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The evaluation of government data sustainability is a multicriteria decision making problem. The analytic network process (ANP) is among the most popular methods in determining the weights of criteria, and its limitation is the un-convergence problem. This paper proposes a hybrid ANP (H-ANP) method, which aims to improve the ANP by combining the weights obtained from the analytic hierarchy process (AHP). The proposed method is proved to be convergent since the network of the H-ANP is strongly connected. According to the simulation experiments, H-ANP is more robust than ANP under different settings of parameters. It also shows a higher Kendall cor-relationship and lower MSE with respect to AHP, compared with the existing method (e.g., the averagely connected ANP method). An empirical example is also provided, which uses H-ANP to evaluate the government data sustainability of a city.

This study evaluates institutional research performance in benchmark technological universities in Taiwan through intelligent research databases (SciVal) in digital libraries with Ministry of Education open data to explore the performance of research indicators and the research trend of topic clusters to ascertain accountability for decision makers. The research performance of eight benchmark technological universities in Taiwan is compared in this study. In addition, the trends in research topics in the top 10% of journals are explored. Descriptive statistics, correlation, ANOVA, and the Boston Consulting Group matrix were used in this study. Research personnel, publications, productivity, total citations, number of international collaborations, and academic research income in 2018 significantly positively correlated with each other. From 719 records of research topics, topic clusters and school types are the significant factors in research outputs. Biosensors, electrodes, and voltammetry are the leading topic clusters in the research trend. The topic cluster of decision-making, fuzzy sets, and models has the best growth rate in the SciVal results. This analysis provides useful insights to policymakers to improve institutional administration and research resource allocation.

Introduction The United Nations Committee on the Rights of Persons with Disabilities identified the Chinese blind massage policy as “reserved employment” in its Concluding Observations in 2012. In response, this paper reviewed the policy on blind massage in China and discussed its effectiveness and social impact. Methods: Adopting a historical perspective, this paper describes the development stages of the blind massage policy in China. It reveals the social construction process of the blind massage policy. Government data were provided to help analyze the positive and negative effects of the policy according to the United Nations’ Convention on the Rights of Persons with Disabilities. Results: The blind massage policy is a national strategy involving semi-reserved employment to improve the low employment rate of people with visual impairments in China. It promoted employment of people with visual impairments at the start, but, as the system of the blind massage gradually took shape, it restricted these individuals from choosing a career freely. The blind massage policy has resulted in deep-rooted social prejudices, and it demonstrates disability-based discrimination and charity-oriented practices. Discussion: The Chinese blind massage policy is discriminatory and does not reflect the modern concept of disability rights advocated in the United Nations’ Convention on the Rights of Persons with Disabilities. Implications for practitioners: The Chinese government needs to promote institutional reforms to provide better education and employment for people with visual impairments to change the limited content of vocational training and eliminate discriminatory policies.

The Australian Institute of Health and Welfare (AIHW) is a leader in the provision of high-quality health and welfare information. Its work program has built a strong evidence base for better decisions that deliver improved health and welfare outcomes. The evolution of the AIHW’s data integration program has exemplified innovation in identifying and addressing key information gaps, as well as responsiveness to opportunities to develop and capture the data required to inform national priorities. The AIHW conducts data integration in partnership with data custodians and specialists in integration and analysis. A linkage project requiring the integration of Australian government data must be undertaken by an accredited integrating authority. The AIHW has met stringent criteria covering project governance, capability, and data management to gain this accreditation. In this capacity, the AIHW is trusted to integrate Australian government data for high-risk research projects. To date, the AIHW’s integration projects have generated improved research outcomes that have identified vulnerable population groups, improved the understanding of health risk factors, and contributed to the development of targeted interventions. These projects have fostered new insights into dementia, disability, health service use, patient experiences of healthcare, and suicide. Upcoming projects aim to further the understanding of interrelationships between determinants of wellbeing.

В статье рассматривается проблема адаптации образовательной программы подготовки ИТ-специалистов к решению сложных инженерных и, одновременно, творческих задач, связанных с развитием дата-журналистики. В качестве источника больших данных используются открытые государственные данные о системе здравоохранения. В статье отражены отдельные положения проектного обучения, сформированного на стандартах проектной и системно-инженерной деятельности, а также на принципах проведения хакатонов, где главным приоритетом является интеллектуальная составляющая работы команды и ее идеи. Приведены некоторые результаты использования проектного обучения при взаимодействии студентов - будущих ИТ-разработчиков с журналистами и исследователями данных. Предложенный подход и полученные на его основе результаты проектного обучения могут использоваться при создании методических рекомендаций для разработки совместных междисциплинарных образовательных программ, объединяющих сферу подготовки будущих ИТ-специалистов и дата-журналистов. The article discusses the problem of adapting the educational program of training IT specialists to solving complex engineering and, at the same time, creative problems associated with the development of data journalism. Open government data on the health care system is used as a source of big data. The article proposes the main provisions of the approach to project training, formed on the standards of project and system engineering activities, as well as on the principles of conducting hackathons, where the main priority is the intellectual component of the team's work and its ideas. Some results of the use of project-based learning in the interaction of students - future IT developers with journalists and data researchers are presented. The proposed approach and the results of project training obtained on its basis can be used to create guidelines for the development of joint interdisciplinary educational programs that combine the field of training future IT specialists and data journalists.

PurposeOpen 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.Design/methodology/approachThis 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.FindingsSix 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.Originality/valueThis 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.

This research investigates whether, why, and how open government data (OGD) is used and reused by Brazilian state and district public administrations. A new online questionnaire was developed and collected data from 26 of the 27 federation units between June and July 2021. The resulting dataset was cleaned and anonymized. It contains an insight on 158 parameters for 26 federation units explored. This article describes the questionnaire metadata and the methods applied to collect and treat data. The data file was divided into four sections: respondent profile (identify the respondent and his workplace), OGD use/consumption, what OGD is used for by public administrations, and why OGD is used by public administrations (benefits, barriers, drivers, and barriers to OGD use/reuse). Results provide the state of the play of OGD use/reuse in the federation units administrations. Therefore, they could be used to inform open data policy and decision-making processes. Furthermore, they could be the starting point for discussing how OGD could better support the digital transformation in the public sector.

Citizen engagement with open government data (OGD) can enhance the effectiveness of governments and improve not only the quality of public policy making but also public services provisioning and ability to address societal problems. Although previous research gives insight into citizen's drivers and inhibitors for engaging with OGD, they have not yet been integrated into a single conceptual model. The aims of this study are twofold: 1) to systematically review the literature on individual citizens' drivers and inhibitors for engaging with OGD and 2) to develop a conceptual model of citizen engagement with OGD based on the findings of the literature review. To attain this objective, the authors systematically analyzed 52 papers published in the period 2009-2019. Seven categories of drivers of citizen engagement are identified: citizen's profile, personal, performance-related, economic, social, technical, and political. Three groups of inhibitors are also identified: citizen's profile, technical, and political. This study helps in understanding how the engagement of citizens can be enhanced.