Étiquette : research data

Catégories
EN

Handling Open Research Data within the Max Planck Society — Looking Closer at the Year 2020

Authors : Martin Boosen, Michael Franke, Yves Vincent Grossmann, Sy Dat Ho, Larissa Leiminger, Jan Matthiesen

This paper analyses the practice of publishing research data within the Max Planck Society in the year 2020. The central finding of the study is that up to 40\% of the empirical text publications had research data available. The aggregation of the available data is predominantly analysed.

There are differences between the sections of the Max Planck Society but they are not as great as one might expect. In the case of the journals, it is also apparent that a data policy can increase the availability of data related to textual publications.

Finally, we found that the statement on data availability « upon (reasonable) request » does not work.

URL : Handling Open Research Data within the Max Planck Society — Looking Closer at the Year 2020

Arxiv : https://arxiv.org/abs/2402.18182

Catégories
EN

From Data Creator to Data Reuser: Distance Matters

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

Catégories
EN

Does the Use of Unusual Combinations of Datasets Contribute to Greater Scientific Impact?

Authors : Yulin Yu, Daniel M. Romero

Scientific datasets play a crucial role in contemporary data-driven research, as they allow for the progress of science by facilitating the discovery of new patterns and phenomena. This mounting demand for empirical research raises important questions on how strategic data utilization in research projects can stimulate scientific advancement.

In this study, we examine the hypothesis inspired by the recombination theory, which suggests that innovative combinations of existing knowledge, including the use of unusual combinations of datasets, can lead to high-impact discoveries. We investigate the scientific outcomes of such atypical data combinations in more than 30,000 publications that leverage over 6,000 datasets curated within one of the largest social science databases, ICPSR.

This study offers four important insights. First, combining datasets, particularly those infrequently paired, significantly contributes to both scientific and broader impacts (e.g., dissemination to the general public). Second, the combination of datasets with atypically combined topics has the opposite effect — the use of such data is associated with fewer citations.

Third, younger and less experienced research teams tend to use atypical combinations of datasets in research at a higher frequency than their older and more experienced counterparts.

Lastly, despite the benefits of data combination, papers that amalgamate data remain infrequent. This finding suggests that the unconventional combination of datasets is an under-utilized but powerful strategy correlated with the scientific and broader impact of scientific discoveries.

URL : https://arxiv.org/abs/2402.05024

Catégories
EN

Agile Research Data Management with Open Source: LinkAhead

Authors : Daniel Hornung, Florian Spreckelsen, Thomas Weiß

Research data management (RDM) in academic scientific environments increasingly enters the focus as an important part of good scientific practice and as a topic with big potentials for saving time and money. Nevertheless, there is a shortage of appropriate tools, which fulfill the specific requirements in scientific research.

We identified where the requirements in science deviate from other fields and proposed a list of requirements which RDM software should answer to become a viable option. We analyzed a number of currently available technologies and tool categories for matching these requirements and identified areas where no tools can satisfy researchers’ needs.

Finally we assessed the open-source RDMS (research data management system) LinkAhead for compatibility with the proposed features and found that it fulfills the requirements in the area of semantic, flexible data handling in which other tools show weaknesses.

URL : Agile Research Data Management with Open Source: LinkAhead

DOI : https://doi.org/10.48694/inggrid.3866

Catégories
EN

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

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

Catégories
EN

The Future of Data in Research Publishing: From Nice to Have to Need to Have?

Authors : Christine L. Borgman, Amy Brand

Science policy promotes open access to research data for purposes of transparency and reuse of data in the public interest. We expect demands for open data in scholarly publishing to accelerate, at least partly in response to the opacity of artificial intelligence algorithms.

Open data should be findable, accessible, interoperable, and reusable (FAIR), and also trustworthy and verifiable. The current state of open data in scholarly publishing is in transition from ‘nice to have’ to ‘need to have.’

Research data are valuable, interpretable, and verifiable only in context of their origin, and with sufficient infrastructure to facilitate reuse. Making research data useful is expensive; benefits and costs are distributed unevenly.

Open data also poses risks for provenance, intellectual property, misuse, and misappropriation in an era of trolls and hallucinating AI algorithms. Scholars and scholarly publishers must make evidentiary data more widely available to promote public trust in research.

To make research processes more trustworthy, transparent, and verifiable, stakeholders need to make greater investments in data stewardship and knowledge infrastructures.

DOI : https://doi.org/10.1162/99608f92.b73aae77

Catégories
EN

More than data repositories: perceived information needs for the development of social sciences and humanities research infrastructures

Authors : Anna Sendra, Elina Late, Sanna Kumpulainen

Introduction

The digitalization of social sciences and humanities research necessitates research infrastructures. However, this transformation is still incipient, highlighting the need to better understand how to successfully support data-intensive research.

Method

Starting from a case study of building a national infrastructure for conducting data-intensive research, this study aims to understand the information needs of digital researchers regarding the facility and explore the importance of evaluation in its development.

Analysis

Thirteen semi-structured interviews with social sciences and humanities scholars and computer and data scientists processed through a thematic analysis revealed three themes (developing a research infrastructure, needs and expectations of the research infrastructure, and an approach to user feedback and user interactions).

Results

Findings reveal that developing an infrastructure for conducting data-intensive research is a complicated task influenced by contrasting information needs between social sciences and humanities scholars and computer and data scientists, such as the demand for increased support of the former. Findings also highlight the limited role of evaluation in its creation.

Conclusions

The development of infrastructures for conducting data-intensive research requires further discussion that particularly considers the disciplinary differences between social sciences and humanities scholars and computer and data scientists. Suggestions on how to better design this kind of facilities are also raised.

URL : More than data repositories: perceived information needs for the development of social sciences and humanities research infrastructures

DOI : https://doi.org/10.47989/ir284598