Code & Data for "Adoption of Transparency and Openness Promotion (TOP) guidelines across journals"
<p>This entry contains code and data that was used in the publication: "Adoption of Transparency and Openness Promotion (TOP) guidelines across journals" submitted in Publications journal.</p> <p>*It was version 2 when we added Fig_3_Tab2_Defining_science_disciplines_plus_plot.R script to version 1.</p> <p>*It was version 3 because we added script that calculates median and mean values of the stringency levels to version 2 data.</p> <p>*Latest version is version 4: we added supplementary data.</p> <p>#IDEA:</p> <p>This project was about analyzing policies of two thousand journals within the framework of eight TOP standards: <br> data citation, transparency of data, material, code and design and analysis, replication, plan and study pre-registration, <br> and two effective interventions: “Registered reports” and “Open science badges”. </p> <p># MATERIALS & METHODS<br> We downloaded the TOP Factor (v33, 2022-08-29 3:12 PM) metric from the https://osf.io/kgnva/files/osfstorage/5e13502257341901c3805317 <br> website and analyzed its content with an in-house R script (in this repo):<br> 1) SCRIPT: fig1_Analyzing_journals_policies_and_TOP_guidelines.R<br> 2) SCRIPT: Figure2a_b_TOP_impl_journal_statistist_0_1_piechart_barplot.R<br> In order to get statistics about implementation of the TOP guidelines across discipline-specific journals, <br> we extracted information about journal’s disciplines from the Scopus content database. <br> We downloaded SCOPUS content coverage from the https://www.elsevier.com/solutions/scopus/how-scopus-works/content?dgcid=RN_AGCM_Sourced_300005030 (existJuly2022.xlsx)<br> and used the first Sheet.<br> We identified match between those 2 tables: <br> 3) SCRIPT: Rscript_overlapping_TOP_dataframe_and_SCOPUS_db.R<br> And resulted in Overlap_SCOPUS_TOP.rds file<br> And performed visualization and statistics:<br> 4) SCRIPT: Fig_3_Tab2_Defining_science_disciplines_plus_plot.R</p> <p> </p> <p>#RESULTS Submitted to Publications 30.9.2022.</p> <p>Reviewed 2.11.2022.</p> <p>Latest version: 25.11.2022.</p>
ShareScore
32/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 0
- Engagement
- 4
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