Metamodel for enterprise architecture: A systematic literature review
Enterprise Architecture (EA) models can be used to support IT/business alignment. Frequent architecture changes and the challenge of collecting EA data from various stakeholders in large organizations can be problematic due to the size and complexity of EA models. A tighter synchronization between E...
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my.utm.987512023-02-02T08:20:15Z http://eprints.utm.my/id/eprint/98751/ Metamodel for enterprise architecture: A systematic literature review Arzimi, Intan Maizura Mahrin, Mohd. Naz'ri Hussein, Surya Sumarni Abu Bakar, Nur Azaliah Hassan, Noor Hafizah Chuprat, Suriayati T Technology (General) Enterprise Architecture (EA) models can be used to support IT/business alignment. Frequent architecture changes and the challenge of collecting EA data from various stakeholders in large organizations can be problematic due to the size and complexity of EA models. A tighter synchronization between EA models and what they represent in the real world is discussed in this paper, resulting in increased model actuality and consistency. To support these processes, the EA model implementation tool must be able to work with contextual data that is not typically stored alongside EA models. The purpose of this paper is to present a systematic review of the criteria for developing an EA metamodel. The criteria for developing an EA metamodel were assessed in research studies published between March 2019 and December 2019. An established method of the systematic literature review was used to extract and synthesize data in this research. 2022 Conference or Workshop Item PeerReviewed Arzimi, Intan Maizura and Mahrin, Mohd. Naz'ri and Hussein, Surya Sumarni and Abu Bakar, Nur Azaliah and Hassan, Noor Hafizah and Chuprat, Suriayati (2022) Metamodel for enterprise architecture: A systematic literature review. In: 6th IEEE International Conference on Recent Advances and Innovations in Engineering, ICRAIE 2021, 1 - 3 December 2021, Virtual, Kedah, Malaysia. http://dx.doi.org/10.1109/ICRAIE52900.2021.9703981 |
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T Technology (General) Arzimi, Intan Maizura Mahrin, Mohd. Naz'ri Hussein, Surya Sumarni Abu Bakar, Nur Azaliah Hassan, Noor Hafizah Chuprat, Suriayati Metamodel for enterprise architecture: A systematic literature review |
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Enterprise Architecture (EA) models can be used to support IT/business alignment. Frequent architecture changes and the challenge of collecting EA data from various stakeholders in large organizations can be problematic due to the size and complexity of EA models. A tighter synchronization between EA models and what they represent in the real world is discussed in this paper, resulting in increased model actuality and consistency. To support these processes, the EA model implementation tool must be able to work with contextual data that is not typically stored alongside EA models. The purpose of this paper is to present a systematic review of the criteria for developing an EA metamodel. The criteria for developing an EA metamodel were assessed in research studies published between March 2019 and December 2019. An established method of the systematic literature review was used to extract and synthesize data in this research. |
format |
Conference or Workshop Item |
author |
Arzimi, Intan Maizura Mahrin, Mohd. Naz'ri Hussein, Surya Sumarni Abu Bakar, Nur Azaliah Hassan, Noor Hafizah Chuprat, Suriayati |
author_facet |
Arzimi, Intan Maizura Mahrin, Mohd. Naz'ri Hussein, Surya Sumarni Abu Bakar, Nur Azaliah Hassan, Noor Hafizah Chuprat, Suriayati |
author_sort |
Arzimi, Intan Maizura |
title |
Metamodel for enterprise architecture: A systematic literature review |
title_short |
Metamodel for enterprise architecture: A systematic literature review |
title_full |
Metamodel for enterprise architecture: A systematic literature review |
title_fullStr |
Metamodel for enterprise architecture: A systematic literature review |
title_full_unstemmed |
Metamodel for enterprise architecture: A systematic literature review |
title_sort |
metamodel for enterprise architecture: a systematic literature review |
publishDate |
2022 |
url |
http://eprints.utm.my/id/eprint/98751/ http://dx.doi.org/10.1109/ICRAIE52900.2021.9703981 |
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1758578014479712256 |
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13.211869 |