Data for Democracy

Session Schedule

Community-Based Research: Lessons from Three Connecticut Projects

Academic and nonprofit researchers strive for community participation whenever possible. In this session, learn how researchers in different contexts engage community members in data analysis and research and support their lived experiences as expertise.

Community Vulnerability vs. Deprivation: Analyzing Spatial Equity Data

Analyzing GIS data is a powerful tool in any analyst's toolkit. In this session, Emil Coman from the Health Disparities Institute at University of Connecticut School of Medicine and Shayna Cunningham, Assistant Professor at UConn Health, will show how combining the use of Excel, GeoDa and PolicyMap to analyze census tract-level socioeconomic indicators from the Area Deprivation Index and Social Vulnerability Index, can result in powerful analysis to address inequities. We will demonstrate how to open files, aggregate data across different geographies, and analyze correlation and spatial statistics. By applying these methods, you will leave with a better understanding of how to utilize spatial analysis in your equity work.

Connie: Transforming Healthcare Through Data Equity and Integration  

Connie, Connecticut's designated Health Information Exchange (HIE), has rapidly become a vital part of the state's healthcare infrastructure, connecting over 3,100 provider locations. Amanda Crociata, Director of Account Management at Connie, and Russel Dexter, Director of Analytics and Data Quality at Connie, will explore how Connie is enabling better care coordination, improving health outcomes, and advancing health and data equity as a neutral, nonprofit platform that ensures all providers can access and share patient information efficiently and equitably. You will learn about the legislative foundation behind Connie's creation, how its services support personalized care while empowering patients with access to their own health information, and how these tools can support health data equity and are transforming healthcare delivery in Connecticut.

Data, Dialogue, and Decisions: Embedding Continuous Learning with the Action Review Toolkit

Many organizations rely on After Action Reviews to reflect on what happened, but in complex environments, hindsight alone is often insufficient. This session introduces the Action Review Toolkit—a structured approach that embeds foresight, insight, and hindsight into how teams learn from data and experience throughout an initiative's lifecycle.

You will explore how to conduct Before Action Review, In Action Review, and After Action Review sessions using key guiding questions, integrate program data into real-time learning, and foster inclusive dialogue through intentional facilitation. This session also explores listening as a core learning practice, offering practical tools for more intentional and timely reflection grounded in data.

Data as Civic Engagement: Communities Thrive When They're Informed

Filling out a survey can be a meaningful way to help shape decisions that affect your community--from how funding is distributed to what services are prioritized. Too often, however, people from marginalized communities are excluded from both the data collection process and access to the resulting findings. Melvette Hill, Megan Baker, Yukiyo Iida of Parent Leadership and Family Engagement for the Commission on Women, Children, Seniors, Equity & Opportunity will examine two important ideas that relate to data as civic engagement: how communities can collect and use data in more inclusive ways, and how data can be used to push for real change. Communities thrive when they’re informed.

Data Strategy in Action

Organizations are interested in using data to improve their work. However, knowing where to begin with your data is a challenge. In this session, Fionnuala Darby-Hudgens, Director of Data Strategic Planning at CTData Collaborative, and Elizabeth Rose, Data Strategy Coach at CTData Collaborative, will show you how to use a strategic tool that Data Strategic Planning participants utilize to improve their data work.

Data Tools for Everyone 101

Data visualization is a powerful skill to foster change and innovation. In this session, we will show you how to go from raw data to impactful visualizations using accessible, easy-to-use tools including Excel, Alteryx, Datawrapper, and Canva. Join us to expand your data toolkit and connect with like-minded professionals! This session is intended for participants who have beginner to intermediate data skills.

Data Tools for Everyone 201

Ready to bring your data skills to the next level? This session will introduce advanced tools for working with U.S. Census Bureau data, including how to use R's tidycensus package to analyze American Community Survey (ACS) data. You'll learn how to create custom data tables using ACS microdata to answer questions that go beyond what's available in standard public data tables. We'll also cover topics such as margins of error and statistical significance testing to add more rigor to your analysis. This session is intended for participants who have intermediate to advanced data skills, or those who are interested in learning about more advanced data skills.

Federal Data Challenges and Changes

This year has brought new uncertainty around the availability of data. Historically, the federal government has moved toward greater transparency in data access. However, in 2025, there were there have been reductions in both the availability and reliability of available federal data, as well as the firing of statistical staff for reporting figures deemed negative by the administration. Michelle Riordan-Nold, Executive Director of CTData Collaborative, will explore the landscape of change to data this year and highlight approaches being developed by Connecticut's state agencies and nonprofit organizations to bridge these information gaps, ensuring that residents maintain the resources necessary for informed decision-making.

Improving Maternal Health Outcomes through Data Connections

The US has continued to see a rise in maternal mortality since 2000. During this session, presenters will explore how data connections can transform and improve maternal health outcomes. Fragmented maternal mortality surveillance systems create data gaps that perpetuate health inequities. Ellyn M. Russo, Senior Data Science Consultant at Milliman, and Kimberly Montero, Administrative Director of Women’s Health Services at Hartford HealthCare, will explore frameworks for improving data collection and integration to improve maternal health outcomes. They will also explore a project based in a Connecticut hospital system that connects patient characteristics, care environments, and social determinants, demonstrating how data integration transforms maternal health insights and drives accountability through quality improvement initiatives that enhance maternity care outcomes.

Strengthening Data Culture: Action Review Toolkit & Cultivating a Trauma-Informed Data Culture

Is your organization seeking to identify new ways to strengthen your data culture? During this session, you will learn about two approaches to this work. First, Ayawa P. Fiagbedzi of the Rockefeller Foundation will present the Action Review Toolkit (ART), a structured approach to learning that moves beyond traditional hindsight-only reflection. You will explore how and what data to bring to key reflection points across a program’s lifecycle to foster actionable learning and continuous improvement. Then Jacquelyn Santiago-Nazario and Mica Knox of COMPASS Youth Collaborative, a Hartford-based organization that works with youth facing severe trauma, will discuss how they intentionally build trauma-informed practices into all aspects of their data culture while supporting staff who bring their own lived experiences to this work. 

The AI Trust Deficit: Why Public Perception Moves Faster Than Policy

Generative AI tools (such as ChatGPT and image generators) are becoming more widely used by Americans, yet public trust isn't keeping pace. The Quinnipiac AI Poll shows over half believe AI will harm education, with most trusting AI only "some of the time" or "hardly ever." Many feel businesses and government manage AI inadequately, while concerns about political misuse and misinformation persist. Tamilla Triantoro, Assoc Prof of Business Analytics and Information Systems, will examine the gap between AI adoption and trust using survey data, deployment trends, and forecasts from the World Economic Forum and Anthropic Economic Index. We'll explore what fuels this skepticism, oversight limitations, and strategies for building human-centered AI systems that can earn trust in 2026 and beyond.