Strengthening Scholarly Metadata with Persistent Identifiers

The scholarly publishing ecosystem consists of many different dimensions, including people, organizations/societies, publications, and the resources directly involved in the making of research. With so many elements in play, it is difficult to disambiguate all the individual data contributors tied to a specific research article as it goes through the publishing process. This can introduce risks to costs, data quality, accuracy, and tracking through editorial, production, publication, and beyond. To avoid confusion among these layers of data, publications, researchers, institutions, and funders can take advantage of persistent identifiers (PIDs) recommended and standardized by the scholarly community.

Assigning a unique iD to specific data elements rather than relying on free-text entry fields enables confidence in the reliability of submitted metadata from Authors, Reviewers, Editors, and other stakeholders. Taking the additional step of incorporating and leveraging standardized identifiers within publishers’ editorial and production tracking systems offer the advantage of a more seamless, interoperable workflow experience. Aries Systems has partnered with several respected identifier providers within the industry and has integrated their use within our Editorial Manager® (EM) and ProduXion Manager® (PM) workflow management solutions, including:

As identifiers are typically entered upstream during Author submission or other early stages of editorial, they are continually harnessed downstream, such as for advanced reporting by the journal, single sign-on options, depositing data to repositories, supporting grant applications, Reviewer recognition opportunities, or through connected third-party tools and services. For example, accurate researcher, funder, and institutional metadata can support the processing of Article Processing Charges (APCs) for open access workflows.

With the “Enter once, Use often” ideal, PIDs can empower stronger reporting with accurate attribution, save time and money with efficient use of resources, connect disparate data silos, and enable a virtuous cycle of identification.

*Infographic property of ORCID