Semantic Science: Ontologies, Data and Probabilistic Theories

  • David Poole
  • Clinton Smyth
  • Rita Sharma
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5327)

Abstract

This chapter overviews work on semantic science. The idea is that, using rich ontologies, both observational data and theories that make (probabilistic) predictions on data are published for the purposes of improving or comparing the theories, and for making predictions in new cases. This paper concentrates on issues and progress in having machine accessible scientific theories that can be used in this way. This paper presents the grand vision, issues that have arisen in building such systems for the geological domain (minerals exploration and geohazards), and sketches the formal foundations that underlie this vision. The aim is to get to the stage where: any new scientific theory can be tested on all available data; any new data can be used to evaluate all existing theories that make predictions on that data; and when someone has a new case they can use the best theories that make predictions on that case.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • David Poole
    • 1
  • Clinton Smyth
    • 2
  • Rita Sharma
    • 2
  1. 1.Department of Computer ScienceUniversity of British ColumbiaCanada
  2. 2.Georeference Online Ltd.Canada

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