Data Science Research Service

The Data Science Research Service (DSRS) drives research within the Gies College of Business by assisting students, faculty, and staff with their data science, machine learning, computational infrastructure, and data acquisition needs. The DSRS works as a component of the Gies Disruption initiative in efforts to make Gies the most technologically-forward and data-capable business college in the world.

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"The DSRS worked on research and boosted confidence in our statistical analyses to be sure our work was based on correct error term after using covariates. Sounds boring perhaps, but it was much needed!"

- Mark Peecher, Data Science Research Associate

About DSRS

Utilizing the DSRS supports faculty through a continuum of services with a highly qualified team of interns. We assess research studies to determine what type of data is needed and the type of computational infrastructure is necessary. We can recommend which statistical and data science methods are most appropriate for research questions, and we can execute these suggestions through machine learning, natural language processing, inferential statistics, and more.

At a high level, what can Data Science Research Service (DSRS) help with?

Assessment and recommendations of what statistical and data science methods are appropriate for your research question(s); some methods that may apply are as follows:
- Inferential Statistics
- Social Media Analytics
- Text Mining
- Natural Language Processing
- Machine Learning
- Deep Learning
Execution of statistical and data science methods for your research study
- This may include sub-contracting the analyses to other units on campus (such as the stats consulting office) in the case that certain methodological expertise exists at those units rather than the individuals in our group; we help to connect you to these resources.
Assessment and recommendations for computational infrastructure needed to execute specified data science methods for your research; infrastructure may include:
- On-Campus Computation
- Cloud Computing
- Custom-Built On-Premise Computation
Assistance in acquiring computational resources for executing data science methods to your research
- This may include sub-contracting the analyses to other units on campus such as NCSA in the case that certain computational infrastructure is already built or is more cost-effective to use on their side rather than within our office; we help to connect you to these resources
Assessment and recommendations for data needed to answer your research question(s), some data that may apply are as follows:
- Social Media Data
- Web Data
- Financial Data
Assistance in locating and acquiring data needed to answer your research question(s) (funds to acquire are your or your department’s responsibility)

What are the costs for these services?

The Gies College of Business has invested in this office, thus initial consultations and work are paid for by the college, although we generally work on a first-come-first-served basis. We retain the right to prioritize projects over others depending on the availability of resources, the specific nature of resources required, etc. Any purchase of sub-contracted analyses, sub-contracted computational infrastructure, computational infrastructure builds that are specific to your research study, and/or data for your research study will need to be paid for by your or your department’s research funding sources.

How is academic credit assigned?

As part of growing our services, we request that consideration for credit takes into account the following matrix. We are absolutely open to negotiating any of this, but this matrix is provided as a place to start conversations.

What we helped with (assessed at the end of the consultation)	What we commit to at this level	What we request for academic credit
We provided a general direction for how you should pursue applying data science to your research study (this includes an assessment of methodology, data needs, and computational infrastructure needs)	The director of DSRS will personally meet with you and provide oral recommendations of specific data science methods to use, data that may be useful, and resource recommendations to connect with	We request an acknowledgment of DSRS in the published research article within the acknowledgments section as well as a commitment to assist in the creation of internal college press releases promoting DSRS
We assisted with the acquisition of data and/or computational resources	We will work with Gies College of Business administration/purchasing to properly purchase data and/or computational resources for data science research	We request an acknowledgment of DSRS in the published research article within the acknowledgments section as well as a commitment to assist in the creation of internal college press releases promoting DSRS
We subcontracted the data science analyses for your research	- We will assist with the initial direction of the analyses being conducted by the subcontracted campus unit - We can help clarify any methodological questions that may arise between the researcher(s) and the subcontracted unit	We request an acknowledgment of DSRS in the published research article within the acknowledgments section as well as a commitment to assist in the creation of internal college press releases promoting DSRS
We executed the data science analyses for your research	- We will conduct the analyses - We will write up the methods and results section within your research article - We will revise the methods and results section within your research article during the revise and resubmit phase	We request consideration of authorship in your paper

What does the process generally look like?

Please begin by sending an email to dsrs@business.illinois.edu with a general explanation of the research study and question at hand. DSRS will then schedule an in-person or Zoom meeting with you to discuss the research study and provide recommendations on how to move forward.

We may not be able to provide immediate recommendations. We may need to do some additional research after listening to the research study details in full. In these cases, we will schedule a follow-up meeting to discuss our recommendations and move forward from there.

I'm a student. How can I get involved?

Students have the opportunity to in a welcoming team environment that emphasizes learning new skills, experimenting with fresh ideas and implementing data driven solutions to enhance faculty research. More more information about internship opportunities, please contact Matias Carrasco Kind.

Where can I find more information about becoming an intern?

The DSRS is regularly looking for data science student interns that will work on various data science projects. There are opportunities for students interested in data science and machine learning infrastructure, text and data mining, data science web visualization and data analytics, and data science business communications. Applications are accepted on a rolling basis. More information on students’ roles are available on the DSRS Gies Groups site.