Recommendations & Outputs Catalogue

RDA Outputs are the technical and social infrastructure solutions developed by RDA Working Groups or Interest Groups that enable data sharing, exchange, and interoperability.

These Outputs have an important impact in two areas: solving problems, and incorporation and/or adoption in infrastructure environments by individuals, projects and organisations. As an organisation, RDA’s goal is to expand awareness and adoption of these Outputs, and hence their impact, within all regions of the world. RDA Outputs are products of the respective Working or Interest Group and should be demonstrably developed and endorsed by the group. Each Output should have the respective Working or Interest Group listed as an author where appropriate.

RDA Outputs are classified as RDA Recommendations (official, endorsed results of RDA Groups), Supporting Outputs (useful solutions from our RDA Working and Interest Groups) or other Outputs – more information can be found at https://www.rd-alliance.org/what-are-recommendations-and-outputsThey are all listed below and can be searched according to their focus, scientific domain, or by status using the filters on the right. Filters can be combined, too (if more than one filter is selected, results sum up).

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1-10 of 121 Results
Working Group Recommendation
Guidance on Data Granularity: Report of the RDA Data Granularity WG
Review Status: In Community Review
Authors: Reyna Jenkyns, Brigitte Mathiak, Katherine McNeill, Graham Smith, Guangyuan Sun, Chris Little, Beverley Jones, David Elbert, Maggie Hellström
Data infrastructure can be built around predefined levels of granularity for data, for which conventions vary. The appropriate level of granularity can optimize discovery, access, interoperability, analysis, identification, citation, curation, and more. This guidance document developed by the Research Data Alliance (RDA) Data Granularity Working Group (WG), along with its Supporting Output, provides guidance on…
September 10, 2024
Working Group Supporting Output
Data Granularity Use Cases
Review Status: In Community Review
Authors: Katherine McNeill, Graham Smith, Guangyuan Sun, Beverley Jones, David Elbert, Maggie Hellström
Data infrastructure can be built around predefined levels of granularity for data, for which conventions vary. The appropriate level of granularity can optimize discovery, access, interoperability, analysis, identification, citation, curation, and more. These use cases developed by the Research Data Alliance (RDA) Data Granularity Working Group (WG), along with its Guidance Document, provide priority use…
September 10, 2024
Working Group Recommendation
Mapping the Landscape of Digital Research Tools
Review Status: Preparing for Council Review
Authors: Adam Vials Moore, Rory Macneil, Connie Clare, Marcelo Garcia, Richard Pitts
The digital research data infrastructure landscape comprises a myriad of tools for managing and sharing research data during various stages of the research data lifecycle (RDL). Such research tools vary widely depending on data type, user requirement, provider, and subject area. In the context of the Mapping the Landscape of Digital Research Tools Working Group…
September 2, 2024
Working Group Supporting Output
AIDV-WG Shared Citation Library
Review Status: Preparing for Council Review
Authors: Natalie Meyers
The AIDV-WG Shared Citation Library on the zotero platform available at https://www.zotero.org/groups/4922635/aidv-wg/library  was developed to support working group members’ research and particularly to support  these three concurrent AIDV-WG  outputs:  Bill of Rights Recommendation[i], Guidance on Informed Consent[ii], and the Guidance for Ethics Committees Reviewing AI and Data Visitation[iii] The AIDV WG’s open, shared citation library…
August 20, 2024
Working Group Recommendation
AI Bill of Rights Recommendation
Review Status: Preparing for Council Review
Authors: Eyiuche Ezigbo, Shiny Martis B, Natalie Meyers, Ronit Purian, Yeyang Su
The AI Bill of Rights team goal is to present recommendations to EOSC Future and Research Data Alliance on the needs for AI Governance/AI Bill of Rights in various jurisdictional, disciplinary and research scenarios taking into account the potential rights of data creators, model developers, model and data re-users, and citizens/communities/patients whose lives/privacy/wellbeing are impacted…
August 20, 2024
Working Group Recommendation
Guidance for Ethics Committees Reviewing AI and DV
Review Status: Preparing for Council Review
Authors: Challace Pahlevan-Ibrekic, Valery Sokolchik, Rita Sitorus, Perihan Elif Ekmekci, Aliaksei Razuvanau, Ülkücan Kaplan, Pukovisa Prawiroharjo
Research Ethics Committees(RECs) and Institutional Review Boards (IRBs) are charged with the responsibility to protect the rights, dignity and welfare of research volunteers, including use of their data that may have been collected for other, non-research purposes. Generally speaking, REC/IRBs review research involving humans according to a principled approach and usually refer to a specific…
August 15, 2024
Working Group Recommendation
GUIDANCE FOR INFORMED CONSENT IN THE CONTEXT OF ARTIFICIAL INTELLIGENCE AND DATA VISITATION
Review Status: Preparing for Council Review
Authors: Luis Jacob Retanan, Noémie Dubruel, Gauthier Chassang, Kristy Hackett, Anne Cambon-Thomsen
The development and use of artificial intelligence (AI) require access to large amounts of different types of data (data visitation) for training, validation, and refinement of models. This includes data visitation that can be regulated under data protection law, the so-called personal data, which is directly or indirectly identifiable personal information that is subject to…
July 23, 2024
Interest Group Output
Ten principles to improve dataset discoverability
Review Status: Endorsed
Authors: Mingfang Wu, Kathleen Gregory, Felicitas Löffler, Brigitte Mathiak, Fotis Psomopoulos, Uwe Schindler, Amir Aryani, Jordi BODERA SEMPERE, Leyla Jael Castro, Antica Culina, Andreas Czerniak, Christopher Erdmann, Jeffrey Grethe, Maggie Hellström, Christin Henzen, Christopher Hunter, Nick Juty, Live Kvale, Allyson Lister, Ying-Hsang Liu, Bénédicte Madon, Andrea Medina-Smith, Graham Parton, Samantha Pearman-Kanza, Andrea Pörsch, Emanuel Soeding, Lucas van der Meer, Nina Weisweiler, Heinrich Widmann, CJ Woodford
The  FAIR (meta) data principles provide overarching guidelines to make metadata and data Findable, Accessible, Interoperable and Reusable. While significant effort has been dedicated to specific recommendations that enable best practices in implementing FAIR principles, particularly from a data curation perspective, this document focuses primarily on enhancing the discoverability of data from the perspectives of…
July 15, 2024
Working Group Recommendation
The Global Open Research Commons International Model, Version 1.1
Review Status: In Council Review Open
Authors: CJ Woodford, Andrew Treloar, Mark Leggott, Karen Payne, Sarah Jones, Javier Lopez Albacete, Devika Madalli, Francoise Genova, Kheeran Dharmawardena, Noel Chibhira, Wolmar Nyberg Åkerström, Rory Macneil, Amy Nurnberger, Hans Pfeiffenberger, Mikiko Tanifuji, Qian Zhang, Nick Jones, Laurents Sesink, Elisha Wood-Charlson
In response to the global movement to implement national and cross-national or global commons, a Research Data Alliance (RDA) Interest Group was formed to work towards a community-developed typology for describing research commons. This Interest Group created a Working Group to develop an International Model describing the attributes of Global Open Research Commons. The RDA…
July 8, 2024
Interest Group Output
RDA Value for the Evaluation of Research
Review Status: Endorsed
Authors: Francoise Genova, Emma Crott, Devika Madalli, Amy Nurnberger
The evaluation of research is evolving from being mostly bibliographic index-based to a broader context, which is now recognised as indispensable for enabling Open Research. In the same way that Open Research promotes the open sharing of FAIR data and other research outputs, evaluators must also value and consider these outputs as part of the…
July 3, 2024