Transforming Ontologies into Nested Facet Systems
Thursday, Sept. 19, 2019
12:30—1:30 pm (Pizza will be served beginning at 12:20 pm)
UHS 130 (Beside Employee Health)
GQ Zhang, PhD
Vice President and Chief Data Scientist
Co-Director Texas Institute for Restorative Neurotechnology
Professor of Medicine, Biomedical Informatics and Public Health
University of Texas Health Science Center at Houston
Irrespective of data size and complexity, query and exploration tools for accessing data resources remain a central linkage for human-data interaction. A fundamental barrier in making query interfaces easier to use, ultimately as easy as online shopping, is the lack of faceted, interactive capabilities. We propose to repurpose existing ontologies by transforming them into nested facet systems (NFS) to support human-data interaction. Two basic issues need to be addressed for this to happen: one is that the structure and quality of ontologies need to be examined and elevated for the purpose of NFS; the second is that mappings from data-source specific metadata to a corresponding NFS need to be developed to support this new generation of NFS-enabled web-interfaces. The purpose of this presentation is to motivate the concept of NFS, provide a preliminary order-theoretic formulation for NFS, and suggest topics for further investigation.
The CCTS Biomedical Informatics (BMI) Core provides access to biomedical informatics expertise, technologies, and data management platforms to CCTS and their investigators. The CCTS BMI team integrates the CCTS BMI Core, Institute for Biomedical Informatics (IBI) and the Institute for Pharmaceutical Outcomes and Policy (IPOP) housed in the College of Pharmacy.
The Institute for Biomedical Informatics (IBI) translates data to knowledge to improve human health and effectively use the latest technology and tools for the advancement of biological sciences. The IBI promotes translational team science and engages the entire campus to develop and grow informatics and data science training programs; share research and data infrastructure; and enable technology innovation.