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This study aims to conduct performance and clustering analyses with the help of Digital Government Reference Library (DGRL) v16.6 database examining the role of emerging technologies (ETs) in public services delivery.

VOSviewer and SciMAT techniques were used for clustering and mapping the use of ETs in the public services delivery. Collecting documents from the DGRL v16.6 database, the paper uses text mining analysis for identifying key terms and trends in e-Government research regarding ETs and public services.

The analysis indicates that all ETs are strongly linked to each other, except for blockchain technologies (due to its disruptive nature), which indicate that ETs can be, therefore, seen as accumulative knowledge. In addition, on the whole, findings identify four stages in the evolution of ETs and their application to public services: the “electronic administration” stage, the “technological baseline” stage, the “managerial” stage and the “disruptive technological” stage.

The output of the present research will help to orient policymakers in the implementation and use of ETs, evaluating the influence of these technologies on public services.

The research helps researchers to track research trends and uncover new paths on ETs and its implementation in public services.

Recent research has focused on the need of implementing ETs for improving public services, which could help cities to improve the citizens’ quality of life in urban areas. This paper contributes to expanding the knowledge about ETs and its implementation in public services, identifying trends and networks in the research about these issues.

In the last few years, the size of Linked Open Data (LOD) describing artworks, in general or domain-specific Knowledge Graphs (KGs), is gradually increasing. This provides (art-)historians and Cultural Heritage professionals with a wealth of information to explore. Specifically, structured data about iconographical and iconological (icon) aspects, i.e. information about the subjects, concepts and meanings of artworks, are extremely valuable for the state-of-the-art of computational tools, e.g. content recognition through computer vision. Nevertheless, a data quality evaluation for art domains, fundamental for data reuse, is still missing. The purpose of this study is filling this gap with an overview of art-historical data quality in current KGs with a focus on the icon aspects.

This study’s analyses are based on established KG evaluation methodologies, adapted to the domain by addressing requirements from art historians’ theories. The authors first select several KGs according to Semantic Web principles. Then, the authors evaluate (1) their structures’ suitability to describe icon information through quantitative and qualitative assessment and (2) their content, qualitatively assessed in terms of correctness and completeness.

This study’s results reveal several issues on the current expression of icon information in KGs. The content evaluation shows that these domain-specific statements are generally correct but often not complete. The incompleteness is confirmed by the structure evaluation, which highlights the unsuitability of the KG schemas to describe icon information with the required granularity.

The main contribution of this work is an overview of the actual landscape of the icon information expressed in LOD. Therefore, it is valuable to cultural institutions by providing them a first domain-specific data quality evaluation. Since this study’s results suggest that the selected domain information is underrepresented in Semantic Web datasets, the authors highlight the need for the creation and fostering of such information to provide a more thorough art-historical dimension to LOD.

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.

The purpose of this study is to offer a checklist that can be used for both creating and evaluating digital collections, which are also sometimes referred to as data sets as part of the collections as data movement, suitable for computational use.

The checklist was built by synthesising and analysing the results of relevant research literature, articles and studies and the issues and needs obtained in an observational study. The checklist was tested and applied both as a tool for assessing a selection of digital collections made available by galleries, libraries, archives and museums (GLAM) institutions as proof of concept and as a supporting tool for creating collections as data.

Over the past few years, there has been a growing interest in making available digital collections published by GLAM organisations for computational use. Based on previous work, the authors defined a methodology to build a checklist for the publication of Collections as data. The authors’ evaluation showed several examples of applications that can be useful to encourage other institutions to publish their digital collections for computational use.

While some work on making available digital collections suitable for computational use exists, giving particular attention to data quality, planning and experimentation, to the best of the authors’ knowledge, none of the work to date provides an easy-to-follow and robust checklist to publish collection data sets in GLAM institutions. This checklist intends to encourage small- and medium-sized institutions to adopt the collection as data principles in daily workflows following best practices and guidelines.

This study presents a review based research framework that aims to influence memory institutions in their projects on digital storytelling from digitized ancient travel records. This study aims to influence research and policymaking related to design and delivery of services based on memory institutions’ collections of historical records.

The demonstrated research framework has been synthesized using inputs from a review of existing studies on the domain accompanied by a short survey created for collecting the opinion of selected experts. Studies demonstrating utilization of semantic web technologies and those that can influence policymaking related to digital storytelling were primarily reviewed.

The core tasks behind digital storytelling vary depending on the project goals. So, a two-part framework had to be proposed that covers the generic fundamental tasks with diverse applicability and digital storytelling related specific tasks separately. Also during the review, it was found that studies demonstrating the use of travel records for digital storytelling were less in number compared to studies using digital storytelling for tourism in general.

The demonstrated research framework can guide memory institutions in exposing their travel-related holdings to a wider audience using innovative semantic web technologies and open up avenues for future empirical research thereby adding to the novelty of the presented research. Also, reviews of articles on digital storytelling or digital humanities in general exist, but, review of digital storytelling initiatives focusing specifically on tourism and travel literature is scarce.

This study aims to underline the possible influence of the moderator, information systems (IS) infusion, on Open Government Data (OGD) adoption and usage.

Using the partial least squares-structural equation modeling methodological approach, the adapted unified theory of acceptance and use of technology (UTAUT) model has been used for understanding the role of the moderating variable, namely, IS infusion.

Findings show that the moderating impact of IS infusion is positively significant with respect to the performance expectancy–behavioral intention relationship thereby bolstering the impact on users’ perception of OGD vis-à-vis work/academics performance and negatively significant for social influence–behavioral intention, information quality–behavioral intention, thereby clinching the fact that with the increased engagement and involvement of OGD in the everyday life of the user, the role of significant others and information quality gets least significant.

Extant OGD-focused research has underscored the impact of different variables as far as OGD adoption and usage is concerned; the present study seeks to add on to the extant literature by understanding the implications of IS infusion on the adapted UTAUT model constructs and behavioral intention relationships.

This study aims to adjust Thesis-type properties on Schema.org using metadata models and standards (MS) (Bibframe, electronic thesis and dissertations [ETD]-MS, Common European Research Information Format [CERIF] and Dublin Core [DC]) to enrich the Thesis-type properties for better description and processing on the Web.

This study is applied, descriptive analysis in nature and is based on content analysis in terms of method. The research population consisted of elements and attributes of the metadata model and standards (Bibframe, ETD-MS, CERIF and DC) and Thesis-type properties in the Schema.org. The data collection tool was a researcher-made checklist, and the data collection method was structured observation.

The results show that the 65 Thesis-type properties and the two levels of Thing and CreativeWork as its parents on Schema.org that corresponds to the elements and attributes of related models and standards. In addition, 12 properties are special to the Thesis type for better comprehensive description and processing, and 27 properties are added to the CreativeWork type.

Enrichment and expansion of Thesis-type properties on Schema.org is one of the practical applications of the present study, which have enabled more comprehensive description and processing and increased access points and visibility for ETDs in the environment Web and digital libraries.

This study has offered some new Thesis type properties and CreativeWork levels on Schema.org. To the best of the authors’ knowledge, this is the first time this issue is investigated.

The rising volume of open government data (OGD) contrasts with the limited acceptance and utilization of OGD among citizens. This study investigates the reasons for citizens’ not using available OGD by comparing citizens’ attitudes towards OGD with the development of OGD portals. The comparison includes four OGD utilization processes derived from the literature, namely OGD awareness, needs, access and consumption.

A case study in China has been carried out. A sociological questionnaire was designed to collect data from Chinese citizens (demand), and personal visits were carried out to collect data from OGD portals (supply).

Results show that Chinese citizens have low awareness of OGD and OGD portals. Significant differences were recognized between citizens’ expectations and OGD portals development in OGD categories and features, data access services and support functions. Correlations were found between citizens’ OGD awareness, needs, access and consumption.

By linking the supply of OGD from the governments with each process of citizens’ OGD utilization, this paper proposes a framework for citizens’ OGD utilization lifecycle and provides a new tool to investigate reasons for citizens’ not making use of OGD.

The opening of government data is high on the policy agenda of governments worldwide. However, data release faces barriers due to limited support of civil servants, whereas the literature neglects civil servants' role in opening data. This paper aims at understanding why civil servants can be reluctant to support the disclosure of data. The authors developed a model to explain civil servants' behavioral intention to open data.

The authors test a series of hypotheses by collecting and analyzing survey data from 387 civil servants and by applying multivariate hierarchical regression.

The results indicate the factors influencing the behavior of civil servants. Social influences, performance expectancy, data management knowledge and risks have a significant influence. Personal characteristics control these effects.

Caution is needed to generalize the findings towards the support to open data provision by civil servants. Though the analyzed sample was limited to Brazil, other countries and cultures might yield different outcomes. Larger and more diversified samples might indicate significant effects on variables not found in this research.

The insights can be used to develop policies for increasing the support of civil servants towards governmental data disclosure.

This study suggests factors of influence to civil servants' behavior intentions to disclose governmental data. It results in a model of factors, specifically for their behavioral intention at the individual level.

The paper aims to review rules and policy guidelines worldwide around non-personal data (NPD) and evaluate the policies on criteria that allow for the use of data for economic and social good. A review related to diverse policy approaches of various countries remains a research gap, and hence the analysis in the paper is designed with the intention of developing a research framework and providing policy gaps for further exploration.

A systematic review of academic and non-academic literature on theoretical foundations, applications of NPD for economic and social good and NPD policies and regulations was conducted to identify the evaluation criteria. A total of 32 dimensions got identified for evaluation. As second step, content analysis was used for evaluation. A total of 13 documents from 6 countries and 1 geographical region were identified for evaluation. The documents were evaluated based on the 32 dimensions spread across 5 domains that facilitate data access and sharing for economic and societal benefit.

The analysis highlights three distinct emerging perspectives on data exchange: most policy and regulatory documents acknowledge the importance of identifying different types of NPD and accordingly describing the distinct roles and responsibilities of data actors for leveraging the data; the policy and regulatory frameworks clearly focus on increasing business opportunities, data sharing cooperation and innovation; and findings also demonstrate certain gaps in the policy frameworks such as a more comprehensive discussion on data access and sharing mechanisms, particularly data sandboxes and open data, and concrete norms and rigorous standards regarding accountability, transparency, ownership and confidentiality. Furthermore, policies and regulations may include appropriate incentive structures for data providers and users to ensure unhindered and sustainable access to data for the common good.

To the best of the authors’ knowledge, this paper represents one of the first research contributions evaluating global data policies focused on NPD in the context of its increasing use as a public good. The paper first identifies evaluation criteria for the analysis on public and social good, and, thus, provides a conceptual framework for future research. Additionally, the analysis identifies the broad domains of policy analysis on social and public good for data economics.