NSF FAIR Hackathon

TheCenter for Research Computingat University of Notre Dame is an innovative and multidisciplinary research environment that supports collaboration to facilitate discoveries in science and engineering, the arts, humanities and social sciences, through advanced computation, data analysis and other digital research tools. The Center enhances the University’s cyberinfrastructure, provides support for interdisciplinary research and education, and conducts computational research.

University of Notre Dame, Center for Research Computing

The MPS FAIR hackathon is an opportunity for the physical sciences community of NSF researchers to share skills, tools and techniques to FAIRify research data and software. Designed to address issues of public access to data and to provide tools and relevant hands-on experience for researchers, the workshop will lay out the FAIR principles and metrics in the context of a hackathon using the successful model of the The Bio-IT World FAIR Data Hackathon organized by GOFAIR. Existing FAIR tools and infrastructure will be introduced.  Hands-on hackathon breakout time will be devoted to FAIRifying physical sciences data and/or software. By providing small groups of investigators having similar preservation needs with FAIR experts, this workshop will serve to introduce available tools and infrastructure. Overviews of existing FAIR tools and infrastructure will be introduced, hands-on hackathon breakout time will be devoted to FAIRifying physical sciences data and/or software.
The hackathon, similar to its GOFAIR counterparts at BioIT in Boston and in the EU, will have separate tracks for metrics, hackathon, and disciplinary trends.  Participants will receive pre-workshop consultation from the organizers and advisors as they select the projects, datasets, and code they want to FAIRify at the workshop hackathon sessions.
By the end of the workshop participants will be familiar with the following list of topics and know how to identify for their projects and disciplines:
(1) What are your required (or preferred) identifier registration services ?
(2) What is your minimal persistence policy?
(3) Can you make your persistence policy machine-readable?
(4) Can you define a minimal set of metadata for your community?
(5) Can you make your metadata machine-readable?
(6) Can you define the metadata model that explicitly links data and metadata?
(7) Can you make this metadata model machine-readable?
(8) What is the required (preferred) search engine for your community ?
(9) What is the required (preferred) communication protocol for your community ?
(10) What is your required (preferred) protocols for restricting access to data ?
(11) Can you make this protocol machine-readable?
(12) What is your minimal persistence policy for metadata?
(13) Can you make this persistence policy machine-readable?
(14) What is your required (preferred) standards in knowledge representation ?
(15) What are your required (preferred) vocabularies ?
(16) What is your required LinkSet ?
(17) What is your required (preferred) usage license framework?
(18) Can you make these usage licenses machine-readable?
(19) What is your required (preferred) provenance metadata descriptions?
(20) Can you make this provenance metadata machine-readable?

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NSF FAIR Hackathon

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NSF FAIR Hackathon

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