Knowledge capture and reuse for geo-spatial imagery tasks

  • Authors:

  • David C. Wilson;Michela Bertolotto;Eoin McLoughlin;Dympna O’Sullivan

  • Affiliations:

  • Smart Media Institute, Department of Computer Science, University College Dublin, Belfield, Dublin, Ireland;Smart Media Institute, Department of Computer Science, University College Dublin, Belfield, Dublin, Ireland;Smart Media Institute, Department of Computer Science, University College Dublin, Belfield, Dublin, Ireland;Smart Media Institute, Department of Computer Science, University College Dublin, Belfield, Dublin, Ireland

  • Venue:
  • ICCBR'03 Proceedings of the 5th international conference on Case-based reasoning: Research and Development
  • Year:
  • 2003

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Abstract

The continuously increasing amount and availability of geospatial image data is giving rise to problems of information overload in organisations that rely on digital geo-spatial imagery. Intelligent support for relevant image retrieval is needed in order to help manage large geospatial image libraries. Moreover, managing the knowledge implicit in using geo-spatial imagery to address particular tasks is crucial for capturing and making the most effective use of organisational knowledge assets. We are developing case-based knowledge-management support for large geo-spatial image repositories, which incorporates sketch-based querying for image retrieval; image manipulation and annotation tools for highlighting and composing relevant aspects of task-relevant imagery; and automatic context-based querying for retrieving relevant previous task experiences. This paper describes our approach to knowledge capture and reuse through task-based image annotation, and it introduces the environment we are developing for capture and reuse of task knowledge involving geo-spatial imagery.