With the growing availability of administrative data in digital form, one of the current challenges of local municipalities is to manage and integrate information coming from different sources and formats with the aim of recognizing irregularities derived from the combination of such data. In this paper, we present our experience in the context of a local project for the semantic integration of real estate and associated tributes data. The integrated access to these data should support semantic visual analytic, and query formulation and geo-visualization. The data integration is based on an ontology that has been specifically developed to represent the main concepts and relations on this domain. This ontology is populated with the data available in different repositories, such as the cadastre, municipal registry, and household utilities. Ontology has been populated with the available data, which need to be normalized, completed, and in some cases disambiguated. Finally, we developed a system for the visual formulation and execution of queries over the integrated knowledge base.

Semantic Visual Query Answering on Heterogeneous Territorial Data

Loris Bozzato;
2020-01-01

Abstract

With the growing availability of administrative data in digital form, one of the current challenges of local municipalities is to manage and integrate information coming from different sources and formats with the aim of recognizing irregularities derived from the combination of such data. In this paper, we present our experience in the context of a local project for the semantic integration of real estate and associated tributes data. The integrated access to these data should support semantic visual analytic, and query formulation and geo-visualization. The data integration is based on an ontology that has been specifically developed to represent the main concepts and relations on this domain. This ontology is populated with the data available in different repositories, such as the cadastre, municipal registry, and household utilities. Ontology has been populated with the available data, which need to be normalized, completed, and in some cases disambiguated. Finally, we developed a system for the visual formulation and execution of queries over the integrated knowledge base.
2020
Samia Aitouche, Aksa Karima, Susan Gauch, Roy Oberhauser, Nitin Agarwal
eKNOW 2020 - The Twelfth International Conference on Information, Process, and Knowledge Management
978-1-61208-765-8
12th International Conference on Information, Process, and Knowledge Management (eKNOW 2020)
Valencia, Spain
November 21-25, 2020
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11383/2183432
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