"Ontology Frameworks for Modeling Observational Data Semantics" 

Shawn Bowers

3p-4:30p, Tuesday, October 7, 2008, LH 3

Abstract:  
Observational data can be broadly characterized as data that records observations and measurements. As a form of scientific data, it plays a key role in many scientific disciplines. Observational data, however, are typically structured and described in ad hoc ways, which make its discovery and integration difficult. The wide range of data collected, the variety of ways the data are used, and the needs of existing analysis applications make it impractical to define "one-size-fits-all" database schemas for most observational data sets.

This talk presents a more generic, ontology-based framework for capturing the semantics of observational data with the aim of making observational data easier to discover (e.g., via web-based search approaches), interpret, and integrate. The framework employs the OWL-DL ontology language with concepts and properties for describing observations and measurements, and provides a structured vocabulary for creating domain-specific ontologies.  A key aspect of the framework is its ability to describe observation context, which can support the often complex, nested contextual relationships found in observational data. This talk also describes applications of this framework for annotating scientific data as well as using the ontology to improve data discovery.

The Speaker:  
Shawn Bowers is a computer scientist at the UC Davis Genome Center and a member of the Data and Knowledge Systems Lab, where he conducts research in conceptual data modeling, data integration, and scientific workflows. He is an active member of the Kepler Scientific Workflow project, where he has contributed to the design and development of Kepler extensions for managing scientific data, data provenance, and ontology-based approaches for organizing and discovering workflow components. He is also a member of the editorial board for the Journal on Data Semantics and is a (co-)principal investigator on five NSF-funded research projects. Shawn holds a Ph.D. and a M.Sc. in Computer Science from the OGI School of Science and Engineering at OHSU, and a B.Sc. in Computer and Information Science from the University of Oregon.

Associated readings: 

• J. Madin, S. Bowers, M. Schildhauer, and M. Jones. (2007) Advancing ecological research with ontologies. Trends in Ecology and Evolution (TREE), 23(3):159--168.
• S. Bowers, J. Madin, and M. Schildhauer. (2008) A Conceptual Modeling Framework for Expressing Observational Data Semantics. Intl. Conf. on Conceptual Modeling (ER), LNCS, to appear.
• Chapters 1-6 and 10 from Lakoff's Women, Fire, and Dangerous Things.  (This is the Week 2 seminar reading for the Data and Information program; it is not otherwise associated with the week's PLATO lecture.)

See the file list below for a printable announcement for this lecture.