Internet researchers’ data sharing behaviors

2018 ◽  
Vol 42 (1) ◽  
pp. 124-142 ◽  
Author(s):  
Youngseek Kim ◽  
Seungahn Nah
Keyword(s):  
Social Norms ◽  
Data Sharing ◽  
Positive Impact ◽  
Scientific Data ◽  
Data Reuse ◽  
Equation Modeling ◽  
Data Repository ◽  
Data Repositories ◽  
Content Type ◽  
And Behaviors

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.

An exploratory study of health scientists’ data reuse behaviors

2017 ◽  
Vol 69 (4) ◽  
pp. 389-407 ◽  
Author(s):  
Soohyung Joo ◽  
Sujin Kim ◽  
Youngseek Kim
Keyword(s):  
Organizational Support ◽  
Exploratory Study ◽  
Scientific Data ◽  
Perceived Usefulness ◽  
Data Reuse ◽  
Health Science ◽  
Equation Modeling ◽  
Survey Method ◽  
Research Model ◽  
Content Type

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.

Determinants of individuals’ entrepreneurial intentions: a gender-comparative study

2016 ◽  
Vol 21 (4) ◽  
pp. 318-339 ◽  
Author(s):  
Muhammad Arshad ◽  
Omer Farooq ◽  
Naheed Sultana ◽  
Mariam Farooq
Keyword(s):  
Social Norms ◽  
Self Efficacy ◽  
Structural Equation ◽  
Positive Impact ◽  
Schema Theory ◽  
Entrepreneurial Intentions ◽  
Equation Modeling ◽  
Gender Schema ◽  
Content Type ◽  
Males And Females

Purpose The purpose of this paper is to examine the differentiated effects of entrepreneurial self-efficacy and social norms on individuals’ entrepreneurial intentions (EIs), through the mediation of attitude toward entrepreneurship, by integrating the framework of gender schema theory with the theory of planned behavior. The authors posit that different factors stimulate the EIs of males and females, through attitude toward entrepreneurship, in developing countries. Design/methodology/approach Data are collected from graduating students of South Asia’s largest university. Structural equation modeling is used for model testing. Findings The results show that perceived entrepreneurial self-efficacy has a greater effect on the attitude of males toward entrepreneurship than on the attitude of females, but perceived social norms have a greater effect on female attitude toward entrepreneurship. Attitude toward entrepreneurship has a positive impact on EIs. Originality/value This is the first study of its nature which demonstrates that the EIs of males and females are induced by different factors. Where the social norms are the major factors in determining the EIs of the females, self-efficacy plays a vital role in predicting the EIs of their male counterparts. This study also attempts to clarify the relationship between self-efficacy, social norms, and EIs by positing entrepreneurial attitude as mediator. Moreover, it brings a fresh perspective through its setting in South Asia. By testing a model in the cultural setting of a developing country, this study differentiates the research from that conducted in the developed world.

scholarly journals Abordagens de reúso e a questão da reusabilidade dos dados científicos | Approaches for data reuse and the issue of scientific data reusability

2019 ◽  
Vol 15 (2) ◽  
Author(s):  
Renata Curty
Keyword(s):  
Data Sharing ◽  
Data Science ◽  
Meta Analysis ◽  
Science Research ◽  
Open Science ◽  
Scientific Data ◽  
Data Reuse ◽  
Data Repositories ◽  
Documentation Quality ◽  
Data Documentation

RESUMO As diretivas governamentais e institucionais em torno do compartilhamento de dados de pesquisas financiadas com dinheiro público têm impulsionado a rápida expansão de repositórios digitais de dados afim de disponibilizar esses ativos científicos para reutilização, com propósitos nem sempre antecipados, pelos pesquisadores que os produziram/coletaram. De modo contraditório, embora o argumento em torno do compartilhamento de dados seja fortemente sustentado no potencial de reúso e em suas consequentes contribuições para o avanço científico, esse tema permanece acessório às discussões em torno da ciência de dados e da ciência aberta. O presente artigo de revisão narrativa tem por objetivo lançar um olhar mais atento ao reúso de dados e explorar mais diretamente esse conceito, ao passo que propõe uma classificação inicial de cinco abordagens distintas para o reúso de dados de pesquisa (reaproveitamento, agregação, integração, metanálise e reanálise), com base em situações hipotéticas acompanhadas de casos de reúso de dados publicados na literatura científica. Também explora questões determinantes para a condição de reúso, relacionando a reusabilidade à qualidade da documentação que acompanha os dados. Oferece discussão sobre os desafios da documentação de dados, bem como algumas iniciativas e recomendações para que essas dificuldades sejam contornadas. Espera-se que os argumentos apresentados contribuam não somente para o avanço conceitual em torno do reúso e da reusabilidade de dados, mas também reverberem em ações relacionadas à documentação dos dados de modo a incrementar o potencial de reúso desses ativos científicos.Palavras-chave: Reúso de Dados; Reprodutibilidade Científica; Reusabilidade; Ciência Aberta; Dados de Pesquisa. ABSTRACT The availability of scientific assets through data repositories has been greatly increased as a result of government and institutional data sharing policies and mandates for publicly funded research, allowing data to be reused for purposes not always anticipated by primary researchers. Despite the fact that the argument favoring data sharing is strongly grounded in the possibilities of data reuse and its contributions to scientific advancement, this subject remains unobserved in discussions about data science and open science. This paper follows a narrative review method to take a closer look at data reuse in order to better conceptualize this term, while proposing an early classification of five distinct data reuse approaches (repurposing, aggregation, integration, meta-analysis and reanalysis) based on hypothetical cases and literature examples. It also explores the determinants of what constitutes reusable data, and the relationship between data reusability and documentation quality. It presents some challenges associated with data documentation and points out some initiatives and recommendations to overcome such problems. It expects to contribute not only for the conceptual advancement around the reusability and effective reuse of the data, but also to result in initiatives related to data documentation in order to increase the reuse potential of these scientific assets.Keywords:Data Reuse; Scientific Reproducibility; Reusability; Open Science; Research Data.  

scholarly journals Data matters: how earth and environmental scientists determine data relevance and reusability

2019 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Angela P. Murillo
Keyword(s):  
Information Needs ◽  
Environmental Science ◽  
Data Reuse ◽  
Data Repository ◽  
Phase 2 ◽  
Data Repositories ◽  
Content Type ◽  
Data Record ◽  
Information Professionals ◽  
Practical Implications

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.

scholarly journals Reuse of scientific data in academic publications

2016 ◽  
Vol 68 (4) ◽  
pp. 478-494 ◽  
Author(s):  
Lin He ◽  
Vinita Nahar
Keyword(s):  
Data Sharing ◽  
Design Methodology ◽  
Scientific Data ◽  
Research Groups ◽  
Digital Repository ◽  
Data Repositories ◽  
Content Type ◽  
Data Intensive ◽  
Academic Publications ◽  
Number Of Citations

Purpose – In recent years, a large number of data repositories have been built and used. However, the extent to which scientific data are re-used in academic publications is still unknown. The purpose of this paper is to explore the functions of re-used scientific data in scholarly publication in different fields. Design/methodology/approach – To address these questions, the authors identified 827 publications citing resources in the Dryad Digital Repository indexed by Scopus from 2010 to 2015. Findings – The results show that: the number of citations to scientific data increases sharply over the years, but mainly from data-intensive disciplines, such as agricultural, biology science, environment science and medicine; the majority of citations are from the originating articles; and researchers tend to reuse data produced by their own research groups. Research limitations/implications – Dryad data may be re-used without being formally cited. Originality/value – The conservatism in data sharing suggests that more should be done to encourage researchers to re-use other’s data.

A study of the roles of metadata standard and data repository in science, technology, engineering and mathematics researchers' data reuse

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Youngseek Kim
Keyword(s):  
Data Reuse ◽  
Data Repository ◽  
Research Model ◽  
Data Repositories ◽  
Scientific Communities ◽  
Metadata Standard ◽  
Content Type ◽  
Science Technology ◽  
Metadata Standards ◽  
And Mathematics

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

scholarly journals Social science data repositories in data deluge

2017 ◽  
Vol 35 (4) ◽  
pp. 626-649 ◽  
Author(s):  
Wei Jeng ◽  
Daqing He ◽  
Yu Chi
Keyword(s):  
Social Science ◽  
Data Sharing ◽  
Qualitative Data ◽  
Data Curation ◽  
Data Repository ◽  
Science Data ◽  
Data Repositories ◽  
Content Type ◽  
Social Science Data ◽  
Current Practices

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.

scholarly journals Responding to Reality: Evolving Curation Practices and Infrastructure at the University of Illinois at Urbana-Champaign

2021 ◽  
Vol 10 (3) ◽  
Author(s):  
Hoa Q. Luong ◽  
Colleen Fallaw ◽  
Genevieve Schmitt ◽  
Susan M. Braxton ◽  
Heidi Imker
Keyword(s):  
Data Sharing ◽  
Positive Impact ◽  
Data Bank ◽  
Research Data ◽  
Data Reuse ◽  
Data Repository ◽  
Data Service ◽  
University Of Illinois ◽  
Service Offering ◽  
The University

Objective: The Illinois Data Bank provides Illinois researchers with the infrastructure to publish research data publicly. During a five-year review of the Research Data Service at the University of Illinois at Urbana-Champaign, it was recognized as the most useful service offering in the unit. Internal metrics are captured and used to monitor the growth, document curation workflows, and surface technical challenges faced as we assist our researchers. Here we present examples of these curation challenges and the solutions chosen to address them. Methods: Some Illinois Data Bank metrics are collected internally by within the system, but most of the curation metrics reported here are tracked separately in a Google spreadsheet. The curator logs required information after curation is complete for each dataset. While the data is sometimes ambiguous (e.g., depending on researcher uptake of suggested actions), our curation data provide a general understanding about our data repository and have been useful in assessing our workflows and services. These metrics also help prioritize development needs for the Illinois Data Bank. Results and Conclusions: The curatorial services polish and improve the datasets, which contributes to the spirit of data reuse. Although we continue to see challenges in our processes, curation makes a positive impact on datasets. Continued development and adaptation of the technical infrastructure allows for an ever-better experience for the curators and users. These improvements have helped our repository more effectively support the data sharing process by successfully fostering depositor engagement with curators to improve datasets and facilitating easy transfer of very large files.

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
Keyword(s):  
Peer Review ◽  
Online Survey ◽  
Secondary Data ◽  
Perceived Usefulness ◽  
Data Reuse ◽  
Data Repository ◽  
Data Repositories ◽  
Content Type ◽  
Quality Checks ◽  
Current Practices

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

scholarly journals Researcher attitudes toward data sharing in public data repositories: a meta-evaluation of studies on researcher data sharing

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jennifer L. Thoegersen ◽  
Pia Borlund
Keyword(s):  
Data Sharing ◽  
Information Science ◽  
Research Literature ◽  
Data Repository ◽  
Library And Information Science ◽  
Data Repositories ◽  
Content Type ◽  
Address Data ◽  
Public Data ◽  
Term Data

PurposeThe purpose of this paper is to report a study of how research literature addresses researchers' attitudes toward data repository use. In particular, the authors are interested in how the term data sharing is defined, how data repository use is reported and whether there is need for greater clarity and specificity of terminology.Design/methodology/approachTo study how the literature addresses researcher data repository use, relevant studies were identified by searching Library Information Science and Technology Abstracts, Library and Information Science Source, Thomas Reuters' Web of Science Core Collection and Scopus. A total of 62 studies were identified for inclusion in this meta-evaluation.FindingsThe study shows a need for greater clarity and consistency in the use of the term data sharing in future studies to better understand the phenomenon and allow for cross-study comparisons. Furthermore, most studies did not address data repository use specifically. In most analyzed studies, it was not possible to segregate results relating to sharing via public data repositories from other types of sharing. When sharing in public repositories was mentioned, the prevalence of repository use varied significantly.Originality/valueResearchers' data sharing is of great interest to library and information science research and practice to inform academic libraries that are implementing data services to support these researchers. This study explores how the literature approaches this issue, especially the use of data repositories, the use of which is strongly encouraged. This paper identifies the potential for additional study focused on this area.

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