Abstraction networks for terminologies: Helping to manage “big knowledge”. (CLaS-CCD Research Colloquium Series 2012)
Speaker : Dr Michael Halper, College of Computing Sciences, New Jersey Institute of Technology, USA.
Date : 22nd of November 2012, 11:00AM until 12:00PM
Location : E6A 202, Macquarie University.
Management of “big data” has become a major focus area in the field of computing. An equally important issue is dealing with “big knowledge” in the form of large terminologies and ontologies, which are particularly prevalent in the biomedical domain. In fact, terminologies and terminological systems have assumed increasingly important roles in many medical information processing environments. However, their very large and involved structures can make them difficult to use and maintain. In this talk, I present the notion of abstraction network as a means for helping to manage large terminologies. An abstraction network overlays a terminology’s underlying network structure at a higher level of abstraction. In particular, it provides a more compact view of the terminology’s content, avoiding the display of minutiae. General abstraction network characteristics are discussed. Example abstraction networks previously developed and deployed for a variety of terminologies are presented along with some details of their respective derivations. I also discuss specific benefits of these alternative terminology network views, such as their facilitating the usability, visualization, and quality assurance of terminologies. In addition, the notion of meta-abstraction network, existing at a higher level of abstraction than a typical abstraction network, is presented along with examples.
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