1. Examining Federal Expert Networking and the Economies of Scale: Moving the “HHS Profiles” Pilot Towards “Experts.gov” James King, Jessica N. Berrellez, Lissa N. Snyders, and Claire Valdivia Back VIVO 2016 Annual Conference 18 August 2016

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3. HHS Organizational Chart

4. NIH Library VISION: To be the premier provider of information solutions that enable discovery and improve health.

5. The Challenge – Facilitating Scientific Advancement New initiatives require collaboration Hard to find the right people: Many potential collaborators Each research group has their own website Unique challenges in identifying the scientific expertise –Publications don’t show all expertise –Hard to find others with similar interests –No shared forum to communicate emerging areas of interest

6. The Vision Platform-agnostic, integrated framework designed to provide easily discoverable profiles of diverse federal experts in order to facilitate science-driven networking across HHS

7. The Vision: Key Requirements Key Features and Capabilities Auto-populated profiles Author disambiguation engine Built-in networks and visualizations Customizable expertise algorithm Proxy administration Federated search Customized to HHS staff expertise Profiled staff can manually enter information User-friendly

8. The Plan: HHS Profiles Pilot HHS Profiles Pilot (http://profiles.catalyst.harvard.edu/) Will install Harvard Profiles on an AWS cloud server Pilot will focus on two easy data sources: –Public HR info from Active Directory/NED for NIH and FDA –Matching author names to PubMed publications data 6 months to Minimum Viable Product (MVP)

9. Timeline

10. Our Partners

11. HHS Profiles Pilot Department of Health & Human Services (HHS) Food and Drug Administration National Institutes of Health Data HHS Active Directory (10,000 sample population for pilot) Publications from PubMed

12. HHS Profiles Project Plan Test viability: Syncing NIH and FDA HR data with PubMed Mix researchers and technologists in pilot Marketing Engaging HHS leadership

13. HHS Profiles Pilot Architecture Only data intended for public consumption is passed up. Data at this level is private within the department. All data at this level is public and read-only HHS Profiles FDA Profiles NIH Profiles HR Data Disambiguation Service & PubMed

14. Use Case Examples FDA Profiles Intramural research expertise for medical device reviews NIH Profiles Extramural scientific staff, grants management, and funding opportunities Intramural researchers HHS Profiles Public Health Emergency Preparedness Team Science and trans-disciplinary research

15. Challenges Funding & Contracting Approvals (Management and IT) Project Champion Agency Goals vs Department Goals/Use Cases Platform Selection User Testing Growth/Economies of Scale

16. Questions? James King – James.King@nih.govJames.King@nih.gov Lissa Snyders – Lissa.Snyders@nih.govLissa.Snyders@nih.gov

18. Research Questions Primary How can we build a system that can scale across multiple agencies? How do we know that a research networking system is adding value? Secondary How do we best support user adoption? How do we incorporate diverse federal expertise?

19. HHS Profiles Pilot: Harvard Profiles Overview Professional networking and expertise mining for collaboration Dr. Griffin Weber, Harvard University NIH and NSF-funded Benefits VIVO and SciENcv collaborator Open source Large, active user and developer community

20. Key Data Elements for Profiles Auto-Populated Fields From the NIH Enterprise Database (NED): Staff member name Workplace Contact Information Position (e.g., Health Scientist Administrator, Staff Scientist) Educational background (e.g., highest degree obtained and highest degree field) From PubMed/other publication database sources: Publications authored/co-authored by the profile owner, disambiguated as much as possible ORCID and related author identifiers From the NIH IMPAC II database: Grants managed Study sections managed From the NIH Guide for Grants and Contracts: Funding Opportunity Announcements (FOAs) for which an individual serves as a contact Descriptive concepts that capture the scientific expertise of individuals, generated by text-mining algorithm or semantic engine search of data contained in the profiles Manually Populated Fields Current Title/Position Narrative description of scientific interests Training background Honors and Awards Keyword interests Photo Link to relevant NIH websites (e.g., IC profile, IC, IC division or branch, etc.) Professional Society memberships (list of societies with option for custom values) Committee membership Professional leadership positions List of past, current, and possible future projects and initiatives (e.g., workshops, training institutes) Whitepapers and reports authored NIH position role or function (e.g., Program Official, Scientific Review Officer, Program Director, Program Analyst, etc.) Previous positions, roles or functions