| |  | Agarwal, P. | Ontological considerations in GIScience read moreAbstract: Ontology is a significant research theme in GIScience. While some researchers believe that the progress in GIScience is being directed through an engagement with the concept of ontology, some dismiss it as irrelevant. This paper is aimed at (i) exploring the theoretical and practical roles of ontologies; (ii) making the definitions and terminology explicit; (iii) assessing the applicability of ontology to problems in the geographical domain; and (iv) assessing whether a unified approach to ontology exists in GIScience. The results will be helpful for GIScientists in (i) understanding the validity of employing ontology within their own work, (ii) assessing what operational framework of terms and methods to use for developing their own ontology, and (iii) to assess what existing ontological models are available and applicable within their domain or application. A comprehensive and critical review will also help in identifying the signficant issues and directing future research agenda in GIScience. | 2005 |
| | | Buttenfield, Barbara P. | Geospatial data mining and knowledge discovery read moreAbstract: The advent of remote sensing and survey technologies over the last decade has
dramatically enhanced our capabilities to collect terabytes of geographic data on a daily
basis. However, the wealth of geographic data cannot be fully realized when information
implicit in data is difficult to discern. This confronts GIScientists with an urgent need for
new methods and tools that can intelligently and automatically transform geographic data
into information and, furthermore, synthesize geographic knowledge. It calls for new
approaches in geographic representation, query processing, spatial analysis, and data
visualization (Yuan 1998, Miller and Han 2000; Gahegan, 2000). Information scientists
face the same challenge as a result of the digital revolution that expedites the production
of terabytes of data from credit card transactions, medical examinations, telephone calls,
stock values, and other numerous human activities. Collaborative efforts in artificial
intelligence, statistics, and databases communities have been the underpinning
technologies of knowledge discovery in databases to extract useful information from
massive amounts of data in support of decision-making (Gardner 1996, Bhandari et al.
1997, Hedberg 1996). | 2000 |
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