Open Data Usage Research Articles

Open government data initiatives as agents of digital transformation in the public sector: Exploring the extent of use among early adopters

Open government data initiatives are important agents of public sector digital transformation and understanding how agencies design, implement, and evaluate strategies for these initiatives is paramount to their ongoing success. However, a challenging and little understood aspect of open government data initiatives is precisely how open data users engage with and use these vital resources. This study examines the extent of open dataset use among early adopters using a cross-sectional analysis of web analytic behavioral data. We quantify early users' extent of use of open datasets from Health Data NY, the first state-level open health data platform. Results of a PLS-SEM analysis provide new empirical evidence that prior, or initial levels of open dataset use positively influence the later extent of open dataset use. Further, prior open government data use influences not only the later variety of open data activities, but also their depth of sophistication. Implications for practice include open data strategies to facilitate deeper, more extensive use of open dataset resources that lead to increased value creation, and ultimately, more effective digital transformation. Theoretically, this study contributes to the body of research on the Unified Theory of Acceptance and Use of Technology (UTAUT) by empirically testing its Use Behavior construct in light of early open data users' extent of use of open datasets, thus providing a more refined understanding of open data use behavior.

A Comparative Study of Digital City Development Using the Data-Driven Smart City Index

This research compares and contrasts the evolution of smart cities using a comparative analysis based on the Data-Driven Smart City Index. The study includes four important tables: the Digital City Development Index, which shows City D as a model smart city because of its high Infrastructure, Data Utilization, and Connectivity Scores, offers a thorough summary of the development of smart cities. The three components of the Data-Driven Smart City Index are Environmental Sustainability, Governance, and Quality of Life. City D excels in all three areas. The importance of big data analytics, IoT adoption, and open data usage—all of which City D leads—is emphasized in Data Utilization in Digital City Development. Lastly, Connectivity Infrastructure in Digital Cities emphasizes the significance of cutting-edge technology, with City D leading the way in terms of availability of public Wi-Fi, 5G network connectivity, and fiber broadband coverage. These results provide insightful information that will help stakeholders, politicians, and urban planners advance cities into the digital age and improve the quality of life for citizens.

Knowledge and usage of open data in Colombia

Knowledge and usage of open data in Colombia

A Systematic Analysis of Problems in Open Collaborative Data Engineering

Collaborative workflows are common in open-source software development. They reduce individual costs and improve the quality of work results. Open data shares many characteristics with open-source software, as it can be used, modified, and redistributed by anyone, for free. However, in contrast to open-source software engineering, collaborative data engineering on open data lacks a shared understanding of processes, methods, and tools. This article presents a systematic literature review of collaboration processes, methods, and tools in data engineering as performed by open data users. An additional interview study with practitioners confirms and enhances the findings and strengthens the resulting insights. We find an ecosystem with heterogeneous participants and no standardized processes, methods, and tools. Participants face a variety of technical and social challenges during their work. Our work provides a structured overview of collaboration systems in open collaborative data engineering, enabling further research. Additionally, we contribute preliminary guidelines for successful open collaborative data engineering projects and recommendations to increase its adoption for open data ecosystems.

Challenges and prospects in big data analytics: a comprehensive review of developments, hurdles, and future research directions

Big data and business analytics are trends that are positively affecting the business world. This comprehensive review article explores the shifting paradigms and dynamic trends within Big Data Technology (BDT), predominantly for last 5 years, based on an extensive literature review and comparative analysis methodology. It elucidates the transformative influence of big data analytics (BDA) in various sectors, emphasizing the rapid ascendance of cloud computing, Artificial Intelligence (AI) integration, and development of sophisticated analytics tools. The review leverages a wealth of academic literature and market research to underscore the predicted expansion of the big data market. This projected growth indicates the widespread adoption of BDT across industries, with healthcare becoming a significant consumer, motivated by the demand for personalized medicine and improved patient care. The review then navigates emerging trends such as open data usage and ethical concerns surrounding big data, indicating the increasing necessity for stringent guidelines for data use and robust individual data control mechanisms. This is derived from a methodical analysis of recent scholarly articles and industry reports. The article also scrutinizes the evolving definition of "big data" through comparative study of the 3V model and the expanded 7V model in various literature sources, reflecting the evolving nature of data and the unique challenges introduced by modern big data analytics. The review also outlines the challenges for successful implementation of big data projects and highlights the current open research directions of big data analytics. The reviewed areas of big data suggest that good management and manipulation of the large data sets using the techniques and tools of big data can deliver actionable insights that create business values.

Using open data to analyse potential shelter for Semeru Volcano hazard mitigation, East Java Province, Indonesia

This paper analyses the usage of open data for planning shelters related to the volcanic hazard posed by Semeru Volcano, Lumajang Regency. The methodology involved open data collecton, spatial data creation and spatial analysis to determine a potential shelter location. Shelter related to Semeru Volcano eruption is based at schools and religious facilities. There are 627 schools, of which 612 (97.61%) are located outside the Semeru Volcano disaster hazard-prone area. There are also 649 religious facilities, of which 622 (95.8%) are located outside the hazard-prone area. Only 48 schools (7.84%) and 36 religious facilities (5.79%) are located within 20 meters of a main road. Others are located within 20-100 meters from a main road or even further. Of the total 48 schools located within 25 meters of a main road, 26 (54.17%) are less than 1 km from health facilities, while ten schools (20.83%) are located 1-2 kilometers away from health facilities. Meanwhile, of the 36 religious facilities located within 25 meters of the main road, only 13 (3.12%) are located less than 1 km away from health facilities, and ten religious facilities (27.76%) are located 1-2 kilometers from health facilities.

Open data: an innovative learning resource for postgraduates

PurposeWith the continuous development of the global COVID-19 epidemic, mobile learning has become one of the most significant learning approaches. The mobile learning resource is the basis of mobile learning; it may directly affect the effectiveness of mobile learning. However, the current learning resources cannot meet users' needs. This study aims to analyze the influencing factors of accepting open data as learning resources among users.Design/methodology/approachBased on the technology acceptance model (TAM) and the unified theory of acceptance and use of technology (UTAUT), this study proposed a comprehensive theoretical research model. Data were obtained from 398 postgraduates from several universities in central China. Confirmatory factor analysis was used to determine the reliability and validity of the measurement model. Data has been analyzed using SPSS and AMOS software.FindingsThe results suggested that perceived usefulness, performance expectancy, social influence and facilitating conditions have a positive influence on accepting open data as learning resources. Perceived ease of use was not found significant. Moreover, it was further shown in the study that behavioural intention significantly influenced the acceptance of open data as learning resources.Originality/valueThere is a lack of research on open data as learning resources in developing countries, especially in China. This study addresses the gap and helps us understand the acceptance of open data as learning resources in higher education. This study also pays attention to postgraduates' choice of learning resources, which has been little noticed before. Additionally, this study offers opportunities for further studies on the continuous usage of open data in higher education.

Quality Assessment and Biases in Reused Data

This article investigates digital and non-digital traces reused beyond the context of creation. A central idea of this article is that no (reused) dataset is perfect. Therefore, data quality assessment becomes essential to determine if a given dataset is “good enough” to be used to fulfill the users’ goals. Biases, a possible source of discrimination, have become a relevant data challenge. Consequently, it is appropriate to analyze whether quality assessment indicators provide information on potential biases in the dataset. We use examples representing two opposing sides regarding data access to reflect on the relationship between quality and bias. First, the European Union open data portal fosters the democratization of data and expects users to manipulate the databases directly to perform their analyses. Second, online behavioral advertising systems offer individualized promotional services but do not share the datasets supporting their design. Quality assessment is socially constructed, as there is not a universal definition but a set of quality dimensions, which might change for each professional context. From the users’ perspective, trust/credibility stands out as a relevant quality dimension in the two analyzed cases. Results show that quality indicators (whatever they are) provide limited information on potential biases. We suggest that data literacy is most needed among both open data users and clients of behavioral advertising systems. Notably, users must (be able to) understand the limitations of datasets for an optimal and bias-free interpretation of results and decision-making.

Do open data impact citizens’ behavior? Assessing face mask panic buying behaviors during the Covid-19 pandemic

Data are essential for digital solutions and supporting citizens’ everyday behavior. Open data initiatives have expanded worldwide in the last decades, yet investigating the actual usage of open data and evaluating their impacts are insufficient. Thus, in this paper, we examine an exemplary use case of open data during the early stage of the Covid-19 pandemic and assess its impacts on citizens. Based on quasi-experimental methods, the study found that publishing local stores’ real-time face mask stock levels as open data may have influenced people’s purchase behaviors. Results indicate a reduced panic buying behavior as a consequence of the openly accessible information in the form of an online mask map. Furthermore, the results also suggested that such open-data-based countermeasures did not equally impact every citizen and rather varied among socioeconomic conditions, in particular the education level.

Application of Open Data in Disaster Risk Research: A Preliminary Review Using Bibliometric Analysis

Open data is a practical source for identifying disaster risks. However, few studies have examined open data usage. This study employed CiteSpace to conduct a bibliometric analysis to determine the evolution of open data in the field of disaster risk based on the literature. The findings were as follows: first, the existing disaster-related research can be classified into four categories: introduction to risk management and its concepts, multi-hazard response, studies on the specific background or context, and analysis of the technology or methods used in disaster risk reduction. Second, the relevant literature first emerged in 1997 and has rapidly expanded in recent years. Top keywords were identified, such as “natural disaster,” “risk,” and “climate change.” Third, the most productive country in terms of publications has been the People’s Republic of China; however, the low centrality indicates a lack of international collaborations. Fourth, several bursts were found in the collected literature. The term “data analysis” appears to be one of the most pressing concerns. Finally, we identified the research frontiers. The topic “accessible global dataset” has been of primary interest to researchers recently. The results of this study can provide directional references for future research in the field.

What Else Is New? Open Data Users Need to Know What’s Changed

What Else Is New? Open Data Users Need to Know What’s Changed

Saudi scholars’ perceptions and use of open government data portals at Shaqra University, Saudi Arabia

This article reports the findings of a study on open data usage among Saudi scholars. It investigates the sample’s perceptions of open data and open data portals. The study reported the factors affecting the participants’ decision to use open data and aimed to understand Saudi researchers’ practices and perceptions related to the use and sharing of open data. It adopted a quantitative approach and a questionnaire was distributed to and collected from 190 Saudi academic staff to measure their perceptions, their open data usage, the benefits of open data, and the factors that significantly impacted their open data utilization. The findings reveal that 42.1% of Saudi researchers used government open data portals and regularly visited open data portals provided by the university and the government mainly for research purposes. The results also indicate that open data portals enabled Saudi researchers to obtain useful data for their research while giving them the tools to visualize and understand the data.

Public Sector Information and Open Data: A Focus on Sweden

Good governance and inclusive development require governments to make their information flows accessible to all citizens. The United Nations Sustainable Development Goal 16 advocates the promotion of peaceful and inclusive societies, with the emphasis being placed on access to government information. Apart from this Sustainable Development Goal, globally, several open-data initiatives and advocates of freedom of information are pushing governments to open up their data flows. Open data are seen as a driver of public service innovation that generates new knowledge and enables the creation of new electronic services. The narrative about open data assumes that the data are within reach of the citizens to explore and to develop new electronic services based on, for example, statistical, mobility, meteorological, judicial and court data to boost national innovation. However, research shows the contrary that open data are still concentrated in the hands of a few people such as politicians, journalists, system developers and data miners. This raises questions about the openness of the data. In Sweden, most of the interactions that citizens have are with the municipalities because they offer a broad range of public services. This is why the researcher argues that to promote awareness and open data usage by ordinary citizens, the Swedish government should work with the municipalities to create platforms for the exploitation of the data and to facilitate the development of technical expertise. If open data are to be inclusive, the data will require the involvement of citizens in the current open-data developments.

Extension agents perception of open data usage in agricultural communication in Abia State

The study assessed agricultural extension agent’s perception of open data usage in agricultural communication in Abia State. Simple random sampling technique was used to select 83 extension agents for the study. Data for the study was collected with the use of questionnaire and described with frequency counts, percentages and mean. A moderate percentage (68%) of extension agents were aware of open data with only 15% and 7% having high and very high level of awareness. A relatively high percentage (54%) understand what open data is all about with only 49% consenting to be involved in the use of open data mainly at a moderate level (66%). Extension agents mainly perceive open data to facilitate agricultural research ( x̄ = 3.2), facilitate access to research findings (x̄ = 3.2), give access to the work of other extension agents in other states ( x̄ = 3.2), expose them to innovation in agriculture ( x̄ = 3.2) and ensure timely access to all necessary information (x̄ = 3.1). The major challenges to the use of open data among extension agents were lack of fund to purchase internet bundle ( x̄ = 2.2), unavailability of internet facilities( x̄ = 2.1), lack of basic ICT facilities ( x̄ = 2.1) as well as lack of adequate knowledge of the use of ICT( x̄ = 2.0) and open data ( x̄ = 2.0). Propagation of the use of open data could be done mainly by provision of ICTs in offices ( = 3.6), training of extension agents to understand the concept of open data ( x̄ = 3.6) and provision of internet facilities for extension agents ( x̄ = 3.5). The study emphasized the need for Government through the Agricultural Development Programme (ADP) to provide basic ICT tools in offices and provision of internet facilities to enable extension agents maximize the use of open data.
 Keywords: Open data, challenges, agriculture, extension agents

Co-Creation of Public Service Innovation Using Open Data and Social Media

This article presents the analysis of the usage of open data and social media in the co-creation of public service innovation. The article concludes that using open data and social media in co-creation of public service innovation is a promising approach but not yet fully implemented. It seems clear that the advances in digital technology may provide a bridge for bringing service providers and service users together. The benefits are clear. First, the more accurate and real-time data available, the more effective the service provision will be. Second, the more citizen participation, the more tailored services can be co-created. Third, the more transparent governance becomes, the more legitimate and accountable it becomes. Fourth, governmental legitimacy increases societal trust which supports knowledge sharing and spurs innovation. However, co-creation of public service innovations can be more complex, more unpredictable, and more political than what the rhetoric indicates.

Development web and mobile application and open data platform for water quality management in Pak Phanang river basin

This paper aims to develop web and mobile application and open data platform to facilitate the community researchers use for monitoring the water quality management in Thailand. The paper developed a mobile and web application to collect and represent WQI data. Besides that, this paper elaborated the open data platform for sharing the WQI data to the other public sectors with two formats are people-readable format and machine-readable format. The population of this research is the community researchers who live in the Pakpanang river basin, including in local authorities, volunteers, and academic researchers. This paper also pays attention to the third parties are living in the outside area, which uses the WQI data. The experiment found that the overall user satisfaction whos participate in this project is in a good rank. The top three ranks of the function usage are: the first rank is a monthly report of the WQI data function. The second rank is a sending the WQI data by the volunteer function, and a calculating the WQI data by the academic researcher function. Finally, The third rank is open data usage function. Also, the measurement station increased from twenty to twenty-two stations. The volunteers expanded from the local authorities, volunteers, and academic researchers to students and teachers. For the future, this paper tries to apply a minimisation method for optimising The WQI parameters and also classify the proper parameters for each measurement station.

Enterprise Architecture Oriented Requirements Engineering for the Design of a School Friendly Open Data Web Interface

Open Data is considered a key to scientific innovations. These freely available datasets can also be used as a foundation to enhance the digital and data literacies among the younger generation of school pupils. This article presents the design and prototype of an Open Data web interface based on the Enterprise Architecture Oriented Requirements Engineering (EAORE) approach for Open Data usage as an educational resource in Danish public schools. We first systematically review the literature on Open Data use in educational fields and selected 14 research articles with a particular focus on the use of Open Data in the educational domain after prescribing an inclusion/exclusion criteria on 101 research articles identified initially. The review indicates that there is a gap between Open Data opportunities within the educational domain and in exploring the use of Open Data as a source to develop twenty-first-century skills, specifically digital and data literacies among younger school pupils. To fill this gap, we propose an EAORE approach that represents how Enterprise Architecture (EA) models can guide the overall Requirements Engineering (RE) process for the use of Open Data in Danish public schools. Based on these EA models, we designed the prototype of an Open Data web interface for schools.

Provision and usage of open government data: strategic transformation paths

PurposeTo create the expected value and benefits through open data, appropriate provision and usage of data are required simultaneously. However, the level of provision and usage of open data differs from country to country. Moreover, previous research on open data has only focused on either open data provision or usage. To fill the research gap, the purpose of this paper is threefold: first, to understand the current status of the provision and usage of open data; second, to identify patterns in the provision and usage of open data; and third, to provide appropriate future directions and guidelines for the transformation paths of each pattern.Design/methodology/approachThe authors analyzed the data collected from open data portals of 13 countries that provide information on the provision and usage of open data together.FindingsThe authors identified four patterns of the provision and usage of open data, namely, availability-driven, government-driven, market-driven and interaction-driven patterns. Furthermore, three strategic paths of transformation reach a high level of open data provision and usage, namely, data provision-focused, data usage-focused and balanced transformation paths.Originality/valueThis study provides a foundation that enables researchers to build a holistic theory that can integrate fragmented and incomplete knowledge of open data and usage, particularly in the context of government.

Extending organizational capabilities with Open Data to support sustainable and dynamic business ecosystems

Open Data (OD) is data available in a machine-readable format and without restrictions on the permissions for using or distributing it. OD may include textual artifacts, images, maps, video content, and other. The data can be published and maintained by different entities, both public and private. Despite its power to distribute knowledge freely and availability of a large number of datasets, OD initiatives face important challenges related to its widespread take up. More specifically, OD provisioning is based on a unidirectional linking from OD providers to OD users without considering requirements and preferences of the users. The OD users also lack metadata, and they need to develop specific technical solutions for providing a continuous OD flow and processing, which is particularly difficult when real-time OD are to be used. In this paper, we propose solving these challenges by envisioning a business ecosystem for OD. It is network-based, federated, and supports interplay between OD provisioning and knowledge management. As a methodological solution, we have applied the capability-driven development approach, which allows modeling of OD processing ecosystems, facilitates knowledge exchange about OD usage among members of the ecosystem, and supports configuring information systems for OD processing. The proposal is explicated with a theoretical study of its usability for the service of road maintenance in varying conditions.

Open data work: understanding open data usage from a practice lens

During recent years, the amount of data released on platforms by public administrations around the world have exploded. Open government data platforms are aimed at enhancing transparency and participation. Even though the promises of these platforms are high, their full potential has not yet been reached. Scholars have identified technical and quality barriers of open data usage. Although useful, these issues fail to acknowledge that the meaning of open data also depends on the context and people involved. In this study we analyze open data usage from a practice lens – as a social construction that emerges over time in interaction with governments and users in a specific context – to enhance our understanding of the role of context and agency in the development of open data platforms. This study is based on innovative action-based research in which civil servants’ and citizens’ initiatives collaborate to find solutions for public problems using an open data platform. It provides an insider perspective of Open Data Work. The findings show that an absence of a shared cognitive framework for understanding open data and a lack of high-quality datasets can prevent processes of collaborative learning. Our contextual approach stresses the need for open data practices that work on the basis of rich interactions with users rather than government-centric implementations.