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The Enterprise Architecture Analysis Tool–Support for the Predictive, Probabilistic Architecture Modeling Framework
KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.ORCID iD: 0000-0002-3293-1681
KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
2013 (English)In: 19th Americas Conference on Information Systems, AMCIS 2013 - Hyperconnected World: Anything, Anywhere, Anytime, Association for Information Systems, 2013, 3350-3364 p.Conference paper, Published paper (Refereed)
Abstract [en]

The business of contemporary organizations is heavily dependent on information systems. Business processes and IT are interwoven and numerous technologies are in use. How the involved systems affect each other or impact the organizations' business domain is often uncertain, thus decision-making regarding information technology is challenging. Enterprise architecture (EA) is a holistic, model-based management approach. Many of the available EA software tools focus on documenting and have limited analysis capabilities. In this article, a tool for EA analysis is presented, supporting the analysis of properties such as business fit, security, and interoperability. The tool is implemented to support the Predictive, Probabilistic Architecture Modeling Framework to specify and apply assessment frameworks for performing property analysis on EA models.

Place, publisher, year, edition, pages
Association for Information Systems, 2013. 3350-3364 p.
Keyword [en]
Enterprise Architecture Analysis, probabilistic inference, system properties, software tool
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:kth:diva-126282Scopus ID: 2-s2.0-84893227613ISBN: 978-162993394-8 (print)OAI: oai:DiVA.org:kth-126282DiVA: diva2:642119
Conference
19th Americas Conference on Information Systems, AMCIS 2013; Chicago, IL; United States; 15 August 2013 through 17 August 2013
Note

QC 20131101

Available from: 2013-08-20 Created: 2013-08-20 Last updated: 2014-03-20Bibliographically approved

Open Access in DiVA

fulltext(2049 kB)671 downloads
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File name FULLTEXT01.pdfFile size 2049 kBChecksum SHA-512
79ac4318137d17bc58e76f3b16ddaa37f1b67aedce44375a9fd460df7a8f12e9e64fdeb8f8eb2267ded699502bfa4115362eb67176c9340b9401c2601c55c055
Type fulltextMimetype application/pdf

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