The heterogeneity of ontologies is a major obstacle to the promised interoperability of knowledge in the Semantic Web. Ontology mappings can help to mitigate the effects by specifying the correspondences between relat...
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The heterogeneity of ontologies is a major obstacle to the promised interoperability of knowledge in the Semantic Web. Ontology mappings can help to mitigate the effects by specifying the correspondences between related ontologies. However, the creation of mappings is still complex and time-consuming and therefore it is appealing to discover existing mappings and to reuse them. For reuse, it is essential to understand how a mapping was created and applied. Thus meta-data documenting the lifecycle of an ontology mapping is essential to facilitate management and reuse. Currently the mapping lifecycle is only fragmentary documented and in general the reuse of ontology mappings is insufficiently supported by applications and formats. This paper addresses the question to what extent a semantically expressive ontology-based meta-data model can aid in the discovery, management and reuse of ontology mappings. In particular, experimental results collected from a use-case study on mapping discovery are presented. Based on findings derived, it is shown that semantic rich and effective meta-data describing the ontology mapping lifecycle are crucial for management of ontology mappings. Finally, to address the identified challenges, a framework for management of ontology mappings is outlined.
Integrating and relating heterogeneous data using inference is one of the cornerstones of semantic technologies and there are a variety of ways in which this may be achieved. Cross source relationships can be automati...
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Integrating and relating heterogeneous data using inference is one of the cornerstones of semantic technologies and there are a variety of ways in which this may be achieved. Cross source relationships can be automatically translated or inferred using the axioms of RDFS/OWL, via user generated rules, or as the result of SPARQL query result transformations. For a given problem it is not always obvious which approach (or combination of approaches) will be the most effective and few guidelines exist for making this choice. This paper discusses these three approaches and demonstrates them using an "acquaintance" relationship drawn from data residing in common RDF information sources such as FOAF and DBLP data stores. The implementation of each approach is described along with practical considerations for their use. Quantitative and qualitative evaluation results of each approach are presented and the paper concludes with initial suggestions for guiding principles to help in selecting an appropriate approach for integrating heterogeneous semantic data sources.
This paper presents an approach for modeling location-based profiles of social image media based on tagging information and collaborative geo-reference annotations. We utilize pattern mining techniques for obtaining s...
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This paper presents an approach for modeling location-based profiles of social image media based on tagging information and collaborative geo-reference annotations. We utilize pattern mining techniques for obtaining sets of tags that are specific for the specified point, landmark, or region of interest. Next, we show how these candidate patterns can be presented and visualized for interactive exploration using a combination of general pattern mining visualizations and views specialized on geo-referenced tagging data. We present a case study using publicly available data from the Flickr photo sharing application.
Federated policy systems are required to support the emergent complexity and organizational heterogeneity of modern Internet service delivery. This paper presents a distributed policy management approach which utilize...
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Federated policy systems are required to support the emergent complexity and organizational heterogeneity of modern Internet service delivery. This paper presents a distributed policy management approach which utilizes a flexible, tree-based capability authority model to partition and delegate federated capabilities or services. A trust management model and a delegation logic is defined which supports secure decentralized policy reasoning and addresses performance overheads due to distributed rule evaluation, threats from malformed or malicious federated principals and allows flexibility with respect to delegation chain reduction or capability authority re-partitioning. The system is evaluated through a security analysis and a prototype implementation of a federated policy engineering framework based on this logic is described. This framework is based on public key certificates and an extension to the Keynote Trust Management language. It provides practical management services such as key discovery and certificate revocation in addition to the core capability delegation function.
Managing networks and services in large virtual enterprises often requires significant expertise to decipher and reconcile information coming from several heterogeneous sources. This presents a significant challenge a...
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The proliferation of smart home technologies providing home users with digital services presents an interoperability problem. This paper asserts that the value of these services can be greatly extended by enabling tec...
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This paper examines the feasibility of using ontologies to model generic sensor networks, based on the capabilities of the current generation of ontology tools. The creation of such an ontology, the current tool's...
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Sometimes users of a music retrieval system are not able to explicitly state what they are looking for. They rather want to browse a collection in order to get an overview and to discover interesting content. A common...
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Sometimes users of a multimedia retrieval system are not able to explicitly state their information need. They rather want to browse a collection in order to get an overview and to discover interesting content. In pre...
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Most ontology mapping research has focused on the matching of ontologies written in the same natural language, and developing tools and techniques that support this monolingual ontology mapping process. However, as kn...
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Most ontology mapping research has focused on the matching of ontologies written in the same natural language, and developing tools and techniques that support this monolingual ontology mapping process. However, as knowledge modelling is not restricted to the usage of a single natural language, mapping systems must be able to operate upon ontologies that are labelled in diverse natural languages. This paper outlines a semanticoriented cross-lingual ontology mapping framework that makes use of several information sources to influence the selection of ontology label translations in the process of generating high quality mapping results, and presents a high-level overview of the evaluation strategy of the proposed framework.
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