Data analytics and data sharing in collaborative and cross-sectoral regulation: a survey of challenges

The paper ”Data analytics and data sharing in collaborative and cross-sectoral regulation: a survey of challenges” (Pisarkiewicz, A. R.,  Parcu P.L., Carrozza, C.) will be presented at the 11th FSR Annual Conference “From Data Spaces to Data Governance” (9-10 June, 2022).

Abstract:

In rapidly evolving digital ecosystems, there is a plethora of institutional public actors which for most of their existence have operated in silos. While cross-sectoral collaboration and multi-sectoral regulators have already emerged, challenges posed by the digital ecosystem will require collaborative regulation that goes far beyond arrangements that we can observe today. Such regulation will have to involve coordination among a wider set of public authorities in order to reflect the multi-stakeholder dimension of the digital world.

Collaboration among authorities will revolve around many issues, but one that is expected to dominate is the collection, analysis, use and sharing of data. While a great part of public discussion focuses on the use of AI, algorithms and data by big tech and private companies, the academic and policy communities are increasingly discussing the increased demand for data sharing (see the recent EU Data Governance Act) involving public sector authorities as the latter are increasingly interested adopting innovative, data-driven and forward-looking regulation that would be apt for the digital environment they oversee.

Considering that data is an integral asset to policy making, as the type and the amount of data change, so should public policy. While an increasing number of authorities may be looking into applying data-driven approaches, they may face a wide variety of challenges surrounding data collection and usage. The truth is that data collection, sharing and analysis is not a one-size-fits-all approach. For example, as the digital economy has grown, the scope of data collection may have increased to a varied extent for different sectoral regulators (consider, for instance the inclusion of OTTs under the EECC), and such expansion may pose different challenges in terms of enforcement. Accordingly, the paper will seek to map challenges that governments may face in developing data-driven regulation in the digital era.

Research Design and Expected Results:

In terms of methodology, this paper will discuss the legal framework governing data collection by sectoral regulators (and competition authorities) and will assess this framework against the management literature on data governance. It will then compare the legal framework with the authorities’ perception of their ability to comply with it, which will be described based on interviews carried out with the officials from a selected set of authorities.

The analysis of the legal framework, the management literature on data governance and individual interviews will allow to map different categories of challenges that governments may face in developing data-driven regulation in the digital era. These challenges could include:

• The availability, quality and relevance of data, considering that data quality is typically determined by data’s fitness for use.
• Data collection and data sharing, both within and across different authorities. This may require addressing organisational (including legal) barriers, management resistance, as well as finding ways to identifying and communicating what is available internally and resolving potential barriers to interoperability. Identifying authorities responsible for data collection and data sharing across different authorities will become particularly important once the Digital Markets Act and Digital Services Act are adopted. As previously telecom or energy operators, now digital platforms will be subject to an increased interaction between competition law and sectoral regulation as well as other policies (such as data protection), which will again bring the topic of data sharing to the fore.
• Skills and capabilities, both in terms of human resources that governments need and technical constraints that they may face, to make the best use of data.

Finally, the paper will consider the question of legitimacy, accountability and public trust, with a focus on transparency and the risks that governments and businesses need to be aware of when implementing data-driven public policies and regulation.