The Resource Identification Initiative: A cultural shift in publishing - PubMed (original) (raw)
doi: 10.12688/f1000research.6555.2. eCollection 2015.
Matthew Brush 2, Jeffery S Grethe 1, Melissa A Haendel 2, David N Kennedy 3, Sean Hill 4, Patrick R Hof 5, Maryann E Martone 1, Maaike Pols 6, Serena Tan 7, Nicole Washington 8, Elena Zudilova-Seinstra 9, Nicole Vasilevsky 2; Resource Identification Initiative Members are listed here: https://www.force11.org/node/4463/members
Affiliations
- PMID: 26594330
- PMCID: PMC4648211
- DOI: 10.12688/f1000research.6555.2
The Resource Identification Initiative: A cultural shift in publishing
Anita Bandrowski et al. F1000Res. 2015.
Abstract
A central tenet in support of research reproducibility is the ability to uniquely identify research resources, i.e., reagents, tools, and materials that are used to perform experiments. However, current reporting practices for research resources are insufficient to allow humans and algorithms to identify the exact resources that are reported or answer basic questions such as "What other studies used resource X?" To address this issue, the Resource Identification Initiative was launched as a pilot project to improve the reporting standards for research resources in the methods sections of papers and thereby improve identifiability and reproducibility. The pilot engaged over 25 biomedical journal editors from most major publishers, as well as scientists and funding officials. Authors were asked to include Research Resource Identifiers (RRIDs) in their manuscripts prior to publication for three resource types: antibodies, model organisms, and tools (including software and databases). RRIDs represent accession numbers assigned by an authoritative database, e.g., the model organism databases, for each type of resource. To make it easier for authors to obtain RRIDs, resources were aggregated from the appropriate databases and their RRIDs made available in a central web portal ( www.scicrunch.org/resources). RRIDs meet three key criteria: they are machine readable, free to generate and access, and are consistent across publishers and journals. The pilot was launched in February of 2014 and over 300 papers have appeared that report RRIDs. The number of journals participating has expanded from the original 25 to more than 40. Here, we present an overview of the pilot project and its outcomes to date. We show that authors are generally accurate in performing the task of identifying resources and supportive of the goals of the project. We also show that identifiability of the resources pre- and post-pilot showed a dramatic improvement for all three resource types, suggesting that the project has had a significant impact on reproducibility relating to research resources.
Keywords: Multi-centre initiative; Post-pilot data; Pre-pilot data; Publishing; Resource identifiers.
Conflict of interest statement
Competing interests: The authors declared no competing interests.
Figures
Figure 1.. The Resource Identification Initiative portal containing citable Research Resource Identifiers (RRIDs).
The workflow for authors is to visit
http://scicrunch.org/resources
, then select their resource type (see community resources box), type in search terms (note that the system attempts to expand known synonyms to improve search results) and open the “Cite This” dialog box. The dialog shown here displays the Invitrogen catalog number 80021 antibody with the RRID:AB_86329. The authors are asked to copy and paste this text into their methods section.
Figure 2.. RRIDs found in the published literature.
A. Google Scholar result for the anti-tyrosine hydroxylase antibody RRID (9/2014;
http://scholar.google.com/scholar?q=RRID:AB\_90755
).B. The most frequently reported RRIDs in the first 100 papers, by number of papers using the identifier. All data is available in the Supplementary Table and all identifiers can be accessed in Google Scholar.
Figure 3.. Percent correctly reported RRIDs.
The percentage of resources that reported an RRID that pointed to the correct resource and with the correct syntax for each resource type is shown. The total number of resources for each type during the post-pilot is: primary antibodies, n = 429; organisms, n = 55; non-commercial tools, n = 78.
Figure 4.. Pre and post-pilot identifiability.
Resources (primary antibodies, organisms, and tools) were considered identifiable if they contained an accurate RRID or by using the same criteria as described in ( Vasilevsky_et al._, 2013). For tools (software and databases, which were not previously analyzed), these resources were considered identifiable if they contained an RRID or reported the manufacturer and version number. The total number of resources for each type is: primary antibodies pre-pilot, n = 140; primary antibodies post-pilot, n = 465; organisms pre-pilot, n = 58; organisms post-pilot, n = 139; non-commercial tools pre-pilot, n = 59; non-commercial tools post-pilot, n = 101. The y-axis is the average percent identifiable for each resource type. Variation from this average is shown by the bars: error bars indicate upper and lower 95% confidence intervals. Asterisks indicate significant difference by a z-score greater than 1.96.
Figure 5.. An exemplar third-party application using the RRID resolving service.
The “Antibody data for this article” application developed by Elsevier enhances articles on ScienceDirect. The application is available in 211 articles in 19 journals (more information can be found at:
http://www.elsevier.com/about/content-innovation/antibodies
).
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