Citing data not only provides proper attribution and credit, it also demonstrates the impact of your work and establishes research data as an important contribution to the scholarly record. Proper citation of data sources has both immediate and long-term benefits to users and producers of data, including:
increased transparency and reproducibility
makes it easier to find datasets
supports long-term persistence of datasets
encourages the reuse of data for new research questions
How to cite data
Citing data is very similar to citing publications; there are many formats to use, but we suggest including the following important information:
creator(s) or contributor(s)
date of publication
title of dataset
publisher
identifier (e.g. Handle, ARK, DOI) or URL of source
version, when appropriate
date accessed, when appropriate
Example:
Barclay, Janet Rice (2013) Stream Discharge from Harford, NY. Cornell University eCommons Repository. http://hdl.handle.net/1813/34425
In honor of Ada Lovelace Day, an international celebration of the contributions of self-identifying women in STEM, Mann Library is hosting a Wikipedia edit-a-thon, which will honor and highlight under-recognized women in science, technology, engineering, mathematics (STEM), and related fields. You can pitch in for just half an hour or the whole day, by writing an entry, adding a footnote, translating text, uploading images, or by looking up information for others.
We want to make Wikipedia a more inclusive space. While Wikipedia is the fifth most popular website in the world, reaching up to 32 million views a day, less than 18% of its English-language biographies are about women. No prior Wikipedia editing experience is necessary! Editing assistance will be provided as needed throughout the event for Wikipedia newcomers. Join the Wikipedia Dashboard to have your editing added to the event count. Learn more.