Anneke Zuiderwijk

Benefits, Adoption Barriers and Myths of Open Data and Open Government

In this article, based on data collected through interviews and a workshop, the benefits and adoption barriers for open data have been derived. The results suggest that a conceptually simplistic view is often adopted with regard to open data, which automatically correlates the publicizing of data with use and benefits. Also, five “myths” concerning open data are presented, which place the expectations within a realistic perspective. Further, the recommendation is provided that such projects should take a users view.

Open data policies, their implementation and impact: A framework for comparison

In developing open data policies, governments aim to stimulate and guide the publication of government data and to gain advantages from its use. Currently there is a multiplicity of open data policies at various levels of government, whereas very little systematic and structured research has been done on the issues that are covered by open data policies, their intent and actual impact. Furthermore, no suitable framework for comparing open data policies is available, as open data is a recent phenomenon and is thus in an early stage of development. In order to help bring about a better understanding of the common and differentiating elements in the policies and to identify the factors affecting the variation in policies, this paper develops a framework for comparing open data policies. The framework includes the factors of environment and context, policy content, performance indicators and public values. Using this framework, seven Dutch governmental policies at different government levels are compared. The comparison shows both similarities and differences among open data policies, providing opportunities to learn from each other’s policies. The findings suggest that current policies are rather inward looking, open data policies can be improved by collaborating with other organizations, focusing on the impact of the policy, stimulating the use of open data and looking at the need to create a culture in which publicizing data is incorporated in daily working processes. The findings could contribute to the development of new open data policies and the improvement of existing open data policies.

Infomediary Business Models for Connecting Open Data Providers and Users

Many public organizations are opening their data to the general public and embracing social media in order to stimulate innovation. These developments have resulted in the rise of new, infomediary business models, positioned between open data providers and users. Yet the variation among types of infomediary business models is little understood. The aim of this article is to contribute to the understanding of the diversity of existing infomediary business models that are driven by open data and social media. Cases presenting different modes of open data utilization in the Netherlands are investigated and compared. Six types of business models are identified: single-purpose apps, interactive apps, information aggregators, comparison models, open data repositories, and service platforms. The investigated cases differ in their levels of access to raw data and in how much they stimulate dialogue between different stakeholders involved in open data publication and use. Apps often are easy to use and provide predefined views on data, whereas service platforms provide comprehensive functionality but are more difficult to use. In the various business models, social media is sometimes used for rating and discussion purposes, but it is rarely used for stimulating dialogue or as input to policy making. Hybrid business models were identified in which both public and private organizations contribute to value creation. Distinguishing between different types of open data users was found to be critical in explaining different business models.

Innovation with open data: Essential elements of open data ecosystems

Open data ecosystems are expected to bring many advantages, such as stimulating citizen participation and innovation. However, scant attention has been given to what constitutes an open data ecosystem. The objective of this paper is to provide an overview of essential elements of open data ecosystems for enabling easy publication and use of open data. To achieve this objective, the literature has been reviewed and a scenario about the publication and use of open data has been analyzed. It was found that various applications, tools and portals are available which together can form an ecosystem. The best functionalities of this ecosystem can be selected and utilized by open data providers and users. To create an open data ecosystem at least four key elements should be captured, namely, 1) releasing and publishing open data on the internet, 2) searching, finding, evaluating and viewing data and their related licenses, 3) cleansing, analyzing, enriching, combining, linking and visualizing data and 4) interpreting and discussing data and providing feedback to the data provider and other stakeholders. Furthermore, to integrate the ecosystem elements and to let them act as an integrated whole, there should be three additional elements 5) user pathways showing directions for how open data can be used, 6) a quality management system and 7) different types of metadata to be able to connect the elements.

Acceptance and use predictors of open data technologies: Drawing upon the unified theory of acceptance and use of technology

Abstract Policy-makers expect that open data will be accepted and used more and more, resulting in a range of benefits including transparency, participation and innovation. The ability to use open data partly depends on the availability of open data technologies. However, the actual use of open data technologies has shown mixed results, and there is a paucity of research on the predictors affecting the acceptance and use of open data technologies. A better understanding of these predictors can help policy-makers to determine which policy instruments they can use to increase the acceptance and use of open data technologies. A modified model based on the Unified Theory of Acceptance and Use of Technology (UTAUT) is used to empirically determine predictors influencing the acceptance and use of open data technologies. The results show that the predictors performance expectancy, effort expectancy, social influence, facilitating conditions and voluntariness of use together account for 45% of the variability in peoples behavioral intention to use open data technologies. Except for facilitating conditions, all these predictors significantly influence behavioral intention. Our analysis of the predictors that influence the acceptance and use of open data technologies can be used to stimulate the use of open data technologies. The findings suggest that policy-makers should increase the acceptance and use of open data technologies by showing the benefits of open data use, by creating awareness of users that they already use open data, by developing social strategies to encourage people to stimulate each other to use open data, by integrating open data use in daily activities, and by decreasing the effort necessary to use open data technologies.

Special issue on innovation through open data: a review of the state-of-the-art and an emerging research agenda: guest editors' introduction

For decades good governance scholarship has focused attention on the importance of government openness [26], [34]. Since the 1960s, Freedom of Information (FOI) legislation has formed the backbone of institutional support for opening information and documents [76] and participatory processes [4], [79]. However, FOI represents a passive approach to releasing information. Persons or organizations must still request the information they want, referred to casually, as freedom of information requests. Since the 1990s, publishing documents on websites or using communication technologies to engage citizens in participation processes has signaled a more proactive approach to releasing government information and political engagement. Since 2003, governments have re-envisioned their passive and proactive approaches to include an open data agenda, [18], [62], where publishing documents and data in open formats, [35], [63] is the preferred way. Collectively, these developments have forged the basis for what has been commonly referred to as the open government and data movements [30]. Open data practices and policies are praised for their potential to generate public value, particularly through innovation, economic growth, and transparency, [5], [9], [18], [21], [81]. The nature and character of open data has been hailed for its innovative capacity and transformative power [19], [35], [40], [45], [80]. Various studies have confirmed that proactively releasing public and private data in open formats creates considerable benefits for citizens, researchers, companies and other stakeholders, such as business creation or having the ability to understand public or private problems in new ways through advanced data analytics, [5], [9], [18], [21], [81]. Only a handful of articles examine both the unintended consequences and negative side effects of opening data, [33] and the underlying causal mechanisms that actually lead to the desired open data benefits [5]. Open data research is still in its infancy, and as a result, the extant literature uses limited application and development of theory toward understanding the open data phenomenon. While scholars acknowledge diverse perspectives, it is not clear which theories are most relevant, nor whether a single or integrated theory is needed. This special issue is part of a series of two special issues about open data. This issue focuses on the relationship between innovation and open data, while the second special issue emphasizes research on open data related to transparency and open data policies. To realize the practical benefits of this transformative practice and to develop theory, more research needs to focus on understanding how innovation occurs through open data activities. The papers in this special issue begin to address this gap. The introductory article discusses the state-of-the-art with respect to understanding the context of open data innovation, developments, challenges and barriers, presents an overview of open data research and outlines emerging research directions.

The negative effects of open government data - investigating the dark side of open data

Reports and research appears to assume that the benefits of open data dominate open datas negative consequences. Moreover, much of the existing research discusses benefits and disadvantages on a high level without providing much detailed insight in the underlying processes. Yet many governments are reluctant to open their data, as they are afraid of possible negative consequences of opening data. The objective of this policy paper is to better understand the aspects of the dark side of open data and contributes to the literature by providing a more realistic perspective on open data. We conducted nineteen in depth interviews with public sector officials and data archivists and identified sixteen categories of negative effects. For the dark side inherent to open data efforts the research suggests that a context and dataset dependent decision-making model needs to be made weighing the benefits of open data on the one hand (e.g. creating transparency, the possibility to strengthen economic growth), and the risks and disadvantages of open data (e.g. violating privacy and possible misuse and misinterpretation of data) on the other hand.

A comparison of national open data policies: lessons learned

Purpose – The purpose of this paper is to provide a comprehensive cross-national comparative framework to compare open data policies from different countries and to derive lessons for developing open data policies. Open data policies guide the opening and stimulate the usage of public data. However, some countries have no or less developed open data policies, in this way missing the opportunity to reap the benefits of open data. Design/methodology/approach – Literature review and case studies were conducted to extend an existing comparison framework, and the framework was used to compare open data policies of the UK, the USA, The Netherlands, Kenya and Indonesia. Findings – The comparison of open data policies highlighted several lessons that can be learned, including actions regarding a robust legal framework, generic operational policies, data providers and data users, data quality, designated agencies or taskforces and initiatives and incentives for stimulating demand for data. National policies should...

Barriers and Development Directions for the Publication and Usage of Open Data: A Socio-Technical View

Open data have considerable potential to provide citizens, researchers, companies and other stakeholders with many advantages, such as a growing economy by stimulating innovation and increased transparency. Nevertheless, the process in which data are created, published, found, analysed, processed and discussed, which is here referred to as the open data process, consists of many complexities and complex relationships among social and technical aspects. Often the complexity, dynamics and heterogeneity of the open data process are neglected, and extensive overviews of barriers for the open data process are lacking. Hence, in this chapter, the questions asked are (1) which socio-technical barriers exist in the open data process and (2) which development directions could be derived from this overview of barriers. Our overview shows that many barriers can be identified with regard to data creation, publication, finding, analysing, processing, discussion and providing feedback. Activities early in the open data process could result in or increase barriers later in the process. Furthermore, the analysis of barriers for the open data process showed the importance of combining a social and technical view to overcome the barriers. A number of development directions for open data are identified. The findings suggest that, to be able to realize the benefits of open data, both social and technical barriers should be considered and an integrated approach to successfully counteract these barriers should be taken. In this integral approach, the social and technical barriers should be dealt with simultaneously rather than separately to successfully realize the benefits of open data.

Designing a Second Generation of Open Data Platforms: Integrating Open Data and Social Media

Two important trends in government that are emerging in the recent years have been on one hand the exploitation of the Web 2.0 social media, supporting a more extensive interaction and collaboration with citizens, and on the other hand the opening of government data to the citizens through the Internet, in order to be used for scientific, commercial and political purposes. However, there has been limited attempt of integrating them. Using a design science approach a second generation of open government data (OGD) platforms has been developed, which offer to the users both the ‘classical’ first generation functionalities, and also a comprehensive set of additional novel Web 2.0 features. The latter aim to provide support to the users in order to generate value from ODG. They enable users to become ‘prosumers’, both producing and consuming data. These novel capabilities for performing various types of processing, information and knowledge exchange, and collaboration were found to be useful and valuable by users in a first evaluation.