Discovery Exchange Overview

Brief Overview of the Discovery Exchange Program. Please be sure to make an account with your Berkeley email!

Introduction to Discovery Exchange

Through the Discovery Program, the UC Berkeley Division of Computing, Data Science, and Society (CDSS) has built a research incubator that leverages that wide use of data science to enhance student learning opportunities with real-world applications. 

To increase opportunities for student-led research, CDSS has launched the Discovery Exchange, an online hub for Berkeley students doing independent data science projects in Fall 2020 and beyond. The Discovery Exchange will provide a platform for Berkeley students to connect with their peers to:

What is research?

Projects can take many forms, informal research lab, working group, or learning support group. Throughout the semester you will learn about ways you can develop your projects and formalize them in the Spring through the Discovery Research program and Big Ideas Contest.

Who can participate?

Berkeley students from any background and level of exposure to data science can participate. Students with no data science background and curiosity for turning data into information are encouraged to participate. Students can find datasets on the web, through graduate student researchers, the library, or create their own. Remember that the semester yields about three months of research time, therefore it’s important to set realistic goals for what you want to accomplish.

Already working on a data-driven passion project? Post a description with us and get access to exclusive workshops and consulting hours, or recruit other students with diverse skill sets to join your team.

Undergraduate Students

We welcome undergraduate students who want to explore a tool or programming language over the semester with the support and accountability of a working group. Undergraduates can form and lead groups of only undergraduates or a mix of statuses. Students need only to have a project description and a timeline for accomplishing goals to post an opportunity. Upperclassmen can also host a workshop or lead a discussion about their experiences as a data scientist.

Graduate Students

Graduate students from any domain or degree are welcome to offer research opportunities and/or mentorship to students at any capacity to undergraduate Data Science students. Projects can be related to your thesis/dissertation or they can engage with other topics of interest, including co-creating a project. Graduate students can engage with Data Science undergraduates in an exchange by learning a new tool together, taking on a passion project (link is external), coaching undergraduates to apply a tool they are already familiar with in a new domain.

We also welcome you to offer your time to mentor students at a lower capacity if you do not have a specific project in mind. Graduate students can choose to be mentors over the semester, committing to at least one informal presentation to undergraduates interested in learning more about their work and academic experiences. Graduates can also practice teaching a lesson on data science applications in their field. 

Why participate?

Student-led data research labs have started to emerge in Berkeley as a way to maximize our capacity to ask questions and do the work to answer them through data analysis. While Data Science can be technically challenging and intimidating, students can reduce their anxiety by working together to learn and create. Tap into the Berkeley Data Science network with a low barrier to entry, collaborative research semester program led by students. 

The Fine Print

Discovery Exchange offers a support network, workshops, consulting, but no financial compensation or course credit at this time. We will be collecting feedback from participants on how to improve future iterations of the program. The main goals of running a pilot this year are: to help students get connected to the Berkeley Data Science ecosystem, stay motivated to learn during this hard time, and build a semester learning community.

Get creative, compensation can come in many forms: meeting learning goals, publishing a blog, paper, or a GitHub page with proper attributions of work contributed. While the Discovery Exchange Program does not offer course credit at this time, what you produce can be used in a portfolio of your work (link is external) that will help find a job or apply to graduate school. Fall research projects can also help students prepare to submit a proposal to the Discovery Research program during the Spring. The Division of Computing, Data Science, and Society also hosts multiple showcases throughout the year where your team can be invited to participate in a poster session or presentation. 

Office Hours

What are Office Hours? 

Office hours are a great way to touch base with a project manager to gain more insight on ways to elevate your project, access resources, build team-building skills, and more! This semester, office hours will be held virtually so you can have access to the Discovery Exchange from anywhere in the world. 

Drop-in office hours are available weekly for individual or group consultation! 

Shruti Bathia: Mondays 8am - 9am | Zoom (Links to an external site.)

Tiffany Taylor: Tuesdays 11am - 12pm | Zoom (Links to an external site.)

Arlo Malmberg: Tuesdays 4pm - 5pm | Zoom (Links to an external site.)

Alex Gao: Wednesdays 11am - 12pm | Zoom (Links to an external site.)

Alternatively, you can book a 1:1 appointment with the Discovery Exchange Staff at available times. These will be posted shortly! 

If you would like more technical help, please visit the Data Peer Consultants (Links to an external site)! They have office hours Monday-Friday from 11 AM - 4 PM PST. 

Ground Rules

Here are some ground rules for the Discovery Exchange: 

No Spam/Advertising/Self-Promotion

We define spam as unsolicited advertisement for goods, services, and/or other websites, or posts with little or completely unrelated content. Please make sure that the content you are posting is data science project related! Please do not spam the Discovery Exchange with links to your site/product, try to self-promote your website (if it's not a team project), etc. Spamming also includes sending private messages to a large number of different users. 

Do not post copyright-infringing material 

Providing or asking for information on how to illegally obtain copyrighted materials is forbidden. We want to make sure to support our peers and other data scientists in the data they collect, the work that they complete, and their intellectual property as a whole. 

Do not post "offensive" posts, links, or images

Any material which constitutes defamation, harassment, or abuse is strictly prohibited. Material that is explicit or otherwise obscene, racist, or otherwise overly discriminatory is not permitted on these forums. This includes user pictures. Use common sense while posting.

Do not cross-post questions/projects 

Please refrain from posting the same question in several sub-sections! You can use the "tag" feature if your project fits into more than one category to help students find projects. 

Remain respectful of other members at all times 

All posts should be professional and courteous. You have every right to disagree with your fellow community members and explain your perspective.

However, you are not free to attack, degrade, insult, or otherwise belittle them or the quality of this community. It does not matter what title or power you hold in these forums, you are expected to obey this rule.