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Authors: Carlos Pinheiro 1 ; 2 ; Sérgio Guerreiro 2 ; 3 and Henrique Mamede 2 ; 4

Affiliations: 1 Universidade de Trás-os-Montes e Alto Douro, Vila Real, Portugal ; 2 INESC-ID, Rua Alves Redol 9, 1000-029 Lisbon, Portugal ; 3 Instituto Superior Técnico, University of Lisbon, Lisbon, Portugal ; 4 INESC TEC, Department of Science and Technology, Universidade Aberta, Lisbon, Portugal

Keyword(s): Enterprise Architecture Management, Enterprise Architecture Mining, Automatic Architecture Modelling, Ontology, API.

Abstract: Enterprise Architecture (EA) is a coherent set of principles, methods, and models that express the structure of an enterprise and its IT landscape. EA mining uses data mining techniques to automate EA modelling tasks. Ontologies help to define concepts and the relationships among these concepts to describe a domain of interest. 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 proposed ontology was developed using the OntoUML language to ensure its quality and avoid anti-patterns through ontology rule checks. Then, a hypothesized scenario using data structures close to the real is used to simulate the ontology application and validate its theoretical feasibility as well as its contribution to the Enterprise Architecture Management field.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Pinheiro, C.; Guerreiro, S. and Mamede, H. (2023). Towards an Ontology to Enforce Enterprise Architecture Mining. In Proceedings of the 25th International Conference on Enterprise Information Systems - Volume 2: ICEIS; ISBN 978-989-758-648-4; ISSN 2184-4992, SciTePress, pages 660-668. DOI: 10.5220/0012032300003467

@conference{iceis23,
author={Carlos Pinheiro. and Sérgio Guerreiro. and Henrique Mamede.},
title={Towards an Ontology to Enforce Enterprise Architecture Mining},
booktitle={Proceedings of the 25th International Conference on Enterprise Information Systems - Volume 2: ICEIS},
year={2023},
pages={660-668},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012032300003467},
isbn={978-989-758-648-4},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 25th International Conference on Enterprise Information Systems - Volume 2: ICEIS
TI - Towards an Ontology to Enforce Enterprise Architecture Mining
SN - 978-989-758-648-4
IS - 2184-4992
AU - Pinheiro, C.
AU - Guerreiro, S.
AU - Mamede, H.
PY - 2023
SP - 660
EP - 668
DO - 10.5220/0012032300003467
PB - SciTePress