Ronald Meijer

Issues and Guiding Principles for Opening Governmental Judicial Research Data

The opening of data is considered to provide many benefits. However, opening up data by public bodies is a complex and ill-understood activity. Although many public bodies might be willing to open up their data, they lack any systematic guidance. In this paper, guidance is provided by investigating the publishing processes at the Dutch Research and Documentation Centre (WODC), which owns governmental judicial research data. We developed guidance by providing 1) a list of issues that play a role in deciding whether to open data, 2) an alternative to completely publishing data (i.e. restricted access) and 3) solutions for overcoming some of the issues. The latter include dealing with privacy-sensitive data, deletion policies, publishing after embargo periods instead of not publishing at all, adding related documents and adding information about the quality and completeness of datasets. The institutional context should be taken into account when using the guidance, as opening data requires considerable changes of organizations.

Design Principles for Improving the Process of Publishing Open data

· Purpose: Governments create large amounts of data. However, the publication of open data is often cumbersome and there are no standard procedures and processes for opening data. This blocks the easy publication of government data. The purpose of this paper is to derive design principles for improving the open data publishing process of public organizations. · Design/methodology/approach: Action Design Research (ADR) was employed to derive design principles. The literature was used as a foundation, and discussion sessions with civil servants were used to evaluate the usefulness of the principles. · Findings: Barriers preventing easy and low-cost publication of open data were identified and connected to design principles, which can be used to guide the design of an open data publishing process. Five new principles are 1) start thinking about the opening of data at the beginning of the process, 2) develop guidelines, especially about privacy and policy sensitivity of data, 3) provide decision support by integrating insight in the activities of other actors involved in the publishing process, 4) make data publication an integral, well-defined and standardized part of daily procedures and routines, 5) monitor how the published data are reused. · Research limitations/implications: The principles are derived using ADR in a single case. A next step can be to investigate multiple comparative case studies and detail the principles further. We recommend using these principles to develop a reference architecture. · Practical implications: The design principles can be used by public organizations to improve their open data publishing processes. The design principles are derived from practice and discussed with practitioners. The discussions showed that the principles could improve the publication process. · Social implications: Decreasing the barriers for publishing open government data could result in the publication of more open data. These open data can then be used and stimulate various public values, such as transparency, accountability, innovation, economic growth and informed decision and policy-making. · Originality/value: Publishing data by public organizations is a complex and ill-understood activity. The lack of suitable business processes and the unclear division of responsibilities blocks publication of open data. This paper contributes to the literature by presenting design principles which can be used to improve the open data publishing process of public sector organizations.

Reconciling contradictions of open data regarding transparency, privacy, security and trust

While Open Data initiatives are diverse, they aim to create and contribute to public value. Yet several potential contradictions exist between public values, such as trust, transparency, privacy, and security, and Open Data policies. To bridge these contradictions, we present the notion of precommitment as a restriction of ones choices. Conceptualized as a policy instrument, precommitment can be applied by an organization to restrict the extent to which an Open Data policy might conflict with public values. To illustrate the use of precommitment, we present two case studies at two public sector organizations, where precommitment is applied during a data request procedure to reconcile conflicting values. In this procedure, precommitment is operationalized in three phases. In the first phase, restrictions are defined on the type and the content of the data that might be requested. The second phase involves the preparation of the data to be delivered according to legal requirements and the decisions taken in phase 1. Data preparation includes amongst others the deletion of privacy sensitive or other problematic attributes. Finally, phase 3 pertains to the establishment of the conditions of reuse of the data, limiting the use to restricted user groups or opening the data for everyone.

Trusted third parties for secure and privacy-preserving data integration and sharing in the public sector

For public organizations data integration and sharing are important in delivering better services. However, when sensitive data are integrated and shared, privacy protection and information security become key issues. This means that information systems must be secured and that access to sensitive data must be controlled. In this paper, a framework is presented to support data sharing between public organizations for collaboration purposes. The framework focuses on solutions towards optimal data sharing and integration while ensuring the security and privacy of individuals. Data sharing is based on the need-to-know principle, that is, data are only made available when they are required to perform core processes. To facilitate this, an approach is introduced in the form of a trusted third party that manages access control to personal information and thus helps to protect the privacy of individuals. It is argued that the proposed framework is suitable for data integration and sharing on various levels. An example of best practices of data sharing in the Netherlands shows how this framework facilitates data sharing to perform knowledge transfer and other higher-level tasks.

Privacy and Security in Smart Data Collections by Citizens

The question of how to make a city or government better by exploiting information and communication infrastructures, referred to as smart city, entails an emerging field of research. Large quantities of data are generated from these infrastructures and infusing these data into the physical infrastructure of a city or government may lead to better services to citizens. Collecting and processing of such data, however, may result in privacy and security issues that should be faced appropriately to create a sustainable approach for smart cities and governments. In this chapter, we focus on data collection through crowdsourcing with smart devices and identify the corresponding security and privacy issues in the context of enabling smart cities and governments. We categorize these issues in four classes. For each class, we identify a number of threats as well as solution directions for these threats.

Capture-Recapture Method for Estimating the Number of Problem Drug Users: The Case of the Netherlands

In this paper, two methods have been compared to estimate the number of problem drug users (PDU): the treatment multiplier (TM) method and the capture-recapture(CRC) method using national police register data and data from probation services and treatment institutes for addiction. This paper introduces the CRC method as a more practical alternative to the TM method, with similar results.

On addressing privacy in disseminating judicial data: towards a methodology

Purpose Information dissemination has become a means of transparency for governments to enable the visions of e-government and smart government, and eventually gain, among others, the trust of various stakeholders such as citizens and enterprises. Information dissemination, on the other hand, may increase the chance of privacy breaches, which can undermine those stakeholders’ trust and thus the objectives of transparency. Moreover, fear of potential privacy breaches compels information disseminators to share minimum or no information. The purpose of this study is to address these contending issues of information disseminations, i.e. privacy versus transparency, when disseminating judicial information to gain (public) trust. Specifically, the main research questions are: What is the nature of the aforementioned “privacy–transparency” problem and how can we approach and address this class of problems? Design/methodology/approach To address these questions, the authors have carried out an explorative case study by reconsidering and analyzing a number of information dissemination cases within their research center for the past 10 years, reflecting upon the whole design research process, consulting peers through publishing a preliminary version of this contribution and embedding the work in an in-depth literature study on research methodologies, wicked problems and e-government topics. Findings The authors show that preserving privacy while disseminating information for transparency purposes is a typical wicked problem, propose an innovative designerly model called transitional action design research (TADR) to address the class of such wicked problems and describe three artifacts which are designed, intervened and evaluated according to the TADR model in a judicial research organization. Originality/value Classifying the privacy transparency problem in the judicial settings as wicked is new, the proposed designerly model is innovative and the realized artifacts are deployed and still operational in a real setting.