The Cancer Imaging Archive (TCIA) hosts collections of de-identified medical images of cancer for research reuse. Non-image data included with many collections lack a common representation scheme. This poster presents work demonstrating use of ontologies and semantic web tools to support querying of non-image data in TCIA collections by transforming spreadsheet contents into an enhanced representation using biomedical ontologies, and loading the result into a triple store database to allow queries based on its contents.
Learning Objective 1: Participants should be able to:
- Recognize and discuss challenges to data integration and discoverability in large heterogeneous archives, and
- Understand and describe the role of biomedical ontologies and semantic web technology in addressing these challenges.
Jonathan Bona (Presenter)
University of Arkansas for Medical Sciences
Tracy Nolan, University of Arkansas for Medical Sciences
Dillon Gibson, University of Arkansas for Medical Sciences
Mathias Brochhausen, University of Arkansas for Medical Sciences