Conceptualizing a national data infrastructure for Switzerland

Abstract

A national data infrastructure (NDI) provides data, data-related services and guidelines for the re-use of data to individuals and organizations. It facilitates efficient sharing of data, supports new business models, and is thus a key enabler for the digital economy, open research, societal collaboration and political processes. While several European countries have taken steps to set up data infrastructures cutting across institutional silos, approaches vary, and there is no common understanding of what a NDI exactly comprises. In Switzerland, activities are still at a conceptual stage. In order to foster a shared vision of what a NDI is about, stakeholder interviews were carried out with representatives of public administration, research, civil society, and the private sector. There is broad consensus among key stakeholders that a NDI is to be conceived as a nationwide distributed technical infrastructure allowing the sharing of data, based on predefined rules. Our findings also suggest that the notion of a NDI should be approached from four perspectives: a big data, a base register, an open data, and a mydata perspective. For its implementation, effective coordination across several dimensions (ethical, legal, political, economical, organizational, semantical, and technical) is crucial, which calls for a truly multidisciplinary approach.

Creating value through data collaboratives

“…Government and semi-government agencies are, for example, opening up datasets for others to use. Their hope in doing so is that wider use and re-use of data may spur data-based innovations, enhance transparency and boost economic growth by enabling new digital services and applications (Estermann et al, 2018;Meijer, 2015Meijer, , 2017Zuiderwijk & Janssen, 2014). These developments are driven by advancements in big, open and linked dat (Janssen & Kuk, 2016).…”

An orchestration approach to smart city data ecosystems

“…Open data platforms are often supported by enabling tools like 'city dashboards', 'datastores' and 'data marketplaces' (Barns, 2018). Irrespective of the approach, known data challenges for urban platforms arise with vendor-lock in problems, misalignment of vendor-government needs, interoperability challenges, complicated data transformation process and fragmented data supply chains (Moshrefzadeh et al, 2017;Suzuki and Finkelstein, 2019) In light of the above challenges, the narrative of city data has moved from platforms to more consolidated infrastructures that provide a wide variety of data to city actors according to their needs using distributed and decentralised architectures (Estermann et al, 2018;Klievink et al, 2017;Moshrefzadeh et al, 2017). This conceptualisation is not only limited to the technology powering these platforms (hard infrastructure) (Blazquez and Domenech, 2018); but also includes their value networks and governance aspects (soft infrastructure) (Jetzek, 2016;Suzuki and Finkelstein, 2019).…”

Approaches to Good Data Governance in Support of Public Sector Transformation Through Once-Only

“…The selection of literature and of strategic documents for this study is based on the one hand on previous research, which the authors conducted in relevant studies (e.g. [10]- [15]). On the other hand, google scholar was scanned and the snowball principle was applied on identified literature to enrich the research with current findings from the literature and with recent strategic documents on public sectors' digital transformation from the EU and Switzerland.…”