Yes. We can help you with data preparation which includes (1) gathering and extracting data from sources, (2) reformating data, (3) consolidating and validating data, (4) transforming data, (5) data cleaning/cleansing, and storing data (Sherman, 2014).

If you're looking for more on this topic, check out Hadley Wickham’s well-known article “Tidy Data” (2014). It introduces the idea that data is easiest to work with when each variable is in its own column, each observation is in its own row, and each type of thing you're observing gets its own table. This approach forms the basis for what’s called “long” data, which is often easier to analyze than “wide” data. And for a critical perspective, check out “Against Cleaning,” by Katie Rawson and Trevor Muñoz. It explores how data cleaning can involve hidden assumptions and biases, and encourages us to think carefully about what we mean when we call data “clean” or “messy.”

Contact the Digital Scholarship and Publishing team to ask a question, set up a consultation, or learn more about the library's research data support services.