Thank you for visiting the “eScience Portal for Librarians.” The “eScience Portal” is no longer being maintained by the University of Massachusetts. This regional resource has been adapted by the National Network of Libraries of Medicine, and is sustained by the network of regional medical libraries across the country. Please visit for up-to-date data services and resources supported and vetted by the National Libraries of Medicine. We look forward to your continued involvement in the programming in the New England Region and beyond. If you have questions, please contact



DataCite is a global not-for-profit international organization formed in London in December 2009. DataCite is a resource for researchers and librarians to find information about data citations and to keep up on new developments in data citation. Working in e-science and data management, librarians may be called upon to help a researcher locate a specific dataset and help that researcher cite that dataset correctly. A librarian may also be called upon to help a researcher create a citation for their dataset or assign a Digital Object Identifier (DOI) so that others can locate and use the dataset with proper attribution. DataCite serves as a platform that provides a data citation format and assigns DOIs to datasets.

DataCite also provides librarians with a metadata schema that describes what information should be included in a dataset for citation and retrieval purposes, along with recommended use instructions. This schema can assist in data management planning, as it provides clear examples of the types of descriptors needed to describe a dataset.

DataCite’s mission to provide data citations and persistent identifiers for attribution is relevant because universities such as Columbia are now adding a researcher’s data as an output that can count towards his or her tenure or promotion. Therefore, librarians should be encouraging their researchers to cite data correctly and to ensure that their own data is cited correctly so that they can give and receive the proper attribution for their data.