Toward model-driven sustainability evaluation

Jörg Kienzle, Gunter Mussbacher, Benoit Combemale, Lucy Bastin, Nelly Bencomo, Jean-Michel Bruel, Christoph Becker, Stefanie Betz, Ruzanna Chitchyan, Betty Cheng, Sonja Klingert, Richard F. Paige, Birgit Penzenstadler, Norbert Seyff, Eugene Syriani, Colin Venters

Research output: Contribution to journalArticlepeer-review

Abstract

Sustainability has emerged as a concern of central relevance. As a wicked problem, it poses challenges to business-as-usual in many areas, including that of modeling. This article addresses a question at the intersection of model-driven engineering and sustainability research: How can we better support sustainability by bringing together model-driven engineering, data, visualization and self-adaptive systems, to facilitate engagement, exploration, and understanding of the effects that individual and organizational choices have on sustainability? We explore this question via an idealized vision of an evaluation environment that facilitates integration and mapping of models from multiple diverse sources, visual exploration, and evaluation of what-if scenarios, for stakeholders with divergent perspectives. The article identifies research challenges to be addressed to enable decision making to support sustainability and provides a map of sustainability modeling issues across disciplines.
Original languageEnglish
Pages (from-to)80-91
Number of pages12
JournalCommunications of the ACM
Volume63
Issue number3
DOIs
Publication statusPublished - 24 Feb 2020

Bibliographical note

© 2019 The Authors

Keywords

  • Sustainability
  • model-driven engineering
  • model-driven evaluation

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