Abstract
Ontology design is an important process for structuring knowledge to be reused in different projects in the health domain. In this paper, we describe an ontology design for the collaborative knowledge building system ACKTUS to be used for developing personalized knowledge applications for different domains. Different foundational ontologies were compared with respect to selected criteria considered vital for the project, such as modularity and descriptiveness.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Lindgren, H., Winnberg, P.: Collaborative and Distributed Guideline Modeling in the Dementia Domain – An Evaluation Study of ACKTUS. In: Poster Proc. MEDINFO 2010, Kapetown, South Africa (2010)
Guarino, N., Welty, C.: Towards a methodology for ontology-based model engineering. In: ECOOP 2001 Workshop on Model Engineering, Cannes, France (2000)
Temal, L., Dojat, M., Kassel, G., Gibaud, B.: Towards an ontology for sharing medical images and regions of interest in neuroimaging. J. of Biomedical Informatics 41(5), 766–778 (2008)
Oberle, D.: Semantic Management of Middleware. In: The Semantic Web and Beyond. vol. I, Springer, New York (2006)
Mascardi, V., Cordì, V., Rosso, P.: Comparison of Upper Ontologies. In: Baldoni, M., Boccalatte, A., De Paoli, F., Martelli, M., Mascardi, V. (eds.) Conf. on Agenti e industria: Applicazioni Tecnologiche Degli Agenti Software, pp. 55–64 (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ahmad, F., Lindgren, H. (2010). Selection of Foundational Ontology for Collaborative Knowledge Modeling in Healthcare Domain. In: Dicheva, D., Dochev, D. (eds) Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 2010. Lecture Notes in Computer Science(), vol 6304. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15431-7_27
Download citation
DOI: https://doi.org/10.1007/978-3-642-15431-7_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15430-0
Online ISBN: 978-3-642-15431-7
eBook Packages: Computer ScienceComputer Science (R0)