Quality of government health data in COVID-19: definition and testing of an open government health data quality evaluation framework

BackgroundOpen health data has implications for clinical care, research, public health, and health policy at regional, national, and global levels. No published attempts have been made to determine, collectively, whether WHO member states and governments have embraced the promise and effort required to officially share open health data. The observational study will provide evidence that World Health Organization (WHO) member states individually and collectively have adopted open data recommended principles, providing access to open health data.
 MethodsUsing the WHO list of member states (n=194), the researchers identified the presence of open health data or initiatives. With each country, the following types of official government web pages were recorded: a Ministry of Health web page; a conspicuous link on a government web page to open health data; additional government health web sites; national government-sponsored open data repositories; unique attributes of national health data web sites; and adherence to the principles of open government data for health. A supplemental PDF file provides a representation of data used for analysis and observations. Our complete data is available at: https://goo.gl/Kwj7mb
 Observations and DiscussionOpen health data is easily discoverable in less than one-third of the WHO member states. 13 nations demonstrate the principle to provide comprehensive open data. Only 16 nations distribute primary, non-aggregated health data. 24 % of the WHO observed member states are providing some health data in a non-proprietary formats such as comma-separated values. The sixth, seventh, and eighth open government data principles for health, representing universal access, non-proprietary formats, and non-patent protection, are observed in about one-third of the WHO member states. While there are examples of organized national open health data, no more than a one-third minority of the world’s nations have portals set up to systematically share open health data. At least 15 WHO member states are observed to not even have a government health ministry representation online.
 ConclusionWe hope the data collected in our Google Sheet and the discussion provided in this paper will generate international interest and advocacy for open health data.

In recent years, the amount of data in the world is growing rapidly. Data growth also occurs in the government sector. All ministries and institutions at every level are data producers. These government‐owned data have a high potential if they can be used properly. Open government data can stimulate innovation and economic growth and enhance business models. In order to increase the willingness of citizens to use open government data and enjoy the benefits mentioned, the quality of open government data needs to be improved. The quality of open government data encompasses a variety of dimensions and criteria. Also, the importance of each dimension and criterion in increasing the quality of open government data is different. Therefore, we are faced with a complex system that requires proper decision‐making and management. In fact, we are dealing with decision‐making in the complex management system. Given the importance of this issue, the purpose of this study is to provide a new and comprehensive method to improve the quality of open government data and increase the willingness of citizens to use the data by considering the complex network of citizens and organizations. For this purpose, library studies have been used to extract comprehensive and effective dimensions and criteria. The statistical population includes all articles related to the criteria of improving the quality of open government data and increasing the willingness of citizens to use the data. The probabilistic sampling method of simple random samples has been used, and 10 articles in this field have been reviewed. After extracting the criteria as well as the data of 112 governmental organizations and institutions related to each criterion from the open data portal, the complex network of citizens and governmental organizations and institutions has been analyzed in order to identify high‐degree centrality organizations. Then, the data characteristics of the organizations that were most desired by the citizens were extracted using data mining techniques including the regression model. Also, field method and multicriteria decision‐making technique including the DEMATEL technique have been used to express the solutions and identify the cause‐and‐effect relationships between the solutions. The criteria extracted in improving the quality of open government data and increasing the willingness of citizens to use the data are included: “data originality,” “license openness,” “up‐to‐datedness,” “data access,” “metadata completeness,” “number of data sets,” “format openness,” “nondiscrimination,” “understandable,” “number of categories of data sets,” “free,” “lack of missing data,” “data request ability,” “visualization,” “feedback,” and “data subject matter.” Based on the results obtained from the analysis of the complex network and the regression model, the criterion of “society subject” with a coefficient of 72.564 and a positive sign has the greatest impact on increasing the number of citizens' visits to open government data. After that, the criterion of “format openness” with a coefficient of 52.682 and a positive sign has the second rank in increasing the number of visits. Extracting comprehensive and effective criteria in improving the quality of open government data and increasing citizens' willingness to use data, calculating the weight and importance of each criterion by analyzing the complex network of citizens and organizations, as well as providing solutions, can help managers in decision‐making and proper management in the complex system of citizens and government organizations.

Government datasets are newly available on open data platforms that are publicly accessible, available in nonproprietary formats, free of charge, and with unlimited use and distribution rights. They provide opportunities for health research, but their quality and usability are unknown. To describe available open health data, identify whether data are presented in a way that is aligned with best practices and usable for researchers, and examine differences across platforms. Two reviewers systematically reviewed a random sample of data offerings on NYC OpenData (New York City, all offerings, n = 37), Health Data NY (New York State, 25% sample, n = 71), and HealthData.gov (US Department of Health and Human Services, 5% sample, n = 75), using a standard coding guide. Three open health data platforms at the federal, New York State, and New York City levels. Data characteristics from the coding guide were aggregated into summary indices for intrinsic data quality, contextual data quality, adherence to the Dublin Core metadata standards, and the 5-star open data deployment scheme. One quarter of the offerings were structured datasets; other presentation styles included charts (14.7%), documents describing data (12.0%), maps (10.9%), and query tools (7.7%). Health Data NY had higher intrinsic data quality (P < .001), contextual data quality (P < .001), and Dublin Core metadata standards adherence (P < .001). All met basic "web availability" open data standards; fewer met higher standards of "hyperlinked to other data." Although all platforms need improvement, they already provide readily available data for health research. Sustained effort on improving open data websites and metadata is necessary for ensuring researchers use these data, thereby increasing their research value.

ABSTRACTOver the last decade, a rapidly growing open data movement has resulted in government agencies quickly publishing a large volume of data, and the data's subsequent use among a variety of open data consumers. Understanding the activities, actors, technologies and factors enabling open data publication and use has been the subject of discussion among academic researchers and practitioners. However, research is limited, with few empirical studies on open data collecting primary research data from the health domain. To address this gap, we conducted 53 semi‐structured key informant interviews with participants in the open health data ecosystem in a variety of roles. Interview data were analyzed using a grounded theory approach to identify common themes and develop insights into the objectives, activities and desired outcomes of the open health data ecosystem. We found that data facilitators – data advocates, typically external to government agencies – are critical to this process by facilitating open data awareness and successful use. We applied activity theory to examine the facilitator theme and develop a preliminary model of the open health data ecosystem, including the roles, responsibilities and activities of different participants and the role of these facilitators. Our findings suggest that consumers' successful engagement with open health data is fostered by, and perhaps dependent upon, facilitators' activities. These empirically based insights into the structure and workings of the open health data engagement ecosystem can inform jurisdictions' development of open health data engagement strategies thereby improving the success of their open health data initiatives.

Nowadays, governments launch open government data (OGD) portals that provide data that can be accessed and used by everyone for their own needs. Although the potential economic value of open (government) data is assessed in millions and billions, not all open data are reused. Moreover, the open (government) data initiative as well as users’ intent for open (government) data are changing continuously and today, in line with IoT and smart city trends, real-time data and sensor-generated data have higher interest for users. These “smarter” open (government) data are also considered to be one of the crucial drivers for the sustainable economy, and might have an impact on information and communication technology (ICT) innovation and become a creativity bridge in developing a new ecosystem in Industry 4.0 and Society 5.0. The paper inspects OGD portals of 60 countries in order to understand the correspondence of their content to the Society 5.0 expectations. The paper provides a report on how much countries provide these data, focusing on some open (government) data success facilitating factors for both the portal in general and data sets of interest in particular. The presence of “smarter” data, their level of accessibility, availability, currency and timeliness, as well as support for users, are analyzed. The list of most competitive countries by data category are provided. This makes it possible to understand which OGD portals react to users’ needs, Industry 4.0 and Society 5.0 request the opening and updating of data for their further potential reuse, which is essential in the digital data-driven world.

Identifying patterns and recommendations of and for sustainable open data initiatives: A benchmarking-driven analysis of open government data initiatives among European countries

The development of ecosystems around open government data in order to generate social and economic value from them requires on one hand the existence of a critical mass of them and on the other hand some level of homogeneity and interoperability among the numerous portals and websites providing them which enables their combined exploitation. This paper presents the Technical, Semantic, Legal, and Organizational (TSLO) Interoperability Framework, a conceptual tool designed to provide a structured evaluation of the interoperability capabilities of open government data infrastructures. It incorporates the technical, semantic, legal, and organizational aspects of open government data provision, which are crucial for developing interoperability between open data portals and websites, which enables the generation of high levels of social and economic value from them, so it can pave the way for creating open data ecosystems for this purpose. We are then applying this TSLO framework to examine from this perspective the open data infrastructures of the Greek local government administration institutions of all three layers of it (decentralized, regional, and municipal). In particular, we examine the open government data portals and websites of the local Greek governments and provide a detailed analysis of them concerning the fore aspects of the framework. This first application of TSLO reveals not only the low participation of Greek local government institutions in the open data movement, and especially of the municipalities, where only 8 out of 332 municipalities provide open data on their portals or websites but also the inconsistent implementation of this, especially with respect to the use of semantic technologies as well as the legal frameworks under which the open data provided. Finally, we propose the automation of the TSLO framework to facilitate the evaluation and standardization of open local government data infrastructure and expand the study to identify and address barriers to open data provision.

Purpose The use of “open data” can help the public find value in various areas of interests. Many governments have created and published a huge amount of open data; however, people have a hard time using open data because of data quality issues. The UK, the USA and Korea have created and published open data; however, the rate of open data implementation and level of open data impact is very low because of data quality issues like incompatible data formats and incomplete data. This study aims to compare the statuses of data quality from open government sites in the UK, the USA and Korea and also present guidelines for publishing data format and enhancing data completeness. Design/methodology/approach This study uses statistical analysis of different data formats and examination of data completeness to explore key issues of data quality in open government data. Findings Findings show that the USA and the UK have published more than 50 per cent of open data in level one. Korea has published 52.8 per cent of data in level three. Level one data are not machine-readable; therefore, users have a hard time using them. The level one data are found in portable document format and hyper text markup language (HTML) and are locked up in documents; therefore, machines cannot extract out the data. Findings show that incomplete data are existing in all three governments’ open data. Originality/value Governments should investigate data incompleteness of all open data and correct incomplete data of the most used data. Governments can find the most used data easily by monitoring data sets that have been downloaded most frequently over a certain period.

While the economic benefit of open data is undeniable, its use as an asset in industrial processes is still a challenge. The lack of quality is indeed a typical argument for not leveraging open data. In fact, per the Data Office of the French government (ETALAB) in charge among others of the French open data initiative, only 9 out of the 34822 open datasets are tagged as reference datasets, that is supplied by certified publishers and which content can be reliable to be shared broadly, privately and publicly. Yet, no actual quality indicators are provided along with the metadata catalog of these 9 files.What would then be the appropriate indicators for open data quality assessment, how would they differ from those used to assess DQ of traditional enterprise data? How can they be measured knowing the multiple reusability scenarios and how can they help users choose the datasets that best fit the purpose?In this work-in-progress paper, we will answer these open data quality indicators questions and illustrate it with some case studies from the industry. KeywordsOpen data catalogLinked open dataReference dataOpen data quality indicatorsOpen meta data quality indicators

Open Government Data (OGD) is data produced or commissioned by the government, which can be publicly published. These data can be accessed freely by anyone, in order to increase public participation and enable government agencies to report their performance transparently. Indonesia is one of many countries that has been applying open government data concept, by establishing Open Government Indonesia (OGI). With the establishment of the OGI, many Indonesian government agencies have developed open government data. However, many of them have low data quality. One standard that can assess open government data quality is Five Star Open Data. This standard uses 5-step concept, with each data requires particular quality to achieve those steps. This paper proposed a solution to enhance the data quality of Indonesian government data and develop a data publishing tool. This data publishing tool accepts data with 2-star and 3-star quality and enhances the quality of input data to 5-star quality respectively. This tool also publishes the data and generates several types of data visualization according to the data. This tool uses data from Hasan Sadikin General Public Hospital (RSHS) as test data. Based on the evaluation conducted, this tool can enhance the data quality of five datasets, from 2-star to 5-star quality. In addition, the tool publishes the datasets and generates data visualization based on the datasets' contents.

Governments are rapidly developing open data platforms to improve transparency and make information more accessible. New York is a leader, with currently the only state platform devoted to health. Although these platforms could build public health departments' capabilities to serve more researchers, agencies have little guidance on releasing meaningful and usable data. Structured focus groups with researchers and practitioners collected stakeholder feedback on potential uses of open health data and New York's open data strategy. Researchers and practitioners attended a 1-day November 2013 workshop on New York State's open health data resources. After learning about the state's open data platform and vision for open health data, participants were organized into 7 focus groups to discuss the essential elements of open data sets, practical challenges to obtaining and using health data, and potential uses of open data. Participants included 33 quantitative health researchers from State University of New York campuses and private partners and 10 practitioners from the New York State Department of Health. There was low awareness of open data, with 67% of researchers reporting never using open data portals prior to the workshop. Participants were interested in data sets that were geocoded, longitudinal, or aggregated to small area granularity and capabilities to link multiple data sets. Multiple environmental conditions and barriers hinder their capacity to use health data for research. Although open data platforms cannot address all barriers, they provide multiple opportunities for public health research and practice, and participants were overall positive about the state's efforts to release open data. Open data are not ideal for some researchers because they do not contain individually identifiable data, indicating a need for tiered data release strategies. However, they do provide important new opportunities to facilitate research and foster collaborations among agencies, researchers, and practitioners.

The next step for our urban areas is to become friendly using open data. The focus of this paper is to highlight the necessity and the implementation of Open Government Data (OGD). It also presents the principles of Open Government Data. The paper aims to analyze the OGD solutions and the impact of these for urban development using a SWOT analysis. In our age OGD confers an important advantage in development economy. In this case everybody tries to implement efficient OGD.Keywords: Open Data, Open Government Data, Smart Cities, Friendly Cities, Knowledge EconomyIntroductionThe paper aims to analyze the impact and the role of open government data in our society and to highlight the trend of European countries in this case.The first part presents the literature review of the open data and open government data. Researchers worldwide are interested in improving governmental activity by implementing the latest innovations to the knowledge economy. The free exchange of ideas, information and knowledge is the support of development [14]. Open data is an essential element for knowledge economy. Knowledge economy emphasizes with lifelong learning, good quality of life and open government data.The second part highlights the opportunities and the changes that will be made in society after will implement an OGD solution. It is essential to the governmental and the citizens to use open data because this will offer independence, transparency, decentralization and, in the same time, aggregation.The third and the fourth part of the paper present the impact and the barriers of open government data. It is very important to highlight the benefits, disadvantages and barriers. These can be presented start from the most important cities how use this kind of solutions.In the fifth part is presented a classification of cities in three main categories based on the usage of open government data and a SWOT analysis about OGD solutions.The paper ends with the conclusion and the most important idea is: for development urban areas we have to use open government data.2 Literature ReviewThe literature review [1], [2], [3] highlight that a group inspired by open source software movements published version 1.0 of a statement they called the Open Knowledge Definition (OKF - Open Knowledge Foundation, 2006). This puts forward a definition of what it means to have open content, stating that: A piece of data or content is open if anyone is free to use, reuse, and redistribute it - subject only, at most, to the requirement to attribute and/or sharealike [6], [7], [8].In our age we can increasing the efficiency of public services and governmental activities by fast adopting the new technologies and the open data solutions.The most recent and important point of view is use of open data solutions is the Europe 2020 Strategy [18], [22], [23]. This strategy try to put the Europe's economy back on the path to growth.The Europe 2020 Strategy promotes the strategic objectives of a smart, sustainable and inclusive growth which are made further operational by a number of five headline targets for 2020 and by seven flagship initiatives.The Europe 2020 Strategy identifies five headlines that European Union should take to boost growth and employment. These are presented in Figure 1.The Europe 2020 Strategy has important direct implications for the future EU Cohesion Policy, because it develops - in fact - the same strategies for the period 2014- 2020. The Europe 2020 Strategy identifies seven flagship initiatives. These flagship initiatives [18], [23] are (Figure 2):· Innovation Union: the most important aspect is to improve framework conditions for better finance of research and innovation;· youth on the move : to reinforce the education systems and to improve the international view of Europe's higher education;· a digital agenda for Europe: the accent is put on the development of high-speed internet and to use the benefits of the one digital market;· resource efficient Europe: to use efficiently the resources for economic growth, increasing the use of renewable sources, improve and modernizing the transport sector and reduce of energy consume;· an industrial policy for the globalization era: the most important objectives are to improve the business environment and to development of a strong and sustainable industrial base able to compete globally. …

Governments and researchers traditionally focus on the publication of Open Government Data (OGD), whereas the actual use of the data is often neglected. Open data initiatives are often criticized for not realising the promoted benefits, yet only the use of OGD can result in these benefits. OGD use requires several actors, activities and tools; however, these are fragmented and depending on each other. The OGD infrastructure presented in this dissertation aims to enhance the coordination of OGD use. Core components are an advanced and interoperable three-tier metadata model to find, analyse, visualise, interact about and assess OGD, interaction mechanisms to stimulate interaction between OGD users, OGD providers and governmental policy makers, and data quality indicators to assess the data’s fitness for use. This study is among the first to describe the design of an OGD infrastructure. This dissertation contributes to science by providing a comprehensive overview of barriers and functional requirements for OGD use from the perspective of the OGD user, by defining functional building blocks for the design of the OGD infrastructure, and by developing and evaluating a prototype of the OGD infrastructure. Furthermore, this study is the first to apply coordination theory in the field of OGD and shows that coordination of OGD use does not merely require a focus on processes, but additionally requires a technical perspective including the integration of tools, a social perspective including interaction between involved actors, and the interaction between the social and technical perspective. Moreover, while OGD infrastructures traditionally mainly provide discovery metadata, this study confirms several recent studies that different types of metadata (discovery, contextual and detailed metadata) need to be combined to improve OGD use. Finally, whereas kernel theories concerning coordination, metadata, interaction and data quality are often studied separately, this study reveals that it is essential for the development of OGD infrastructures to combine these four kernel theories.

Open government data has become an important movement for government administrations in numerous countries. Previous studies have paid less attention to the complex relationship among the historical performance gap, the readiness of government (including policy and action dimensions), and open data quality. Therefore, on the basis of performance feedback theory, a theoretical model has been developed and tested to analyze the impact of the historical performance gap on the readiness of government and open data quality. The model is empirically tested by the partial least squares method using sample data from 115 countries. The results show that the historical performance gap could indirectly contribute to a country's open data quality by promoting the readiness of government. In addition, the impact of this gap on the readiness of government and open data quality shows a U-shaped curve. In other words, a greater change in the effect of open data utilization in a country in the previous year entails a more significant promotion of readiness of government and open data quality in the next year. These findings drive governments to pay more attention to performance evaluation in open data and improve the readiness of government to improve their respective country's open data quality.

Government support for disclosing open data to end users greatly expanding as part of the transparency policy. Although numerous studies have addressed open data portals and data quality, only some have analyzed the influence of organizational resources and administrative processes on open data quality. This issue is particularly relevant because access to and use of open data is believed to support social and economic development. The article analyses data dissemination tools, resources, processes, and leadership practices that can influence data quality. The study was conducted based on secondary information from a perception survey aimed at teams responsible for processing and disseminating datasets from Brazilian federal organizations. The study results reveal that dedicated organizational structures, support resources, administrative processes, and open data dissemination instruments influence open data quality. Leadership was not found to influence data quality. These conclusions interest public decision-makers and professionals involved in data dissemination that seek to stimulate economic development due to the impact that the resources and processes used for data dissemination have on data quality.