Ontology-based data integration

About: Ontology-based data integration is a research topic. Over the lifetime, 11065 publications have been published within this topic receiving 216888 citations.

WikiMatch: using wikipedia for ontology matching

Abstract: Finding correspondences between different ontologies is a crucial task in the Semantic Web. Ontology matching tools are capable of solving that task in an automated manner, some even dealing with ontologies in different natural languages. Most state of the art matching tools use internal element and structure based techniques, while the use of large-scale external knowledge resources, especially internet resources, is still rare. In this paper, we introduce WikiMatch, a matching tool that exploits Wikipedia as an external knowledge source. We show that using Wikipedia is a feasible way of performing ontology matching, especially if different natural languages are involved.

The Cell Cycle Ontology: an application ontology for the representation and integrated analysis of the cell cycle process

Abstract: The Cell Cycle Ontology (http://www.CellCycleOntology.org) is an application ontology that automatically captures and integrates detailed knowledge on the cell cycle process. Cell Cycle Ontology is enabled by semantic web technologies, and is accessible via the web for browsing, visualizing, advanced querying, and computational reasoning. Cell Cycle Ontology facilitates a detailed analysis of cell cycle-related molecular network components. Through querying and automated reasoning, it may provide new hypotheses to help steer a systems biology approach to biological network building.

Research on heterogeneous data integration model of group enterprise based on cluster computing

Abstract: Cluster, consisting of a group of computers, is to act as a whole system to provide users with computer resources. Each computer is a node of this cluster. Cluster computer refers to a system consisting of a complete set of computers connected to each other. With the rapid development of computer technology, cluster computing technique with high performance---cost ratio has been widely applied in distributed parallel computing. For the large-scale close data in group enterprise, a heterogeneous data integration model was built under cluster environment based on cluster computing, XML technology and ontology theory. Such model could provide users unified and transparent access interfaces. Based on cluster computing, the work has solved the heterogeneous data integration problems by means of Ontology and XML technology. Furthermore, good application effect has been achieved compared with traditional data integration model. Furthermore, it was proved that this model improved the computing capacity of system, with high performance---cost ratio. Thus, it is hoped to provide support for decision-making of enterprise managers.

OntoMedia: An Ontology for the Representation of Heterogeneous Media

Abstract: With the emergence of the Semantic Web, a shared vocabulary is necessary to annotate the vast collection of heterogeneous media already in existence. The OntoMedia ontology aims to provide a meaningful set of relationships which may enable this process, while being suited to mapping and extension. In this paper we outline the salient features of our ontology as well as initial applications and comparisons to existing technologies.

An environment for distributed ontology development based on dependency management

Abstract: This paper describes a system for supporting development of ontology in a distributed manner. By a distributed manner, we mean ontology is divided into several component ontologies, which are developed by different developers in a distributed environment. The target ontology is obtained by compiling the component ontologies. These component ontologies are identified according to their conceptual level or domain characteristics. The distributed development of ontologies applies to many situations such as cooperative development, reusing ontologies and so on. To support such a way of ontology development, we investigate the dependency between component ontologies and design some functions for management of these ontologies based on their dependencies. We next consider the influence of a change of one ontology to others through its dependencies and design a function to suggest a few candidate modifications of the influenced ontology for keeping the consistency. We also present some examples of how the system works.