Tackling biodiversity information is essentially a distributed effort. Data handled are inherently heterogeneous, being provided by distinct research groups and using different vocabularies. Queries in biodiversity systems require to correlate these data, using many kinds of knowledge on geographic, biologic and ecological issues. Available biodiversity systems can only cope with part of these queries, and end users must perform several manual tasks to derive the desired correlations, because of semantic mismatches among data sources and lack of appropriate operators. This paper presents a solution based on Web services to meet these challenges. It relies on ontologies to retrieve the query contexts and uses the terms of this context to discover suitable sources in data repositories. This approach is being tested using real data, with new services.
This paper describes the development of an open source CASE tool, the ArgoCASEGEO, and its modular architecture. The ArgoCASEGEO allows the geographic database modelling based on the UML-GeoFrame conceptual model that is specific for Geographic Information Systems applications. The data dictionary associated to the modelled schema is stored as a XML/XMI document, aiming its use by other software. The ArgoCASEGEO follows a design methodology based on a reusable collection of analysis patterns. The analysis patterns collection is stored in a data base composing a Catalog. The catalog is attached to the ArgoCASEGEO. Thus, searching for existing analysis patterns will be an easier and efficient task.
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