OnToContent 2013 - 9th International Workshop on Ontology Content (OnToContent 2013)

The Semantic Web is increasingly growing, and the need to capture and share the semantics especially in the large and complex networked information systems is becoming increasingly important. Ontologies and semantic data all represent information sources valuable to end users and are fundamental resources that support a variety of applications in several domains, e.g., data integration, document management, information retrieval, web engineering, and so on.
For this reason Onto-Content 2013 focuses on issues related to the creation, publication, and evaluation of content for ontologies and semantic data. In particular, developing and evaluating the content of ontologies is notoriously a time consuming task when performed manually, but the increasing demand for domain specific ontologies is creating a corresponding demand for rapid assimilation of new content into ontologies without jeopardizing the quality of the ontologies themselves. There is, then, a need for the automation and semi-automation of tasks that develop ontology content, and there is also a need for automation and semi-automation of tasks that evaluate ontologies.
The main topics investigated in this workshop are related to the development, evaluation (both black box an glass box), management, multi-lingual mapping, and documentation of ontologies using automated and semi-automated methods. Furthermore, two special tracks dedicated to specific domain of interest are open; the first track focuses on content creation and evaluation in the e-Governance domain while the second track focuses on Life Sciences.
We invite papers and project descriptions that discuss tools and the methodologies for accomplishing any of these tasks, particularly:
Research papers presenting theoretical solutions, but with a clear illustration on how these solutions can be applied in real-world application domains.
Position papers presenting opinions on some aspect of ontology practice, or describing work that is still in progress, but sufficiently mature to warrant attention.
Business experience and case studies specifying requirements, challenges, or opportunities of modeling and applying ontologies in industry.
We also strongly encourage critical papers deriving lessons from failures in dealing with ontologies, not only stereotypical success reports!
Topics
Methodology and Engineering
Modeling and Engineering Methodologies
Ontology Design Patterns
Quality of Ontologies
Quality of Linked Open Data
Metrics and Tasks for Evaluation of Ontologies
Metrics and Tasks for Evaluation of Linked Open Data
Ontology Reusability
Ontological Usability and Usefulness
Ontology Metadata and Libraries
Ontology Evolution and Versioning
Methodologies for Consensus Reaching
Good, Best, and Bad Practices
Experiences/Empirical results of Ontology Management
Experiences of Light-weight vs. Heavy-weight Ontologies
Automatic and Semi-automatic Content Generation
Knowledge Harvesting
Inductive Methods for Ontologies
Quality of Ontology Mappings
Metrics and Tasks for Evaluation of Ontology Mappings
Multi-lingual and Cross-lingual Ontology Mappings
Semantic Distance and Similarity
Semantics in Sensor Networks
Crowdsourcing Content Generation
Participatory and Evolutionary Approaches to Ontology Engineering
Conflict Resolution and Self-adaptation in ad hoc Networks
Experiences of Light-weight vs. Heavy-weight Ontologies
Metrics and Tasks for Evaluation of Automatically and Semi-automatically Generated Content
e-Governance Ontology
Legal/Legislation Ontologies
Local Government Ontologies
Location Ontology (Real-Estate)
Person/Identity Ontology
Ontologies for Organizations
Ontologies for Social Networks
Ontologies for Digital Libraries
Ontologies for Public Utilities
Ontologies for Modeling Business Process
Ontologies for Supply Chains Management
Ontologies for Risk Analysis
Mappings Between e-Governance Ontologies
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Life Sciences
Biomedical Ontologies
Ontologies for Biology
Ontologies for Natural Sciences
Ontologies for Pharmacology
Ontologies for Food Science
Linked Open Data in Life Sciences
Mappings between Life Science Ontologies