Abstract
Enterprise architecture management is the basis of systemic enterprise transformations and information technology architecture development. Nowadays enterprise architecting is almost synonymous to diagramming. Diagrams are effective for knowledge elicitation, structuring, and dissemination. But as the number of diagrams and their types grows, they overlap and evolve, it becomes hard to maintain a collection of interrelated diagrams, even with the help of a common repository. Besides the very nature of enterprise architecting requires a lot of classifications (e.g. process architecture/classification) and matrices (goals - processes, processes - organizational roles, processes - applications…). The ORG-Master tool combines classifications and matrices with traditional diagram-based technologies.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Buckl, S., Schweda, C.M.: On the State-of-the-Art in Enterprise Architecture Management Literature. Technical University of Munich (2011)
Scott Bittler, R.: Magic Quadrant for Enterprise Architecture Tools, ID G00234030, Gartner Inc. (2012)
Lengler, R., Eppler, M.: Towards a Periodic Table of Visualization Methods for Management. In: Conference on Graphics and Visualization in Engineering, pp. 1–6 (2007)
Ghoniem, M., Fekete, J., Castagliola, P.: On the readability of graphs using node-link and matrix-based representations: a controlled experiment and statistical analysis. Information Visualization 4(2), 114–135 (2005)
Keller, R., Eckert, C.M., Clarkson, P.J.: Matrices or node-link diagrams: which visual representation is better for visualising connectivity models? Information Visualization 5, 62–76 (2006)
TOGAF® 9.1, Part IV: Architecture Content Framework: Architectural Artifacts, http://pubs.opengroup.org/architecture/togaf9-doc/arch/chap35.html (retrieved June 20, 2013)
Davis, R.: ARIS Design Platform Advanced Process Modelling and Administration. Springer-Verlag London Limited, London (2008)
IBM Rational® System Architect v. 11.4, Information center, http://publib.boulder.ibm.com/infocenter/rsysarch/v11/topic/com.ibm.sa.help.doc/topics/c_Matrix_Editor.html (retrieved March 15, 2013)
Casewise Modeler, http://www.casewise.com/products/modeler (retrieved March 15, 2013)
Grigoriev, L., Kudryavtsev, D.: The ontology-based business architecture engineering framework. In: The 10th International Conference on Intelligent Software Methodologies, Tools and Techniques, Saint-Petersburg, Russia. Frontiers in Artificial Intelligence and Applications, pp. 233–252. IOS Press (2011)
Staab, S., Studer, R. (eds.): Handbook on Ontologies. Springer (2009)
Gavrilova, T.: Ontological engineering for practical knowledge work. In: Apolloni, B., Howlett, R.J., Jain, L. (eds.) KES 2007, Part II. LNCS (LNAI), vol. 4693, pp. 1154–1161. Springer, Heidelberg (2007)
France, R., Rumpe, B.: Domain specific modeling. Software and Systems Modeling 4(1), 1–3 (2005)
Koznov, D.: Process Model of DSM Solution Development and Evolution for Small and Medium-Sized Software Companies. In: Workshops of the 15th IEEE International Conference on Enterprise Distributed Object Computing, pp. 85–92 (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Grigoriev, L., Kudryavtsev, D. (2013). ORG-Master: Combining Classifications, Matrices and Diagrams in the Enterprise Architecture Modeling Tool. In: Klinov, P., Mouromtsev, D. (eds) Knowledge Engineering and the Semantic Web. KESW 2013. Communications in Computer and Information Science, vol 394. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41360-5_20
Download citation
DOI: https://doi.org/10.1007/978-3-642-41360-5_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-41359-9
Online ISBN: 978-3-642-41360-5
eBook Packages: Computer ScienceComputer Science (R0)