Spatial and geographical data as well as spatial referencing frameworks are key assets for the green transformation of our societies. They correspond to a diversity of scopes and technologies (Masser and Crompvoet, 2018). These can be topographical data, digital elevations models, land cover or land use maps as well as statistical surveys using spatial grids. The digital transformation of society and the trend towards open data have exponentially increased the amount of data publicly available, for example Web content, digitised archives, social media, many of which have some spatial characteristics. All these data help us to visualise and better understand the world around us, for example monitor crops or evaluate urban sprawl. They are important tools in the decision-making process for both private and public sectors. Combined this data can become even more valuable than it already is, for example to detect urban heat islands and to evaluate vulnerable population living there (Masson et al., 2020). Space often acts as a common referencing framework to integrate different information into a spatial analysis model, which can show spatial correlations and predict future trends. Such common referencing framework can be direct – if the information can be associated with geodetical coordinates – or indirect – if the information can be associated with entities which themselves have coordinates. Examples of entities that support indirect spatial referencing are administrative units, addresses or place names.

 There is a need for more assistance in discovering and exploring available data as well as integration technologies, and eventually selecting data and integration technologies to prepare data that can support the decisions at stake (Bucher et al., 2023) (Zrhal et al., 2021). This discovery and reuse process require users to be familiar with different search portals and different integration and analysis technologies. They even may need to download the data to better assess if potential uncertainties propagate in their application and affect the result. Altogether, this can be so challenging that users may consider producing new data instead, or simply using the data easiest to find even if it isn’t the most relevant and reliable. Conversely, data providers are faced with the challenge of making their data visible to potential users and receiving feedback on the pertinence and usability of their data.

 These challenges are particularly experienced by national mapping and cadastral agencies (NMCAs). They lack efficient solutions to share data internally within their organizations in a context where multiple data are derived from core products. They also need to discover and reuse external data sources relevant to their activities, e.g. to get to know, in between aerial campaigns, what changes occur that should be propagated in core products, like the development of a wasteland. They need to monitor more systematically the effective usages of the data they publish, which could be useful to report on the value of the product and to improve data to better meet users’ needs.