M. J. S. García, C. P. Herrero, Jaime A. Hernandez, I. H. P. Torres
{"title":"Ontology Based Framework to Represent Relationships between Biomedical Spatial Data","authors":"M. J. S. García, C. P. Herrero, Jaime A. Hernandez, I. H. P. Torres","doi":"10.1109/MICAI.2013.37","DOIUrl":null,"url":null,"abstract":"Geographic Information Systems (GIS) and services describe formalized knowledge from spatial domain. GIS use spatial data referring to places names (toponyms) in a geographical space, which could be ambiguous. Ontologies allow support for storing information in this context, providing a structure which defines the data integration and also supports toponyms disambiguation. This article presents an ontology based framework including the interpretation of the geographical biomedical domain concepts and their spatial relationships. The work is focused on solving queries involving ambiguous toponyms, illness and health services. Emphasis has been placed on the topological relationships, which will be used later in the spatial axioms definition. The framework is complemented with Google Maps and Jena APIs.","PeriodicalId":340039,"journal":{"name":"2013 12th Mexican International Conference on Artificial Intelligence","volume":"69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 12th Mexican International Conference on Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MICAI.2013.37","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Geographic Information Systems (GIS) and services describe formalized knowledge from spatial domain. GIS use spatial data referring to places names (toponyms) in a geographical space, which could be ambiguous. Ontologies allow support for storing information in this context, providing a structure which defines the data integration and also supports toponyms disambiguation. This article presents an ontology based framework including the interpretation of the geographical biomedical domain concepts and their spatial relationships. The work is focused on solving queries involving ambiguous toponyms, illness and health services. Emphasis has been placed on the topological relationships, which will be used later in the spatial axioms definition. The framework is complemented with Google Maps and Jena APIs.
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