A Layered Ontology-Based Architecture for Integrating Geographic Information
Architectural solutions to information integration have extensively appeared during the last years, mostly from the federated system research field. Some of these solutions were created to deal with geographic information, whose inherent features make the
- PDF / 503,656 Bytes
- 10 Pages / 430 x 660 pts Page_size
- 79 Downloads / 183 Views
2
3
GIISCO Research Group, Departamento de Ciencias de la Computaci´ on, Universidad Nacional del Comahue, Neuquen, Argentina {abuccel,acechich}@uncoma.edu.ar Dipartimento di Informatica, University of Bari, Via E. Orabona, 4 - 70125, Bari, Italy {gendarmi,lanubile,semeraro}@di.uniba.it Dipartimento Tutela delle Acque Interne e Marine, APAT, Via Curtatone, 3 - 00185, Rome, Italy [email protected]
Abstract. Architectural solutions to information integration have extensively appeared during the last years, mostly from the federated system research field. Some of these solutions were created to deal with geographic information, whose inherent features make the integration process particularly complex. Among others, the use of ontologies has been proposed as a way of supporting an automated integration. However, how to specify and use a geographic ontology is not so clear in this context. In this paper, we introduce an ontology-based architectural solution as an extension of a federated system (Information Broker) built by the Italian Agency for Environmental Protection and Technical Services (APAT). Our extension is aimed at improving integration by adding semantic features through the use of ontologies and the ISO 19100 standards. Keywords: Geographic Information Systems, Federated Systems, Ontology, ISO 19100 Standards.
1 Introduction Currently, the information integration research is focusing on Geographic Information Systems (GIS). Most of the proposals in this area come from the federated system research field and use conventional information sources. However, the use of ontologies [1], thesaurus, metadata and other types of semantic resources for integrating Geographic Information Systems is increasingly common. For example, ontologies have become the main tools to solve heterogeneity problems. Therefore, proposals based on conventional systems might be extended to better analyze and compare geographic information. Extending a system by using ontologies implies two main tasks: semantic enrichment and mapping N.T. Nguyen, R. Katarzyniak (Eds.): New Chall. in Appl. Intel. Tech., SCI 134, pp. 135–144, 2008. c Springer-Verlag Berlin Heidelberg 2008 springerlink.com
136
A. Buccella et al.
discovery. The former is aimed to reconcile semantic heterogeneity, so it involves adding more semantic information about the data. Many approaches add extra semantic information through the use of metadata or ontologies. For example, proposals extending common data models such as Entity-Relationship diagrams [2] and object-oriented ones [3] have been presented in order to add geographic features. For the latter, mapping discovery, several surveys [4, 5] have emerged describing and analyzing methodologies, frameworks, and systems proposed for semantic matching, i.e. ontology matching. The proposal of Euzenat & Shvaiko [5] is one of the more recent works describing and analyzing a wide set of ontology matching proposals1. However, all these surveys are focused on conventional systems, and they do not analyze systems
Data Loading...
