NITRD Big Data Interagency Working Group Workshop: Pioneering the Future of Federally Supported Data Repositories Jan 13, 2021 - Opening comments on where we are and one suggestion of where we might go with an International Data Science Institute (IDSI) - A blue sky view.

1. SWOT Analysis – What Does it
Tell Us?
Federally Supported Data Repositories
Philip E. Bourne
Stephenson Dean
Professor of Data Science and Biomedical Engineering
peb6a@virginia.edu
January 13, 2021
@pebourne

2. Perspective
• Oversight of data - the Protein Data Bank (PDB),
Immune Epitope Database (IEDB)
• Researcher - user of supported data
• Fed - First NIH Associate Director for Data Science
(ADDS)
• Dean - School of Data Science

3. Disclaimer
This list is not meant to be definitive, simply
illustrative

4. Strengths
• Scope and depth
• Proven track record
• == Trust, reliability
• Maintained by domain experts
• == curated, high quality
• Funded
• == Vested, “sustained” – intramural vs extramural?
• Institutional recognition/branding

5. Weaknesses
• Data are international, funding is national
• == Repetition, wasted resources, lack of collaboration
• Curators et al. not fully appreciated
• == Attrition, continuity, sustainability
• Feature creep (Extramural)
• == Cost, ease of use
• Accountability (Intramural)
• == Technically backward, non-competitive, entrenched
• Lack of federation

6. Opportunities
• The data just keeps coming
• Newish compute modalities – notably cloud
• The “Commons” concept is abuzz
• Aggregation
• == Interdisciplinarity, multi-scale modeling
• The rise of data science
• == Interdisciplinarity, applied machine learning, open
• The role of libraries
• == Preservation, governance

7. Threats
• Demand outweighs supply
• == Lose of productivity & scientific opportunity
• Security, integrity
• == Loss of Trust
• Private sector takeover, notably publishers
• == Closed, costly, constrained

8. Blue Sky Recommendation –
IDSI
• Establish an International Data Science Institute
(IDSI) == CERN, Int space station
• Shared governance, software, hardware, people
• Cloud based
• Ten year commitment
• Measure – Impact, FAIRness, cost/benefit,
interdisciplinarity
• Include all sectors .gov, .com, .org, .edu …
• Include all countries

9. Core
Infrastructure
Data
Cloud
Tools
IDSI

10. Core
Infrastructure
Data
Cloud
Tools
Research
Software
Engineers
RSEs
IDSI

11. Core
Infrastructure
Data
Cloud
Tools
Research
Software
Engineers
RSEs
Domain Experts
IDSI

12. Core
Infrastructure
Data
Cloud
Tools
Research
Software
Engineers
RSEs
Domain Experts
Funders
Private
Sector
IDSI

13. Core
Infrastructure
Data
Cloud
Tools
Research
Software
Engineers
RSEs
Domain Experts
Funders
Private
Sector
International Governance International Evaluation
IDSI
IDSI
IDSI
IDSI

14. This Model is Not New – But it
Has Not Been Perfected
• Supercomputer Centers
• == Not integrated well enough with the domains
• National Labs
• == Just that national not international
• Domains (eg NCBI, EBI)
• == Limited cross talk across domains
• All
• == Lack of private sector engagement