Challenges of curating data from interdisciplinary and collaborative research
Submitted by Inna Kouper
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Share experiences working with interdisciplinary research teams and their data.
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Share examples of different approaches to discipline-specific data stewardship provision.
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Examine data discovery in an interdisciplinary research context.
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Identify the emergent themes from the discussion to transform them into action items for a potential WG or IG to address.
Collaborative meeting notes:
https://docs.google.com/document/d/1rZMaDJQTHPqoTav8NstGHKaMr_GAQk2lS0rG...
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Overview (the meeting structure, initial definitions of the terms) ~5 min
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Panel introductions ~5 min
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Panel presentations (designed to answer the following questions) ~50 min:
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What are the greatest challenges in curating interdisciplinary data?
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What are the barriers to expanding existing curation services to interdisciplinary data?
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What are the most effective strategies for interdisciplinary data curation, including technical tools and human interactions?
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What are the advantages and disadvantages of different data stewardship provision models?
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Open discussion ~20 min
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Closing thoughts/next steps ~10 min
This session draws on the experiences of several projects and initiatives, including a multi-institutional effort led by Indiana University in the US, the FAIRsFair project, and 4TU.ResearchData. Addressing interdisciplinary data from multiple perspectives, including sharing, interoperability and re-use, these projects seek to describe the current landscape of interdisciplinary data curation, develop workflows to support it, and provide informed recommendations for interdisciplinary teams. The proposed session will create a space where people with a variety of experience in curating interdisciplinary data can share their knowledge and expertise and, potentially, develop a plan for delivering tangible outcomes through a WG or IG work. As research incentives become increasingly focused on collaborative work that spans multiple disciplines, more work is needed to address the technological and social issues that come with it. Thus, conversations from this session will be leveraged to form a working group in which best practices for interdisciplinary data activities can be resolved.
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