PIDs and the discoverability of relevant research data

Post by Audrey Hamelers, Senior Software Developer and the Dryad team

Is there a published article associated with a particular dataset? Have the authors deposited any other data? Are there other Dryad datasets associated with the same journal?

Following an update to our interface, that information is now included in Dryad search and on our dataset landing pages. The change offers researchers, administrators, compliance officers, and others a more networked view of our data. Now, users can more easily discover related datasets, and answer questions about the association of Dryad data with specific publications, institutions, funding bodies, and individual researchers.

Persistent identifiers, or PIDs make these powerful connections possible. URLs can degrade. Names can change, or two people may share the same name. Article and dataset titles are often confusingly similar. PIDs are unique codes used to identify digital objects durably over time, and to forge connections between related research data, individuals, organizations, and other digital records. Common examples of PIDs in scholarly communications include DOIs for articles and datasets, ORCID IDs for people, and ROR numbers for institutions.

See For authors: What are PIDs and how do they amplify your data’s impact?

DOIs and ISSNs connect Dryad data with related research

All Dryad submissions are assigned a Digital Object Identifier (DOI), registered through our partners at DataCite. DOIs, as persistent identifiers which individually identify a dataset and resist breaking over time, are preferred links for reference lists, and turn Dryad datasets into citable objects.

In turn, Dryad uses DOIs to link data publications with other publishable and citable research outputs such as articles, preprints, other datasets, and software. These links are displayed along with the data on Dryad to provide context and further information about the data.

Dryad also captures the ISSN (International Standard Serial Number) of the publication where the primary article associated with a Dryad dataset is published. ISSNs identify periodicals. They are among the oldest PIDs, predating digital journals and most digital objects. The ISSN allows users to locate additional Dryad datasets associated with the same journal.

ROR IDs connect Dryad data with institutions

Dryad can also link datasets to associated institutions. Dataset authors are affiliated with institutions, perform their research at specific sites, or receive funding to collect data and perform research. For all of these associations, Dryad uses Research Organization Registry (ROR) to identify each organization and associate it with the dataset. These links now appear on dataset landing pages and in data searches, allowing users to click through to view other datasets from the same institution.

ORCID iDs connect Dryad data with researchers

When submitting, authors login in to Dryad with their Open Researcher and Contributor ID (ORCID). Upon publication of the dataset, coauthors are invited to associate their ORCIDs with the dataset as well, and to add the Dryad dataset to their personal ORCID bibliography. ORCID iDs unambiguously identify researchers, differentiating them from others with similar names to ensure research outputs are correctly credited.

On Dryad dataset landing pages, the names of authors who have associated their ORCID with the data now link to searches for their ORCID iDs. The search results create a collection of all the datasets which that specific researcher has published and claimed on Dryad.

Datasets in context

Datasets do not exist in a vacuum. By surfacing the connections between Dryad datasets, authors, and related institutions and publications, we aim to place the research in context, facilitate connections, and increase data discovery, access, and reuse. We believe that open data availability and routine reuse can drive progress, accelerate discovery, and benefit society worldwide.

Funding
This work was, in part, funded by the U.S. National Institutes of Health, Office of Data Science Strategy and the Generalist Repository Ecosystem Initiative (GREI) OTA-21-00 [3OT2DB000005-01S3]. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the NIH.

 

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