RDA Groups

RDA Interest Group Charter

Name of Interest Group:  Data Discovery Paradigms IG

Introduction:

The Data Versioning WG has transitioned to the Data Versioning IG as of July 2021. The email address and group space have remained the same. 

The evolution of the evaluation of research from being mostly bibliographic index-based is now recognized to be indispensable to enable Open Science. In the same way that Open Science promotes the open sharing of FAIR data and other research outputs, evaluators must also value and consider these outputs as part of the wider research evaluation framework. The RDA is an appropriate forum for addressing the evolving requirements of research evaluation as they relate to Open Science practices.

The FAIR for Machine Learning (FAIR4ML) Interest Group will enable community members to discuss the various aspects of FAIR as applied to Machine Learning, looking both at domain specific and domain-agnostic use cases, and creating task forces and working groups as needed for specific guidance documents, recommendations, definitions and technical specification to that effect. The overall aim is to foster collaborations among researchers and developers who are interested in making machine learning (data, models, workflows, etc.) FAIR, along with those who contribute to the infrastructure and policies that support this.

How to get involved with this interest Group?

• Join the RDA group and be part of the mailing list to get updates

The proposed Global Water Information Interest Group (GWIIG) will serve as a platform leading to formation of RDA working group; as a venue for communication among RDA WGs and IGs focused on both technical eInfrastructure aspects (e.g. brokering; metadata and catalogs, dynamic data citation) and on related research domains (e.g. geosciences, agriculture, biodiversity); and as a coordination mechanism across a wide group of water information stakeholders, in particular those not previously involved in the OGC/WMO water standardization work.

The proposed Interest Group on “Health Data” (HD-IG) is a long-term initiative in the framework of RDA. It follows a rather successful BoF Session during the 6^th RDA Plenary Meeting in Paris, which was attended by over 35 researchers and professionals from diverse backgrounds, who discussed several relevant issues, expressed significant interest in forming the proposed Interest Group, and helped shape its focus as presented here.

The call for Indigenous data sovereignty (ID-Sov) —the right of a nation to govern the collection, ownership, and application of its own data—has grown in intensity and scope over the past five years. To date three national-level Indigenous data sovereignty networks exist: Te Mana Raraunga - Maori Data Sovereignty Network, the United States Indigenous Data Sovereignty Network (USIDSN), and the Maiamnayri Wingara Aboriginal and Torres Strait Islander Data Sovereignty Group in Australia. Similar initiatives are underway in Hawaii and Sweden.

Mission

Webinar - Professionalising Data Stewardship | Global updates to inform RDA community on future directions - 30 June 2022

This is the webpage of the RDA Interest Group on professionalising data stewardship. 

Interest Group Title: RDA for the Sustainable Development Goals

Introduction: Fit with the overall RDA vision and mission

This interest group seeks to advance and enable reproducibility in research based on or producing datasets that require code. Our goals are to build bridges with the many RDA external efforts addressing reproducibility, doing so in coordination with the other RDA Working and Interest Groups where appropriate.

This Group follows the broad definition of reproducibility stated by Turing Way in order to provide an inclusive framework for discussions.

Engineering comprises a vast span of sub-disciplines including for example chemical, civil, electrical, and mechanical engineering. Traditionally, engineering disciplines apply scientific knowledge and empirical evidence to finding (innovative) solutions in areas that range from design, creating and building to production of software and innovative materials. Therefore, research in engineering disciplines is highly multi-disciplinary and works in close collaboration with industry.