Meet Elizabeth Wickes, Data Curation Specialist


Elizabeth with a rebuilt and functional Colossus computer at the British National Museum of Computing.

This post is the third in our series profiling the expertise housed in the Scholarly Commons and our affiliate units in the University Library. Today we are featuring Elizabeth Wickes, Data Curation Specialist.

What is your background education and work experience?

I started in psychology and then moved to sociology. I also have a secretarial certificate and I use that training a lot! I worked at Wolfram Research as a Project Manager and then Curation Manager before I started library school.

What led you to this field?

Data curation just finds you. It’s a path where people with certain interests find themselves in.

What is your research agenda?

I’m exploring new and innovative ways to teach data management skills, especially computational research skills that normalize and practice defensive data management skills.

Do you have any favorite work-related duties?

My favorite thing to do is leading workshops and teaching. I really love listening to people’s research and helping them do it better. It’s great hearing about lots of different fields of research. It’s really important to me that I’m not stuck in a single college or field, that we’re a resource for the whole university.

What are some of your favorite underutilized resources that you would recommend to researchers?

I think consultation services in library are underutilized, including consultation for personalized data management.

If you could recommend only one book to beginning researchers in your field, what would you recommend?

Where Wizards Stay Up Late by Katie Hafner and Matthew Lyon. It’s a book all librarians should read, and it would be great for undergraduate reading, too. It’s the history of how the internet was born, explained through biographies of the key players. The book also covers the social and political situation at the time which was really interesting. It’s fascinating that this part of the world (the internet, data curation, etc.) was developed by people who were in college before this was a major or a field of study.

There are a lot of statistics out there about how much data we are producing now: For example: “Data production will be 44 times greater in 2020 than it was in 2009” and “More data has been created in the past two years than in the entire previous history of the human race”… How do you feel about the increase in big data?

Excited. When people ask me “What is big data?” I tell them that there’s a technological answer and a philosophical answer. The philosophical answer is that we no longer have to have a sampling strategy because we can get it all. We can just look at everything. From a data curation and organizational perspective it’s terrifying because there’s so much of it, but exciting.

To learn more about Research Data Service, you can visit their website. Elizabeth also holds Data Help Desk Drop-In Hours in the Scholarly Commons, every Tuesday from about 3:15-5 pm. To get in touch with Elizabeth, you can reach her by email.

Getting Over Data Anxiety

For some people, looking at a spreadsheet brings back bad memories of sixth grade Pre-Algebra classes and mediocre grades. Unlearning your fear of numerical data may take time and patience, but will ultimately leave you a better, well-rounded researcher. Here are a few tips on how to start the process of embracing numbers in your research and life.

  1. Find data that interests you. If you weren’t someone with a heavy interest in math, the mere sight of an equation may make you shiver. That’s why it’s important to begin your journey with data by practicing with data that actually keeps you absorbed in your work. If you’re invested in the outcome, you’re more likely to put in the time and effort to learn skills and best practices that will ultimately make using data easier for you in the long run.
  2. Find some guidance. Staring at a sheet of numbers while scratching your head isn’t always a great plan. Find resources that will help you. Here at the University of Illinois, the Scholarly Commons, Research Data Service, and the Center for Innovation in Teaching & Learning offer frequent Savvy Researcher workshops to help people learn how to use data and corresponding software. You can also schedule a consultation request with a Scholarly Commons expert online, or e-mail the Scholarly Commons for simple questions. If you want to keep to yourself, there are also a number of data analysis LibGuides, which you can peruse.
  3. Start simple.  Don’t try to learn R in a day. You’ll end up frustrated and discouraged. Take some time to survey your options, and start simple, with Excel and SPSS, for example. Each software has unique things that it can do, and figure out a system that works for you.
  4. Understand why you’re doing this. Everyone has had the moment where they look at their research and think to themselves, “Why am I doing this? Why didn’t I go into the private sector?” It’s understandable. Looking at some of the incredible things people are doing with numerical data can help you remember why it is that you’re taking the time to learn these skills — which will actually be very marketable if you do decide to go into the private sector, just saying — and what you can do with them. A few favorite projects of mine are Institute for Health Metrics and Evaluation’s GBD Compare visualization, The Daily Routines of Famous Creative People by Mason Currey, and Two Centuries of US Immigration.

Just like any skill, learning how to handle and understand numerical data takes time and effort. But mastering data will add depth to your research, and allow you to present your findings in new, interactive ways.