October 1 – 3, 2025

A 3-day Virtual Event on Data Governance, and Open Source AI.

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A premier virtual gathering of leading AI & Data practitioners.

🌐 Global Audience Reach

Our 2023 webinar series drew attendees from all over the world that tuned in to hear from renowned experts in their fields.		🔓Open by Design

From speakers to code to conversations, everything about this event supports transparency, reuse, and open participation.		🎙️Speaker-Driven Content

Talks are curated through a public CFP. We shape the agenda with what really matters: licensing, bias, governance, and more.
🗞️ Beyond the Event

Selected speakers will publish essays on OpenSource.net — extending their impact beyond the webinar and into open discourse.		💡A Launchpad for Ideas

This is a space for experimental formats and early-stage thinking — demos, provocations, and community feedback welcome.		👩‍🚀 Ties to All Things Open

Top talks may earn a stage at ATO in Raleigh, NC, connecting our virtual event with one of the biggest OSS gatherings in the world.

What we’ll cover

  • Data Governance: Provenance, signaling, stewardship, standards
  • Ethics & Accountability: Bias, fairness, responsibility 
  • Open Infrastructure: Sustainability and interoperability
  • Real-World Case Studies: What’s working (and what’s not)

Key dates

  • Call for Proposals: Opens May 1, 2025
  • Speaker Submission Deadline: June 28, 2025
  • Event Dates: October 1 – 3, virtual format
  • Essay Publication on OpenSource.net: August through October
Submit your proposal

Read our white paper

Artificial intelligence (AI) is changing the world at a remarkable pace, with Open Source AI playing a pivotal role in shaping its trajectory. Yet, as AI advances, a fundamental challenge emerges: How do we create a data ecosystem that is not only robust but also equitable and sustainable?

Read the white paper

Watch the 2023 recordings

As part of our original Deep Dive:AI, we gathered a diverse collection of leaders to collaborate in drafting a definition for “Open Source AI”.

Speakers from law, academia, NGOs, enterprise, and the Open Source community shared their thoughts on pressing issues and offered potential solutions in our development and use of AI systems. 

Challenges welcoming AI in openly-developed open source projects Operationalising the SAFE-D principles for Open Source AI The Ideology of FOSS and AI: What 'Open' means relating to platforms and black box systems Open source AI between enablement, transparency and reproducibility
Federated Learning: A Paradigm Shift for Secure and Private Data Analysis Opening up ChatGPT: a case study in operationalizing openness in AI Perspectives on Open Source Regulation in the upcoming EU AI Act Data privacy in AI
Covering your bases with IP Indemnity Data Cooperatives and Open Source AI Should OpenRAIL licenses be considered OS AI Licenses? Commons-based data governance
Fairness & Responsibility in LLM-based Recommendation Systems Copyright — Right Answer for Open Source Code, Wrong Answer for Open Source AI? Should we use open source licenses for ML/AI models? Preempting the Risks of Generative AI

Sponsors

Put your brand at the center of the Data Governance & Open Source AI conversation.

  • Visibility: Brand logo on event materials
  • Engagement: Hosted sessions or roundtables
  • Reach: Newsletter shoutouts and blog features
  • Access: Post-event metrics & audience summary

Custom packages available. Contact us to learn more!

Submit your proposal