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Lessons learned in aligning data and model evolution in collaborative information systems

Published: 14 May 2016 Publication History

Abstract

Today's enterprises have to align their information systems continuously with their dynamic business and IT environment. Collaborative information systems address this challenge by involving diverse users in managing the application's data as well as its conceptual model. In this sense, both the data and the model co-evolve. There are different approaches for aligning data and model evolution, wherein either the data is aligned to the model, or vice versa.
In this work, we present a hybrid approach supporting both strategies and elaborate on our experiences of applying the approach in projects for over five years. Thereby, we discuss challenges and issues faced in those projects, and how we addressed them by redesigning and reimplementing the approach. We formulate those issues and respective solutions as lessons learned, which not only hold for the concrete system which was applied in those projects, but which should guide the design and implementation of all software systems supporting the co-evolution of data and model.

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cover image ACM Conferences
ICSE '16: Proceedings of the 38th International Conference on Software Engineering Companion
May 2016
946 pages
ISBN:9781450342056
DOI:10.1145/2889160
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 14 May 2016

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Author Tags

  1. best practices
  2. collaborative information systems
  3. data evolution
  4. lessons learned
  5. model evolution
  6. semantic wiki

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  • (2018)Modeling and Visualizing Smart City Mobility Business Ecosystems: Insights from a Case StudyInformation10.3390/info91102709:11(270)Online publication date: 29-Oct-2018
  • (2018)From Expert Discipline to Common Practice: A Vision and Research Agenda for Extending the Reach of Enterprise ModelingBusiness & Information Systems Engineering10.1007/s12599-017-0516-y60:1(69-80)Online publication date: 3-Jan-2018
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