The Resource Identification Initiative: A Cultural Shift in Publishing

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 identify the exact resources that are reported or to answer basic questions such as "How did other studies use 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 articles and thereby improve identifiability and scientific 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 articles prior to publication for three resource types: antibodies, model organisms, and tools (i.e., software and databases). RRIDs are assigned by an authoritative database, for example, a model organism database 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 (http://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 articles have appeared that report RRIDs. The number of journals participating has expanded from the original 25 to more than 40, with RRIDs appearing in 62 different journals to date. Here we present an overview of the pilot project and its outcomes to date. We show that authors are able to identify resources and are supportive of the goals of the project. Identifiability of the resources post-pilot showed a dramatic improvement for all three resource types, suggesting that the project has had a significant impact on identifiability of research resources.

Keywords: Resource Identification Initiative; identifiability; research resources.

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.

Figure 2

RRIDs found in the published literature. Google Scholar result for the anti‐tyrosine hydroxylase antibody RRID (9/2014; http://scholar.google.com/scholar?q=RRID:AB_90755) and the most frequently reported RRIDs in the first 100 articles, by number of articles using the identifier. All data are available in the Supplementary Table and all identifiers can be accessed in Google Scholar (see also Supplemental Table).

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; noncommercial 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; noncommercial tools pre‐pilot, n = 59; noncommercial 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).