Archives des mots-clés : open research data

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

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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

Development and preliminary validation of an open access, open data and open outreach indicator

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Authors : Evgenios Vlachos, Regine Ejstrup, Thea Marie Drachen, Bertil Fabricius Dorch

We present the development and preliminary validation of a new person-centered indicator that we propose is named “OADO” after its target concepts: Open Access (OA), Open Data (OD) and Open Outreach (OO).

The indicator is comprised of two factors: the research factor indicating the degree of OA articles and OD in research; and the communication factor indicating the degree of OO in communication activities in which a researcher has participated. We stipulate that the weighted version of this new indicator, the Weighted-OADO, can be used to assess the openness of researchers in relation to their peers from their own discipline, department, or even group/center.

The OADO is developed and customized to the needs of Elsevier’s Research Information Management System (RIMS) environment, Pure. This offers the advantage of more accurate interpretations and recommendations for action, as well as the possibility to be implemented (and further validated) by multiple institutions, allowing disciplinary comparisons of the open practices across multiple institutes.

Therefore, the OADO provides recommendations for action, and enables institutes to make informed decisions based on the indicator’s outcome. To test the validity of the OADO, we retrieved the Pure publication records from two departments for each of the five faculties of the University of Southern Denmark and calculated the OADO of 995 researchers in total.

We checked for definition validity, actionability, transferability, possibility of unexpected discontinuities of the indicator, factor independence, normality of the indicator’s distributions across the departments, and indicator reliability.

Our findings reveal that the OADO is a reliable indicator for departments with normally distributed values with regards to their Weighted-OADO. Unfortunately, only two departments displayed normal distributions, one from the health sciences and one from engineering.

For departments where the normality assumption is not satisfied, the OADO can still be useful as it can indicate the need for making a greater effort toward openness, and/or act as an incentive for detailed registration of research outputs and datasets.

URL : Development and preliminary validation of an open access, open data and open outreach indicator

DOI : https://doi.org/10.3389/frma.2023.1218213

The Effects of Research Data Management Services: Associating the Data Curation Lifecycle with Open Research Output

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Authors : Nicolas Pares, Peter Organisciak

This study seeks to understand the relationship between research data management (RDM) services framed in the data curation life cycle and the production of open data. An electronic questionnaire was distributed to US researchers and RDM specialists, and the results were analyzed using Chi-Square tests for association.

The data curation life cycle does associate with the production of open data and shareable research, but tasks like data management plans have stronger associations with the production of open data. The findings analyze the intersection of these concepts and provide insight into RDM services that facilitate the production of open data and shareable research.

URL : The Effects of Research Data Management Services: Associating the Data Curation Lifecycle with Open Research Output

DOI : https://doi.org/10.5860/crl.84.5.751

Cluster Analysis of Open Research Data: A Case for Replication Metadata

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Author : Ana Trisovic

Research data are often released upon journal publication to enable result verification and reproducibility. For that reason, research dissemination infrastructures typically support diverse datasets coming from numerous disciplines, from tabular data and program code to audio-visual files. Metadata, or data about data, is critical to making research outputs adequately documented and FAIR.

Aiming to contribute to the discussions on the development of metadata for research outputs, I conducted an exploratory analysis to determine how research datasets cluster based on what researchers organically deposit together. I use the content of over 40,000 datasets from the Harvard Dataverse research data repository as my sample for the cluster analysis.

I find that the majority of the clusters are formed by single-type datasets, while in the rest of the sample, no meaningful clusters can be identified. For the result interpretation, I use the metadata standard employed by DataCite, a leading organization for documenting a scholarly record, and map existing resource types to my results.

About 65% of the sample can be described with a single-type metadata (such as Dataset, Software orReport), while the rest would require aggregate metadata types. Though DataCite supports an aggregate type such as a Collection, I argue that a significant number of datasets, in particular those containing both data and code files (about 20% of the sample), would be more accurately described as a Replication resource metadata type. Such resource type would be particularly useful in facilitating research reproducibility.

URL : Cluster Analysis of Open Research Data: A Case for Replication Metadata

DOI : https://doi.org/10.2218/ijdc.v17i1.833

Open research data: A case study into institutional and infrastructural arrangements to stimulate open research data sharing and reuse

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Authors : Thijmen van Gend, Anneke Zuiderwijk

This study investigates which combination of institutional and infrastructural arrangements positively impact research data sharing and reuse in a specific case. We conducted a qualitative case study of the institutional and infrastructural arrangements implemented at Delft University of Technology in the Netherlands.

In the examined case, it was fundamental to change the mindset of researchers and to make them aware of the benefits of sharing data. Therefore, arrangements should be designed bottom-up and used as a “carrot” rather than as a “stick.” Moreover, support offered to researchers should cover at least legal, financial, administrative, and practical issues of research data management and should be informal in nature.

Previous research describes generic institutional and infrastructural instruments that can stimulate open research data sharing and reuse. This study is among the first to analyze what and how infrastructural and institutional arrangements work in a particular context. It provides the basis for other scholars to study such arrangements in different contexts.

Open data policymakers, universities, and open data infrastructure providers can use our findings to stimulate data sharing and reuse in practice, adapted to the contextual situation. Our study focused on a single case and a particular part of the university.

We recommend repeating this research in other contexts, that is, at other universities, faculties, and involving other research data infrastructure providers.

URL : Open research data: A case study into institutional and infrastructural arrangements to stimulate open research data sharing and reuse

DOI : https://doi.org/10.1177/09610006221101200