Data Curation Network (DCN)

The Data Curation Network (DCN) is a real, named membership organization — not to be confused with data curation as a generic activity or data curator as a generic role. DCN is a consortium of academic and non-profit research-data repositories that pools trained data curators across its member institutions, so that a dataset arriving at any one participating library can be reviewed by a curator with the right subject or format expertise, even if no one on staff at that specific institution has it. It is administratively hosted by the University of Minnesota Libraries.

Origin

DCN launched publicly in April 2018, funded by a three-year Alfred P. Sloan Foundation grant. The founding member institutions were the University of Minnesota Libraries, Johns Hopkins University’s Sheridan Libraries, the University of Michigan Library, the University of Illinois at Urbana-Champaign Library, Cornell University Library, Penn State University Libraries, Dryad Digital Repository, and Duke University Libraries. The network has since grown beyond this founding cohort; current membership is listed on the organization’s own site.

What DCN actually does — the shared-staffing model

The problem DCN was built to solve is a real operational bottleneck in institutional data repositories: a single library’s repository may receive datasets spanning dozens of disciplines — genomics, geospatial survey data, qualitative interview transcripts, simulation output — and no repository can staff in-house expertise for every one of those data types. DCN’s model addresses this by connecting member institutions to a shared pool of curators, so a dataset can be routed to whichever network curator has the relevant domain or format background, regardless of which institution employs that curator or which institution’s repository the dataset is going into.

In practice this means member-institution staff submit a dataset for curation review through the network, a matched curator elsewhere in the network performs the review (checking documentation, file formats, metadata completeness, and reusability against the standards the receiving repository has adopted), and the results go back to the submitting institution. This is meaningfully different from a repository simply accepting whatever a researcher deposits: the network model is built specifically to make specialist-level review available to institutions that could not justify hiring that specialism on their own.

How DCN relates to the generic terms

Data curation the activity — organizing, describing, validating, and preserving a dataset so it’s usable by someone other than its creator — and data curator the role are generic, standard-agnostic concepts that apply regardless of who is doing the curating or where. DCN is one specific organizational answer to the question of how an individual institution gets access to curation expertise: rather than every library independently building out full in-house curation capacity, DCN lets institutions share it. A repository can practice data curation and employ data curators without any involvement in DCN at all; DCN is a named consortium that happens to be one widely-cited model for delivering that activity collaboratively, not a synonym for the activity itself.

Example

A mid-sized university library operates an institutional data repository but has no staff member trained in curating genomic sequencing data. Through DCN, the dataset is routed to a curator at a different member institution with that specific expertise, who reviews the deposit’s documentation and file formats before it is published in the submitting institution’s repository — without the submitting institution needing to hire that specialism directly.

Counter-example

A university library’s in-house data services team reviews and curates a deposited dataset entirely using its own staff, with no involvement from any external network or consortium. This is still data curation in the generic sense, and the reviewer is still a data curator — but it is not an instance of the Data Curation Network specifically, since DCN refers to the named, cross-institutional pooled-staffing consortium, not to any curation work performed independently.