Search results

The purpose of this paper is to conduct a usability evaluation of governmental data portals and provide a list of best practices for improving stakeholders’ ability to discover, access, and reuse of these online information sources.

The developed methodology was based on the comprehensive literature review that resulted in a benchmarking framework of the most important criteria. A usability testing method was then applied with accordance to unique requirements of open data portals. This approach was demonstrated by using of a case study.

The main found weakness was a lack of support for active engagement of stakeholders. The list of best practices was introduced to improve the quality of these portals. This should help to improve the discoverability and facilitate the access to data sets in order to increase their reuse by stakeholders.

The creation of appropriate open data portals aims to fulfill the principles of open government, i.e., to promote transparency and openness through the publication of government data, enhance the accountability of public officials and encourage public participation, collaboration, and cooperation of involved stakeholders.

This paper proposed a new approach for the usability evaluation of open data portals on national level from an ordinary citizen’s point of view and provided important insights on improving their quality regarding data discoverability, accessibility, and reusability.

The purpose of this paper is to study the select Smart Cities of Czech and Indian counterparts and assess the extent to which open government data (OGD) standards are being adhered to using select indicators.

This study integrates the benchmarking frameworks provided in literature on OGD and apply them to evaluate the OGD standards of the Smart Cities’ websites.

Whereas the Czech Smart Cities are relatively more advanced in their OGD initiatives, the Indian counterpart is far lagging behind in their endeavors.

While there are many studies on OGD and Smart Cities, there has been no study which seeks to appreciate if the OGD initiatives are being adhered to by the Smart Cities.

Benchmarking e-government and digital society developments using relevant indicators provides crucial insights into what aspects to consider while building a resilient digital society in which digital public services are delivered effectively and sustainably. The purpose of this paper is to analyse selected indices and indicators over the years and provide findings and recommendations on what indicators contribute most to the development.

A mixed research approach was used to conduct the research and collect, analyse and interpret data. A qualitative analysis involving the search, decomposition and comparison approaches to identify e-government and digital society reports, indices, rankings and indicators was followed by a quantitative analysis comprising of regression and cluster analyses.

The findings revealed that changes in the mix of indicators used by e-government and digital society indices can be attributed to advances in ICT and channels through which people communicate and receive information. The authors found that digital and telecommunication infrastructures and the quality of their parameters such as broadband have the biggest influence on progress of the e-government and digital societies developments and contribute most to clustering of the EU member states into groups.

The paper provides insights into how the structures of related indices changed over the years and how different indicators contribute to benchmarking of e-government and digital society developments by means of their weights. It provides governments with recommendations on which indicators to focus most.

Open government data (OGD) are considered as a technology capable of promoting transparency openness, and accountability, which in turn has a positive impact on innovation activities and creates responsive government, collaboration, cooperation, co-creation and participation. The purpose of this paper is to explore the adoption of OGD and open data portals among students, in an attempt to discover how governments can improve their actions in this respect.

This study develops a behavioural intention-based analysis using constructs from the Unified Theory of Acceptance and Use of Technology, which is supplemented with additional constructs that meet the purpose of the study. In total, ten constructs divided into 33 items constituted the input for our study. Input data for the developed model have been collected through a structured questionnaire distributed between bachelor's and master's level students in three countries – the Czech Republic, India and Latvia. A structural equation modelling technique was used to analyse the relationships between variables of the model and test the nine hypothesis defined.

Six constructs have been identified to facilitate significant relationships with behavioural intention. The analysis of the results of the three countries allows us to draw more objective conclusions in respect to the aim of the study and to reveal country-specific aspects that need to be addressed in the future.

This study adds to the existing literature few theoretical and practical aspects. It highlights the role of open data portals as a central point of OGD infrastructures. It enables governments to understand the relationships among the related constructs, improving their actions and modifying their data infrastructures accordingly.

The purpose of this paper was to draw on evidence from computer-mediated transparency and examine the argument that open government data and national data infrastructures represented by open data portals can help in enhancing transparency by providing various relevant features and capabilities for stakeholders' interactions.

The developed methodology consisted of a two-step strategy to investigate research questions. First, a web content analysis was conducted to identify the most common features and capabilities provided by existing national open data portals. The second step involved performing the Delphi process by surveying domain experts to measure the diversity of their opinions on this topic.

Identified features and capabilities were classified into categories and ranked according to their importance. By formalizing these feature-related transparency mechanisms through which stakeholders work with data sets we provided recommendations on how to incorporate them into designing and developing open data portals.

The creation of appropriate open data portals aims to fulfil the principles of open government and enables stakeholders to effectively engage in the policy and decision-making processes.

By analyzing existing national open data portals and validating the feature-related transparency mechanisms, this paper fills this gap in existing literature on designing and developing open data portals for transparency efforts.

Increasingly, Open Government Data (OGD), a philosophy and set of policies, gains on momentum today. Believed to promote transparency, accountability and value creation by making government data available to all (OECD, 2018), OGD constitutes a yet another field in which the interlocking relation between technological advances and politics can be studied. Using the national OGD portal of the Kingdom of Saudi Arabia (http://www.data.gov.sa/en) as a case study, this evaluates the portal to underline the significance of maintaining the quality of the data sets published online. The usability framework (Machova, Hub, & Lnenicka 2018) constitutes the framework for evaluation of the OGD portal. The findings suggest that there are many drivers to re-use the data sets published via the portal. At the same time, however, there are barriers to re-use the data sets on account of the non-publication of updated data sets. Implicitly, quality of the data sets should be improved. More involvement of the government agencies is required for contributing toward the data sets. Also, user involvement should be promoted by encouraging them to contribute to the data sets and lending recommendations for the improvisation of the data sets published via the portal.

The purpose of this study is to explore open data portals as data literacy learning environments. The authors examined the obstacles faced and strategies used by university students as non-expert open data portal users with different levels of data literacy, to inform the design of portals intended to scaffold informal and situated learning.

The authors conducted an observational user study, in which 14 student participants grouped by self-reported data literacy measures carried out assigned tasks in an open data portal. Data were collected through screen capture, think-aloud protocols and post-session interviews.

Participants experienced numerous challenges in finding and using data, with some variation shown between the different literacy groups. The higher data literacy group primarily faced challenges using unfamiliar tools, which may be addressed by improving system usability, while the lower data literacy group struggled due to gaps in basic understanding, which may be addressed by increasing point of need instruction and guidance. Participants used several learning strategies but primarily relied upon trial and error, which was less effective for low data literacy users.

This study is unique in comparing open data portal use among adult students across data literacy levels through an empirical user study. It contributes methodologically by proposing an instrument for data literacy assessment. It offers a novel perspective on information systems as sites for informal learning and skills development, beyond the immediate goals of system use, and offers concrete suggestions for the future design of open data portals for students and non-expert, citizen users.

This study aimed to develop a taxonomy of research areas in open government data (OGD) through a bibliometric mapping tool and a qualitative analysis software.

In this study, the authors extracted metadata of 442 documents from a bibliographic database. The authors used a bibliometric mapping tool for familiarization with the literature. After that, the authors used qualitative analysis software to develop taxonomy.

This paper developed taxonomy of OGD with three research areas: implementation and management, architecture, users and utilization. These research areas are further analyzed into seven topics and twenty-eight subtopics. The present study extends Charalabidis et al. (2016) taxonomy by adding two research topics, namely the adoption factors and barriers of OGD implementations and OGD ecosystems. Also, the authors include artificial intelligence in the taxonomy as an emerging research interest in the literature. The authors suggest four directions for future research: indigenous knowledge in open data, open data at local governments, development of OGD-specific theories and user studies in certain research themes.

Early career researchers and doctoral students can use the taxonomy to familiarize themselves with the literature. Also, established researchers can use the proposed taxonomy to inform future research. Taxonomy-building procedures in this study are applicable to other fields.

This study developed a novel taxonomy of research areas in OGD. Taxonomy building is significant because there is insufficient taxonomy of research areas in this discipline. Also, conceptual knowledge through taxonomy creation is a basis for theorizing and theory-building for future studies.

This study investigates the individual and binary (i.e. combined) effects of institutional dimensions of open government data (which include instructional, structural and accessible rules) on scientific research innovation, as well as the mediating roles that researchers' perceived data usefulness and data capability play in between.

Based on a sample of 1,092 respondents, this study uses partial least squares structural equation modeling (PLS-SEM) and polynomial regression with response surface analysis to evaluate the direct and indirect effects of individual and binary institutional dimensions on scientific research innovation.

The findings demonstrate that instructional, structural and restricted access data have a positive effect on scientific research innovation in the individual effect. While the binary effect of institutional dimensions produces varying degrees of scientific research innovation. Furthermore, this study discovers that the perceived usefulness and data capability of researchers differ in the mediating effect of institutional dimensions on scientific research innovation.

Theoretically, this study contributes new knowledge on the causal links between data publication institutions and innovation. Practically, the research findings offer government data managers timely suggestions on how to build up institutions to foster greater data usage.