TY - JOUR
T1 - Toward model-driven sustainability evaluation
AU - Kienzle, Jörg
AU - Mussbacher, Gunter
AU - Combemale, Benoit
AU - Bastin, Lucy
AU - Bencomo, Nelly
AU - Bruel, Jean-Michel
AU - Becker, Christoph
AU - Betz, Stefanie
AU - Chitchyan, Ruzanna
AU - Cheng, Betty
AU - Klingert, Sonja
AU - Paige, Richard F.
AU - Penzenstadler, Birgit
AU - Seyff, Norbert
AU - Syriani, Eugene
AU - Venters, Colin
N1 - © 2019 The Authors
PY - 2020/2/24
Y1 - 2020/2/24
N2 - 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.
AB - 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.
KW - Sustainability
KW - model-driven engineering
KW - model-driven evaluation
UR - https://dl.acm.org/doi/10.1145/3371906
UR - http://www.scopus.com/inward/record.url?scp=85080891648&partnerID=8YFLogxK
U2 - 10.1145/3371906
DO - 10.1145/3371906
M3 - Article
SN - 0001-0782
VL - 63
SP - 80
EP - 91
JO - Communications of the ACM
JF - Communications of the ACM
IS - 3
ER -