Showing papers by "Anneke Zuiderwijk published in 2020"

What drives and inhibits researchers to share and use open research data? A systematic literature review to analyze factors influencing open research data adoption.

Abstract: Both sharing and using open research data have the revolutionary potentials for forwarding scientific advancement. Although previous research gives insight into researchers' drivers and inhibitors for sharing and using open research data, both these drivers and inhibitors have not yet been integrated via a thematic analysis and a theoretical argument is lacking. This study's purpose is to systematically review the literature on individual researchers' drivers and inhibitors for sharing and using open research data. This study systematically analyzed 32 open data studies (published between 2004 and 2019 inclusively) and elicited drivers plus inhibitors for both open research data sharing and use in eleven categories total that are: 'the researcher's background', 'requirements and formal obligations', 'personal drivers and intrinsic motivations', 'facilitating conditions', 'trust', 'expected performance', 'social influence and affiliation', 'effort', 'the researcher's experience and skills', 'legislation and regulation', and 'data characteristics.' This study extensively discusses these categories, along with argues how such categories and factors are connected using a thematic analysis. Also, this study discusses several opportunities for altogether applying, extending, using, and testing theories in open research data studies. With such discussions, an overview of identified categories and factors can be further applied to examine both researchers' drivers and inhibitors in different research disciplines, such as those with low rates of data sharing and use versus disciplines with high rates of data sharing plus use. What's more, this study serves as a first vital step towards developing effective incentives for both open data sharing and use behavior.

Citizen Engagement with Open Government Data : Lessons learned from Indonesia’s Presidential Election

Abstract: Citizen engagement is key to the success of many Open Government Data (OGD) initiatives. However, not much is known regarding how this type of engagement emerges. This study aims to investigate the necessary conditions for the emergence of citizen-led engagement with OGD and to identify which factors stimulate this type of engagement.,First, the authors created a systematic overview of the literature to develop a conceptual model of conditions and factors of OGD citizen engagement at the societal, organizational and individual level. Second, the authors used the conceptual model to systematically study citizens’ engagement in the case of a particular OGD initiative, namely, the digitization of presidential election results data in Indonesia in 2014. The authors used multiple information sources, including interviews and documents, to explore the conditions and factors of OGD citizen-led engagement in this case.,From the literature the authors identified five conditions for the emergence of OGD citizen-led engagement as follows: the availability of a legal and political framework that grants a mandate to open up government data, sufficient budgetary resources allocated for OGD provision, the availability of OGD feedback mechanisms, citizens’ perceived ease of engagement and motivated citizens. In the literature, the authors found six factors contributing to OGD engagement as follows: democratic culture, the availability of supporting institutional arrangements, the technical factors of OGD provision, the availability of citizens’ resources, the influence of social relationships and citizens’ perceived data quality. Some of these conditions and factors were found to be less important in the studied case, namely, citizens’ perceived ease of engagement and citizens’ perceived data quality. Moreover, the authors found several new conditions that were not mentioned in the studied literature, namely, citizens’ sense of urgency, competition among citizen-led OGD engagement initiatives, the diversity of citizens’ skills and capabilities and the intensive use of social media. The difference between the conditions and factors that played an important role in the case and those derived from the literature review might be because of the type of OGD engagement that the authors studied, namely, citizen-led engagement, without any government involvement.,The findings are derived using a single case study approach. Future research can investigate multiple cases and compare the conditions and factors for citizen-led engagement with OGD in different contexts.,The conditions and factors for citizen-led engagement with OGD have been evaluated in practice and discussed with public managers and practitioners through interviews. Governmental organizations should prioritize and stimulate those conditions and factors that enhance OGD citizen engagement to create more value with OGD.,While some research on government-led engagement with OGD exists, there is hardly any research on citizen-led engagement with OGD. This study is the first to develop a conceptual model of necessary conditions and factors for citizen engagement with OGD. Furthermore, the authors applied the developed multilevel conceptual model to a case study and gathered empirical evidence of OGD engagement and its contributions to solving societal problems, rather than staying at the conceptual level. This research can be used to investigate citizen engagement with OGD in other cases and offers possibilities for systematic cross-case lesson-drawing.

Citizens’ Trust in Open Government Data: A Quantitative Study about the Effects of Data Quality, System Quality and Service Quality

Abstract: Previous research assumes that poor quality of Open Government Data (OGD), OGD portals, and the services provided for OGD may result in reduced trust of citizens in OGD. However, studies that empirically test this assumption are scarce. Using the Information Systems (IS) Success Model as a theoretical basis, this study aims to examine the effects of data quality, system quality, and service quality on citizens’ trust in OGD. We used Structural Equation Modeling (SEM) to analyze the 200 responses to our online questionnaire. We found that trust in OGD can be predicted by citizens’ perceptions of OGD system quality and service quality. Furthermore, citizens’ perception of service quality positively influences their perceptions of data and system quality, whereas citizens’ perception of system quality positively influences their perception of data quality. This study is among the first that quantitatively examines the effects of data quality, service quality, and system quality on citizen's trust in OGD. It contributes to the scientific literature by providing an operationalization of elements of the IS Success Model in the context of OGD and by developing and applying a model of factors influencing citizen's trust in OGD. While previous research finds that perceived data quality is the most crucial driver for trust in OGD, our study finds that citizens’ perception of OGD service quality is a more important driver for trust in OGD. With regard to the practical contributions of this study, open data policymakers should be aware that citizens’ perceptions on data quality can be greatly improved when appropriate human services are provided (e.g., designated civil servants offering support or help to data users) in addition to the provision of OGD portal functionalities (e.g., data visualization and comparison tools).

Scholarly Research and Publications Over Time: Identifying Trends for an Open Access Journal by Applying Data-Mining Methods

Abstract: See RECORDING (starts at 00:22:38). Journal editors of all types of scholarly publishing face various issues and choices in order to support the development of the journals they lead and manage. One particular issue is what strategic choices can be made to enhance the visibility, accessibility and impact of research published in their journal as much as possible. Another issue is how to provide potential authors of the journal with useful information that will support them with their publication choice. The objective of this study is twofold. First, it aims to provide an approach that can be used by journal editors to identify topical trends in scholarly-led publishing in their journal, in order to better inform potential future authors of the journal. In particular, we analyse what factors impact the trends and research cooperations over time with a view to research topics and thematic streams, regions, and the research methods employed by authors in previous publications. Second, this study derives potential factors responsible for specific journal developments, such as the influence of open access principles, guest editors, indexing systems, research cooperations and topics addressed by the journal on the visibility, accessibility and impact of the journal. To attain the above-mentioned objectives, this study uses data-mining methods to analyse all the articles published in one journal in particular, namely the (diamond(/platinum) open access e-journal for eDemocracy and Open Government called “JeDEM” (see www.jedem.org) that was set up in 2009. The methods used are a combination of data mining (such as the text mining, topic modelling, k-means clustering, social network analysis and community detection) of journal content and metadata with further qualitative interpretation of results from a journal management perspective. The qualitative part confirms or challenges the data analysis part, particularly with view to potential outliers or developments that cannot be explained by quantitative data analysis alone. Combined with internal knowledge from the journal management perspective, we are able to provide an interpretative component and are to relate the trends emerging from the data to strategic decisions or publication details. The results are as follows. First, our study shows the most prominent research topics of the studied journal, and their evolution over time. Second, the research methods employed by authors publishing in the journal are identified, as well as the research cooperations established through publications in the journal. Third, the crucial factors such as indexing, communication with the community and changes in journal management are derived. The developed approach was found to be useful to gain insights concerning journal developments, and might also be used by editors of other journals to determine their journal strategy. For example, using data mining methods, editors can analyse whether the topics included in their call for papers match the topics on which the journal publishes or whether it needs adaptations to better manage the expectations of future authors of the journal. Thus, our results might also help authors with their publication choices and tracing the evolutionary stages of the studying scientific problem. Finally, our study derives further research questions aiming at achieving a critical assessment of scholarly developments within the publishing sphere over time.

Open Government Data Systems: Learning from a Public Utility Perspective

Abstract: Previous research on Open Government Data (OGD) struggles with synthesising a holistic perspective of OGD systems. A perspective that has dealt with vast, complex systems is public utility. Public utilities are, for example, water supply networks and electric power grids. This study explores what we can learn from a public utility perspective when perceiving and organising OGD systems. We used a hermeneutic literature review combined with a snowballing approach, resulting in a selection of 39 studies. We compare public utilities and OGD systems to derive five lessons: (1) an OGD system can be perceived from a node-flow view, (2) the foundational data flow of an OGD system starts at data collection and ends at data used by the public in an everyday context, (3) the organisation of OGD systems needs to consider the combinability, interpretability, and boundless reusability of data, (4) OGD systems need governance organisations that cover the whole system, and (5) OGD systems could replace existing data provision systems and be made a public utility if certain characteristic problems are overcome.