminology artefacts, models/formats, reporting guidelines, and identifier schemas.” Includes a meta-metadata standard which documents characteristics like: domain, subject, associated tools, accommodating databases.
Resource Title: Building a metadata schema – where to start
Organization:International Organization for Standardization (ISO)
Description / Summary: A guide provided by the International Organization for Standardization (ISO) to assist with the creation of a metadata schema.
Organizations#
Organization Name: Research Data Alliance (RDA)
Relevant Components/Aspects: Data Granularity WG, Data Repository Attributes WG, FAIRsharing Registry: Connecting data policies, standards and databases RDA WG, Metadata Standards Catalog WG, Research Metadata Schemas WG, FAIR Instrument Data IG, Metadata IG, Social Dynamics of Data Interoperability IG, Data Type Registries WG & #2
Other#
Hillel Wayne. The Hunt for The Missing Data Type. Mar 02, 2024. URL: https://www.hillelwayne.com/post/graph-types/
Tyler Hou. The “missing” graph datatype already exists. It was invented in the 70’s. 05 Mar 2024. URL: https://tylerhou.com/posts/datalog-go-brrr/