Enabling FAIR Data in the Earth and Space Sciences - Shelley Stall, American Geophysical Union
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PARALLEL SPEAKS
Cross-institutional and national data services (Eliane)
Lisa R. Johnston - Data Curation Network: A cross Institutional Staffing Model for curating research data
- Building the data curation network
- all universities in USA
Idea: collaboratively sharing data curation staff
- How would we deal with conflicting policy issues?
- What do researchers actually need our help with? Will they care if curation is distributed?
- Can I trust someone else to curate our data? What about quality control?
Start with: 9 institutions (all of them contributing to the curators) , 19 data curators, 1 project cooridnator, 1 program director, 8 DCN representatives, 2 admin leads
Day 1: Business Meeting
Day 2-3 : Curator Training/Network
Process: Ingest, Appraise and Select, DCN, Facilitate Access, Preserve Long-term
DCN: Review, Assign, CURATE, Mediate, Approve
- Check files and metadata
- Understand and run files
- Request missing information
- Augment metadata
- Transform file formats
- Evalute for FAIRness
= CURATE
Assessment:
- Is a network approach to curate research data more efficient? Indicators: number of datasets, frequency, variey, efficiency
- Are Curated data more valuableIndicators: track reuse indicators, implement a DCN registry, apply badges and metadata to signal that data sets curated by the DCN are FAIR
Making everything available: British Library Research Services and research Data Strategy : Rachel Kotorski, British Library
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naitonal Reserach Infrastructure - funder or partner ? Angeletta Miranda Leggio (ANDS)