Next Generation Cancer Data Discovery, Access, and Integration Using Prizms and Nanopublications

Printer-friendly version


To encourage data sharing in the life sciences, supporting tools need to minimize effort and maximize incentives. We have created infrastructure that makes it easy to create portals that supports dataset sharing and simplified publishing of the datasets as high quality linked data. We report here on our infrastructure and its use in the creation of a melanoma dataset portal. This portal is based on the Comprehensive Knowledge Archive Network (CKAN) and Prizms, an infrastructure to acquire, integrate, and publish data using Linked Data principles. In addition, we introduce an extension to CKAN that makes it easy for others to cite datasets from within both publications and subsequently derived datasets using the emerging nanopublication and World Wide Web Consortium provenance standards.


DateCreated ByLink
June 19, 2013
Jamie McCuskerDownload

Related Research Areas:

Data Frameworks
Lead Professor: Peter Fox
Description: None.
Knowledge Provenance
Lead Professor: Deborah L. McGuinness
Description: Knowledge Provenance
Concepts: Provenance,
Semantic Foundations
Lead Professor: Deborah L. McGuinness
Description: Semantic Foundations
Web Science
Lead Professor: Jim Hendler, Deborah L. McGuinness
Description: Web Science is the study of the World Wide Web and its impact on both society and technology, positioning the Web as an object of scientific study unto itself. Web Science recognizes the Web as a transformational, disruptive technology; its practitioners study the Web, its components, facets and characteristics. Ultimately, Web Science is about understanding the Web and anticipating how it might evolve in the future.