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18 results for “open government data”
User-centered Usability Analysis of 41 Open Government Data Portals
<p>The data were collected during the user-centered analysis of usability of 41 open government data portals including EU27, applying a common methodology to them, considering aspects such as specification of open data set, feedback and requests, further broken down into 14 sub-criteria. Each aspect was assessed using a three-level Likert scale (fulfilled - 3, partially fulfilled - 2, and unfulfilled – 1), that belongs to the acceptability tasks. This dataset summarises a total of 1640 protocols obtained during the analysis of the selected portals carried out by 40 participants, who were selected on a voluntary basis. This is complemented with 4 summaries of these protocols, which include calculated average scores by category, aspect and country. These data allow comparative analysis of the national open data portals, help to find the key challenges that can negatively impact users’ experience, and identifies portals that can be considered as an example for the less successful open data portals.</p>
An Integrated Usability Framework for Evaluating Open Government Data Portals and Analysis of EU and GCC OGD Portals
<p><span>This dataset contains data collected during a study (<em><strong>"<a href="https://arxiv.org/ftp/arxiv/papers/2403/2403.08451.pdf">An Integrated Usability Framework for Evaluating Open Government Data Portals: Comparative Analysis of EU and GCC Countries</a>"</strong></em>) conducted by Fillip Molodtsov and Anastasija Nikiforova (University of Tartu).</span></p> <p><span> </span><span>It being made public both to act as supplementary data for the paper and in order for other researchers to use these data in their own work potentially contributing to the improvement of current data ecosystems and develop user-friendly, collaborative, robust, and sustainable open data portals.</span></p> <p><span>***Purpose of the study***</span></p> <p><span>This paper develops an integrated framework for evaluating OGD portal effectiveness that accommodates user diversity (regardless of their data literacy and language), evaluates collaboration and participation, and the ability of users to explore and understand the data provided through them. </span></p> <p><span>The framework is validated by applying it to 33 national portals across European Union (EU) and Gulf Cooperation Council (GCC) countries, as a result of which we rank OGD portals, identify some good practices that lower-performing portals can learn from, and common shortcomings.</span></p> <p><span>***Methodology***</span></p> <p><span>(1) systematic literature review to establish a knowledge base and identify frameworks have been used to evaluate OGD portals, we conducted a systematic literature review - Dataset_ Usability_Framework_SLR;</span></p> <p><span>(2) development of the Integrated Usability Framework for Evaluating Open Government Data Portals, which content is based on the outputs of the first step, along with selected articles of experts in portal design, and an exploratory assessment of the French, Irish, Estonian and Spanish portals - Dataset_Integrated_Usability_Framework;</span></p> <p><span>(3) data collection, that is a completion of the protocol developed in the previous step by analysing 34 national OGD portals of the EU and GCC countries. When all individual protocols were collected, the total score are calculated using the weighting system. The average scores are calculated for the EU and GCC. The portals are ranked. The top portals (best performers) are determined for each dimension - Dataset_EU_GCC_OGDportal_Usability_results_clustering.</span></p> <p><span>(4) identification of relationships and patterns among different portals based on their performance metrics as a result of the cluster analysis. By calculating the average dimensional scores of portals from both types of clusters, their performance across multiple dimensions is evaluated - Dataset_EU_GCC_OGDportal_Usability_results_clustering.</span></p> <p> </p> <p><strong><em><span>For more details see Molodtsov, F., Nikiforova, A. (2024). “An Integrated Usability Framework for Evaluating Open Government Data Portals: Comparative Analysis of EU and GCC Countries”. In Proceedings of the 25th Annual International Conference on Digital Government Research (DGO 2024), June 11--14, 2024, Taipei, Taiwan, 10.1145/3657054.3657159</span></em></strong></p> <p><span>***Format of the file***</span></p> <p><span>.xls, .csv</span></p> <p><span>***Licenses or restrictions***</span></p> <p><span>CC-BY</span></p>
Smarter open government data for Society 5.0: analysis of 51 OGD portals
<p>This dataset contains data collected during a study <a href="https://doi.org/10.3390/s21155204">"Smarter open government data for Society 5.0: are your open data smart enough"</a> (<em>Sensors</em>. 2021; 21(15):5204) conducted by Anastasija Nikiforova (University of Latvia).<br> It being made public both to act as supplementary data for "Smarter open government data for Society 5.0: are your open data smart enough" paper and in order for other researchers to use these data in their own work.</p> <p>The data in this dataset were collected in the result of the inspection of 60 countries and their OGD portals (total of 51 OGD portal in May 2021) to find out whether they meet the trends of Society 5.0 and Industry 4.0 obtained by conducting an analysis of relevant OGD portals.</p> <p>Each portal has been studied starting with a search for a data set of interest, i.e. “real-time”, “sensor” and “covid-19”, follwing by asking a list of additional questions.<br> These questions were formulated on the basis of combination of (1) crucial open (government) data-related aspects, including open data principles, success factors, recent studies on the topic, PSI Directive etc., (2) trends and features of Society 5.0 and Industry 4.0, (3) elements of the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use Model (UTAUT).</p> <p>The method used belongs to typical / daily tasks of open data portals sometimes called “usability test” – keywords related to a research question are used to filter data sets, i.e. “real-time”, “real time” and “real time”, “sensor”, covid”, “covid-19”, “corona”, “coronavirus”, “virus”. In most cases, “real-time”, “sensor” and “covid” keywords were sufficient.<br> The examination of the respective aspects for less user-friendly portals was adapted to particular case based on the portal or data set specifics, by checking:<br> 1. are the open data related to the topic under question ({sensor; real-time; Covid-19}) published, i.e. available?<br> 2. are these data available in a machine-readable format?<br> 3. are these data current, i.e. regularly updated? Where the criteria on the currency depends on the nature of data, i.e. Covid-19 data on the number of cases per day is expected to be updated daily, which won’t be sufficient for real-time data as the title supposes etc.<br> 4. is API ensured for these data? having most importance for real-time and sensor data;<br> 5. have they been published in a timely manner? which was verified mainly for Covid-19 related data. The timeliness is assessed by comparing the dates of the first case identified in a given country and the first release of open data on this topic.<br> 6. what is the total number of available data sets?<br> 7. does the open government data portal provides use-cases / showcases? <br> 8. does the open government portal provide an opportunity to gain insight into the popularity of the data, i.e. does the portal provide statistics of this nature, such as the number of views, downloads, reuses, rating etc.?<br> 9. is there an opportunity to provide a feedback, comment, suggestion or complaint?<br> 10. (9a) is the artifact, i.e. feedback, comment, suggestion or complaint, visible to other users?</p> <p>***Format of the file***<br> .xls, .ods, .csv (for the first spreadsheet only)</p> <p>***Licenses or restrictions***<br> CC-BY</p> <p>For more info, see README.txt</p>
Identifying patterns and recommendations of and for sustainable open data initiatives: a benchmarking-driven analysis of open government data initiatives among European countries
<p>This dataset contains data collected during a study <a href="https://www.sciencedirect.com/science/article/pii/S0740624X23000989"><em><strong>"Identifying patterns and recommendations of and for sustainable open data initiatives: a benchmarking-driven analysis of open government data initiatives among European countries"</strong></em></a> conducted by <em>Martin Lnenicka (University of Pardubice, Pardubice, Czech Republic), Anastasija Nikiforova (University of Tartu, Tartu, Estonia), Mariusz Luterek (University of Warsaw, Warsaw, Poland), Petar Milic (University of Pristina - Kosovska Mitrovica, Kosovska Mitrovica, Serbia), Daniel Rudmark (University of Gothenburg and RISE Research Institutes of Sweden, Gothenburg, Sweden), Sebastian Neumaier (St. Pölten University of Applied Sciences, Austria), Caterina Santoro (KU Leuven, Leuven, Belgium), Cesar Casiano Flores (University of Twente, Twente, the Netherlands), Marijn Janssen (Delft University of Technology, Delft, the Netherlands), Manuel Pedro Rodríguez Bolívar (University of Granada, Granada, Spain).</em></p> <p>It is being made public both to act as supplementary data for "<em>Identifying patterns and recommendations of and for sustainable open data initiatives: a benchmarking-driven analysis of open government data initiatives among European countries</em>", Government Information Quarterly*, and in order for other researchers to use these data in their own work. </p> <p>***Methodology***</p> <p>The paper focuses on benchmarking of open data initiatives over the years and attempts to identify patterns observed among European countries that could lead to disparities in the development, growth, and sustainability of open data ecosystems. </p> <p>This study examines existing benchmarks, indices, and rankings of open (government) data initiatives to find the contexts by which these initiatives are shaped, both of which then outline a protocol to determine the patterns. The composite benchmarks-driven analytical protocol is used as an instrument to examine the understanding, effects, and expert opinions concerning the development patterns and current state of open data ecosystems implemented in eight European countries - Austria, Belgium, Czech Republic, Italy, Latvia, Poland, Serbia, Sweden. 3-round Delphi method is applied to identify, reach a consensus, and validate the observed development patterns and their effects that could lead to disparities and divides. Specifically, this study conducts a comparative analysis of different patterns of open (government) data initiatives and their effects in the eight selected countries using six open data benchmarks, two e-government reports (57 editions in total), and other relevant resources, covering the period of 2013–2022.</p> <p>***Description of the data in this data set***</p> <p>The file "OpenDataIndex_<em>2013_</em>2022" collects an overview of 27 editions of 6 open data indices - for all countries they cover, providing respective ranks and values for these countries. These indices are:</p> <p>1) Global Open Data Index (GODI) (4 editions)</p> <p>2) Open Data Maturity Report (ODMR) (8 editions)</p> <p>3) Open Data Inventory (ODIN) (6 editions)</p> <p>4) Open Data Barometer (ODB) (5 editions)</p> <p>5) Open, Useful and Re-usable data (OURdata) Index (3 editions)</p> <p>6) Open Government Development Index (OGDI) (2 editions)</p> <p>These data shapes the third context - open data indices and rankings. The second sheet of this file covers countries covered by this study, namely, Austria, Belgium, Czech Republic, Italy, Latvia, Poland, Serbia, Sweden. It serves the basis for Section 4.2 of the paper.</p> <p>Based on the analysis of selected countries, incl. the analysis of their specifics and performance over the years in the indices and benchmarks, covering 57 editions of OGD-oriented reports and indices and e-government-related reports (2013-2022) that shaped a protocol (see paper, Annex 1), 102 patterns that may lead to disparities and divides in the development and benchmarking of ODEs were identified, which after the assessment by expert panel were reduced to a final number of 94 patterns representing four contexts, from which the recommendations defined in the paper were obtained. These patterns are available in the file "OGDdevelopmentPatterns". The first sheet contains the list of patterns, while the second sheet - the list of patterns and their effect as assessed by expert panel.</p> <p>***Format of the file***<br>.xls, .csv (for the first spreadsheet only)</p> <p>***Licenses or restrictions***<br>CC-BY</p> <p> </p> <p>For more info, see README.txt<br> </p>
Data for: Open Infrastructure Governance: Current structures, nomenclature, composition, and service trends, 2024 State of Open Infrastructure Report
<p>The purpose of the analysis based on these data was to<span> record information about community governance groups for open infrastructures, focused primarily on the individuals and institutions that serve in these groups. The data were summarized and reported in the “2024 State of Open Infrastructure Report” section “Open infrastructure governance: Current structures, nomenclature, composition, and trends.” The full report is available at <a href="The%20data%20were%20summarized%20and%20reported%20in%20the%20&ldquo;2024%20State%20of%20Open%20Infrastructure%20Report&rdquo;%20section%20&ldquo;Open%20infrastructure%20governance:%20Current%20structures,%20nomenclature,%20composition,%20and%20trends,&rdquo;%20available%20at%20https:/doi.org/10.5281/zenodo.10934089.">https://doi.org/10.5281/zenodo.10934089</a>.</span></p> <p><span>A readme is provided with the dataset with additional detail.</span></p>
Resource Metadata Harvested from Government and Research Open Data Portals
<p>This dataset consists of resource metadata harvested from the APIs of hundreds of government and research data portals from all over the world. This dataset was harvested between the 13<sup>th</sup> and 15<sup>th</sup> of September 2018. The metadata harvested from these portals was translated to a single metadata format (see <em>metadata_format.odt</em>). An overview of all harvested domains is given in <em>portal_list.txt</em>.</p> <p>The harvested data is divided into five gzipped json-lines files, based on the ‘type’ of the resource that is derived from the data of the APIs:</p> <ul> <li><em>dataset_metadata.jsonl.gz</em>: Resources classified as a Dataset, or subsets of dataset (e.g. Dataset:Image and Dataset:Audio) [6 246 250 resources]</li> <li><em>document_metadata.jsonl.gz</em>: Resources classified as a Document, or subset of document (e.g. Document:Paper:Conference and Document:Book) [15 626 541 resources]</li> <li><em>software_metadata.jsonl.gz</em>: Resources classified as Sofware (including Software:Model) [42 036 resources]</li> <li><em>service_metadata.jsonl.gz</em>: Resources classified as a service (e.g. WMS, APIs) [1257 resources]</li> <li><em>other_metadata.jsonl.gz</em>: Resources of which the ‘type’ could not be determined from the data the API returned. This set still contains many datasets [1 502 979 resources]</li> </ul>
Integrated Statistical Indicators from Scottish Linked Open Government Data
<p>Integrated statistical indicators that were retrieved from the official Scottish data portal in order to facilitate the exploitation of Machine Learning methods in Open Government Data. Data include 60 statistical indicators from seven categories such as health and social care, housing, and crime and justice. The indicators refer to the 6,976 “2011 data zones” of Scotland, while the year of reference is 2015. Data are ready to be used by the research community, students, policy makers, and journalists and give rise to plenty of social, business, and research scenarios that can be solved using Machine Learning technologies and methods.</p>
(open) data literacy as barrier and enabler of open government data enhancement. A systematic review of the literature.
<p>This systematic review of the literatu was conducted with the PRISMA method, to explore the contexts in which the use of open government data germinates, identifying barriers to its use and identifying, the role of data literacy among those barriers to use; and the role of open data in promoting informal learning that supports the development of critical data literacy. This file includes a codebook of the main characteristics that were studied in a systematic literature review, where data from 66 articles related to Open Data Usage were identified and coded. Also, the file includes an analysis of Cohen's Kappa, a concordance statistic used to measure the level of agreement among researchers in classifying articles on the characteristics defined in the Codebook. Finally, it includes main tables of the results' analysis.</p>
Open Government Data Corpus for Table Search
<p>Increasing amounts of structured data can provide value for research and business if the relevant data can be located. Often the data is in a data lake without a consistent schema, making locating useful data challenging. Table search is a growing research area, but existing benchmarks have been limited to displayed tables. Tables sized and formatted for display in a Wikipedia page or ArXiv paper are considerably different from data tables in both scale and style. By using metadata associated with open data from government portals, we create the first dataset to benchmark search over data tables at scale. We demonstrate three styles of table-to-table related table search. The three notions of table relatedness are: tables produced by the same organization, tables distributed as part of the same dataset, and tables with a high degree of overlap in the annotated tags. The keyword tags provided with the metadata also permit the automatic creation of a keyword search over tables benchmark. We provide baselines on this dataset using existing methods including traditional and neural approaches. </p>
Additional data to the article "Educational Open Government Data in Germany"
<p>This dataset contains the raw data of the quantitative evaluation of German open government portals, conducted in March 2020 as well as the questions to the interviews we conducted with researchers from educational research.</p>
Supporting data for Open government data for regulation of energy resources in India
<p>This dataset contains supporting tables from the paper "Open government data for regulation of energy resources in India" published as part of the Exploring the Emerging Impacts of Open Data in Developing Countries project.</p> <p>Contextual information on each table is provided in the associated report.</p>
Data underlying research paper: Exploring Governance Modes in Open Data Initiatives: Insights from France and Ireland
<p><span><span>The folder </span><span>contains</span> <span>the interview questions</span> <span>of</span><span> the research paper “</span></span><span><span>Exploring Governance Modes in Open Data Initiatives: I</span></span><span><span>nsights</span><span> from France and Ireland</span></span><span><span>” and consists of the interview questions. </span></span><span> </span></p> <div> <p><strong><span><span>Note about the interview </span><span>and the interview </span><span>questions:</span></span><span> </span></strong></p> </div> <div> <p><span><span>The </span><span>semi-structured </span><span>interviews were conducted with </span><span>(three) </span><span>experts selected through purposive</span> <span>sampling combined with snowballing approach to gain knowledge from</span> <span>key people who actively worked in the coordination bodies in France and Ireland. In</span> <span>the case of France, the first interviewee was reached following the reading of a blogpost</span> <span>on the governance of open data during the Covid-19 crisis. The first interviewee</span> <span>allowed the identification of a second expert who could complement his knowledge on</span> <span>the governance of the open data in France. In the case of Ireland, the expert was</span> <span>identified through the reading of an academic article that explained in great details the</span> <span>unfolding of the events that led to the Covid-19 open data strategy in Ireland. All</span> <span>the interviewees were approached through email exchange. Interviews took place in</span> <span>August 2022 online through the Microsoft Teams and Webinaire de l’État platforms,</span> <span>each lasting approximately forty-five minutes.</span></span><span> </span></p> <p><strong><span>Acknowledgment:</span></strong></p> </div> <p><span>This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 955569. The opinions expressed in this document reflect only the author’s view and in no way reflect the European Commission’s opinions. The European Commission is not responsible for any use that may be made of the information it contains.</span></p>
Open Government Data des Bundes auf GovData
<p>Datensatz zu Auswertung der durch Stellen des Bundes auf dem Open-Data-Portal GovData (www.govdata.de) veröffentlichten Datensätze. Auswertung in:</p> <p>Herfurth, Anne; Lange, Felix: Transparenz bewahren. Open Government Data im Bundesarchiv. In: Becker, Irmgard Ch. u.a. [Hrsg.]: Born digital – neue Archivaliengattungen und ihre Bearbeitung im Archiv. Beiträge zum 28. Archivwissenschaftlichen Kolloquium der Archivschule Marburg. Veröffentlichungen der Archivschule Marburg, Nr. 72. Hochschule für Archivwissenschaft, 2025. S. 331-355.</p> <p>S.a. https://www.archivschule.de/DE/forschung/archivwissenschaftliche-kolloquien/28-archivwissenschaftliches-kolloquiumganz.html</p>
Factors influencing open government data post-adoption in the public sector: The perspective of data providers
Providing access to non-confidential government data to the public is one of the initiatives adopted by many governments today to embrace government transparency practices. The initiative of publishing non-confidential government data for the public to use and re-use without restrictions is known as Open Government Data (OGD). Nevertheless, after several years after its inception, the direction of OGD implementation remains uncertain. The extant literature on OGD adoption concentrates primarily on identifying factors influencing adoption decisions. Yet, studies on the underlying factors influencing OGD after the adoption phase are scarce. Based on these issues, this study investigated the post-adoption of OGD in the public sector, particularly the data provider agencies. The OGD post-adoption framework is crafted by anchoring the Technology–Organization–Environment (TOE) framework and the innovation adoption process theory. The data was collected from 266 government agencies in the Malaysian public sector. This study employed the partial least square-structural equation modeling as the statistical technique for factor analysis. The results indicate that two factors from the organizational context (top management support, organizational culture) and two from the technological context (complexity, relative advantage) have a significant contribution to the post-adoption of OGD in the public sector. The contribution of this study is threefold: theoretical, conceptual, and practical. This study contributed theoretically by introducing the post-adoption framework of OGD that comprises the acceptance, routinization, and infusion stages. As the majority of OGD adoption studies conclude their analysis at the adoption (decisions) phase, this study gives novel insight to extend the analysis into unexplored territory, specifically the post-adoption phase. Conceptually, this study presents two new factors in the environmental context to be explored in the OGD adoption study, namely, the data demand and incentives. The fact that data providers are not influenced by data requests from the agency's external environment and incentive offerings is something that needs further investigation. In practicality, the findings of this study are anticipated to assist policymakers in strategizing for long-term OGD implementation from the data provider's perspective. This effort is crucial to ensure that the OGD initiatives will be incorporated into the public sector's service thrust and become one of the digital government services provided to the citizen.
Analysing the Characteristics of Open Government Data Portals in Croatia
<p>Open government data (OGD) paradigm gained momentum in the recent years resulting in numerous OGD initiatives. These initiatives assured reliable and faster development of open data ecosystem on different administration levels. Diversity of government organizations dealing with different kinds of data, however, resulted in a variety of OGD initiatives. As a direct result, OGD portals developed through these initiatives show different functionalities, characteristics, and quality of provided data and services. This paper therefore aims to provide a better insight into the similarities and differences of data portals by analyzing their characteristics from thematical, semantical, functional, and technological perspective. The methodology used relies on the framework previously developed and implemented in Greece in 2015, consisting of multiple indicators assessing different characteristics of portals, in each of four perspectives. Results of the assessment show Croatian portals have well developed functionalities but also have limitations preventing data reuse. These limitations are mostly related to data discovery and absence of metadata and licenses by the publishing institutions.</p>
Associated data underlying the article "OPEN GOVERNMENT DATA (OGD) IN EUROPEAN EDUCATIONAL PROGRAMS CURRICULUM CURRENT STATE AND PROSPECTS"
<p>Associated data underlying the article</p> <p>Rizun, Nina; Ciesielska, Magdalena; Alexopoulos, Charalampos; Saxena,Stuti; Papageorgiou, Georgios International Conference on Open Data (ICOD 2022): Book of abstracts, Faculty of Law, University of Zagreb, Zagreb, Croatia, pp. 26-29 (978-953-270-167-8).</p> <pre><a href="https://doi.org/10.5281/zenodo.8069910">https://doi.org/10.5281/zenodo.8069910</a></pre> <p>It is everybody’s knowledge now that Open Government Data (OGD) pertains to the availability of datasets pertaining to government operations and functioning via license-free formats (Afful-Dadzie and Afful-Dadzie, 2017) and these datasets are linked with different themes contingent upon the area of administration like energy, education, climate, tourism, environment, infrastructure, etc. (Ubaldi, 2013). Governments have been benchmarking their OGD initiatives across standard indices like ODIN, OKFN, Open Data Barometer, etc. (Lnenicka et al., 2022; Lnenicka and Nikiforova, 2021) and ample research exists on assessing the quality of OGD portals from the demand (i.e. the governments’ efforts at maintaining the quality of datasets) and supply (i.e. the perceptions of users regarding the quality of datasets) side (Crusoe et al., 2019; de Souza et al., 2022; Islam et al., 2021; Kaasenbrood et al., 2015; Khurshid et al., 2022; Lnenicka et al., 2022; Purwanto et al., 2020; Saxena and Janssen, 2017; Shehata and Elgllab, 2021; Talukder et al., 2019; Weerakkody et al., 2017; Wirtz et al., 2016; Wirtz et al., 2018; Wirtz et al., 2019; Zuiderwijk et al., 2015). Given the magnitude of academic interest on OGD- especially in the last 10 years- it remains to be assessed as to how far has the domain progressed in the academic environs and surprisingly, no research has been conducted to elucidate the infusion of this very significant domain- that is relatable to the extent to which the governments are forwarding their claims regarding the furtherance of transparent and corruption-free administration apart from bolstering citizen participation, collaboration and trust (Gil-Garcia et al., 2020; Hellberg and Hedstrom, 2015) besides serving as a means for value creation and innovation by a range of stakeholders (Jetzek et al., 2012; Jetzek et al., 2014) - in the diverse platforms that are meant for furthering academic dialogue and discussion.</p>
Factors influencing open government data post-adoption in the public sector: The perspective of data providers
Open the record for dataset details and reuse information.
Open government data and big data from a quality perspective
<p>This dataset contains information about the documents and the analysis categories related to open government data and big data from a quality perspective.</p>
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OpenNeuro
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