Workflow for detecting biomedical articles with underlying open and restricted-access datasets.
To monitor the sharing of research data through repositories is increasingly of interest to institutions and funders, as well as from a meta-research perspective. Automated screening tools exist, but they are based on either narrow or vague definitions of open data. Where manual validation has been...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2024-01-01
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| Series: | PLoS ONE |
| Online Access: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0302787&type=printable |
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| author | Anastasiia Iarkaeva Vladislav Nachev Evgeny Bobrov |
| author_facet | Anastasiia Iarkaeva Vladislav Nachev Evgeny Bobrov |
| author_sort | Anastasiia Iarkaeva |
| collection | DOAJ |
| description | To monitor the sharing of research data through repositories is increasingly of interest to institutions and funders, as well as from a meta-research perspective. Automated screening tools exist, but they are based on either narrow or vague definitions of open data. Where manual validation has been performed, it was based on a small article sample. At our biomedical research institution, we developed detailed criteria for such a screening, as well as a workflow which combines an automated and a manual step, and considers both fully open and restricted-access data. We use the results for an internal incentivization scheme, as well as for a monitoring in a dashboard. Here, we describe in detail our screening procedure and its validation, based on automated screening of 11035 biomedical research articles, of which 1381 articles with potential data sharing were subsequently screened manually. The screening results were highly reliable, as witnessed by inter-rater reliability values of ≥0.8 (Krippendorff's alpha) in two different validation samples. We also report the results of the screening, both for our institution and an independent sample from a meta-research study. In the largest of the three samples, the 2021 institutional sample, underlying data had been openly shared for 7.8% of research articles. For an additional 1.0% of articles, restricted-access data had been shared, resulting in 8.3% of articles overall having open and/or restricted-access data. The extraction workflow is then discussed with regard to its applicability in different contexts, limitations, possible variations, and future developments. In summary, we present a comprehensive, validated, semi-automated workflow for the detection of shared research data underlying biomedical article publications. |
| format | Article |
| id | doaj-art-22fa9600cfd34044a6186338fd5d9527 |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-22fa9600cfd34044a6186338fd5d95272025-01-08T05:33:35ZengPublic Library of Science (PLoS)PLoS ONE1932-62032024-01-01195e030278710.1371/journal.pone.0302787Workflow for detecting biomedical articles with underlying open and restricted-access datasets.Anastasiia IarkaevaVladislav NachevEvgeny BobrovTo monitor the sharing of research data through repositories is increasingly of interest to institutions and funders, as well as from a meta-research perspective. Automated screening tools exist, but they are based on either narrow or vague definitions of open data. Where manual validation has been performed, it was based on a small article sample. At our biomedical research institution, we developed detailed criteria for such a screening, as well as a workflow which combines an automated and a manual step, and considers both fully open and restricted-access data. We use the results for an internal incentivization scheme, as well as for a monitoring in a dashboard. Here, we describe in detail our screening procedure and its validation, based on automated screening of 11035 biomedical research articles, of which 1381 articles with potential data sharing were subsequently screened manually. The screening results were highly reliable, as witnessed by inter-rater reliability values of ≥0.8 (Krippendorff's alpha) in two different validation samples. We also report the results of the screening, both for our institution and an independent sample from a meta-research study. In the largest of the three samples, the 2021 institutional sample, underlying data had been openly shared for 7.8% of research articles. For an additional 1.0% of articles, restricted-access data had been shared, resulting in 8.3% of articles overall having open and/or restricted-access data. The extraction workflow is then discussed with regard to its applicability in different contexts, limitations, possible variations, and future developments. In summary, we present a comprehensive, validated, semi-automated workflow for the detection of shared research data underlying biomedical article publications.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0302787&type=printable |
| spellingShingle | Anastasiia Iarkaeva Vladislav Nachev Evgeny Bobrov Workflow for detecting biomedical articles with underlying open and restricted-access datasets. PLoS ONE |
| title | Workflow for detecting biomedical articles with underlying open and restricted-access datasets. |
| title_full | Workflow for detecting biomedical articles with underlying open and restricted-access datasets. |
| title_fullStr | Workflow for detecting biomedical articles with underlying open and restricted-access datasets. |
| title_full_unstemmed | Workflow for detecting biomedical articles with underlying open and restricted-access datasets. |
| title_short | Workflow for detecting biomedical articles with underlying open and restricted-access datasets. |
| title_sort | workflow for detecting biomedical articles with underlying open and restricted access datasets |
| url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0302787&type=printable |
| work_keys_str_mv | AT anastasiiaiarkaeva workflowfordetectingbiomedicalarticleswithunderlyingopenandrestrictedaccessdatasets AT vladislavnachev workflowfordetectingbiomedicalarticleswithunderlyingopenandrestrictedaccessdatasets AT evgenybobrov workflowfordetectingbiomedicalarticleswithunderlyingopenandrestrictedaccessdatasets |