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Rule‐Based Discovery in Spatial Data Infrastructure
Author(s) -
Lutz Michael,
Kolas Dave
Publication year - 2007
Publication title -
transactions in gis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.721
H-Index - 63
eISSN - 1467-9671
pISSN - 1361-1682
DOI - 10.1111/j.1467-9671.2007.01048.x
Subject(s) - computer science , variety (cybernetics) , data science , data discovery , semantic web , spatial analysis , domain (mathematical analysis) , spatial data infrastructure , data model (gis) , information retrieval , data mining , world wide web , geography , metadata , artificial intelligence , mathematics , mathematical analysis , remote sensing
Answering questions based on spatial data is becoming increasingly important in a variety of domains. Often the required data are distributed and heterogeneous, and several data sources need to be combined in order to derive the information required by a user. Spatial data infrastructures (SDIs) are aimed at making the discovery and access to distributed geographic data more efficient. However, the catalogue services currently used in SDIs for discovering geographic data do not allow expressive queries and do not take into account that more than one data source might be required to answer a question. In this paper, we present a methodology that uses rules for both the discovery of data sources and, based on the discovered data, answering user queries in SDIs. We illustrate how this methodology allows inferences that use relationships between individuals and the combination of data from different sources, thus overcoming some of the limitations of other Semantic Web approaches that are based on Description Logics. The approach is illustrated by an example from the domain of disaster management.