DocumentCode :
3576439
Title :
Enhancing Business Process modelling for e-Government processes using semantic web technologies and Linked Data principles
Author :
Maalouf, Eliane ; Sokhn, Maria
Author_Institution :
Univ. of Appl. Sci. of Western Switzerland, Sierre, Switzerland
fYear :
2014
Firstpage :
1
Lastpage :
8
Abstract :
Semantic Web technologies are being applied more and more in business context applications. The domain of Business Process Management (BPM) is no exception. Additionally, Linked Data principles become interesting to apply in this context as well to enrich processes with information from more diverse sources. We aim to apply Semantic Web technologies and Linked Data principles to enhance Business Process modelling of Swiss e-Government public processes. To favour the reuse of processes from a process repository, the modelling tool will assist the user while modelling through auto completion, process translation, decomposition and annotation. Annotations on processes will allow linking those processes to ontology concepts related to the cyber administration standards. This paper will focus on translating processes to Resource Description Framework (RDF) and the creation of the data links, as well as process translation from German to French.
Keywords :
business data processing; data structures; government data processing; language translation; natural language processing; ontologies (artificial intelligence); publishing; semantic Web; BPM; RDF; Swiss e-government public processes; annotation; auto completion; business process modelling enhancement; cyber administration standards; data links; decomposition; linked data principles; modelling tool; ontology concepts; process repository; process translation; resource description framework; semantic Web technologies; Business; Context; Data models; Ontologies; Resource description framework; Semantics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
eChallenges e-2014, 2014 Conference
Print_ISBN :
978-1-9058-2445-8
Type :
conf
Filename :
7058152
Link To Document :
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