
This dataset contains the results from the ODDPubb text mining algorithm and the findings from manual analysis. Full-text PDFs of all articles parallel-published by Linköping University in 2022 were extracted from the institute's repository, DiVA. These were analyzed using the ODDPubb (https://github.com/quest-bih/oddpub) text mining algorithm to determine the extent of data sharing and identify the repositories where the data was shared. In addition to the results from ODDPubb, manual analysis was conducted to confirm the presence of data sharing statements, assess data availability, and identify the repositories used.
Open Science, ODDPub, Open Data, Data availability statement, Research data
Open Science, ODDPub, Open Data, Data availability statement, Research data
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
