Titlebook: Journal on Data Semantics I; Stefano Spaccapietra,Sal March,Karl Aberer Book 2003 Springer-Verlag Berlin Heidelberg 2003 DOM.artificial in

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On Using Conceptual Data Modeling for Ontology Engineering,ata modeling techniques for building ontologies. Firstly, conceptual schemes are intended to be used during design phases and not at the run-time of applications, while ontologies are typically used and accessed at run-time. To handle this first difference, we define a conceptual markup language (OR

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The , Broker: Querying Data and Their Quality in Cooperative Information Systems,o data quality can imply data of low quality to spread all over the cooperative system. At the same time, improvement can be based on comparing data, correcting them and disseminating high quality data. In this paper, a framework and a related architecture for managing data quality in cooperative in

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Attribute-Based Semantic Reconciliation of Multiple Data Sources,ue ranges, as specializations of a more gemeral attribute. We discuss the approach, analyze its potential advantages, suggest a formalization, demonstrate its use with examples, and suggest directions for further research.

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On Using Conceptual Data Modeling for Ontology Engineering,bles reusing conceptual modeling approaches in modeling and representing ontologies. In this approach we prevent application-specific knowledge to enter or to be mixed with domain knowledge. To end, we present DogmaModeler: an ontology-engineering tool that implements the ideas presented in the pape

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0302-9743 ong-term success is a hard job nowadays, due to a generally di?cult market situation, and library budget restrictions in particular. Because many of the proceedings in LNCS, and especially many978-3-540-20407-7978-3-540-39733-5Series ISSN 0302-9743 Series E-ISSN 1611-3349

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