Open Data Summit 2026

The Vermont Open Data Summit 2026, hosted by the Vermont Research Open Source Program Office (VERSO) and the UVM Libraries, brings together researchers, students, data practitioners, government staff, and community members to share, learn, and build around open data. This free, single-track conference supports UVM's and Vermont's commitment to transparent, accessible, and community-driven research and public data.

Whether you work with data professionally, teach with it, or are just getting started — this event is for you. Come ready to connect with a growing community of open data practitioners from across the university and the state.

What are the Details?

• When: Friday, October 9, 2026 | 10:00am – 4:00pm (EST)
• Location: Innovation Hall, Room E105, University of Vermont, Burlington, VT
• Format: Single-track conference with talks, presentations, and discussion
• Attendance: Open to UVM students, faculty, staff, and the broader Vermont community
• Capacity: Limited to 120 participants — register early!
• Cost: Free to attend; pre-registration is required
• Food: Morning snacks, coffee, and tea provided; lunch included

Schedule

The Importance of Shared Data: The Vermont Data Collaborative

Serena Buono, Research & Policy Assistant, Leahy Institute for Rural Partnerships

Crafting creative solutions to Vermont's challenges requires access to reliable and useful data. However, Vermont's current data ecosystem is fragmented, with many datasets outdated or simply hard to find and access. When data is this inaccessible, well-informed decisions require more time and resources, which many rural Vermont towns cannot spare. Local organizations also suffer when they cannot use this data to advocate for improvements in their communities.

This session showcases a solution: the Vermont Data Collaborative (VDC), a partnership between UVM's Leahy Institute for Rural Partnerships, the Vermont Research Open Source Program Office (VERSO), and the Center for Rural Studies. The VDC is a platform that consolidates data from local, state, and federal public sources and allows users to compare relevant statistics and metrics across the state in a variety of customizable visuals. Everything is organized around challenges your community might be facing, from housing to hazard mitigation. This lets users clearly identify their community's biggest issues and track progress in comparison to other regions. Rural communities benefit from tools geared toward the questions they are asking and that recognize the capacity limitations of local leadership. Across Vermont, the VDC can become an asset to local organizations working to solve regional issues and can amplify the important work already being done at the community level.

The first half of the session will present the VDC as a solution to Vermont's data challenges, including a live demonstration. The second half will be a question-and-answer period and group discussion about how the VDC can benefit rural communities and the issues they face.

Where Are Vermont Businesses Disappearing? An Open-Data Look at Business Closures Across Vermont

Jiya, High School Student

Vermont small businesses play an important role in local communities, but individual business closures can make it difficult to understand broader patterns across the state. This project asks: How have business closures changed over time, and how do closure patterns differ by industry and community?

Using publicly available economic and business data, I will examine business establishments over time and look for patterns in when businesses close, which industries are most affected, and whether closure patterns vary across Vermont communities or regions. The goal of this presentation is not to speculate about why individual businesses closed, but to use open data to identify patterns that may be difficult to see when looking at individual businesses or communities in isolation. I am interested in whether certain industries or areas experience different levels of business turnover and what those patterns might mean for future research into Vermont's local economy.

The presentation will explain the data sources, methods, and findings. As a high school student interested in business, economics, and community development, I became interested in this question by learning about local Vermont businesses and economic development efforts. This project is an opportunity to move from individual observations to a broader, data-driven examination of Vermont's changing landscape.

AMMonitor: An Open-Source Ecosystem for Remote Wildlife Monitoring

Laurence Clarfeld, Research Associate, Vermont Cooperative Fish and Wildlife Research Unit, University of Vermont

The AMMonitor R package, developed by the Vermont Cooperative Fish and Wildlife Research Unit, provides an adaptive framework for remote monitoring of biodiversity using trail cameras and acoustic recorders. Through partnerships and data management workflows, the platform supports the collection, organization, publication, and reuse of large ecological monitoring datasets. To date, ~2 million trail camera images and thousands of hours of acoustic recordings from 15 AMMonitor projects have been released through USGS ScienceBase with standardized metadata designed to facilitate discovery, interoperability, and reuse.

The openly available datasets have supported a growing range of applications, including integration into new data repositories and the development of AI models for automated species recognition. In this presentation, we describe the AMMonitor ecosystem, its data publication workflow, currently available datasets, and future development plans. We also share lessons learned from implementing large-scale ecological monitoring in an open-source environment, including challenges related to data management, metadata standards, and the technical capacity required to deploy and maintain monitoring workflows. Finally, we introduce the Alliance for Monitoring Biodiversity and Ecosystems Remotely (AMBER), which builds on the AMMonitor ecosystem by providing shared infrastructure and services, including data storage, AI-enabled media analysis, and data publication, helping organizations with limited technical resources participate in large-scale biodiversity monitoring and open data initiatives.  

Evaluating Hydrologic Response to Rain-on-Snow Events in NOAA's National Water Model

Will Behm, Graduate Research Assistant, Water Resources Institute

Rain-on-snow (ROS) events produce a wide range of streamflow responses due to complex hydrometeorological processes within a catchment, ranging from no marked hydrograph rise to devastating floods. A current priority in the global hydrology community is improving mechanistic understanding of ROS events so they can be accurately represented in operational forecasting tools such as NOAA's National Water Model (NWM).

Using publicly available datasets, I delineate 51,160 ROS event-response windows from a new dataset of ROS days at USGS Geospatial Attributes of Gages for Evaluating Streamflow (GAGES-II) reference basins, covering the continental United States from October 10, 1979, to September 23, 2022. Within these windows, I obtain observed and NWM-simulated streamflow data and derive event-scale performance metrics. I plan to evaluate the NWM's performance across the range of observed hydrologic responses to ROS using signature-based clustering and interpretable machine learning techniques such as random forest (RF) and Shapley Additive Explanations (SHAP). This data-driven approach may identify mechanisms or parameters that cause the NWM to underperform for certain ROS events, which could guide future model versions and further research on the principles governing ROS response.

This ongoing M.S. thesis research uses open datasets and reproducible scientific programming workflows (e.g., Snakemake, Quarto, uv).
 

Registration

Registration is free and open to UVM students, faculty, staff, and the broader Vermont community. Space is limited to 120 participants, so we encourage you to register early once registration opens.

Registration will open closer to the event. Check back here or follow VERSO's website for updates.

Venue

The Vermont Open Data Summit 2026 will be held in Innovation Hall, Room E105 on the University of Vermont campus in Burlington, Vermont.

Innovation Hall is located at 85 South Prospect Street, Burlington, VT 05405. Parking is available in the nearby Gutterson/Wheelock parking area. UVM's Campus Transportation page has details on parking, transit, and bike facilities.

About the Summit

The Vermont Open Data Summit is an annual conference that grows out of VERSO's commitment to building a regional culture of open data and open science. In January 2025, VERSO and the UVM Libraries co-hosted the first Data + Open Science Summit, bringing together approximately 80 faculty, graduate students, and staff for three days of workshops and presentations featuring speakers from NASA, the Software Carpentries, and across UVM.

The 2026 Summit expands that model — broadening participation to the full Vermont community, focusing on open data as a civic and research resource, and shifting to a community-curated program through an open call for talks. The event is supported in part by NSF Award #2531964, Empowering Vermont Open Data, which funds VERSO's work to build sustainable FAIR data infrastructure and open science capacity across Vermont.

Partners and Sponsors

The Vermont Open Data Summit 2026 is co-hosted by:

• Vermont Research Open Source Program Office (VERSO), University of Vermont
• UVM Libraries, University of Vermont
• Funding in part by the NSF FAIROS #2531964, "Empowering Vermont Open Data"

Interested in sponsoring or partnering with the Summit? Contact us.

Code of Conduct

This event is held under the University of Vermont Code of Conduct. The University of Vermont is committed to continually strengthening its ethical culture. From the University's motto of "Studiis et Rebus Honestis" (Integrity in Theoretical and Practical Pursuits) to our values stated in Our Common Ground, all participants are expected to engage respectfully and ethically. We are dedicated to providing a welcoming and inclusive experience for everyone, regardless of background, identity, or experience level.