RDA Groups

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RDA directly and logically tackles numerous data infrastructure challenges through the work of its Working Groups, Interest Groups and Communities of Practice.

What's the difference?

Working Groups (WG)

WGs are short-term (18 months) and come together to develop and implement data infrastructure, which could be tools, policy, practices and products that are adopted and used by projects, organizations, and communities. Embedded within these groups are individuals who will use the infrastructure and help in making it broadly available to the public. Any RDA member can join or initiate a WG. 

Learn more about  Joining or Initiating a Working Group >>

View the current listing of Working Groups>> 

Interest Groups (IG)

IGs are open-ended in terms of longevity.  They focus on solving a specific data sharing problem and identifying what kind of infrastructure needs to be built.  These groups identify specific pieces of work and can start up a WG to tackle those projects. Any RDA member can join or initiate an IG.

Learn more about  Joining or Initiating an Interest Group >>

View the current listing of Interest Groups >>

Communities of Practice (CoP)

CoPs investigate, discuss and provide knowledge and skills within a specific discipline and/or research domain. These groups are committed to directly or indirectly enabling data sharing, exchange and/or interoperability by serving as THE coordination focal point for RDA in specific disciplines/research domains. 

Learn more about Joining  or Initiating a CoP >>


WG Working Groups - IG Interest Groups - CoP Communities of Practice

24 Jun 2021

IGAD Community of Practice

In Community Review

The Interest Group on Agricultural Data (IGAD) came to life in Gothenburg (Göteborg, Sweden) in 2013 at the beginning of the Research Data Alliance (RDA) and has since grown to include over 260 registered members, from across continents. IGAD is a domain-oriented interest group working on all issues related to food and agricultural data. It represents stakeholders in managing data for food and agricultural research and innovation, including producing, aggregating and consuming data.


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