scholarly journals Are data repositories fettered? A survey of current practices, challenges and future technologies

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nushrat Khan ◽  
Mike Thelwall ◽  
Kayvan Kousha

PurposeThe purpose of this study is to explore current practices, challenges and technological needs of different data repositories.Design/methodology/approachAn online survey was designed for data repository managers, and contact information from the re3data, a data repository registry, was collected to disseminate the survey.FindingsIn total, 189 responses were received, including 47% discipline specific and 34% institutional data repositories. A total of 71% of the repositories reporting their software used bespoke technical frameworks, with DSpace, EPrint and Dataverse being commonly used by institutional repositories. Of repository managers, 32% reported tracking secondary data reuse while 50% would like to. Among data reuse metrics, citation counts were considered extremely important by the majority, followed by links to the data from other websites and download counts. Despite their perceived usefulness, repository managers struggle to track dataset citations. Most repository managers support dataset and metadata quality checks via librarians, subject specialists or information professionals. A lack of engagement from users and a lack of human resources are the top two challenges, and outreach is the most common motivator mentioned by repositories across all groups. Ensuring findable, accessible, interoperable and reusable (FAIR) data (49%), providing user support for research (36%) and developing best practices (29%) are the top three priorities for repository managers. The main recommendations for future repository systems are as follows: integration and interoperability between data and systems (30%), better research data management (RDM) tools (19%), tools that allow computation without downloading datasets (16%) and automated systems (16%).Originality/valueThis study identifies the current challenges and needs for improving data repository functionalities and user experiences.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-04-2021-0204

2017 ◽  
Vol 35 (6) ◽  
pp. 1141-1161 ◽  
Author(s):  
Yeon Kyoung Joo ◽  
Youngseek Kim

Purpose The purpose of this research is to investigate the factors that influence engineering researchers’ data reuse behaviours. Design/methodology/approach The data reuse behaviour model of engineering researchers was investigated by using a survey method. A national survey was distributed to engineering researchers in the USA, and a total of 193 researchers responded. Findings The results showed that perceived usefulness, perceived concerns and norms of data reuse have significant relationships with attitudes toward data reuse. Also, attitudes toward data reuse and the availability of data repositories were found to have significant influences on engineering researchers’ intention to reuse data. Research limitations/implications This research used a combined theoretical framework by integrating the theory of planned behaviour (TPB) and the technology acceptance model (TAM). The combination of the TPB and the TAM effectively explained engineering researchers’ data reuse behaviours by addressing individual motivations, norms and resource factors. Practical implications This research has practical implications for promoting more reliable and beneficial data reuse in the engineering community, including encouraging positive motivations toward data reuse, building community norms of data reuse and setting up more data repositories. Originality value As prior research on data reuse mainly used interviews, this research used a quantitative approach based on a combined theoretical framework and included diverse research constructs which were not tested in the previous research models. As one of the initial studies investigating data reuse behaviours in the engineering community, the current research provided a better understanding of data reuse behaviours and suggested possible ways to facilitate engineering researchers’ data reuse behaviours.


2018 ◽  
Vol 42 (1) ◽  
pp. 124-142 ◽  
Author(s):  
Youngseek Kim ◽  
Seungahn Nah

Purpose The purpose of this paper is to examine how data reuse experience, attitudinal beliefs, social norms, and resource factors influence internet researchers to share data with other researchers outside their teams. Design/methodology/approach An online survey was conducted to examine the extent to which data reuse experience, attitudinal beliefs, social norms, and resource factors predicted internet researchers’ data sharing intentions and behaviors. The theorized model was tested using a structural equation modeling technique to analyze a total of 201 survey responses from the Association of Internet Researchers mailing list. Findings Results show that data reuse experience significantly influenced participants’ perception of benefit from data sharing and participants’ norm of data sharing. Belief structures regarding data sharing, including perceived career benefit and risk, and perceived effort, had significant associations with attitude toward data sharing, leading internet researchers to have greater data sharing intentions and behavior. The results also reveal that researchers’ norms for data sharing had a direct effect on data sharing intention. Furthermore, the results indicate that, while the perceived availability of data repository did not yield a positive impact on data sharing intention, it has a significant, direct, positive impact on researchers’ data sharing behaviors. Research limitations/implications This study validated its novel theorized model based on the theory of planned behavior (TPB). The study showed a holistic picture of how different data sharing factors, including data reuse experience, attitudinal beliefs, social norms, and data repositories, influence internet researchers’ data sharing intentions and behaviors. Practical implications Data reuse experience, attitude toward and norm of data sharing, and the availability of data repository had either direct or indirect influence on internet researchers’ data sharing behaviors. Thus, professional associations, funding agencies, and academic institutions alike should promote academic cultures that value data sharing in order to create a virtuous cycle of reciprocity and encourage researchers to have positive attitudes toward/norms of data sharing; these cultures should be strengthened by the strong support of data repositories. Originality/value In line with prior scholarship concerning scientific data sharing, this study of internet researchers offers a map of scientific data sharing intentions and behaviors by examining the impacts of data reuse experience, attitudinal beliefs, social norms, and data repositories together.


2019 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Angela P. Murillo

Purpose The purpose of this study is to examine the information needs of earth and environmental scientists regarding how they determine data reusability and relevance. Additionally, this study provides strategies for the development of data collections and recommendations for data management and curation for information professionals working alongside researchers. Design/methodology/approach This study uses a multi-phase mixed-method approach. The test environment is the DataONE data repository. Phase 1 includes a qualitative and quantitative content analysis of deposited data. Phase 2 consists of a quasi-experiment think-aloud study. This paper reports mainly on Phase 2. Findings This study identifies earth and environmental scientists’ information needs to determine data reusability. The findings include a need for information regarding research methods, instruments and data descriptions when determining data reusability, as well as a restructuring of data abstracts. Additional findings include reorganizing of the data record layout and data citation information. Research limitations/implications While this study was limited to earth and environmental science data, the findings provide feedback for scientists in other disciplines, as earth and environmental science is a highly interdisciplinary scientific domain that pulls from many disciplines, including biology, ecology and geology, and additionally there has been a significant increase in interdisciplinary research in many scientific fields. Practical implications The practical implications include concrete feedback to data librarians, data curators and repository managers, as well as other information professionals as to the information needs of scientists reusing data. The suggestions could be implemented to improve consultative practices when working alongside scientists regarding data deposition and data creation. These suggestions could improve policies for data repositories through direct feedback from scientists. These suggestions could be implemented to improve how data repositories are created and what should be considered mandatory information and secondary information to improve the reusability of data. Social implications By examining the information needs of earth and environmental scientists reusing data, this study provides feedback that could change current practices in data deposition, which ultimately could improve the potentiality of data reuse. Originality/value While there has been research conducted on data sharing and reuse, this study provides more detailed granularity regarding what information is needed to determine reusability. This study sets itself apart by not focusing on social motivators and demotivators, but by focusing on information provided in a data record.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Youngseek Kim

PurposeThis research investigates how the availabilities of both metadata standards and data repositories influence researchers' data reuse intentions either directly or indirectly as mediated by the norms of data reuse and their attitudes toward data reuse.Design/methodology/approachThe theory of planned behavior (TPB) was employed to develop the research model of researchers' data reuse intentions, focusing on the roles of metadata standards, data repositories and norms of data reuse. The proposed research model was evaluated using the structural equation modeling (SEM) method based on the survey responses received from 811 STEM (science, technology, engineering and mathematics) researchers in the United States.FindingsThis research found that the availabilities of both metadata standards and data repositories significantly affect STEM researchers' norm of data reuse, which influences their data reuse intentions as mediated by their attitudes toward data reuse. This research also found that both the availability of data repositories and the norm of data reuse have a direct influence on data reuse intentions and that norm of data reuse significantly increases the effect of attitude toward data reuse on data reuse intention as a moderator.Research limitations/implicationsThe modified model of TPB provides a new perspective in apprehending the roles of resource facilitating conditions such as the availabilities of metadata standards and data repositories in an individual's attitude, norm and their behavioral intention to conduct a certain behavior.Practical implicationsThis study suggests that scientific communities need to develop more supportive metadata standards and data repositories by considering their roles in enhancing the community norm of data reuse, which eventually lead to data reuse behaviors.Originality/valueThis study sheds light on the mechanism of metadata standard and data repository in researchers' data reuse behaviors through their community norm of data reuse; this can help scientific communities and academic institutions to better support researchers in their data sharing and reuse behaviors.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-09-2020-0431


2017 ◽  
Vol 35 (4) ◽  
pp. 626-649 ◽  
Author(s):  
Wei Jeng ◽  
Daqing He ◽  
Yu Chi

Purpose Owing to the recent surge of interest in the age of the data deluge, the importance of researching data infrastructures is increasing. The open archival information system (OAIS) model has been widely adopted as a framework for creating and maintaining digital repositories. Considering that OAIS is a reference model that requires customization for actual practice, this paper aims to examine how the current practices in a data repository map to the OAIS environment and functional components. Design/methodology/approach The authors conducted two focus-group sessions and one individual interview with eight employees at the world’s largest social science data repository, the Interuniversity Consortium for Political and Social Research (ICPSR). By examining their current actions (activities regarding their work responsibilities) and IT practices, they studied the barriers and challenges of archiving and curating qualitative data at ICPSR. Findings The authors observed that the OAIS model is robust and reliable in actual service processes for data curation and data archives. In addition, a data repository’s workflow resembles digital archives or even digital libraries. On the other hand, they find that the cost of preventing disclosure risk and a lack of agreement on the standards of text data files are the most apparent obstacles for data curation professionals to handle qualitative data; the maturation of data metrics seems to be a promising solution to several challenges in social science data sharing. Originality/value The authors evaluated the gap between a research data repository’s current practices and the adoption of the OAIS model. They also identified answers to questions such as how current technological infrastructure in a leading data repository such as ICPSR supports their daily operations, what the ideal technologies in those data repositories would be and the associated challenges that accompany these ideal technologies. Most importantly, they helped to prioritize challenges and barriers from the data curator’s perspective and to contribute implications of data sharing and reuse in social sciences.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Floriana Fusco ◽  
Renato Civitillo ◽  
Paolo Ricci ◽  
Sylwia Morawska ◽  
Katarzyna Pustułka ◽  
...  

Purpose That on accountability in public organizations is quite an old debate. Its introduction in judicial systems is, however, still viewed with some suspicion, due to its potential trade-off with independence and impartiality. Nevertheless, the need to respond to the demands for greater transparency and accountability has also pushed judicial organizations to establish a dialogue with a wide range of subjects. This study aims to explore the understanding and the current practices of sustainability reporting currently in place in judicial systems. Design/methodology/approach The study adopts a comparative approach, conducting an online survey in two European countries (Italy and Poland). The survey was built around the research questions and literature and administered between February and March 2020. Specifically, 804 courts were involved, of which 430 are in Italy and 374 in Poland. Findings Findings show that the current practices are still not widespread and there is still a lack of understanding of what sustainability reporting is, and therefore, of what its potential usefulness within the courts could be. Moreover, many differences between the two countries are pointed out, so it is possible to assume that the different cultural and institutional settings influence sustainability reporting practices. Finally, some interesting implications for policymakers are provided. Originality/value Judicial organizations are still poorly investigated in the literature, despite being at the center of a wide public and political debate. Moreover, the international comparative perspective adopted constitutes a further aspect of novelty.


2019 ◽  
Vol 29 (1) ◽  
pp. 167-193 ◽  
Author(s):  
Yu-Hsin Chen ◽  
Ching-Jui Keng

Purpose The purpose of this paper is to develop an extended Push-Pull-Mooring-Habit (PPMH) framework in order to better understand users’ intention of switching from offline to an online real-person English learning platform service. Design/methodology/approach Based on 301 valid responses collected from an online survey questionnaire, structural equation modeling was employed to examine the research model. Findings The causal model was validated using SmartPLS 3.0, and all study hypotheses were supported. The results show that push effects (learning convenience, service quality and perceived price), pull effects (e-learning motivation, perceived usefulness), mooring effects (learning engagement, switching cost and social presences) and habit effects (relationship inertia) all significantly influence users’ switching intentions from offline to an online real-person English learning platform. Practical implications The findings should help online English learning service providers and marketers to understand the intention of offline English learning users to switch to an online real-person English learning platform, and develop related theories, services and regulations. Originality/value The present study extends the prior research of an online real-person English learning platform by providing PPMH as the general framework and demonstrating its efficacy in explaining user switching intentions.


2017 ◽  
Vol 69 (4) ◽  
pp. 389-407 ◽  
Author(s):  
Soohyung Joo ◽  
Sujin Kim ◽  
Youngseek Kim

Purpose The purpose of this paper is to examine how health scientists’ attitudinal, social, and resource factors affect their data reuse behaviors. Design/methodology/approach A survey method was utilized to investigate to what extent attitudinal, social, and resource factors influence health scientists’ data reuse behaviors. The health scientists’ data reuse research model was validated by using partial least squares (PLS) based structural equation modeling technique with a total of 161 health scientists in the USA. Findings The analysis results showed that health scientists’ data reuse intentions are driven by attitude toward data reuse, community norm of data reuse, disciplinary research climate, and organizational support factors. This research also found that both perceived usefulness of data reuse and perceived concern involved in data reuse have significant influences on health scientists’ attitude toward data reuse. Research limitations/implications This research evaluated its newly proposed research model based on the theory of planned behavior using a sample from the community of scientists’ scholar database. This research showed an overall picture of how attitudinal, social, and resource factors influence health scientists’ data reuse behaviors. This research is limited due to its sample size and low response rate, so this study is considered as an exploratory study rather than a confirmatory study. Practical implications This research suggested for health science research communities, academic institutions, and libraries that diverse strategies need to be utilized to promote health scientists’ data reuse behaviors. Originality/value This research is one of initial studies in scientific data reuse which provided a holistic map about health scientists’ data sharing behaviors. The findings of this study provide the groundwork for strategies to facilitate data reuse practice in health science areas.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Balakrishna Grandhi ◽  
Nitin Patwa ◽  
Kashaf Saleem

PurposeIn the current business environment, more uncertain than ever before, understanding consumer behavior is an integral part of an organization's strategic planning and execution process. It is the key driver for becoming a market leader. Therefore, it is important that all processes in business are customer centric. Marketers need to harness big data by engaging in data driven-marketing (DDM) to help organizations choose the “right” customers, to “keep” and “grow” them and to sustain “growth” and “profitability”. This research examines DDM adoption practices and how companies can aim to enhance shareholder value by bringing about “customer centricity”.Design/methodology/approachAn online survey conducted in 2016 received 180 responses from junior, middle and senior executives. Of the total responses, 26% were from senior management, 39% from middle management and the remaining 35% from junior management. Industries represented in the survey included retail, BFSI, healthcare and government, automobile, telecommunication, transport and logistics and IT. Other industries represented were aviation, marketing research and consulting, hospitality, advertising and media and human resource.FindingsSuccess of DDM depends upon how well an organization embraces the practice. The first and foremost indicator of an organization's commitment is the extent of resources invested for DDM. Respondents were divided into four categories; Laggards, Dabblers, Contenders and Leaders based on their “current level of investments” and “willingness to enhance investments” soon.Research limitations/implicationsWith storming digital age and the development of analytics, the process of decision-making has gained significant importance. Judgment and intuition too are critical to the process. Choosing an appropriate action cannot be done strictly on a rational basis.Practical implicationsThe results of the study offer interesting implications for managing the growing sea of data. An iterative and incremental approach is the need of the hour, even if it has to start with baby steps, to invest in and reap the fruits of DDM. The intention to use any system is always dependent on two primary belief factors: perceived usefulness and perceived ease of use; however, attitudes and social factors are equally important.Originality/valueThere is a dearth of knowledge with regards to who is and is not adopting DDM, and how best big data can be harnessed for enhancing effectiveness and efficiency of marketing budget. It is, therefore, imperative to build a knowledge base on DDM practices, challenges and opportunities. Better use of data can help companies enhance shareholder value by bringing about “customer centricity”.


2017 ◽  
Vol 11 (1) ◽  
pp. 22-40 ◽  
Author(s):  
Madhurima Deb ◽  
Aarti Agrawal

Purpose The purpose of this study has been to understand brand India’s potential for financial inclusion in the future. As, digital channels like mobile banking (m-banking) are likely to provide better coverage and more cost-effective services to the unbanked population of India. Conventional banking might not be cost-effective for low-ticket-size transactions, hence financial inclusion, which is on the “Digital India” agenda of the Government of India (GoI), might not be feasible. However, to understand brand India’s potential for financial inclusion in the future, it would be essential to understand Indian customers’ attitudes toward m-banking, especially those who have not yet adopted it. This would bring out the potential of m-banking as a channel to drive financial inclusion based on customers’ intentions to adopt it. Until every Indian has access to a wider range of financial services, there cannot be financial inclusion. Similarly, until every Indian adopts digital channels to access a wider range of financial and non-financial services, the GoI’s initiatives for “Digital India” cannot be realized. Furthermore, a review of the literature suggests that there are very few studies concerning m-banking worldwide and still fewer in the context of India. Design/methodology/approach The present study used IBM SPSS and Amos software to test the conceptual model developed using secondary data. Findings The findings of the study suggest that subjective norm, output quality and personal innovativeness have impacts on the perceived usefulness of, and attitudes toward, the ultimate adoption of m-banking. Originality/value The paper is the original work of the authors. An attempt has been made to integrate all the existing literature on m-banking to develop a complete model for the technology’s adoption.


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