DataLab FAQ

What is Data Science?

There are many definitions. But the broad, common answer is all of the activities involved in working with data: identifying, acquiring and accessing, transforming and manipulating, exploring, visualizing, modeling, summarizing data and making inferences from the data and making decisions based on these. It also involves data engineering, reproducibility, provenance and data governance and ethics. The entire process typically involves computing, statistics, visualization and domain knowledge.

What is DataLab?

The DataLab is a UC Davis-wide activity that aims to foster, promote and facilitate “data science” and “big data” across all disciplines in both research and education. Our goal is to help make qualitatively new research possible, accelerate data-driven exploration, and help train a new type of researcher that is skilled in working with data at all stages of the analysis pipeline.

To meet these goals, DataLab:

  • engages in collaborative research projects with faculty and students
  • provides consulting services to UC Davis researchers
  • offers training in intermediate and advanced data science topics
  • fosters a transdisciplinary data science community
  • organizes research clusters, reading groups, talks, seminars, colloquia, and symposia
  • develops and teaches short-format computational skills training opportunities
  • assists in integrating data literacy and computational thinking into the classroom

DataLab is supported by the Provost and Library, and evolved from the start-up UC Davis Data Science Initiative (2016-2019). DataLab is directed by the Executive and Associate Directors with engagement by its faculty Directors, a faculty advisory committee, and oversight by the Vice Provost for Digital Scholarship.

Does the DataLab offer courses?

We offer workshops, tutorials, seminars, and mini-courses. We collaborate with our faculty and affiliates on quarter-long courses. Our faculty engage in the broader data science academic landscape, including the development of new majors and curriculum.

Does the DataLab help graduate students with their research?

Yes! We have a core service of data science consultants that can advise with accessing, managing, analyzing and visualizing data as well as learning to work with new technologies. We can’d do your coding for you, but we can help convey best practices and debug your code. To learn more, check out our office hours.

Do we have to pay for consulting?

No! Because of support from the UC Davis Provost and Library, office hours are free for UC Davis researchers (students, postdocs, faculty and staff). A limited number of weekly consultations are also available for advice on more complex questions. Engagement of our data science and informatics teams to work on your start-up research projects is awarded on a competitive basis.

Is the DataLab interested in collaborations?

Absolutely! A major part of our mission is to help to provide important data skills to enable qualitatively new research. In addition to our competitive start-up collaborations, DataLab staff can also be contracted to work on extramurally funded research projects. Learn more about our collaborations.

Where is the DataLab located?

DataLab is housed on the third floor of the Shields library. Get directions to DataLab.

Who is involved with the DataLab?

Data-enabled researchers from across UC Davis engage with DataLab, including faculty, professional staff and graduate students and postdoctoral scholars. See our membership page for more information.

What facilities are in the DataLab space?

There is a classroom with projectors for workshops and seminars (room 360).
There are several conference rooms for consultation services with wide
screen TVs for pair programming. There is also a big work space for our DataLab Affiliates to collaborate and work in. The lab space has multiple white boards for sketching out ideas, many big computer monitors for affiliates to use, not to mention big TVs for broadcasting screenshots and webinars.

How do we find out about upcoming events?

Check out our calendar and sign up for our Data Science mailing list!