1 research outputs found
Data sharing of computer scientists: an analysis of current research information system 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 publications are used to
analyse the ways in which computer scientists share research data. All journal
articles published by researchers in the computer science department of the
case studys 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.
Furthermore, a rudimentary classification of the main study types exhibited in
the investigated articles was developed to accommodate the multidisciplinary
nature of the case departments research agenda. Human interaction and
intervention studies often collected original data, whereas research on novel
computational methods and life sciences more frequently used openly available
data. Articles that made data available for reuse were most often in life
science studies, whereas data sharing was least frequent in human interaction
studies. The use of open code was most frequent in life science studies and
novel computational methods. The findings highlight that multidisciplinary
research organisations may include diverse subfields that have their own
cultures of data sharing, and suggest that research information system-based
methods may be valuable additions to the questionnaire and interview
methodologies eliciting insight into researchers data sharing. The collected
data and coding framework are provided as open data to facilitate future
research