RDA Groups

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. 

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.

RDA & ESIP Physical Samples Webinar Series:

• Supporting Reproducibility by Capturing Physical Sample Data and Metadata in a Connected Electronic Lab Notebook - 30 June 2021

• RRIDs: A Way to Track Samples Through the Scientific Literature - 10 August 2021

Aligning with RDA’s mission, the purpose of the Psychology RDA Interest Group (IG) is to raise awareness of the importance of data sharing, and to provide support with respect to the technical skills needed for FAIR data sharing within the Psychology community. This IG brings together Psychology researchers with an interest in open, transparent, and reproducible research methods and practices.

This IG starter out as a Working Group, to explore issues related to scientific research data sets that contains human subject information, as well as related datasets that have the potential to be combined in a way that can expose private information. The goal of the group is to develop a framework for how researchers and repositories should appropriately manage human-subject datasets, to develop a metadata set to describe the privacy-related aspects of research datasets, and to build awareness of the privacy implications of research data sharing.

Context and purpose

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.

Sensitive data is increasingly used for research purposes. However, there are a number of barriers which need to be overcome before sensitive data can be fully operationalized in the research context. Chief among these is that not all sensitive data is alike, with significant disciplinary variation in how sensitive data is defined, linked, managed, stored, and reused. Additionally, common approaches to data optimization are not always appropriate for sensitive data, such as the relationship between the FAIR and CARE principles for data management. Nonetheless, sensitive data has significant

FAIR research software skills and training curriculums need to be identified and incorporated into broader efforts to facilitate increased support and recognition for the qualified personnel needed to achieve open science.

Extensive work has been, and continues to be done on data interoperability at the technical and information domains. However, a large portion of the challenges in building interoperable information infrastructures are the result of the interplay between organisations, institutions, economics, and individuals.