The top strategy for finding data that already exists is to look in the academic literature. What data sources are researchers already using? Here's how to do this:
Ask yourself about your research question. What is your topic and what kind of claim do you want to make? Now consider, what kind of evidence would you need to support those claims? You can use that to describe your ideal dataset.
Ask yourself, in an ideal world, what do you want for your:
Keep in mind that just because you can imagine it, does not mean it exists. This is especially something to consider when you are under a tight deadline to finish a research project. (This is especially true for DMP projects at UVA.) These are common limitations to finding your perfect dataset:
Other ways to brainstorm is to consider who might have collected the data? Data are expensive and time consuming to collect. They don't just appear out of thin air. Common sources of data are:
You can also use specialized search tools. Take a look at the platforms listed on Find Data Archives and Find Data by Topic.
Ask yourself questions about the data that you find.
1. Find overview information
Who created the data? Why? What is the scope? What is the geography and time period?
2. Find technical documentation
Look for and download or document technical documentation about the dataset, including information on how it was created (e.g., survey, administrative reporting, direct measure), variable definitions, indications of what was included or excluded. Survey instruments are also helpful. Hint: look for a codebook, user guide, or documentation section of the site.
3. Identify the Download Options and Access Restrictions
Who gets to use the data? Contact a librarian if you are unsure if you can access it. What formats of download are available - CSV, text, Excel? If it is not formatted for the statistical package you use, contact a librarian for assistance.
Much of this content is adapted from:
Carleton College Gould Library. "Data, Datasets, and Statistical Resources - When you're not sure where to start."