Distributed and Parallel Databases
Knowledge management systems: issues, challenges, and benefits
Communications of the AIS
Post-Capitalist Society
The Social Life of Information
The Social Life of Information
Determining Semantic Similarity among Entity Classes from Different Ontologies
IEEE Transactions on Knowledge and Data Engineering
A Complexity Measure for Ontology Based on UML
FTDCS '04 Proceedings of the 10th IEEE International Workshop on Future Trends of Distributed Computing Systems
Direct Verbal Communication as a Catalyst of Agile Knowledge Sharing
ADC '04 Proceedings of the Agile Development Conference
Toward Contextualized Theories of Trust: The Role of Trust in Global Virtual Teams
Information Systems Research
An Efficient Ontology Comparison Tool for Semantic Web Applications
WI '05 Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence
Coupling Metrics for Ontology-Based Systems
IEEE Software
A semiotic metrics suite for assessing the quality of ontologies
Data & Knowledge Engineering - Special issue: Natural language and database and information systems: NLDB 03
Journal of Software Maintenance and Evolution: Research and Practice
Situated Learning and the Situated Knowledge Web: Exploring the Ground Beneath Knowledge Management
Journal of Management Information Systems
Development of a Software Engineering Ontology for Multisite Software Development
IEEE Transactions on Knowledge and Data Engineering
Design and natural science research on information technology
Decision Support Systems
An evaluation method for ontology complexity analysis in ontology evolution
EKAW'06 Proceedings of the 15th international conference on Managing Knowledge in a World of Networks
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Challenges over multi-site software development are on working in virtual teams and sharing knowledge. It is quite normal that software engineers working in a virtual team have never met face to face in multi-site environments. In addition they have different educational backgrounds and interpret methods in different ways. Software engineering education, training, and practice are different between universities, cities, and countries. As a result, it is difficult to share a piece of knowledge between distributed teams and among remote team members. There are a number of standards that different teams could be referring to. Remote software engineers use a particular standard as their own individual guide and when they share their own knowledge base and terminology is different from those of others. Most issues raised are related to inconsistency in understanding software engineering theories and practice. Therefore sharing knowledge is the challenge and to resolve the differences between the distributed teams we need to understand its key variables of knowledge sharing. In this paper we propose an ontology-based approach for knowledge sharing measurement. Particularly in the approach, we look into measurement of transferability and complexity of knowledge. The impact of nature of knowledge on knowledge sharing is focused. A prototype is developed taking Software Engineering Ontology as example.