0. Research Data Management Infrastructure at NIST
Robert Hanisch
Director, Office of Data and Informatics
Material Measurement Laboratory
National Institute of Standards and Technology
Friday September 15, 2017

1. Policies
NIST policies on research data reflect OSTP and OMB directives of 2013
NIST P , eff. 6/26/2015: “To the extent feasible and consistent with law, agency mission, resource constraints, and U.S. national, homeland, and economic security, NIST will promote the deposit of scientific data arising from unclassified research and programs, funded wholly or in part by NIST, except for Standard Reference Data,* free of charge in publicly accessible databases.”
*The SRD Act of 1968, amended 2017, authorizes NIST through the Dept. of Commerce
to collect fees to offset the cost of data collection, critical evaluation, and dissemination.

2. Public Data Access Policy Goals
Strengthen NIST’s commitment to providing public access to scientific research results
Support governance of and best practices for managing peer-reviewed scholarly publications and digital scientific data across NIST
Ensure effective access to and reliable preservation of NIST peer-reviewed scholarly publications and digital scientific data for use in research, development, education, and scientific discovery
Increase use to NIST research results to enhance scientific discovery, education, and research and development across the US
Enhance innovation and competitiveness by maximizing the potential to create new business opportunities

3. NIST Data Pyramid data.gov public data SRD and Published Results
Publishable Results
Derived Data
storage,
sharing, and
collaboration
Working Data

4. Data from NIST-Sponsored Research
For external research funded by NIST, PR requires
Grantees to have a data management plan if the research will produce public data
Grantees to provide metadata about public data products
NIST program officer to enter metadata into the NIST Enterprise Data Inventory
Grantees to make data available through a public data repository

5. Practice NIST basic practice Beyond the minimums
Data Management Plans and Enterprise Data Inventory: MIDAS (Management of Institutional Data Assets)
EDI public metadata records copied to data.gov
Beyond the minimums
New Public Data Repository and associated data portal; all public data sets assigned DOIs
Global data discovery tools for materials science, metrology: resource registries
Generic data annotation tool: MDCS (Materials Data Curation System)

6. Gather Data Management Plans
MML DMPs
midas.nist.gov
minerva.nist.gov
A DMP tells us
What are the data-generating activities
What types of data are produced
How the data are managed and preserved
How they are reviewed and made available

7. Feed a System of Metadata Catalogs
NIST Enterprise Data Inventory (EDI)
Data.gov
Dataset information:
Title
Access (public?)
Description
Location of data
Contact
References/Guides
Keywords
Last update
License
MML dataset information

9. Creating an
Enterprise
Data
Inventory
Record

10. Materials Resource Registry

13. Federated Architecture
Full
Searchable
Registry
Resource
Registry
harvest
(pull)
replicate
Local
Publishing
Registry
OAI/PMH
Full
Searchable
Registry
major
data
providers
Local
Publishing
Registry
search
queries
Users,
applications

14. Data Discovery for Public Research Data
Search NIST public data records
View metadata
Filter results
Access data files, metadata
APIs allow interoperability with client tools
Records link to Public Data Repository

15. NIST Public Data Repository – Basic Landing Page
Publication landing page example using a standard MIDAS publication
The Public Data Repository is being developed to provide capabilities for rich Data Publications

16. Research Data Infrastructure

17. Sharing with Socrata Publishing Tool
NIST public data records hosted in external Socrata publishing system
Provides web landing page view and catalog for tabular datasets
Search, filtering, and visualization tools
Auto-generated API allows users to access data by script rather than by website

18. materialsdata.nist.gov

19. materialsdata.nist.gov

20. Laboratory Information Management Systems
Integrated Collaborative Environment (ICE)
Running now at
Developed by Air Force Research Laboratory
Timely and Trustworthy Curating and Coordinating Data Framework (T2C2) 4CeeD system
Running now at
Developed by University of Illinois at Urbana-Champaign
Also considering Discovery Environment for Relational Information and Versioned Assets (DERIVA) from USC

21. Laboratory Information Management Systems
Capture instrument metadata at the source
Metadata extractors
Often must reverse engineer proprietary binary formats
Move experiment metadata into database
Enable search across many experiments
Do not use filenames/file system for metadata storage
Enable scripted data processing, calibration, feature extraction
Support data management from acquisition to publication; improve reproducibility

22. Reproducibility
As the US National Metrology Institute it seems incumbent upon NIST to address the reproducibility “crisis”
e.g., “Rigor Mortis: How Sloppy Science Creates Worthless Cures, Crushes Hopes, and Wastes Billions” by Richard Harris
“…the goal of achieving confidence in research results may be more effectively realized if a comprehensive, systematic approach for reporting and assessing research quality was considered by authors and reviewers” (Plant, Becker, Hanisch, Boisvert, and Possolo, PLOS Bio., subm.)
 Sound data management is essential

23. Challenges Incredible diversity of research programs
Size, complexity, discipline
Most data generated by small research groups
Conservative culture, reluctance to change practice
Must demonstrate high ratio of benefit to cost
Little recognition for data sharing/publication for advancement
Proprietary data formats
Many bench instruments have opaque formats
Vendors want to sell proprietary software as well as the instrument
IT security
Widely-used tools like dropbox prohibited
New deployments require A&A, ATO – takes time and effort

24. Outlook
NIST is working to establish a sound infrastructure for data discovery, access (curation and preservation), and interoperability
Much more to be done!
Build up informatics/analytics capabilities, machine learning, data mining
Expand scope from pilot projects to routine operations
Strengthen Standard Reference Data program and expand NIST portfolio with complementary data products and services
Make it easy for staff to share and annotate data products, provide enhanced metadata to increase interoperability
Further strengthen NIST’s role in the international metrology arena through excellence in data management and data science
Communicate, inform, educate, support