SDG indicator set as multi-level and multi-sectorial decision support tool combining national reporting and local knowledge on the built environment

Providing a sustainable built environment through appropriate actions and investment decisions taken by various decision-makers calls for a renaissance of planning and a targeted supply and use of data as information. Data is seen as lowest level of abstraction constituting the basis for creating information and knowledge through interpretation (Dühr et al. 2012). Data as interpreted information and knowledge would eventually turn into decision support systems (Evers 2008) and thus unfold its internal power related to the translation from a complex reality into data as well as its external power referring to the communicative function of data (Söderström 1996). Before completing this turn, data needs to be validated. This is a process that requires both, generating and aggregating data on higher levels of abstraction and governance as well as integrating data, which originates from local sources (Kyttä et al. 2013), while pursuing the objective of providing a multi-level and multi-sectorial decision support tool for purposes of planning and decision-making. The 17 SDGs and their 169 sub-goals as part of the Agenda 2030 as well as the 175 paragraphs of the New Urban Agenda provided as starting points for this provision the basis for collecting in Germany in cooperation with cities and counties official data deriving from multi-level sources (Bertelsmann Stiftung 2018). A set of respective indicators has been developed in cooperation with local authorities and national statistical institutions as well as by using publically available open data sources (e.g. Open.NRW, Hackday Niederrhein) and is currently being tested. Considering the sustainable built environment, it is particularly SDG 11 that bridges between overall planning orientations and detailed building actions. The author of the paper suggests combining national reporting mechanisms and local knowledge, reflecting data sources and indicators in urban and spatial typologies as well as referencing the elements against other cultural approaches and international standards.