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.

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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.@en

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.@en

To harness the promises of digital transformation, different players take different paths. Departing from corporate-driven (e.g., the United States) and state-led (e.g., China) approaches, in various documents, the European Union states its goal to establish a citizen-centric data ecosystem. However, it remains contentious the extent to which the envisioned digital single market can enable the creation of public value and empower citizens. As an alternative, in this article, we argue in favor of a fair data ecosystem, defined as an approach capable of representing and keep in balance the data interests of all actors, while maintain a collective outlook. We build such ecosystem around data commons—as a third path to market and state approaches to the managing of resources—coupled with open data (OD) frameworks and spatial data infrastructures (SDIs). Indeed, based on literature, we claim that these three regimes complement each other, with OD and SDIs supplying infrastructures and institutionalization to data commons’ limited replicability and scalability. This creates the preconditions for designing the main roles, rules, and mechanisms of a data republic, as a possible enactment of a fair data ecosystem. While outlining here its main traits, the testing of the data republic model is open for further research.@en

To achieve sustainable development goals, georeferenced data and geographic information systems play a crucial role. Yet, the way in which these data and systems are summoned upon rests on positivist assumptions which overlook both epistemological and ethical concerns. This is epitomized by the integrated geospatial information framework (IGIF) of the United Nations, which, from the perspective of sustainable development, aims to provide guidance for the management of geoinformation and related tools, considering these as mirrors of the physical world. In this respect, the article has three main goals. First, it delivers an epistemological and ethical critique of the IGIF, by highlighting its internal tensions. Second, it suggests how the IGIF and similar geoinformation initiatives can benefit from an ethical reflection that allows to conduct georeferenced practices in a fair(er) way. Third, it designs an ethics assessment list for self-evaluating the ethical robustness of geoinformation initiatives as ecosystems.

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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. @en

Children in the primary educational level learn about fundamental reading, writing and mathematics skills as a basis for future learning. In some European Union countries, they are also taught basic informatics and computer usage. However, only a few efforts are made to start teaching them about (open) data literacy. When teaching about data, multiple stages of the data value chain can be tackled, adapted to children’s capabilities; from data production or collection to data usage or impact. Such teaching can be more theoretical, with already prepared examples, or a complete hands-on experience, where the data is collected from the environment, further analyzed, visualized and the conclusions about data are made. In this paper, we will present the currently available research on the approaches to teaching children about data. We will also discuss the potential benefits and the main issues impeding such an effort. Finally, we will propose the way forward for informal active learning about data for lower-level primary school children, based on the hands-on workshops using environmental data.@en

In various official documents, the European Union has declared its goal to pursue a citizen-centric governance of digital transformation. Through a critical review of several of these documents, here we show how “citizen-centric” is more a glamouring than a driving concept. De facto, the EU is enabling a federated data system that is corporate-driven, economic-oriented, and GDPR-compliant; in other words, a Digital Single Market (DSM). This leaves out societal and collective-level dimensions of digital transformation—such as social inclusion, digital sovereignty, and environmental sustainability—which are acknowledged, but not operationalized, by the EU as pillars of a citizen-centric governance. Hence, the door is open to a complementary approach to the governance of digital transformation. We argue that, while a federated data model can constitute the tech-legal backbone of the emerging DSM, a commoning of data, as an ecosystemic approach that maintains a societal and collective outlook by default, can represent a complement to enact a truly citizen-centric governance.

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A new active teaching and learning approach has been implemented in the BSc course Open Urban Data Governance.. This course is part of the minor Spatial Computing for Digital Twinning in the Bachelor of Architecture, Urbanism and Building Sciences at the Faculty of Architecture and The Built Environment, TU Delft, and offered TU wide as an elective. At the start of the course the students were tasked to collect and analyse noise level data, and to reflect on this process. In the second (main) assignment they had to develop an urban challenge to be answered with geo-data. Also here a reflection was required including an assessment of the FAIRness of the data. Both students and teachers highly appreciated the new approach. Through applying active teaching and learning we created an example of the theory on students’ activities. This approach also links students’ real world experiences to the content of the course, which allows them to put theory into context. Teachers especially appreciated the interaction with the students, the depth of the discussions, and were impressed by the steep learning curve of the students. Students enjoyed the freedom to operate, the frequent feedback sessions and the application of theory into practice. For the next year the lectures will take into account that ‘minor’ students do prepare well for their classes.@en

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.@en

There is an increasing need for spatial data to be used for informed decision-making and as a resource for developing innovative products and services. A Spatial Data Infrastructure (SDI) facilitates access to and sharing of spatial data by providing a framework in which technical and non-technical aspects are established. Traditionally, SDIs are developed by and for government organisations to share spatial information within government. Non-government parties may also use SDIs to access government spatial data, either as open data or as fee-based data. There are also non-government SDIs, such as company SDIs used to share spatial information within a private sector organisation. OpenStreetMap is another example of a non-government SDI, whereby citizens have created a worldwide map based on crowd-sourced information and contributions from private and public sector organisations. The concept of Open SDIs has emerged from an increased interest in open data initiatives steered by national and international directives, such as the EU Open Data Directive (Directive (EU) 2019/1024), as well as the large investment of European public authorities in developing SDIs. Open SDIs are SDIs in which citizens, research institutions, private organizations and other businesses and non-governmental actors are recognized as key stakeholders of the infrastructure (Vancauwenberghe and van Loenen, 2018; Vancauwenberghe et al., 2018). The concept of Open SDIs is about openness to new stakeholders in the open data ecosystem, in which stakeholders can be both producers and users of spatial data. Open SDIs are also linked to developments and trends in other domains, such as open government, open data, open science, and open software. This new paradigm regarding Open SDIs means that new particular skills are required, which currently are not offered by traditional SDI education@en

The new concept of Open Spatial Data Infrastructures (Open SDIs) has emerged from an increased interest in open data initiatives together with national and international directives, such as the EU Open Data Directive (Directive (EU) 2019/1024), and the large investment of European public authorities in developing SDIs for sharing spatial data within public authorities. Open SDIs have the potential to boost reaching SDIs’ general aims and goals of facilitating the exchange and sharing of spatial data to support planning and decision-making by including public participation and increased openness in all aspects of SDIs, including Open SDI Education. The open SPatial data Infrastructure eDucation nEtwoRk (SPIDER) project aims to address Open SDI Education by particular emphasis on studying Active Learning and Teaching (ALT) methods for SDI education. This article provides a theoretical basis of ALT for SDI methodologies. We show in which way ALT practices were already implemented in SDI education at the Partner universities before the COVID-19 pandemic. We also describe how the pandemic functioned as a catalyst for implementing ALT practices to an online environment, and how students evaluated these practices. The outcomes of our research can serve as an inspiration for SDI education in other countries.@en

The successful adoption of digital innovations in agricultural production systems is based on the proactive participation of all stakeholders and represents an important step in establishing resilient agri-food chains and creating sustainable value. The key tool for the creation of sustainable value is integrating the nine aspects of the business process (cooperation; inclusion; financing; diversification; communication; policies; knowledge with entrepreneurship; and production) by re-using of open governmental and public endeavours data as well as by the contractual sharing. The objectives of this research are to identify stakeholders in the Croatian agricultural system, and to explore their roles and their potential for data supply and needs for data uptake. Open access repositories were queried to identify stakeholders. Direct observation methods and semi-structured conservational qualitative interviews were used for stakeholder characterisation and data flow detection. Stakeholder importance with respect to current data supply was analysed. Underdeveloped data flow relationships in the agricultural data ecosystem in Croatia could be built in a spontaneous process following the data opening of the Research and Consumer group of stakeholders and promoting data sharing initiatives of the early adopters in the Supplier group. In that way, data opening would be the driver of the effective cooperation creation required for sustainable value creation but also the adoption of the best management practices, sustainable solutions and digital development.@en

Various “open” concepts in Computing, such as open standards, open data, open licenses or system interoperability are becoming more important in the professional lives of software engineers. However, students usually do not receive a systematic education about these concepts; rather they sporadically learn about a subset of these topics. This paper presents the revised version of the Open Computing course in the University of Zagreb, Faculty of Electrical Engineering and Computing (FER),which teaches a clear set of current topics focused on open data and correlating concepts. The new e-learning course is carried out using the “flipped classroom ”educational method; students construct their knowledge in a set of real-world mini-activities throughout the course, instead of passively learning from the official course resources. In this paper, we discuss our flipped classroom activities, their relation to revised Bloom’s taxonomy of educational objectives, and present the evaluation of the first course instance using this model. Students’ feedback shows they welcome this change in approach, finding the course useful and interesting, and preferring this method to the traditional full lecture setting.@en

Developments toward Open Government Data (OGD) also affect the data from National Continuously Operating Reference Station (NCORS), an infrastructure supporting standard and precise positioning in spatial activities. The application of OD policies on NCORS data (OD-NCORS) varies per country. This paper explores the approaches and impact of OD-NCORS in three European countries: Germany, the Netherlands and Sweden. Understanding the differences in the implementations may benefit other countries in their strategies to implement OD for their NCORS. It may also provide insights for organisations considering OD for other data. The research found that the key factors affecting OD-NCORS implementation are the national governing nature and the existence of commercial CORS networks. There is no single approach for OD-NCORS implementation that fits every national context.@en

The creation of open data has seen a series of waves in which every growing resources of data are becoming accessible to a growing number of users from a diversifying number of public entities. The European Commission anticipates this movement by setting a new scope to the re-use of Public Sector Information Directive. Instead of exclusively focusing on Public Sector Information (PSI), the new scope of its successor, the Open Data Directive (ODD), includes data from public undertakings as well. In order for public undertakings to comply with this future legislation, research into the current openness of public undertakings and the barriers to open data is key. This research presents three different levels of openness of data: (1) data is only open for the own organisation, (2) data is open for the internal organisation and trusted parties can use the data, and (3) open data for all. In this case the public undertakings are Port of Rotterdam (PoR) and Schiphol Airport. The results showed that the data policy of PoR matches openness level 1. The data policy of Schiphol Airport matches level two. The open data policy of Dutch grid operator, Liander, corresponds with the third level as this organisation provides open data since 2014 for everyone. It can be stated that neither PoR nor Schiphol Airport is ready to comply with the future rules when the ODD requirements become mandatory. Barriers that are associated with achieving a higher level of open data are related to institutional, financial, legal, and quality and technical aspects. Overcoming these barriers requires, among other things, highly motivated staff to provide open data. @en

This research aims to assess available spatial open data related to access to hospitals in the three largest Croatian cities (Zagreb, Split, Rijeka), with a future aim to create digital services as an ecosystem that will be used in everyday situations, as part of the concept of “digital society”. Data analysis is performed for the following datasets: hospitals, hospital specialization, public transport (tram, bus), bike routes, car routes, parking and parking for people with disabilities. The future aim is to create a new mobile, multilingual and voice-based application that would enable quick access to information on hospital access, relying on the principles of the open data ecosystem, which would improve over time. There are four specific aims: (1) to identify and analyze portals and open datasets of the selected categories for the three largest Croatian cities; (2) to analyze existing open data assessment frameworks and detect gaps; (3) to create a conceptual open data assessment framework as an open data ecosystem that integrates new end-user perspectives; and (4) to analyze existing open datasets for the three largest cities in Croatia, based on supply and demand by researcher/developer categories, using the newly developed framework. The results show that existing open datasets related to hospital access in the three largest Croatian cities are scattered across different portals. Analyzed frameworks existing on the supply side of open data are more focused on the status of the components, lacking evaluation scales and not including end-user-driven aspects, which would be crucial for the open data ecosystem. As a result, the new “Hospital Access Framework” is created as a conceptual ecosystem, including five categories: supply, demand by researcher/developer, demand by end-user, legal aspect and impact. Analysis of existing open data for the three Croatian cities is performed for two categories (supply and demand by researcher/developer), for which KPIs, indicators and evaluation scales are developed. The other three categories are not analyzed, since the application cannot be developed from existing data, which are insufficient for the creation of a smart application. Results show that existing open data related to hospital access are incomplete or do not exist at all (hospital specialization, parking for people with disabilities, data on multilingualism and voice enabling). Average scores of the supply category are higher than those for demand by researcher/developer, although they are below the average grade, showing a lack of available data that could be used for further development. The new conceptual “Hospital Access Framework” open data ecosystem would benefit from end-user interaction, therefore, improving over time with end-users through interaction.@en