Report on mapping, harmonising and integrating novel data sources for research purposes

Sustainability, a complex and multi-dimensional phenomenon at the crossroads of environmental, social, geographical, and economic considerations, becomes increasingly crucial to explore and measure as we work towards a more sustainable future. Over the past decades, the rise of innovative data sources has significantly expanded our ability to assess the various dimensions of sustainability. Thus, this report provides on the one hand a mapping of innovative data sources used to measure the dimensions of sustainability transition and on the other hand an overview of data integration methods which enable the use of this novel data sources for research purposes. The first part of this research consists in a Large Language Models-enabled distant reading of a large collection of academic texts related to innovative data sources used in the study of sustainability. We developed an expansive operationalization of the notion of sustainability, grounded in the SPES framework, to account for its multi-dimensional and inter-disciplinary character. GPT models have been used at various stages to extract, classify and organise information. The analysis shows which type of innovative data categories have been associated to which dimensions of sustainability. To illustrate this, we also present several selected examples. The second part of this report explores the evolving domain of data integration methods in official statistics and survey methodology. It investigates the possible methods to reach integration of alternative data sources, e.g., administrative records, satellite data, and web data, highlighting their potential to complement and enrich traditional data sources. It offers insights into the challenges and opportunities associated with data integration, providing a comprehensive overview for a broad audience interested in the evolving landscape of statistical methods. Read the full publication here.