@inproceedings{Gailly2013,

title = {Enterprise-specific ontology-driven process modelling},

author = { Frederik Gailly and Sven Casteleyn and Nadejda Alkhaldi},

editor = {W Ng and S.C. Storey and J. Trujillo},

doi = {10.1007/978-3-319-22348-3_26},

isbn = {978-3-642-41923-2},

year  = {2013},

date = {2013-01-01},

booktitle = {ER 2013: 32th International Conference on Conceptual Modeling proceedings. Hong Kong, china, 11-13 November 2013},

volume = {8217},

pages = {487-494},

publisher = {SPRINGER-VERLAG BERLIN},

organization = {Inst Syst & Technol Informat Control & Commun; Assoc Advancement Artificial Intelligence; IEICE Special Interest Grp Software Interprise Modelling; ACM Special Interest Grp Artificial Intelligence; ACM Special Interest Grp Management Informat Syst; ACM Sp},

series = {Lecture Notes in Computer Science},

abstract = {In different fields, ontologies are increasingly deployed to specify and fix the terminology of a particular domain. In enterprise modelling, their main use lies in serving as a knowledge base for enterprise model creation. Such models, based on one or several compatible so-called enterprise-specific ontologies, allow for model alignment and solve interoperability issues. On the other hand, enterprise models may enrich the enterprise-specific ontology with concepts emerging from practical needs. In order to achieve this reciprocal advantage, we developed an ontology-based enterprise modeling meta-method that facilitates modelers to construct their models using the enterprise-specific ontology. While doing so, modelers give their feedback for ontology improvement. This feedback is subject to community approval, after which it is possibly incorporated into the ontology, thereby evolving the ontology to better fit the enterprise's needs.},

keywords = {enterprise modelling, ontologies},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Gur2012,

title = {GI Systems for Public Health with an Ontology Based Approach},

author = { Nurefsan Gur and Laura Díaz-Sánchez and Tomi Kauppinen},

editor = {Jêrome Gensel and Didier Josselin and Danny Vandenbroucke},

url = {http://hdl.handle.net/10234/159859},

isbn = {978-90-816960-0-5},

year  = {2012},

date = {2012-01-01},

booktitle = {Bridging the Geographic Information Sciences International AGILE2012 Conference Avignon France april 24- 27, 2012},

pages = {86-91},

publisher = {AGILE Digital Editions},

abstract = {Public health research brings substantial benefit to society. Finding data in an efficient way is necessary to carry out relevant space time analysis to address particular studies such as mortality rates and their causes for instance due to environmental exposure. However, health-related information systems remain isolated from other systems such as those managing geospatial and environmental information making it difficult and time-consuming to study relations and patterns in multidisciplinary scenarios. In this paper we employ Linked Open Data technologies to publish health and related data. We report results of the approach with a case study to expose mortality atlas data of the Valencia Community in Spain. The results show how to overcome the lack of semantic relations between resources and published data, and how to reduce disparity and redundancy},

keywords = {geospatial data, Health applications, linked open data, ontologies},

pubstate = {published},

tppubtype = {inproceedings}

}