Toward model-driven sustainability evaluation

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.

Publication DOI: https://doi.org/10.1145/3371906
Divisions: Engineering & Applied Sciences > Computer Science
Engineering & Applied Sciences
Engineering & Applied Sciences > Systems analytics research institute (SARI)
Additional Information: © 2019 The Authors
Uncontrolled Keywords: Sustainability,model-driven engineering,model-driven evaluation,Computer Science(all)
Full Text Link: https://hal.inr ... fr/hal-02146543
Related URLs: https://dl.acm. ... 10.1145/3371906 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2020-02-24
Accepted Date: 2019-05-24
Authors: Kienzle, Jörg
Mussbacher, Gunter
Combemale, Benoit
Bastin, Lucy (ORCID Profile 0000-0003-1321-0800)
Bencomo, Nelly (ORCID Profile 0000-0001-6895-1636)
Bruel, Jean-Michel
Becker, Christoph
Betz, Stefanie
Chitchyan, Ruzanna
Cheng, Betty
Klingert, Sonja
Paige, Richard F.
Penzenstadler, Birgit
Seyff, Norbert
Syriani, Eugene
Venters, Colin

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