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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Working Group Recommendation Guidance on Data Granularity: Report of the RDA Data Granularity WG

Review Status: Preparing for Council 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: Preparing for Council 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: Endorsed

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

Interest Group Output Recommendations on Open Science Rewards and Incentives: Guidance for multiple stakeholders in Research.

Review Status: Endorsed

Authors: Laurence Mabile, Hanna Shmagun, Christopher Erdmann, Anne Cambon-Thomsen, Mogens Thomsen, Florencia Grattarola

Open Science contributes to the collective building of scientific knowledge and societal progress. However, academic research currently fails to recognise and reward efforts to share research outputs. Yet it is crucial that such activities be valued, as they require considerable time, energy, and expertise to make scientific outputs usable by others, as stated by the…

June 25, 2024

Working Group Supporting Output Research Hardware Definition

Review Status: Endorsed

Authors: Nadica Miljković, Julien Colomb, Moritz Maxeiner, Ana Petrus, Vladimir Milovanović, Mirco Panighel, Alexander Struck, Robert Mies

Research Hardware is a physical object developed as part of or for a research process.” This definition is proposed after reviewing and discussing the literature about the related concept of open (source) hardware, scientific hardware, other hardware in research, and related research outputs. We also discuss the relation between research hardware and its package of…

March 14, 2024