FAIR and Open Core Data – Fils

Open Core Data approaches to exposing facility data to support FAIR principles

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Presentation Slides: TBD

Audio: (link in prep) |Video: (link in prep)

Learn more about Open Core Data and Dr. Fil’s research at:  http://opencoredata.org/

Presented at: IS-GEO Monthly Telecon | December 2017

Abstract: The Open Core Data (OCD) award from NSF is focused on exposing scientific drilling data from the JOIDES Resolution Science Operator (JRSO) and Continental Scientific Drilling Coordination Office (CSDCO) following guidance from the Force 11 FAIR principles and the W3C “best practices” recommendations and notes. The goal of this implementation is to provide the identification, access, citation and provenance of these data to support the research community.

OCD employs Linked Open Data (LOD) patterns and HTML5 microdata publishing via JSON-LD using various vocabularies. These vocabularies include schema.org, GeoLink and other relevant community vocabularies. Attention is paid to enabling hypermedia navigation between resources to aid in fast and efficient harvesting of the metadata directly from the LOD approach using web architecture patterns. Further, the vocabularies are employed to address the need of both DOI assignment and creation of data citation entries following ESIP data citation recommendations. The use of LOD, community vocabularies and persistent identifiers has enabled linking between hosted and remote data resources.

In addition to the semantic metadata and LOD pattern, OCD is implementing approaches to data packaging to facilitate data use. OCD is currently using the CSV for the Web approach but is moving to implement frictionless data packages. This data package model provide access to a large suite of tools, libraries and workbenches to support data utilization, validation and visualization.

Further, a basic reference implementation of the W3C PROV-AQ pingback pattern is under testing. This work is done in coordination with the RDA Provenance Patterns WG and follows patterns already employed by Geoscience Australia. This development is also done in coordination with ESIP provenance work.

As needed, more traditional Application Program Interfaces (APIs) are exposed following best practices in RESTful services. All these capabilities are implemented in Open Core Data in the lightest possible manner to address the desired functions while being as easy to maintain as possible. The approaches, lessons learned and takeaways from this work at Open Core Data to date will be presented.

 

See the full abstract from the AGU 2017 Annual Meeting Program here:

https://agu.confex.com/agu/fm17/meetingapp.cgi/Paper/240169