Towards Generic Business Models of Intermediaries in Data Collaboratives: From Gatekeeping to Data Control

Abstract

Data has become a core asset, as well as a "management fashion", of our time. It brings about unprecedented opportunities for data-driven decision making and innovation in various spheres of public life. This concerns data held by governments, as well as companies, academic institutions, non-profits, and citizens. In our study we investigate a novel form of cross-sector partnership called Data Collaborative, and namely the business models employed by intermediaries in data collaboratives. Based on an analysis of six cases, we derived four generic business models based on the level of openness and added value of the data: Data Gatekeeper model, One-stop-shop model, Information-as-a-service model, and Data Controls model. Our study contributes to the literature on data partnerships and on intermediation and information sharing more broadly.

How to Enable Collaboration in Open Government Data Ecosystems: A Public Platform Provider’s Perspective

“…The co-ownership of the platform provider provides a somewhat neutral body among the public and private actors, who some may consider to be competitors. This consortium-based governance structure (Dal Bianco et al 2014) may be a way to ensure the critical aspect of trust in the platform provider's commitment and a guarantee for the long-term stability and collaboration within the ecosystem (Susha et al 2020). Similarities may be drawn from the role of data trusts (Coyle, Diepeveen, and Wdowin 2020) as well as OSS foundations (De Noni, Ganzaroli, and Orsi 2013) as proxy-organizations and neutral homes for data and OSS projects respectively.…”

“…Besides being data providers, all four platform providers may be described as data brokers as they gather, promote, and distribute data from third-party (Immonen, Palviainen, and Ovaska 2014) (cf. data intermediaries (Susha et al 2020)), but also data transformers as they transform data between different standards based on ecosystem needs (Lindman, Kinnari, and Rossi 2015). An example of the latter can be found in the case of Trafiklab where Samtrafiken transforms incoming data to the GTFS format.…”

“…To collaborate on data, the platform providers need to consider what type of data that is (or could be) shared and provided on the platform. If the data is produced externally, the platform provider takes on the role of a broker (Immonen, Palviainen, and Ovaska 2014) or intermediary (Susha et al 2020), passing data on from the producers to the consumers which is mainly the case for Samtrafiken in the Trafiklab ecosystem. The other three ecosystems provide both internally and externally produced data.…”

“…Also, considering open data ecosystems, such as OpenStreetMap 1 and Wikidata 2 , there may also be a potential for catalyzing both the sharing and adoption of OGD by extending collaboration to include open development of boundary resources (Dal Bianco et al 2014) such as related standards and software as OSS (Zuiderwijk, Janssen, and Davis 2014;Immonen, Palviainen, and Ovaska 2014;Rudmark 2020). As we consider current definitions of data ecosystems (Oliveira, Lima, and Lóscio 2019) (including related concepts (Susha et al 2020)) lacking in terms of these characteristics, we define a data ecosystem, adapted from three sources (Zuiderwijk, Janssen, and Davis 2014;Jansen 2020;Oliveira, Lima, and Lóscio 2019), as: a networked community of actors (organizations and individuals), which base their relations to each other on a common interest (Zuiderwijk, Janssen, and Davis 2014), supported by an underpinning technological platform (Jansen 2020) that enables actors to process data (for example, find, archive, publish, consume, or reuse) as well as to foster innovation, create value, or support new businesses (Oliveira, Lima, and Lóscio 2019). Actors collaborate on the data and boundary resources (for example, software and standards), through the exchange of information, resources, and artifacts (Jansen 2020).…”

“…The platform provider lays out the development direction of the platform, decides what is shared, and establishes the governance structure (Baars and Jansen 2012), i.e., rules and processes for how the ecosystem can influence and collaborate on the development and any shared resources (for example, data, software, or standards). We find this as an interesting perspective as trust towards the platform provider is pivotal to enable the collaboration and growth of an ecosystem (Susha et al 2020;Coyle, Diepeveen, and Wdowin 2020).…”