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Towards an ontology to enforce enterprise architecture mining

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dc.contributor.authorPinheiro, Carlos
dc.contributor.authorGuerreiro, Sérgio
dc.contributor.authorSão Mamede, Henrique
dc.date.accessioned2023-06-12T15:12:33Z
dc.date.available2023-06-12T15:12:33Z
dc.date.issued2023
dc.description.abstractEnterprise Architecture (EA) is a coherent set of principles, methods, and models that express the structure of an enterprise and its IT landscape. Ontologies help to define concepts and the relationships among these concepts that describe a domain of interest. EA mining uses data mining techniques to automate the EA modelling. This work presents an extensible ontology for EA mining focused on extracting architectural models that use logs from an API gateway as the data source. The Unified Foundational Ontology (UFO) provided the foundations of ontology and OntoUML, the ontology language. A hypothesized scenario using data structures close to the real is used to simulate the ontology application and validate its theoretical feasibility. This research aims to contribute to the Enterprise Architecture Management acknowledgement base.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.5220/0012032300003467pt_PT
dc.identifier.issn2184-4992
dc.identifier.urihttp://hdl.handle.net/10400.2/14012
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherScitepresspt_PT
dc.relationInstituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento em Lisboa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectEnterprise architecture managementpt_PT
dc.subjectEnterprise architecture miningpt_PT
dc.subjectAutomatic architecture modellingpt_PT
dc.subjectOntologypt_PT
dc.subjectAPIpt_PT
dc.titleTowards an ontology to enforce enterprise architecture miningpt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.awardTitleInstituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento em Lisboa
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F50021%2F2020/PT
oaire.citation.endPage668pt_PT
oaire.citation.startPage660pt_PT
oaire.citation.titleICEIS 2023. 25th International Conference on Enterprise Information Systemspt_PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameSão Mamede
person.givenNameHenrique
person.identifierR-002-0P0
person.identifier.ciencia-id7F17-9DAD-C007
person.identifier.orcid0000-0002-5383-9884
person.identifier.scopus-author-id36458782500
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsrestrictedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublication86fd6131-eed5-42be-9639-9466ddf680ab
relation.isAuthorOfPublication.latestForDiscovery86fd6131-eed5-42be-9639-9466ddf680ab
relation.isProjectOfPublicationdb90d70d-e43e-4cab-9cfd-9b4f4db2e7af
relation.isProjectOfPublication.latestForDiscoverydb90d70d-e43e-4cab-9cfd-9b4f4db2e7af

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