Image Description: Person using a laptop to interact with a dataset on a laptop.
There are many reasons why you may want to use existing data. Below are some examples of common reasons to reuse data:
We are incredibly lucky to live during a time when the amount of available digital data is skyrocketing! Using existing data for research projects can help save time and money, and supports innovation within the scholarly community. For more information on the benefits of reusing data, please visit this resource:
When citing data which was gathered by another researcher or organization, it is important to appropriately cite where you obtained the data to give them proper credit. In general, your citation should include information on:
DataCite offers a recommended format for data citation at the following website: https://datacite.org/cite-your-data.html
Open data can be found in a variety of places, and knowing where to look can feel a bit daunting! Below, we've included some links to other LibGuides and external resources to help you find the data you need:
Business and Economic Datasets: https://guides.library.cmu.edu/datasets
Finding & Using Social Science Data from ICPSR: https://guides.library.cmu.edu/ICPSR
Find Data for Text Mining: https://guides.library.cmu.edu/c.php?g=827727&p=5916796
Open Data Repositories
Search Engines for Data
DataONE Search: a platform for finding open data on environmental and earth science topics from across the world, with descriptive metadata for each available dataset.
When looking for data, ask yourself the following questions:
Navigating whether you can reuse data in your research can be a tricky process. Luckily, CMU Libraries can help you! Feel free to reach out to our Research Data Management Consultant Hannah Gunderman at email@example.com for help!
The CMU Libraries Data Collaboration Lab (DataCoLAB) connects the research community across disciplinary borders, and facilitates collaborations between data producers and data scientists. The program connects researchers who want more from their datasets with individuals who have data and computer science skills, creating opportunities for people with different technical and disciplinary backgrounds to work together.
Want to learn more or ask questions? Email dataCoLAB@andrew.cmu.edu.