Archives des mots-clés : data sharing

When data sharing is an answer and when (often) it is not: Acknowledging data-driven, non-data, and data-decentered cultures

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Authors : Isto Huvila, Luanne S. Sinnamon

Contemporary research and innovation policies and advocates of data-intensive research paradigms continue to urge increased sharing of research data. Such paradigms are underpinned by a pro-data, normative data culture that has become dominant in the contemporary discourse. Earlier research on research data sharing has directed little attention to its alternatives as more than a deficit. The present study aims to provide insights into researchers’ perspectives, rationales and practices of (non-)sharing of research data in relation to their research practices.

We address two research questions, (RQ1) what underpinning patterns can be identified in researchers’ (non-)sharing of research data, and (RQ2) how are attitudes and data-sharing linked to researchers’ general practices of conducting their research. We identify and describe data-decentered culture and non-data culture as alternatives and parallels to the data-driven culture, and describe researchers de-inscriptions of how they resist and appropriate predominant notions of data in their data practices by problematizing the notion of data, asserting exceptions to the general case of data sharing, and resisting or opting out from data sharing.

URL : When data sharing is an answer and when (often) it is not: Acknowledging data-driven, non-data, and data-decentered cultures

DOI : https://doi.org/10.1002/asi.24957

Why academics under-share research data: A social relational theory

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Authors : Janice Bially Mattern, Joseph Kohlburn, Heather Moulaison-Sandy

Despite their professed enthusiasm for open science, faculty researchers have been documented as not freely sharing their data; instead, if sharing data at all, they take a minimal approach. A robust research agenda in LIS has documented the data under-sharing practices in which they engage, and the motivations they profess.

Using theoretical frameworks from sociology to complement research in LIS, this article examines the broader context in which researchers are situated, theorizing the social relational dynamics in academia that influence faculty decisions and practices relating to data sharing.

We advance a theory that suggests that the academy has entered a period of transition, and faculty resistance to data sharing through foot-dragging is one response to shifting power dynamics. If the theory is borne out empirically, proponents of open access will need to find a way to encourage open academic research practices without undermining the social value of academic researchers.

URL : Why academics under-share research data: A social relational theory

DOI : https://doi.org/10.1002/asi.24938

To share or not to share? Image data sharing in the social sciences and humanities

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Authors : Elina Late, Mette Skov, Sanna Kumpulainen

Introduction

The paper aims to investigate image data sharing within social science and humanities. While data sharing is encouraged as a part of the open science movement, little is known about the approaches and factors influencing the sharing of image data.

This information is evident as the use of image data in these fields of research is increasing, and data sharing is context dependent.

Method

The study analyses qualitative semi-structured interviews with 14 scholars who incorporate digital images as a core component of their research data.

Analysis

Content analysis is conducted to gather information about scholars’ image data sharing and motivating and impeding factors related to it.

Results

The findings show that image data sharing is not an established research practice, and when it happens it is mostly done via informal means by sharing data through personal contacts. Supporting the scientific community, the open science agenda and fulfilling research funders’ requirements motivate scholars to share their data. Impeding factors relate to the qualities of data, ownership of data, data stewardship, and research integrity.

Conclusion

Advancing image data sharing requires the development of research infrastructures and providing support and guidelines. Better understanding of the scholars’ image data practices is also needed.

URL : To share or not to share? Image data sharing in the social sciences and humanities

DOI : https://doi.org/10.47989/ir292834

Research Data Management in the Croatian Academic Community: A Research Study

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Author : Radovan Vrana

This paper presents the results of an empirical research study of Croatian scientists’ use and management of research data. This research study was carried out from 28 June 2023 until 31 August 2023 using an online questionnaire consisting of 28 questions. The answers of 584 respondents working in science were filtered out for further analysis. About three-quarters of the respondents used the research data of other scientists successfully. Research data were mostly acquired from colleagues from the same department or institution.

Roughly half of the respondents did not ask other scientists directly for their research data. Research data are important to the respondents mostly for raising the quality of research. Repeating someone else’s research by using their research data is still a problem. Less than one-third of the respondents provided full access to their research data mostly due to their fear of misuse.

The benefits of research data sharing were recognized but few of the respondents received any reward for it. Archiving research data is a significant problem for the respondents as they dominantly use their own computers prone to failure for that activity and do not think about long-term preservation. Finally, the respondents lacked deeper knowledge of research data management.

URL : Research Data Management in the Croatian Academic Community: A Research Study

DOI : https://doi.org/10.3390/publications12020016

An analysis of the effects of sharing research data, code, and preprints on citations

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Authors : Giovanni Colavizza, Lauren Cadwallader, Marcel LaFlamme, Grégory Dozot, Stéphane Lecorney, Daniel Rappo, Iain Hrynaszkiewicz

Calls to make scientific research more open have gained traction with a range of societal stakeholders. Open Science practices include but are not limited to the early sharing of results via preprints and openly sharing outputs such as data and code to make research more reproducible and extensible. Existing evidence shows that adopting Open Science practices has effects in several domains.

In this study, we investigate whether adopting one or more Open Science practices leads to significantly higher citations for an associated publication, which is one form of academic impact. We use a novel dataset known as Open Science Indicators, produced by PLOS and DataSeer, which includes all PLOS publications from 2018 to 2023 as well as a comparison group sampled from the PMC Open Access Subset. In total, we analyze circa 122’000 publications. We calculate publication and author-level citation indicators and use a broad set of control variables to isolate the effect of Open Science Indicators on received citations.

We show that Open Science practices are adopted to different degrees across scientific disciplines. We find that the early release of a publication as a preprint correlates with a significant positive citation advantage of about 20.2% on average. We also find that sharing data in an online repository correlates with a smaller yet still positive citation advantage of 4.3% on average.

However, we do not find a significant citation advantage for sharing code. Further research is needed on additional or alternative measures of impact beyond citations. Our results are likely to be of interest to researchers, as well as publishers, research funders, and policymakers.

Arxiv : https://arxiv.org/abs/2404.16171

From Data Creator to Data Reuser: Distance Matters

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Authors : Christine L. Borgman, Paul T. Groth

Sharing research data is complex, labor-intensive, expensive, and requires infrastructure investments by multiple stakeholders. Open science policies focus on data release rather than on data reuse, yet reuse is also difficult, expensive, and may never occur. Investments in data management could be made more wisely by considering who might reuse data, how, why, for what purposes, and when.

Data creators cannot anticipate all possible reuses or reusers; our goal is to identify factors that may aid stakeholders in deciding how to invest in research data, how to identify potential reuses and reusers, and how to improve data exchange processes.

Drawing upon empirical studies of data sharing and reuse, we develop the theoretical construct of distance between data creator and data reuser, identifying six distance dimensions that influence the ability to transfer knowledge effectively: domain, methods, collaboration, curation, purposes, and time and temporality.

These dimensions are primarily social in character, with associated technical aspects that can decrease – or increase – distances between creators and reusers. We identify the order of expected influence on data reuse and ways in which the six dimensions are interdependent.

Our theoretical framing of the distance between data creators and prospective reusers leads to recommendations to four categories of stakeholders on how to make data sharing and reuse more effective: data creators, data reusers, data archivists, and funding agencies.

URL : From Data Creator to Data Reuser: Distance Matters

arXiv : https://arxiv.org/abs/2402.07926

Building a Trustworthy Data Repository: CoreTrustSeal Certification as a Lens for Service Improvements

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Authors : Cara Key, Clara Llebot, Michael Boock

Objective

The university library aims to provide university researchers with a trustworthy institutional repository for sharing data. The library sought CoreTrustSeal certification in order to measure the quality of data services in the institutional repository, and to promote researchers’ confidence when depositing their work.

Methods

The authors served on a small team of library staff who collaborated to compose the certification application. They describe the self-assessment process, as they iterated through cycles of compiling information and responding to reviewer feedback.

Results

The application team gained understanding of data repository best practices, shared knowledge about the institutional repository, and identified areas of service improvements necessary to meet certification requirements. Based on the application and feedback, the team took measures to enhance preservation strategies, governance, and public-facing policies and documentation for the repository.

Conclusions

The university library gained a better understanding of top-notch data services and measurably improved these services by pursuing and obtaining CoreTrustSeal certification.

URL : Building a Trustworthy Data Repository: CoreTrustSeal Certification as a Lens for Service Improvements

DOI : https://doi.org/10.7191/jeslib.761