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To learn more about the RDMC Data Curation service or to obtain a quote, please submit a your request via the RDMC Services website.
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As a disciplined practice, data curation is essential for the long-term accessibility and usability of research data assets. Data curation goes beyond putting data files in a safe place. It not only anticipates inevitable changes in technology that are likely to make it impossible to open a file in a few years' time, but also it is sensitive to changes in how research is done. Even if data are housed in an established data repository, there are no guarantees that the files anyone, including you, will be usable able to use or even understandable understand them if the data are insufficiently documented. The video below offers a light-hearted (but very real) portrayal of why data curation should be incorporated into the research process.
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Data curation standards and best practices
The RDMC Data Curation service Service was designed to align with prevailing standards and best practices for research data management and sharing including the ones those listed below.
Data Curation Lifecycle Model. The lifecycle model emphasizes the holistic nature of data curation practice and its application throughout the research process from project conceptualization to data sharing.CURATE(D). The Data Curation Network, which is a membership organization of data repositories, developed a checklist of standard data curation steps for publishing high-quality data.
FAIR Principles. Originally published in Science in 2016, the FAIR Principles for findable, accessible, interoperable, reusable data have been promoted by major funding agencies as a set of recommended guidelines for ensuring access to scientific data.
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OAIS Reference Model. The Reference Model for an Open Archival Information System (OAIS) is an ISO standard (ISO 14721) that outlines recommend practices for digital archive organizations and the requirements of the systems they support.
CURATE(D). The Data Curation Network, which is a membership organization of data repositories, offers a checklist of standard data curation steps for publishing high-quality data.
RDMC Data Curation Service
The RDMC Data Curation Service is offered to UNC researchers to assist with data file preparation and transfer to a data repository. Working with the project team, RDMC data curation specialists will design and execute standards-based data curation workflows, which may include file format normalization, document preparation, metadata generation, dataset package quality review, and transfer of dataset packages to the specified repository. These curation activities consider the specific needs of the data according to their type, format, size, and content to help ensure that the data are findable, accessible, interoperable, and reusable (i.e., FAIR), and satisfy all requirements of the data management and sharing plan (DMSP).
Scope of work
The scope of work for the RDMC Data Curation Service scope of work for most projects will include the following primary data curation activities:
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Dataset file transfer. Upload of dataset files to a dataset record. Includes creation of file-level metadata, checksums review, application of access restrictions (if required), and inspection of files in the repository to confirm successful transfer.
For other data management and sharing needs that fall outside of this scope of work for the Data Curation Service, please visit the RDMC Add-on Services webpage for information about other services offered by RDMC that may meet project needs.
Requesting the Data Curation Service
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Once the RDMC team reviews submitted materials, you will receive a quote for the Data Curation Service for that includes a recommended scope of work. Please note that this quote is offered as a broad-brush scope of work estimate based on several assumptions about project needs and timelines. If these assumptions are inaccurate or if the scope of work changes, the associated fees will be updated.
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