Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
An enterprise architecture framework for multi-attribute information systems analysis
KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.ORCID iD: 0000-0003-3922-9606
2014 (English)In: Journal of Software and Systems Modeling (online), ISSN 1619-1366, E-ISSN 1619-1374, Vol. 13, no 3, 1085-1116 p.Article in journal (Refereed) Published
Abstract [en]

Enterprise architecture is a model-based IT and business management discipline. Enterprise architecture analysis concerns using enterprise architecture models for analysis of selected properties to provide decision support. This paper presents a framework based on the ArchiMate metamodel for the assessment of four properties, viz., application usage, system availability, service response time and data accuracy. The framework integrates four existing metamodels into one and implements these in a tool for enterprise architecture analysis. The paper presents the overall metamodel and four viewpoints, one for each property. The underlying theory and formalization of the four viewpoints is presented. In addition to the tool implementation, a running example as well as guidelines for usage makes the viewpoints easily applicable.

Place, publisher, year, edition, pages
2014. Vol. 13, no 3, 1085-1116 p.
Keyword [en]
Enterprise architecture, Enterprise architecture analysis, Enterprise architecture tool, Data accuracy, Technology usage, Service availability, Service response time
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:kth:diva-102187DOI: 10.1007/s10270-012-0288-2ISI: 000338502600010Scopus ID: 2-s2.0-84903448926OAI: oai:DiVA.org:kth-102187DiVA: diva2:551321
Note

QC 20140813. Updated from manuscript to article in journal.

Available from: 2012-09-12 Created: 2012-09-10 Last updated: 2017-12-07Bibliographically approved
In thesis
1. Enterprise Architecture for Information System Analysis: Modeling and assessing data accuracy, availability, performance and application usage
Open this publication in new window or tab >>Enterprise Architecture for Information System Analysis: Modeling and assessing data accuracy, availability, performance and application usage
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Decisions concerning IT systems are often made without adequate decision-support. This has led to unnecessary IT costs and failures to realize business benefits. The present thesis presents a framework for analysis of four information systems properties relevant to IT decision-making. The work is founded on enterprise architecture, a model-based IT and business management discipline. Based on the existing ArchiMate framework, a new enterprise architecture framework has been developed and implemented in a software tool. The framework supports modeling and analysis of data accuracy, service performance, service availability and application usage. To analyze data accuracy, data flows are modeled, the service availability analysis uses fault tree analysis, the performance analysis employs queuing networks and the application usage analysis combines the Technology Acceptance Model and Task-Technology Fit model. The accuracy of the framework's estimates was empirically tested. Data accuracy and service performance were evaluated in studies at the same power utility. Service availability was tested in multiple studies at banks and power utilities. Data was collected through interviews with system development or maintenance staff. The application usage model was tested in the maintenance management domain. Here, data was collected by means of a survey answered by 55 respondents from three power utilities, one manufacturing company and one nuclear power plant. The service availability studies provided estimates that were accurate within a few hours of logged yearly downtime. The data accuracy estimate was correct within a percentage point when compared to a sample of data objects. Deviations for four out of five service performance estimates were within 15 % from measured values. The application usage analysis explained a high degree of variation in application usage when applied to the maintenance management domain. During the studies of data accuracy, service performance and service availability, records were kept concerning the required modeling and analysis effort. The estimates were obtained with a total effort of about 20 man-hours per estimate. In summary the framework should be useful for IT decision-makers requiring fairly accurate, but not too expensive, estimates of the four properties.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2012. xiii, 41 p.
Series
Trita-EE, ISSN 1653-5146 ; 2012:035
Keyword
Enterprise Architecture, Metamodeling, Decision-making, Data Accuracy, Service Availability, Service Performance, Technology Acceptance Model, Task Technology Fit
National Category
Information Systems
Identifiers
urn:nbn:se:kth:diva-101494 (URN)978-91-7501-444-9 (ISBN)
Public defence
2012-09-17, F3, Lindstedtsvägen 26, KTH, Stockholm, 10:00 (English)
Opponent
Supervisors
Note

QC 20120912

Available from: 2012-09-12 Created: 2012-08-29 Last updated: 2013-01-28Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textScopus

Authority records BETA

Ekstedt, Mathias

Search in DiVA

By author/editor
Närman, PerBuschle, MarkusEkstedt, Mathias
By organisation
Industrial Information and Control Systems
In the same journal
Journal of Software and Systems Modeling (online)
Computer and Information Science

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 473 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf