Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Selected Study Data. Study data excluding selected columns. See Data Availability Statement for more information.
This study describes a methodology where departmental academic publications are used to analyse the ways in which computer scientists share research data.
Without sufficient information about researchers’ data sharing, there is a risk of mismatching FAIR data service efforts with the needs of researchers. This study describes a methodology where departmental academic publications are used to analyse the ways in which computer scientists share research data. The advancement of FAIR data would benefit from novel methodologies that reliably examine data sharing at the level of multidisciplinary research organisations. Studies that use CRIS publication data to elicit insight into researchers’ data sharing may therefore be a valuable addition to the current interview and questionnaire methodologies.
Data was collected from the following sources:
All journal articles published by researchers in the computer science department of the case study’s university during 2019 were extracted for scrutiny from the current research information system. For these 193 articles, a coding framework was developed to capture the key elements of acquiring and sharing research data. Article DOIs are included in the research data.
The scientific journal articles and theirs DOIs are used in this study for the purpose of academic expression.
The raw data is compiled into a single CSV file. Rows represent specific articles and columns are the values of the data points described below. Author names and affiliations were not collected and are not included in the data set. Please, contact the author for access to the data.
The following data points were used in the analysis:
Data points
Main study types
Literature-based study (e.g. literature reviews, archive studies, studies of social media)
yes/no
Novel computational methods (e.g. algorithms, simulations, software)
yes/no
Interaction studies (e.g, interviews, surveys, tasks, ethnography)
yes/no
Intervention studies (e.g., EEG, MRI, clinical trials)
yes/no
Measurement studies (e.g. astronomy, weather, acoustics, chemistry)
yes/no
Life sciences (e.g. “omics”, ecology)
yes/no
Data acquisition
Article presents a data availability statement
yes/no
Article does not utilise data
yes/no
Original data was collected
yes/no
Open data from prior studies were used
yes/no
Open data from public authorities, companies, universities and associations
yes/no
Data sharing
Article does not use original data
yes/no
Data of the article is not available for reuse
yes/no
Article used openly available data
yes/no
Authors agree to share their data to interested readers
yes/no
Article shared data (or part of) as supplementary material
yes/no
Article shared data (or part of) via open deposition
yes/no
Article deposited code or used open code
yes/no
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Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Selected Study Data. Study data excluding selected columns. See Data Availability Statement for more information.