Despite an increasing interest in the strategies to promote open data use in recent years, there has been a substantial lack of empirical and theoretical analysis of the governance modes that favored different types of open data initiatives. To address this gap, this study asks: How do governance modes support open data sharing in open government data platforms? To answer this question, we assess the coherence of the open data governance contexts of France and Ireland when sharing data on open government data platforms during the Covid-19 crisis. The study uses a multi-method approach involving both interviews with experts, identified through purposive sampling, and secondary sources for triangulation purposes. Overall, the governance context supported open data sharing in France and Ireland. Both cases are characterized by a strong central coordination with a solid trust relationship and clear legal frameworks. France, more than Ireland, relied on a market governance mode, and Ireland scored higher in networked governance due to the creation of social capital. The results provide new insights on how to combine governance modes that support open government data initiatives through coordination, collaboration with the private sector, and involvement of different actors. Practitioners can use our insights as examples of governance strategies that are fit for events that need a timely open data response.

Public administrations are increasingly relying on collaboration within inter-organizational networks to coordinate the development and provisioning of integrated digital public services. Collaboration strategies are necessary to focus collaborative efforts, align and prioritize goals, and leverage concrete results that advance integrated service delivery (ISD). However, literature on inter-organizational collaboration strategies for integrated service delivery is scarce. This research identifies collaboration strategies in three qualitative case studies in Belgium. The cases present 33 collaboration strategies categorized into engagement, motivation, and joint action strategies. Collaboration strategies should complement each other. Together these strategies can help to overcome the adoption paradox, one of the key issues to advance ISD, which refers to service providers not being inclined to adopt an ISD unless it has many users, but users might not be willing to use and ISD before many service providers have adopted it. Policy-makers can use the identified collaboration strategies to advance integrated service delivery.

The implementation of open data policies requires the efforts of many public employees across different levels of government, who may be unaware of the benefits and risks of open data. Serious games have demonstrated potential for training in a professional environment. For this research, a collaborative digital serious game about open data was developed. A sample of 24 civil servants played the game. Pre-test and post-test surveys were used to evaluate the effects of the game on participants’ perception of open data. Likert score changes between pre-test and post-test indicated that the game had a positive effect on the willingness to share public sector data. By simulating the setting of a public office and by having players make decisions about whether to open certain datasets, the game facilitated learning about the benefits and disadvantages of opening data.

Different actor roles in inter-organizational digital public services are often neither understood nor acknowledged. This can result in challenges regarding the proper design and result in a lack of adoption of these services. In the literature, there exist various taxonomies outlining roles such as users, consumers or co-creators, although their value is limited. We define roles as the expectations regarding the actors and their responsibilities in the governance of a digital public service. The aim of this research is to better understand the various roles in inter-organizational digital service provisioning. This objective is achieved by examining existing classifications and using them to analyze the roles in three inter-organizational cases in Belgium. The multiple-case study reveals natural persons and legal entities often combine several roles. Public administrations have to collaborate to establish inter-organizational digital public services, but might be confronted with different perspectives regarding the end-user or other roles. This might lead to tensions and could have consequences regarding adoption. The results show that intermediary roles performed by non-public sector parties, such as mandate holders or private service providers, are lacking in existing classifications. A novel classification is proposed together with suggestions for the concept of roles, taking a comprehensive view on actor roles in the entire service delivery chain.

Current open data systems lag behind in their promised value creation and sustainability. The objective of the current study is twofold: 1) to investigate whether existing open data systems meet the requirements of open data ecosystems, and 2) to develop a research agenda that discusses the gaps between current open data systems on the one hand and participatory, value-creating, sustainable open data ecosystems on the other hand. The literature reveals that the main characteristics of value-creating, sustainable open data ecosystems are user-drivenness, inclusiveness, circularity, and skill-based. Our comparative case study of five open data systems in various application domains and countries highlighted that none of these systems are real open data ecosystems: they often do not balance open data supply and demand, exclude specific user groups and domains, are linear, and lack skill-training. We elaborate on a research agenda that discusses how research should address the challenge of making open data ecosystems more value-generating and sustainable.

According to open government principles, public administration should make its data available to the public to create transparency, accountability, and to facilitate participation in public decision-making. Open-Data Policies (ODPs) were developed to encourage the opening of governmental data to the public, but require collaboration and awareness from all levels of government. Gaming has proved to be successful for creating awareness. Yet the pandemic hinders in-person gameplay, and there is a need for an online game that can be played remotely. This research uses an in-person game as the starting point to develop an online collaborative digital game. The feature and design choices of the digital game are described, along with its main differences when compared to the in-person one. The essential features include interaction and discussion about open data among players, the assignment of different roles, and points awarded when making the right decision to open, partially share, or close a dataset.

Governments aim to digitalize public services. Whereas initially they worked in isolation, nowadays they increasingly link different building blocks together to realize integrated public services. This evolution poses challenges concerning the governance of public services. The purpose of this paper is to identify governance challenges in inter-organizational digital public service delivery. To do this, we investigated a case study that deals with the creation of digital invoicing services in Belgium. The findings show seven groups of governance challenges that incorporate technical, organizational and inter-organizational factors. Governance challenges can be external, related to the environment and the users, as well as internal, related to the digitalization objectives and governance dynamics. Moreover, as public services evolve over time, so do governance challenges, suggesting that governance regimes may have to evolve accordingly to maintain coordinated service delivery.

Various types of stakeholders are often involved in the process of deciding to open data. However, the influence of multiple–actors on the decision-making process is ill-understood. Stakeholders play different roles and have different interests in opening and analyzing datasets. The objective of this paper is to understand the influence of the stakeholder’s roles and their interests in the decision-making process to open data. The roles-interest grid method is used to determine the stakeholder’s concerns and how they influence the decision-making process to open data. In addition to stakeholder theory, we employ muddling through and bounded rationality theories to create a comprehensive analysis of the decision-making process. Stakeholders are found to be diverse, where some are proponents of opening data, and others are risk-averse and do not favor disclosing data. Stakeholder’s responsible for the actual opening of data are often focused on the risks resulting in a tension between the ambitions of politicians to open data, and the practices of administrators and decision-makers. Understanding the stakeholder’s roles and their tensions can help to ensure better decisions are made. We recommend creating incentives for generating shared objectives.

The public expects government institutions to open their data to enable society to reap the benefits of these data. However, governments are often reluctant to disclose their data due to possible disadvantages. These disadvantages, at the same time, can be circumstances by processing the data before disclosing. Investments are needed to be able to pre-process a dataset. Hence, a trade-off between the benefits and cost of opening data needs to be made. Decisions to disclose are often made based on binary options like “open” or “closed” the data, whereas also parts of a dataset can be opened or only pre-processed data. The objective of this study is to develop a decision tree analysis in open data (DTOD) to estimate the costs and benefits of disclosing data using a DTA approach. Experts’ judgment is used to quantify the pay-offs of possible consequences of the costs and benefits and to estimate the chance of occurrence. The result shows that for non-trivial decisions the DTOD helps, as it allows the creation of decision structures to show alternatives ways of opening data and the benefits and disadvantages of each alternative.

Intensifying and increasingly complex physical developments under, on, and above ground, as well as the speed and accessibility of digital innovation, is resulting in growing interest in public sector investment in 3D geo-information. In Europe, a consortium of 11 public mapping agencies (PMAs) recently undertook a cost-benefit analysis for pursuing adoption of 3D geo-information. However, broader public management literature has shown that while economic value is vital for justifying public investment, it is not the only driving factor and that the creation of public value is crucially and equally significant as it conveys social and political legitimacy. Using a public value perspective, this paper aims to re-examine the data collected by the consortium of PMAs. Content analysis of the qualitative data provides strong examples of how 3D geo-information may potentially manifest as different types of public value across a broad public of stakeholders as well as providing evidence that such innovation would likely be politically as well as operationally viable. Nonetheless, the lack of a clear obvious need for 3D geo-information that responds to a specific societal challenge may pose an impediment to successful innovation.

The effective development and implementation of spatial data infrastructures (SDIs) requires governance in order to avoid gaps, duplications, contradictions and missed opportunities in the implementation of different SDI components. Appropriate governance instruments should be established to coordinate the activities and contributions of different stakeholders. This article reviews the governance of national SDIs in Europe before, during and after the adoption of the European INSPIRE Directive, which aimed to establish an infrastructure for spatial information in the European community. The analysis is based on a governance instruments approach as introduced by public administration researchers to analyse coordination and governance in the public sector. The study shows that the instruments-based approach is a useful tool for analysing governance in the context of SDIs and contributes to a better understanding of SDI governance. Evidence was found for the adoption and use of each of six sets of governance instruments in the governance of national SDIs in Europe: collective decision-making structures, strategic management, allocation of tasks and responsibilities, creation of markets, inter-organizational culture and knowledge management, and regulation and formalization of the infrastructure.

Governments are releasing their data to the public to accomplish benefits like the creation of transparency, accountability, citizen engagement and to enable business innovation. At the same time, decision-makers are reluctant to open their data due to some potential risks like misuse, sensitivity, ownership, and inaccuracy of the data. The goal of the study presented in this paper is to develop a Fuzzy Multi-Criteria Decision Making (FMCDM) approach to analyze the risks and benefits to determine the decision to open a dataset. FMCDM is chosen due to its capability to measure and weight the relative importance of the criteria. FMCDM need the weighting of criteria as input. For this Fuzzy Analytical Hierarchy Process (FAHP) is utilized by collecting input from experts’ knowledge and expertise. The scores for each criterion are summed up to rank the importance of the alternatives. Four main criteria are used, e.g. data sensitivity and data ownership representing risks criteria, and data availability and data trustworthy as benefits criteria. For each criterion, there were two sub-criteria identified. Four types of decisions to open data can be made: completely open, maintain suppression, provide limited access, and remain closed. A health patient record dataset is used to illustrate the approach. In further research, we recommend to develop automated approaches that take a dataset as an input and can provide an advice.

The effective development and implementation of open data initiatives requires governance in order to avoid gaps, duplications, contradictions and missed opportunities. Appropriate governance instruments should be established to coordinate the activities and contributions of different stakeholders. This chapter reviews the governance of open data initiatives worldwide, using a governance instruments approach as introduced by public administration researchers to analyse coordination and governance in the public sector. Six sets of governance instruments in the governance of open data initiatives are identified: collective decision-making structures, strategic management, allocation of tasks and responsibilities, creation of markets, interorganizational culture and knowledgemanagement, and regulation and formalization of open data initiatives. The chapter shows how each of these six sets of instruments have been applied in various countries in the governance of nation-wide open data initiatives.

Open government data initiatives result in the expectation of having open data available. Nevertheless, some potential risks like sensitivity, privacy, ownership, misinterpretation, and misuse of the data result in the reluctance of governments to open their data. At this moment, there is no comprehensive overview nor a model to understand the mechanisms resulting in risk when opening data. This study is aimed at developing a Bayesian-belief Networks (BbN) model to analyse the causal mechanism resulting in risks when opening data. An explanatory approach based on the four main steps is followed to develop a BbN. The model presents a better understanding of the causal relationship between data and risks and can help governments and other stakeholders in their decision to open data. We use the literature review base to quantify the probability of risk variables to give an illustration in the interrogating process. For the further study, we recommend using expert’s judgment for quantifying the probability of the risk variables in opening data.

This book is about open data, i.e. data that does not have any barriers in the (re)use. Open data aims to optimize access, sharing and using data from a technical, legal, financial, and intellectual perspective. Data increasingly determines the way people live their lives today. Nowadays, we cannot imagine a life without real-time traffic information about our route to work, information of the daily news or information about the local weather. At the same time, citizens themselves now are constantly generating and sharing data and information via many different devices and social media systems. Especially for governments, collection, management, exchange, and use of data and information have always been key tasks, since data is both the primary input to and output of government activities. Also for businesses, non-profit organizations, researchers and various other actors, data and information are essential.

Many countries and also cities have their own open data portal, which provide geographic data that can be used even by citizens. One of the current challenges is to satisfy user needs to ensure that the data that is provided through the portal is actually used. This paper provides insights in the findability of datasets through of a special kind of portal: the geoportal. It presents the main findings of research accomplished on the findability, attainability and usability of geoportals through an assessment of the transaction costs involved.

Spatial Data Infrastructures (SDIs) have been developed over the last decades all over the world. SDI is the integration of several components to create a platform which enables a wide variety of stakeholders to access, share and use spatial data in an efficient and effective way. To stimulate the SDI development effectively and efficiently, it is key to assess the progress and benefits of the SDI. Currently, several SDI assessment methods exist. However, most assessment methods are analyzing the SDI as a whole, which does not allow understanding their internal dynamics and none of these appear to meet the requirements of practitioners. Thus, SDI decision makers are still without any guidance on the success of their SDI. The research on this paper stands on an ongoing PhD research project on the development of a sound foundation for an academic theoretical framework for the STIG, Stress Test for Infrastructure of Geographic information. The last paper was focused on the similarities of the Financial infrastructures with the Spatial Data Infrastructures and if the financial stress testing which is commonly used to assess the sustainability and success of the financial system can be used for SDI assessment. Based on a review of the nature and concept of the SDI and Financial Infrastructure (FI) we conclude that there is significant similarity between these two infrastructures and the stress test methodology is likely to be an appealing alternative way of assessing SDIs. The purpose of this paper is to define the Core SDI Principles based on the 29 Basel Core Principles and setting up the Core SDI performance indicators. Additionally, a set of essential and additional assessment criteria for each Core SDI Principle will be defined. From all the examined types of risk factors and methods to construct financial stress tests, the Multi-factor Stress tests (Hypothetical and a Non-systematic Subjective scenario model) are most promising as a basis for SDI assessment. This hypothetical scenario first chooses and then stresses risk factors based on expert inputs including users, producers, data owners, management, consultants etc. SDI practitioners can construct hypothetical scenarios when no historical scenarios match the special features of their situation or when they want to stress new combinations of risk factors. Stress testing as a SDI assessment method once implemented in the decision-making process, can effectively increase system robustness of a SDI. When implementing stress testing, challenges remain in modeling the interaction of different risk factors and their impacts. Such things as: integrating stress testing at different levels and making stress tests workable, realistic and timely remain complicated. These issues will be addressed in the research further developing the Stress Test for Infrastructure of Geographic information: the STIG. The paper ends with a shortlist of issues for discussion on the way to move forward.

The China Government enacted the Provisional Regulations on Real Estate Registration (RER) in July 2015. These regulations were in full operation from the beginning of 2016. In this context, real estate refers to land, sea, houses, trees and other fixed objects which have spatial distribution and are subject to social and economic activities in the same time. The RER provides opportunities to strengthen the Chinese National Spatial Data Infrastructure (NSDI), because the RER involves spatial information which can be shared with stakeholders of the NSDI. The paper explores the relationship between the Chinese NSDI and RER in order to find a mutual way to inspire their developments in the same time. This exploration includes several issues. First, a clear definition of sharable information is necessary which helps to reduce data duplication and extend the application of Chinese NSDI. Second, there must be a common recognition and strong coordination among powerful ministries which can improve the adjustment of business processes. Third, reasonable mechanisms and feasible approaches should be explored from different perspectives to underpin the spatial governance level. Fourth, government administrators must achieve the strategic benefits of integrating RER and NSDI from multiple perspectives, and fifth the influence and profile should be evaluated based a long term consideration. The development of NSDIs is a dynamic process and the performance of RER is a key point for the Chinese NSDI. By integrating RER, the Chinese NSDI can penetrate to the actual process of government management and improve the capability of spatially assistant decision-making.