Open data intermediaries are critical for enhancing value generation from open data. However, empirical research on their business model archetypes remains limited. This gap constrains our understanding of the conditions and potential innovations required to perform the roles of open data intermediaries sustainably. To address this gap, we developed a taxonomy and empirically derived business model archetypes based on 190 open data intermediaries. We identified nine archetypes: collaborative open data platforms, premium self-service data delivery, personalized open data services, interactive apps with other complementary products, open data repositories funded by sponsorship, one-stop packages around an (augmented) open data platform/repository, single-purpose apps, interactive apps without complementary products, and open data advocacy. We also described each archetype’s value proposition, value creation, and value capture dimensions. Our findings support further research into the conditions that contribute to the success of open data intermediaries’ business models and the design of new, innovative ones. They also provide business model inspiration for existing and potential open data intermediaries, thereby encouraging greater exploitation of open data value.

Open data intermediaries are crucial for the sustainability (i.e., long-term durability) of the open data ecosystem (ODE). They enhance the access to and the (re-)use of open data and connect other open data actors. Additionally, open data intermediaries play a role in mitigating information asymmetry between actors. However, despite the importance of open data intermediaries in the ODE having been widely acknowledged in research and practice, studies on open data intermediation business models are limited. This knowledge is essential to better understand the role of open data intermediaries within the ODE and provide recommendations to develop their business models in such a way that they support the overall sustainability of the ODE.

Through various methods, including case studies of Esri and OpenStreetMap, this dissertation advances the understanding of open data intermediaries, their position within the ODE, and their business models. In particular, this dissertation theoretically contributed to the definition of open data intermediaries, potential contributions of open data intermediaries, and the archetypes of open data intermediation business models. It also identified practical aspects to consider in developing open data intermediation business models that contribute to a sustainable ODE, ultimately enhancing the generation of open data value. This value, in turn, can be leveraged to foster innovation, promote economic well-being, and address pressing social and environmental challenges.

Despite the many promises of open data, numerous challenges inhibit its full potential, such as its poor or inconsistent quality, a lack of complementary assets, and the limited skills of data providers and end-users. Open data intermediaries are instrumental in addressing some of these challenges. They provide specialized resources and capabilities to enhance the supply, flow, or use of open data, or strengthen the relationships among various open data ecosystem (ODE) actors. However, in-depth studies on open data intermediation business models are limited, with most having only offered birds-eye views of those business models. This deficiency has limited our knowledge to develop open data intermediation business models that contribute positively to the ODE. In the geospatial domain, Esri is an important open data intermediary, having been involved in such a role since the 1990s. This article unpacks Esri's open data intermediation business model and analyses its current strengths and weaknesses as well as its potential opportunities and threats to the ODE. Finally, this article recommends factors to consider in developing an open data intermediation business model that supports the sustainability of the ODE.

Open data promises various benefits, including stimulating innovation, improving transparency and public decision-making, and enhancing the reproducibility of scientific research. Nevertheless, numerous studies have highlighted myriad challenges related to preparing, disseminating, processing, and reusing open data, with newer studies revealing similar issues to those identified a decade prior. Several researchers have proposed the open data ecosystem (ODE) as a lens for studying and devising interventions to address these issues. Since actors in the ecosystem are individually and collectively impacted by the sustainability of the ecosystem, all have a role in tackling the challenges in the ODE. This paper asks what the contributions of open data intermediaries may be in addressing these challenges. Open data intermediaries are third-party actors providing specialized resources and capabilities to (i) enhance the supply, flow, and/or use of open data and/or (ii) strengthen the relationships among various open data stakeholders. They are critical in ensuring the flow of resources within the ODE. Through semi-structured interviews and a validation exercise in the European Union context, this study explores the potential contribution of open data intermediaries and the specific ODE challenges they may address. This study identified 20 potential contributions, addressing 27 challenges. The findings of this study pave the way for further inquiry into the internal incentives (viable business models) and external incentives (policies and regulations) to direct the contributions of open data intermediaries toward addressing challenges in the ODE.

The world is becoming more and more data driven. There are many ways to collect, analyse and disseminate data, and data ecosystems are among the most important environments that we have for facilitating this. Spatial data is one of the data types in data ecosystems, and data ecosystems play a key role in further value creation of the spatial data created, maintained and shared in the SDI. The workshop on “Data Ecosystems and Spatial Data Infrastructure (SDI) - facilitators for data value creation” brought together the views from actors ranging from the Local and National Authorities from Norway, Sweden and Denmark, European organisations such as the EC Joint Research Centre, The Alexandra Institute, and researchers working from different domains like spatial data, energy transition and building infrastructure. This report summarises the key takeaways from the presentations and the discussions during the breakout sessions that followed each of the topics as well as presenting a synthesis of the main findings of the workshop including the main take-aways for the SDI community.

Open data has many potential benefits including stimulating innovation, enhancing accountability and transparency, and improving the reproducibility and dissemination of research (Janssen et al., 2012; Uhlir and Schröder, 2007; Zhu et al., 2019). However, there are various shortcomings in the current open data initiatives such as the mismatch between the supply and demand of open data, the lack of appropriate software to process data, and confusion regarding data licenses (Johnson et al., 2017; van Loenen et al., 2021). The role of open data intermediaries is considered important to address these weaknesses. Open data intermediaries facilitate the use of and access to open data (Chattapadhyay, 2014; González-Zapata and Heeks, 2015) and build connections among open data stakeholders (Mayer-Schönberger and Zappia, 2011). It follows that open data intermediaries are regarded as one of the priority areas in open data research (Davies and Perini, 2016). Nevertheless, in-depth studies on open data intermediaries are scarce. Within the limited studies, they are found to face several challenges that may undermine their potential contribution to other open data stakeholders. For example, lack of financial planning (Flores, 2020), over-reliance on volunteers (Reggi and Dawes, 2016), and difficulty in securing data experts (Andrason and van Schalkwyk, 2017). Some of these challenges are associated with the lack of development of open data intermediaries’ business models (Kitsios et al., 2021; Reggi and Dawes, 2016). Before any research-based development of their business models can be carried out, a clear view of the existing business models is needed. Given this, the objective of this extended abstract is to review existing business models of open data intermediaries from the academic literature through a systematic literature review (SLR). Section 2 provides a brief background on the concept of a business model. Section 3 describes the research method. Section 4 presents the findings. Last but not least, Section 5 discusses the findings and proposes considerations for future studies.

The role of open data intermediaries is considered instrumental in the supply and use of open data. There are various definitions of open data intermediaries in the literature and some of them are quite different from each other. These definitions
can benefit from harmonization so knowledge about open data intermediaries can be developed on top of a shared understanding of what open data intermediaries mean. The objective of this article is to propose a common definition of open data intermediaries. We first carried out a systematic literature review and compiled the definitions of open data intermediaries from the literature. We found that each definition can be broken down into four basic components: (i) Who are the actors of open data intermediaries? (ii) What do they do? (iii) Where are they located in the open data lifecycle? and (iv) Why are they needed? We then conducted another round of data gathering and analysis to substantiate the four basic components. We proposed the following common definition of open data intermediaries: Third-party actors who provide specialized resources
and capabilities to (i) enhance the supply, flow, and/or use of open data and/or (ii) strengthen the relationships among various open data stakeholders.