If you are interested in working with data, you've come to the right place! Below you will find some guiding principles and questions that you may find helpful as you begin your research. Use the lefthand navigation bar to jump to information about the ethical use of data, citation and documentation, creating data visualizations, and for a wide range of public and subscription data sources.
For better or worse (as defined and measured and reported by whom?), we live in a data-driven world. It can feel like everyone is talking about data and everyone is talking about it differently - and that is true! Economists, Sociologists, Biologists, and Humanists might all have something slightly different in mind when thinking about data. However, at its core, data is simply the building blocks of information. Once humans organize, code, and interpret data, it becomes useful, actionable information. One could argue that everything is data!
It is our goal that every member of our community become comfortable finding, reading, evaluating, and working with data.
Defining and refining your data need:
Why are you looking to engage with data?
Are you making a qualitative or quantitive argument? Perhaps both?
What variables inform your research question?
Do you want data or statistics?
Data is uninterpreted, while statistics are data that have been processed and analyzed
Now let's think about your ideal data set. What does it look like?
What observational unit do you need?
To best answer your question, would individual, community, regional, or national data work best?
What time period are you looking for?
What geographical area are you interested in?
What frequency would be ideal?
Would your ideal dataset include daily, weekly, monthly, annual, or decennial data?
The ideal data set is almost never waiting for you to find it, unfortunately. As you begin your search, cast a wide net and think about:
Who else would be interested in this topic?
Where would they be sharing this information?
Data literacy is the ability to read, interpret, analyze, and apply data. Broadly speaking, it is the ability to both comprehend and communicate with data. Below are a collection of resources to help you hone your data literacy skills.