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Many governments are working toward a vision of government-wide transformation that strives to achieve an open, transparent and accountable government while providing responsive services. The purpose of this paper is to clarify the concept of transparency-by-design to advance open government.

The opening of data, the deployment of tools and instruments to engage the public, collaboration among public organizations and between governments and the public are important drivers for open government. The authors review transparency-by-design concepts.

To successfully achieve open government, fundamental changes in practice and new research on governments as open systems are needed. In particular, the creation of “transparency-by-design” is a key aspect in which transparency is a key system development requirement, and the systems ensure that data are disclosed to the public for creating transparency.

Although transparency-by-design is an intuitive concept, more research is needed in what constitutes information and communication technology-mediated transparency and how it can be realized.

Governments should embrace transparency-by-design to open more data sets and come closer to achieving open government.

Transparency-by-design is a new concept that has not given any attention yet in the literature.

With the progressive trends in Open Data, this paper aims to underscore the significance of Open Linked Statistical Data (OLSD) and identifies the trajectory of development of OLSD besides underlining the prospects and challenges underlying OLSD.

Being exploratory in nature, this viewpoint seeks to present a trajectory of OLSD which seeks to emphasize upon the futuristic trend in the development of OLSD.

Eight stages have been identified in the OLSD trajectory. The opening of more and more data results in new possibilities for combining data and gaining new insights. In the future, data will automatically be opened and streamed and could be used in using OLSD algorithms. Algorithms will mention the shortcomings and limitations of data and help to interpret the data in such a way that the user is in the driver’s seat.

While the paper follows an exploratory approach, there are a couple of implications for the practitioners and academicians. For instance, government may become more accountable with the adoption of advanced OLSD algorithms. Further research on OLSD may be required in appreciating the impact of OLSD in different settings, and this would be helpful in providing novel insights to the concerned stakeholders.

While Big and Open Linked Data (BOLD) has gained prominence in academic research, the focus on OLSD has remained scanty. This paper seeks to underline the futuristic trends in OLSD.

The study aims to investigate the utilisation of open research data repositories (RDRs) for storing and sharing research data in higher learning institutions (HLIs) in Tanzania.

A survey research design was employed to collect data from postgraduate students at the Nelson Mandela African Institution of Science and Technology (NM-AIST) in Arusha, Tanzania. The data were collected and analysed quantitatively and qualitatively. A census sampling technique was employed to select the sample size for this study. The quantitative data were analysed using the Statistical Package for the Social Sciences (SPSS), whilst the qualitative data were analysed thematically.

Less than half of the respondents were aware of and were using open RDRs, including Zenodo, DataVerse, Dryad, OMERO, GitHub and Mendeley data repositories. More than half of the respondents were not willing to share research data and cited a lack of ownership after storing their research data in most of the open RDRs and data security. HILs need to conduct training on using trusted repositories and motivate postgraduate students to utilise open repositories (ORs). The challenges for underutilisation of open RDRs were a lack of policies governing the storage and sharing of research data and grant constraints.

Research data storage and sharing are of great interest to researchers in HILs to inform them to implement open RDRs to support these researchers. Open RDRs increase visibility within HILs and reduce research data loss, and research works will be cited and used publicly. This paper identifies the potential for additional studies focussed on this area.

With the worldwide open government data (OGD) movement and frequent public health emergencies in recent years, academic research on OGD for public health emergencies has been growing. However, it is not fully understood how to promote OGD on public health emergencies. Therefore, this paper aims to explore the factors that influence OGD on public health emergencies.

The technology–organization–environment framework is applied to explore factors that influence OGD during COVID-19. It is argued that the effects of four key factors – technical capacity, organizational readiness, social attention and top-down pressure – are contingent on the severity of the pandemic. A unique data set was created by combining multiple data sources which include archival government data, a survey of 1,034 Chinese respondents during the COVID-19 outbreak and official COVID-19 reports.

The data analysis indicates that the four factors positively affect OGD, and pandemic severity strengthens the effects of technical capacity, organizational readiness and social attention on OGD.

This study provides theoretical insights regarding how to improve OGD during public health emergencies, which can guide government efforts in sharing data with the public when dealing with outbreak in the future.

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.

In the data economy era, despite the tremendous effort of governments to actively provide and use open data, its effect on national performance such as competitiveness differs widely from country to country. A sufficient knowledge base and its appropriate management are important to effectively derive the potential value from open data. A country can implement multiple and equally viable means to effectively align open data with knowledge management, which lead to high national performance. However, previous studies lack consideration of the possibility of these various configurations. To fill the research gap, this study aims to investigate the configurational patterns constituted by government data openness and knowledge management for national competitiveness.

From the open innovation perspective, this study collected data from the global reports of 76 countries and examined them through fuzzy-set qualitative comparative analysis (fsQCA).

Four configurational patterns are identified, namely, coupled (outbound-focused)-, coupled (inbound-focused)-, inbound-focused-, and outbound-focused national competitiveness.

This study provides a foundation that enables researchers to build a holistic and balanced perspective that can manage open government data and develop knowledge management capability.

This study aimed to present a model for open-data management for developing innovative information flow in Iranian knowledge-based companies (businesses).

The method was mixed (qualitative-quantitative) and data collection tools were interview and questionnaire. The qualitative part was done to identify the influential components in open data management (ecosystem) using the grounded theory method. A questionnaire was developed based on the results of the qualitative section and the theoretical foundations, and the quantitative section was conducted by analytical survey method and the model was extracted using factor analysis and the integration of the qualitative section.

Seven categories of entrepreneurial incentives, sustainable value, innovative features, challenges and barriers, actors, business model and requirements are the main categories that should be considered in open data management (ecosystem) with all categories of research have a significant relationship with open data management.

The study focused on open data management from an innovation paradigm perspective and its role in developing innovative information flow. The study aimed to identify the key components of the open data ecosystem, open-data value creation, and the need to use the “open data” approach to develop data-driven and knowledge-based businesses in Iran–an emerging approach largely ignored.

The purpose of this paper is to explore the challenges that open government data initiatives present to records management within the public sector in England and to identify areas of practice and policy that will need to be developed to ensure compliance with such environments.

A review of current literature underpins the analysis of data collected through an anonymised case study of a National Health Service (NHS) hospital trust. Data were collected through a qualitative research in the form of semi-structured interviews with information professionals at the case study site. Additionally, a short descriptive online survey was distributed to the members of a specialist interest group, the Health Archives and Records Group.

Open government data presents a series of interconnected practical challenges to records management at a local level as the open government data environment continues to develop. These practical challenges overshadow a number of technical challenges, such as ensuring the accuracy and integrity of proactively published data.

The main limitation of this research is the small number of interviews conducted during data collection, which limits its capacity to present more generalised findings.

The case study of an individual NHS hospital trust allows for a specific insight into the challenges that open government data presents to records management within a single operational unit.

At exceptional times, governments are entrusted with greater authority. This creates significant concerns over governments’ transparency and accountability. This paper aims to pursue a twofold objective: assessing the patterns of open government data during the extraordinary time initiated by the COVID-19 pandemic drawing relevant policy and managerial implications regarding the future development of open data as a mechanism of accountability at times of exception.

The study follows exploratory research, relying on a web content analysis. The empirical setting is provided by 20 Italian regional governments during the COVID-19 pandemic as a shock that has triggered an exceptional time for governments.

Results on the desirable (extrinsic and intrinsic) characteristics of the data analyzed show that in the empirical setting investigated, open data does not enable to properly address the accountability concerns of a demanding forum at times of exception.

The paper enriches the state of the art on accountability and provides both scholars and practitioners (e.g. policymakers, managers, etc.) a current reading of data-driven orientation as a stimulus to the accountability of public administrations during exceptional times.

The paper investigates open data as a condition of public accountability, assessing whether and how Italian regional governments have concretely opened their data to enable their forums to elaboration of an informed opinion about their conduct during the ongoing pandemic. This fosters the understanding of how accountability is deployed in times of exception in light of the possibilities offered by the availability of online platforms.

The paper presents a literature review on research data management services in African academic and research libraries on the backdrop of the advancing open science and open research data infrastructures. It provides areas of focus for library to support open research data.

The literature analysis and future role of African libraries in research data management services were based on three areas as follows:open science, research infrastructures and open data infrastructures. Focussed literature searches were conducted across several electronic databases and discovery platforms, and a qualitative content analysis approach was used to explore the themes based on a coded list.

The review reports of an environment where open science in Africa is still at developmental stages. Research infrastructures face funding and technical challenges. Data management services are in formative stages with progress reported in a few countries where open science and research data management policies have emerged, cyber and data infrastructures are being developed and limited data librarianship courses are being taught.

The role of the academic and research libraries in Africa remains important in higher education and the national systems of research and innovation. Libraries should continue to align with institutional and national trends in response to the provision of data management services and as partners in the development of research infrastructures.