How it works
The DataSquad model
A DataSquad is a team of paid undergraduate analysts who help researchers work with data. The model is deliberately portable: the network defines what a DataSquad is and how squads coordinate, and each institution runs the day-to-day its own way.
What a DataSquad does
Squads support researchers, instructors, and staff across the full life of a data project. The exact mix grows with each squad's skills.
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Data wrangling & transformation
Accessing, importing, cleaning, and restructuring data from files, APIs, and cloud platforms.
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Data management & lifecycle
Combining datasets, querying databases, and planning how data is managed, published, and preserved.
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Visualization & storytelling
Building clear visualizations and advising on choices that match the research question and audience.
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Reproducibility & open science
Testing whether code runs start to finish, reviewing documentation, and adopting open practices.
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Statistical & analytical support
Helping researchers choose appropriate methods and interpret results in R, Python, Stata, or SPSS.
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Emerging methods
Geospatial workflows, 3D and immersive data, and other new modalities as squads grow into them.
What a DataSquad doesn't do
The guardrails matter as much as the services. They protect researchers' trust and keep students in a supportable role.
- We help researchers work with their data, we don't alter or reinterpret its substance, or change their research questions.
- We hold consultations in confidence and stay neutral about the research itself.
- It's research support, not the research, and not tutoring or homework help.
- Students ask for help early; staff back them up. No one is left stuck alone.
Who's on a squad
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Data analysts
Undergraduates who do the hands-on data work with researchers.
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Technical writers
Students who document projects, write guides, and keep the squad legible.
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Project manager
A student lead who triages requests and keeps work moving.
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Program staff
Library or department staff who supervise, fund, and sustain the program.
Shared model, local autonomy
You adopt a model and a community, not a software stack. The network standardizes the minimum that makes squads interoperable and leaves the rest to you, so you can launch with the tools your institution already has.
| Piece | Layer | |
|---|---|---|
| What a DataSquad is and does | Network | The definition, services, and tenets below |
| Service scope & guardrails | Network | A policy template you adapt |
| Role shapes & onboarding pattern | Network | Portable; titles are yours to set |
| Network coordination & peer support | Network | GitHub Projects + Discussions |
| Researcher intake & scheduling | Your institution | UCLA uses LibCal; you choose |
| Request & project tracking | Your institution | GitHub Projects is the shared default |
| Funding, payroll & HR | Your institution | Wholly institutional |
Think this fits your institution?
See the adoption path and what you'll need to launch.
How to adopt the model →