How to Measure Sustainability? An Open-Data Approach

David Ziegler (), Sebastian Wolff, Ana-Beatrice Agu, Giorgio Cortiana, Muhammad Umair, Flore de Durfort, Esther Neumann, Georg Walther, Jakob Kristiansen and Markus Lienkamp
Additional contact information
David Ziegler: Institute of Automotive Technology, Department of Mobility Systems Engineering, School of Engineering and Design, Technical University of Munich, Boltzmannstr. 15, 85748 Garching bei München, Germany
Sebastian Wolff: Institute of Sustainable Mobile Drivetrains, Department of Mobility Systems Engineering, School of Engineering and Design, Technical University of Munich, Schragenhofstr. 31, 80992 München, Germany
Ana-Beatrice Agu: Data Analytics and IoT, E.ON Digital Technology GmbH, Georg-Brauchle Ring 52-54, 80992 München, Germany
Giorgio Cortiana: Data Analytics and IoT, E.ON Digital Technology GmbH, Georg-Brauchle Ring 52-54, 80992 München, Germany
Muhammad Umair: Data Analytics and IoT, E.ON Digital Technology GmbH, Georg-Brauchle Ring 52-54, 80992 München, Germany
Flore de Durfort: Data Analytics and IoT, E.ON Digital Technology GmbH, Georg-Brauchle Ring 52-54, 80992 München, Germany
Esther Neumann: Data Analytics and IoT, E.ON Digital Technology GmbH, Georg-Brauchle Ring 52-54, 80992 München, Germany
Georg Walther: Data Analytics and IoT, E.ON Digital Technology GmbH, Georg-Brauchle Ring 52-54, 80992 München, Germany
Jakob Kristiansen: Institute of Automotive Technology, Department of Mobility Systems Engineering, School of Engineering and Design, Technical University of Munich, Boltzmannstr. 15, 85748 Garching bei München, Germany
Markus Lienkamp: Institute of Automotive Technology, Department of Mobility Systems Engineering, School of Engineering and Design, Technical University of Munich, Boltzmannstr. 15, 85748 Garching bei München, Germany

Sustainability, 2023, vol. 15, issue 4, 1-23

Abstract: Determining quantitative sustainable development metrics can be difficult and requires a high effort in manual data acquisition on an institutional level, like the Word Bank or the United Nations, without adequately reflecting reality. To overcome the lack of a transparent and scalable method, which links local actions to global sustainability metrics, the Sustainability Mirror connects the Sustainable Development Goals (SDGs) with publicly and locally available data to proxy SDG metrics. By applying the approach to Germany, we calculated eight SDG metrics on a regional level. Comparing our results to two German cities, we show that the Sustainability Mirror reflects economic and ecological sustainability measures. Furthermore, we demonstrate the mirror’s scalability and spatial resolution by applying the method to each German county. Presenting a proof-of-concept, we show that proxy data can link local and global sustainability metrics. However, further research should include more social sustainability topics. Finally, we are sure our approach and its implementations can contribute to a continuous assessment of spatial and temporal spreads and changes in SDG metrics.

Keywords: SDGs; sustainability; indicators; spatial; temporal; open data; proxy (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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