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Please use this identifier to cite or link to this item: http://dspace.ucuenca.edu.ec/handle/123456789/29197
Title: Towards the creation of a semantic repository of iStar-based context models
Authors: Abad Regalado, Karina Alexandra
Carvallo Vega, Juan Pablo
Espinoza Mejía, Jorge Mauricio
Saquicela Galarza, Víctor Hugo
metadata.dc.ucuenca.correspondencia: Abad, K.; Departamento de Ciencias de la Computación, Universidad de CuencaEcuador; email: karina.abadr@ucuenca.edu.ec
metadata.dc.ucuenca.nombrerevista: 4th International Conference on Software Process Improvement CIMPS 2015
Keywords: Context Actors
Context Models
Linked Data
Ontology
Semantic Repository
Strategic Dependency
Issue Date: 28-Oct-2015
metadata.dc.ucuenca.embargoend: 1-Jan-2022
metadata.dc.ucuenca.volumen: 405
metadata.dc.source: Advances in Intelligent Systems and Computing
metadata.dc.identifier.doi: 10.1007/978-3-319-26285-7_11
Publisher: SPRINGER VERLAG
metadata.dc.description.city: 
Mazatlán Sinaloa
metadata.dc.type: Article
Abstract: 
The System Architecture definition of the majority of organizations requires a deep understanding about its environment and organizational structure; nevertheless, the construction of such models is not an easy task because of the gap of knowledge and communication between the technical and administrative staff. The DHARMA method, which makes intensive use of the i* notation, propose a solution to that problem, supporting the Context Models construction. This paper presents an approach for annotating the i* models with semantic technologies, to support the search and generation of Context Models based on the knowledge defined in ontological models, allowing the creation of a Semantic Repository of Context Models, which will be used to discover relations between different i* models and extract patterns from them.
URI: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84983119284&doi=10.1007%2f978-3-319-26285-7_11&partnerID=40&md5=af792af942fb69e79063a5e572018133
http://dspace.ucuenca.edu.ec/handle/123456789/29197
ISBN: 9783319262833
ISSN: 21945357
Appears in Collections:Artículos

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