Resolving Ontological Heterogeneity in the KRAFT Project

Visser, Pepijn R. S.; Beer, Martin; Bench‐Capon, Trevor; Diaz, Bernard M.; Shave, Michael J. R.

doi:10.1007/3-540-48309-8_62

Cited by 35 publications

(19 citation statements)

References 4 publications

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“…Some of the major researches and approaches in web data integration domain are SIMS [5], COIN [6], MOMIS [7], KRAFT [8], OBSERVER [9]. For reconciliation of semantic conflicts between heterogeneous data sources, the above mentioned projects create one global or shared ontology by integrating or merging local schemas or ontologies.…”

Section: System Approach and Architecturementioning

confidence: 99%

Web Data Integration System: Approach and Case Study

Hajmoosaei

Kareem

2008

Business Information Systems

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Abstract. There are a lot of valuable data on the web that organizations or users can use to improve their decision making process. It is therefore, very important and critical that this information be complete, precise and can be acquired on time. Most web sources provide data in semi-structured form on the internet. The extraction and combination of semi-structured data from different sources on the internet often fails because of syntactic and semantic differences. The access, retrieval and utilization of information from the different web data sources imposes a need for the data to be integrated. Integration of web data is a complex process because of the open, dynamic and heterogeneity nature of web data. The solution to this problem is a web data integration system. External information can be extracted from web sources and utilized for users through a web data integration system. In this paper, we first propose an approach and architecture for web data integration system and then develop a prototype of the proposed system for Malaysian universities.

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Section: System Approach and Architecturementioning

confidence: 99%

Web Data Integration System: Approach and Case Study

Hajmoosaei

Kareem

2008

Business Information Systems

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“…KRAFT is a research project on the integration of heterogeneous information using agent architecture [37]. The project is a joint collaboration between the Universities of Aberdeen, Cardiff and Liverpool in conjunction with British Telecom and began in May 1996.…”

Section: Kraft (Wwwcsdabdnacuk/~apreece/research/ Krafthtml)mentioning

confidence: 99%

A review of ontologies with the Semantic Web in view

Ding

2001

Journal of Information Science

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The World Wide Web is currently starting to move from the first generation to the second generation: the Semantic Web. Ontologies are the backbone for this Semantic Web. This paper aims to introduce and give the readers an overview of ontology in general. It discusses the definitions of ontology, kinds of ontology, ontology tools, ontology language and some important ontology projects, both current and completed. 2

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“…Ceri and Widom (1993) listed four categories of semantic conflicts concerning schema matching: naming conflicts, domain conflicts, meta‐data (or datatype) conflicts, and structural conflicts. Visser et al (1997) classified ontology mismatches into two levels: conceptualization mismatches (class mismatches and property mismatches) and explication mismatches (abstraction‐level mismatches and categorization mismatches). Here, we adopt a strategy similar to those of these previous works and classify the semantic heterogeneity in ontologies into four categories.…”

Section: Introductionmentioning

confidence: 99%

A philosophy-driven entity classification and enrichment for ontology mapping

Tun¹,

Dong

Tojo

2010

Expert Systems

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Ontologies are intended to facilitate semantic interoperability among distributed and intelligent information systems. Because of the distributed nature of the World Wide Web, Web ontologies have been developing in multiple forms of heterogeneity. For interoperating among information systems through heterogeneous ontologies, ontology mapping is a prerequisite process to generate alignment between two ontologies. In order to improve alignment accuracy, our approach is to clarify and enrich the semantics of ontological entities before mapping. For this purpose, we present a semi-automatic framework of entity classification and enrichment by applying three philosophical notions: identity condition, existential rigidity, and external dependency. Our objective is to supply a set of philosophy-driven anchors into ontologies for their mapping process by using a sortal taxonomy as a background knowledge model.

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Resolving Ontological Heterogeneity in the KRAFT Project

Cited by 35 publications

References 4 publications

Web Data Integration System: Approach and Case Study

Web Data Integration System: Approach and Case Study

A review of ontologies with the Semantic Web in view

A philosophy-driven entity classification and enrichment for ontology mapping

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