The Agenda 2030 includes a set of targets that need to be achieved by 2030. Although none of the 17 Sustainable Development Goals (SDGs) focuses exclusively on cultural heritage, the resulting Agenda includes explicit reference to heritage in SDG 11.4 and indirect reference to other Goals. Achievement of international targets shall happen at local and national level, and therefore, it is crucial to understand how interventions on local heritage are monitored nationally, therefore feeding into the sustainable development framework. This paper is focused on gauging the implementation of the Sustainable Development Goals with reference to cultural heritage, by interrogating the current way of classifying it (and consequently monitoring). In fact, there is no common dataset associated with monitoring SDGs, and the field of heritage is extremely complex and diversified. The purpose for the paper is to understand if the taxonomy used by different national databases allows consistency in the classification and valuing of the different assets categories. The European case study has been chosen as field of investigation, in order to pilot a methodology that can be expanded in further research. A cross-comparison of a selected sample of publicly accessible national cultural heritage databases has been conducted. As a result, this study confirms the existence of general harmonisation of data towards the achievement of the SDGs with a broad agreement of the conceptualisation of cultural heritage with international frameworks, thus confirming that consistency exists in the classification and valuing of the different assets categories. However, diverse challenges of achieving a consistent and coherent approach to integrating culture in sustainability remains problematic. The findings allow concluding that it could be possible to mainstream across different databases those indicators, which could lead to depicting the overall level of attainment of the Agenda 2030 targets on heritage. However, more research is needed in developing a robust correlation between national datasets and international targets.
The Collective Intelligence based Program to Accelerate Achievement of the Sustainable Development Goals as a Case Study for Collectively Intelligent Program Design