Research and Learning Clusters

The DataLab Research and Learning Clusters (RLCs) are community driven, interdisciplinary groups of scholars that meet to learn and apply concepts and methods with an aim towards furthering their research and data capabilities.

Membership is open to the UC Davis community including undergraduate and graduate students, faculty, post docs, and staff. Each group acts autonomously with DataLab support including expertise, space, and infrastructure.

Active Clusters

Data Feminism

The Data Feminism RLC explores the interaction between systems of power and oppression within the development and application of the data sciences. Specifically, this working group examines the intersection of feminist theory, critical data studies, and data science within four themes surrounding data feminism: feminist critiques of data science, causes and consequences of the lack of diversity in the data sciences, how mis-applications of data science perpetuate social inequality, and critical and participatory data science.

Davis Python User's Group

D-PUG meets in the DataLab (Shields 362) to work through learning and applying Python for research. Meetups for Fall 2021 are Tuesdays 1-2:30pm. This group is run by Professor Andrew Fox with support from graduate student Cameron Riddel.

Davis R Users Group (D-RUG)

D-RUG is a community of R-Users at UC Davis who support each other in using R for science and research.  D-RUG meets weekly in the DataLab classroom (Shields 360) during the academic year to provide a space for beginning and intermediate users to learn from each other in an open and informal setting. Meetup times for Fall 2021 are Thursdays 10am-noon. Find more information join D-RUG’s listserv for meetup announcements and schedule.

Digital Humanities

The Digital Humanities RLC is an interdisciplinary research cluster that is designed to equip graduate students in the humanities with practical skills and knowledge in programming to assist with their research projects. It is a multi-year, ongoing cluster that accommodates all levels of experience, with topics, themes, discussions, and readings being decided collaboratively by attendees. The cluster is co-sponsored by DataLab and the English Department. For more information please contact DataLab Executive Director Carl Stahmer.

Health Data Science

Health Data Science (HDS)'s focus is on computing systems and approaches, data security technology, and analytic drivers to advance research on  health data. Examples of foci areas include secure virtual computing platforms for advancing machine learning capabilities and analysis on protected health information (PHI) data. This cluster serves as a hub for the community with bi-weekly meetings, short lectures and thematic discussion groups, and will serve as a home for the interdisciplinary scholars in computer science, health informatics, and data science to develop next-generation systems for health data science research. Meetups in Fall 2021 are bi-weekly on Fridays noon-1pm.

Spatial Sciences

The Spatial Sciences Research & Learning Cluster is a community for people (undergraduate and graduate students, faculty, post docs, staff, etc.) at UC Davis and our immediate community with an interest in working with spatial data. Participation is open to everyone, at any skill level. The Spatial Sciences Research & Learning Cluster is a welcoming and supportive community. Meetups in Fall 2021 are Tuesdays 10am-noon.

Past Clusters

Applied Bayesian Statistics

Our RLC is convening an Applied Bayesian Statistics cluster to work through an finalized copy of the recently released 2nd edition of former UC Davis Professor Richard McElreath's Statistical Rethinking. Each week, we'll discuss the text and problem sets of a single chapter of the Rethinking text. Participants are expected to have independently engaged the material between meetings and come prepared with thoughts and confusions. Most meetings cover a single chapter of the book and focus on discussing Bayesian theory and applications (i.e., chapter content and problem sets), with extensions into the participants' own work.

Hack 4 California

The Hack for California RLC provides a space for civically-minded data scientists, social scientists, and humanists to collaborate in critically examining how open government data can be configured towards understanding social and environmental inequities. We convene weekly to identify pressing issues throughout the state of California and examine the availability and quality of open government data resources for evaluating their impact on communities. We interview and co-design with relevant stakeholders to produce maps, dashboards, and/or other tools that help to translate the nature of the problems, legitimate their stakes and urgency, while constantly assessing the risks such data aggregations pose to those represented by the numbers.

Network Science

The Network Science Research and Learning Cluster is dedicated to network data analysis and research. The cluster is headed by Raissa D’Sousa, Mark Lubell, and Tyler Scott. To learn more about the cluster, subscribe to the network_science mailing list.