Some of the most promising data that describe flows and interactions across territorial boundaries, such as social media data, customer data, and price scanner data, raise legitimate privacy concerns among the citizens. This is why legislation both nationally and internationally is necessary to provide clarity and uniformity that are needed across national boundaries regarding how privacy can be protected while utilising such datasets for policy-making in the public interest across administrative boundaries.

According to the findings of our ESPON project, BIG DATA such legislation would support the development of new methodologies that couple new datasets with new processes to analyse the data. Further, it would support the development of big data and analytics ecosystems that would ease the usage of the data for public sector purposes.

Since utilisation of new datasets requires expertise from several fields, EU and national actors should prioritise long-term research on how new data sources can be analysed to support territorial development and cohesion.

Furthermore, data standardization, quality benchmarking and data harmonization across administrative boundaries would further promote transnational corridor development and platform creation to enable wide-spread data utilisation. Currently, the lack of harmonization makes the utilisation of big data challenging, especially when crossing national boundaries. The development of a joint harmonized system that takes into account the special needs of corridor governance should be a common objective.

The case study of Estonia: Mobile positioning data

An example from Estonia illustrates how mobile positioning data provides more frequent and up-to-date Spatio-temporal information than conventional methods used in transportation planning. The value of data utilisation relates strongly to the possibility of having near real-time insights into a nation or city’s mobility patterns. An objective of the case study was to develop a high-quality database useful for the spatial and transportation planning in the Ministry of Economic Affairs and Communications of the Republic of Estonia.

Mobile positioning has proved itself as a very good and promising data source for studying mobility-related aspects of the society and/or smaller groups. The data has high time accuracy which reveals short-term differences, includes movements between the place of residence and the workplace as well as other regular places, and differentiates the movements of different social groups (e.g. by gender, age, nationality) and the types of movers. The ESPON project Big Data developed a methodology for producing an everyday mobility database containing abstracted Origin-Destination matrices (or O-D Matrices) of individual-level movements between territorial communities.

In this case study mobile positioning data has been used only to analyse movements within Estonia, but mobile positioning data also allows to estimate flows for cross-border movements based on mobile network operators roaming data. The possibilities of mobile positioning data for cross-border settings should be studied further, as the data is increasingly available in neighboring nations of Finland, Estonia, and Sweden. This kind of data exists in all European nations and if it became more accessible to researchers and government agencies, it could support cross-cutting analyses of the functionalities of all of Europe’s main corridors (e.g. the TEN-T network).

To achieve such ambitions, legislation and ecosystem development are needed to support and ease the usage of mobile positioning data in both the public sector and academic research supporting territorial development. The utilisation of this data has historically required long value chains requiring expertise from several fields, thus indicating the need for public-private partnerships and ecosystem building to foster public value creation. The analytical approach used in this Estonia case is nearly ready for wider use.

Read more about Estonia and the rest of the project's case studies in the final results of the ESPON project BIG DATA