Information integration in the enterprise
Communications of the ACM - Enterprise information integration: and other tools for merging data
Using Graph Transformation to Support Collaborative Ontology Evolution
Applications of Graph Transformations with Industrial Relevance
Towards a Pattern-Driven Topical Ontology Modeling Methodology in Elderly Care Homes
OTM '09 Proceedings of the Confederated International Workshops and Posters on On the Move to Meaningful Internet Systems: ADI, CAMS, EI2N, ISDE, IWSSA, MONET, OnToContent, ODIS, ORM, OTM Academy, SWWS, SEMELS, Beyond SAWSDL, and COMBEK 2009
Business semantics management: A case study for competency-centric HRM
Computers in Industry
Scaling alignment of large ontologies
International Journal of Bioinformatics Research and Applications
Supporting concurrent ontology development: Framework, algorithms and tool
Data & Knowledge Engineering
Ontology-based expert system for home automation controlling
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part I
ADBIS'11 Proceedings of the 15th international conference on Advances in databases and information systems
Cancer data integration and querying with genetegra
DILS'12 Proceedings of the 8th international conference on Data Integration in the Life Sciences
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Managing ontologies and annotated data throughout their life-cycles is at the core of semantic systems of all kinds. Ontology Management, an edited volume by senior researchers in the field, provides an up-to-date, concise and easy-to-read reference on this topic. This volume describes relevant tasks, practical and theoretical challenges, limitations and methodologies, plus available software tools. The editors discuss integrating the conceptual and technical dimensions with a business view on using ontologies, by stressing the cost dimension of ontology engineering and by providing guidance on how up-to-date tooling helps to build, maintain, and use ontologies. Also included is a one-stop reference on all aspects of managing ontological data and best practices on ontology management for a number of application domains. Ontology Management is designed as a reference or secondary text for researchers and advanced-level students studying semantic systems, Semantic Web Services (SWS) and Web Services, information systems, data and knowledge engineering, and the Semantic Web in general. Practitioners in industry will find this work invaluable as well.