About
What is the best way to manage invasive buckthorn? How could species reintroduction change ecosystems? What improves ecosystem resilience? These are crucial questions in the restoration and conservation of biodiversity. Typically they would take years to answer through an exhaustive synthesis of the literature. We are going to try to answer them in a weekend.
Evidence Jam is a blitz-style hackathon that challenges teams to synthesize evidence using cutting-edge technology. This year we focus on causality. Six teams will be tasked with mapping the causes and effects in ecology to address three challenges: the use of LLMs for information extraction; the use of LLMs for question-answering; and the design and details of presenting such rich information.
Who Should Apply
- Software developers & ML engineers
- Restoration & conservation ecologists
- UX/UI designers
- Data scientists & knowledge engineers
- Philosophers of science
Team Size
Six teams of 2–6 people. You may apply as an individual and be matched to a team, or apply as a group. Interdisciplinary teams are strongly encouraged and will be prioritized.
Tracks
Teams pick one track. Each is a single open problem. Two cross-team check-ins over the weekend encourage collaboration and knowledge-sharing between tracks.
Turn papers into a causal graph
Given a corpus of restoration ecology journal articles, extract their causal claims into a graph. How much of the CAMO schema's richness you capture, and how you get there, is your call.
You get: the corpus, the schema, a few hand-annotated examples.
Judged on: accuracy, richness, cleverness, scalabilityAsk the graph
Build something that lets a restoration practitioner ask a question and get a trustworthy, evidence-grounded answer from a CAMO graph — without inventing anything the graph doesn't contain.
You get: a pre-built CAMO graph, the schema.
Judged on: usefulness, traceability, confidence, graceful "I don't know"Help a practitioner decide
Build an interface that helps someone planning a restoration make a decision from this evidence. What they care about: will it work, how sure are we, can it be undone, does it fit my site.
You get: evidence data, existing wireframes (use them or don't).
Judged on: real-world usefulness, honest confidence displayWhat is the Causal Mosaic Schema?
The core of this challenge is the Causal Mosaic Schema (CAMO) — a data schema written in LinkML that works like a fill-in-the-blanks form for documenting causal claims. If a researcher says "X causes Y," CAMO provides ways to document exactly how X causes Y and how certain the researcher is that the relationship is causal rather than correlational.
The schema has been collaboratively developed with philosophers of causality, including Dr. Phyllis Illari, who wrote the book on causality. All teams receive a half-page primer and a worked example graph as part of their starter repository.
What's in the repos
- The CAMO schema
- One worked sample graph
- A half-page primer
- Environment setup
Track extras
- Track 1: paper corpus, hand-annotated examples, held-out judging set
- Track 2: pre-built CAMO graph
- Track 3: practitioner evidence data, wireframes
Awards
Three award categories recognise the best solution in each track, sustainable AI practices, and outstanding collaboration.
Gold Raccoon — Best Solution
Awarded to the team delivering the strongest solution in each track. Prize details to be announced.
Green Raccoon — Most Sustainable Use of AI
Awarded to the team best demonstrating efficient, responsible AI use — thoughtful model selection, minimal compute footprint, and a sustainable approach throughout the weekend.
Most Valuable Possum — Best Collaborator
Voted on by all individual project participants. Awarded to the person who most enriched the weekend through cross-team collaboration, knowledge-sharing, and generosity with their work.
Schedule
Physical access to the DRAGEN Lab runs from 9 a.m. to 9 p.m. on Saturday and Sunday. Teams may submit jobs to the Nibi supercomputer at four checkpoints across both days. Two cross-team check-ins encourage collaboration between tracks.
Friday · November 13
Saturday · November 14
Sunday · November 15
Monday · November 16
The Space
Evidence Jam takes place in the DRAGEN Lab — the Medieval Digital Research in Arts and Graphical Environmental Networks Laboratory — at St. Jerome's University on the University of Waterloo campus. Founded in 2016, the DRAGEN Lab is a purpose-built digital humanities research space that deploys a collaborative, learner-centred approach to knowledge production across disciplines.
The lab occupies 3,600 ft² (242 m²) within the newly renovated St. Jerome's University Library. It was built to support exactly the kind of work Evidence Jam demands: expert and student researchers working side-by-side in teams, with access to high-performance computing, digital fabrication tools, and flexible collaborative space. It also includes a Makerspace with professional-grade 3D scanning, 3D printing, and high-performance computing units — a fitting home for a hackathon pushing the edges of AI-assisted ecological knowledge.
Photos via dragenlab.ca · St. Jerome's University, University of Waterloo.
Facilities
- 3,600 ft² collaborative lab space
- Makerspace with HPC units & fabrication tools
- Flexible team work areas
- GPU workstations for local model inference
- Strong campus WiFi throughout
Food & Coffee
Breakfast and lunch is provided on both Saturday and Sunday. Coffee is available from 9 am each morning. We are also planning an evening social event — details to follow. Participants with dietary requirements will be accommodated.
St. Jerome's University is located at 290 Westmount Road North, Waterloo, ON — a short walk from the heart of the University of Waterloo campus and accessible via the ION light rail. Learn more at sju.ca and dragenlab.ca.
Register Interest
Applications will be open to teams of 2–6. Teams are selected based on the range and quality of skills represented. Each applicant provides a ~150-word biography; one member is designated as the corresponding contact. Selected teams complete a Team Charter before the event.
You may also apply as an individual — we will do our best to match you with a team that complements your skillset.
Ready to map the evidence?
Registration is managed via Luma. Click below to register your interest —
full applications will open once the date is confirmed.
Sponsors & Partners
Evidence Jam 2026 is looking for sponsors to support prizes, food, and infrastructure. Prize categories include the Gold Raccoon, Green Raccoon, and Most Valuable Possum. We are particularly interested in contributions of API credits, hardware, cash prizes, and software subscriptions.
If your organization is interested in sponsoring, please contact Tim.A@uwaterloo.ca.
Organised by
Tim Alamenciak
Carleton University & University of Waterloo
Infrastructure
Nibi — Sustainable HPC
GPU Workstations — On-site inference
University of Waterloo
St. Jerome's University (venue)
Support
Evidence Jam 2026 is made possible through the support of the following organisations, who provide infrastructure, venue, and knowledge systems for the event.