• Live on Zoom
  • 1 Hour

Data Stewardship at a Time of AI | Expanding the FAIR principles to FAIR-R

A focused masterclass on responsible data governance for civil society professionals working on data reuse projects.

8 spots remaining

Stefaan Verhulst headshot

Your Lecturer

Stefaan Verhulst

Course Lead

Dr. Stefaan Verhulst is Co-Founder of the DataTank and The GovLab and the main lecturer of the data stewardship academy. In addition, he is a Research Professor at the Center for Urban Science and Progress at the Tandon School of Engineering of New York University; and a Senior Advisor to the Markle Foundation where he spent more than a decade as Chief of Research. He is also the Editor-in-Chief of the open-access journal Data & Policy (Cambridge University Press); the Research Director of the MacArthur Research Network on Opening Governance; Chair of the Data for Children Collaborative with Unicef; a member of the High-Level Expert Group to the European Commission on Business-to-Government Data Sharing; and of the Expert Group to Eurostat on using Private Sector data for Official Statistics. In addition he is also a member of the UNESCO Information Ethics Working Group; Researcher at the ISI Foundation (Torino, Italy); Senior Researcher at SMIT (Studies in Media, Innovation and Technology) at the Free University of Brussels (VUB) . In 2018 he was recognized as one of the 10 Most Influential Academics in Digital Government globally (by the global policy platform Apolitical). Previously at Oxford University, he was the UNESCO Chairholder in Communications Law and Policy and co-founded and was the Head of the Program in Comparative Media Law and Policy at the Center for Socio-Legal Studies. He was the Socio-Legal Fellow at Wolfson College, and is still an emeritus fellow at Oxford. He also taught for several years at the London School of Economics and was Co-Founder and Co-Director of the International Media and Info-Comms Policy and Law Studies (IMPS) at the University of Glasgow School of Law. He has published widely - including seven books- and his writings and work have appeared in the Harvard Business Review, Stanford Social Innovation Review, Project Syndicate, Wall Street Journal, and The Conversation (among many other outlets). He is asked regularly to present at international conferences including, for instance, TED, Collision, and the UN World Data Forum. Numerous organizations have sought his counsel on a variety of topics including data and AI governance - including the WorldBank; IDB, CAP, USAID, DFID, IDRC, AFP, the European Commission, Council of Europe, the World Economic Forum, UNICEF, OECD, UN-OCHA, UNDP, UNESCO and several other international and national private and public organizations. He is also a Linkedin Learning instructor seeking to democratize the practice of data stewardship globally.

Learning Objectives

  • Understand the FAIR-R and Data Stewardship Principles

  • Learn practical approaches to making open data ready for AI (optimized for training, fine-tuning and augmentation)

  • Explore real-world case studies of AI-ready data

  • Brainstorm adoption mechanisms of FAIR-R principles

  • Develop strategies for data stewardship at a time of AI

Expected Outcomes

  • 1

    A clear action plan for embedding FAIR-R principles into your work

  • 2

    Practical templates and use cases on AI-ready data

  • 3

    A peer network of data stewardship practitioners

  • 4

    Confidence to lead data reuse initiatives responsibly

Who Should Apply?

This deep dive is designed for professionals working on data and AI related projects at civil society, public, private, and non-profit sectors. Whether you’re a program manager, data analyst, AI lead, researcher, or policy advocate — if your work involves collecting, sharing, or reusing data for social impact, this deep dive is for you.

Reserve Your Spot

8 spots remaining — register now to secure your place.

Select up to 3.