Ten simple rules for using public biological data for your research
PLoS Computational Biology, ISSN: 1553-7358, Vol: 19, Issue: 1, Page: e1010749
2023
- 3Citations
- 26Captures
- 1Mentions
Metric Options: Counts1 Year3 YearSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations3
- Citation Indexes3
- Captures26
- Readers26
- 26
- Mentions1
- Blog Mentions1
- 1
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Article Description
AWUith: aPnleianscerceoansfiirnmgthaamtaolulhnetaodfinbgiolelovgeliscaarledraeptareasvenatieladbcloerrpeucbtllyic: ly, there is a need for a guide on how to successfully download and use this data. The 10 simple rules for using public biological data are: (1) use public data purposefully in your research; (2) evaluate data for your use case; (3) check data reuse requirements and embargoes; (4) be aware of ethics for data reuse; (5) plan for data storage and compute requirements; (6) know what you are downloading; (7) download programmatically and verify integrity; (8) properly cite data; (9) make reprocessed data and models Findable, Accessible, Interoperable, and Reusable (FAIR) and share; and (10) make pipelines and code FAIR and share. These rules are intended as a guide for researchers wanting to make use of available data and to increase data reuse and reproducibility.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85145669028&origin=inward; http://dx.doi.org/10.1371/journal.pcbi.1010749; http://www.ncbi.nlm.nih.gov/pubmed/36602970; https://dx.plos.org/10.1371/journal.pcbi.1010749; https://dx.doi.org/10.1371/journal.pcbi.1010749; https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1010749
Public Library of Science (PLoS)
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