  Introduction: Increasingly, the label data trust is being applied to
repeatable mechanisms or approaches to sharing data in a timely, fair, safe and
equitable way. However, there is a gap in terms of practical guidance about how
to establish and operate a data trust.
  Aim and Approach: In December 2019, the Canadian Institute for Health
Information and the Vector Institute for Artificial Intelligence convened a
working meeting of 19 people representing 15 Canadian organizations/initiatives
involved in data sharing, most of which focus on public sector health data. The
objective was to identify essential requirements for the establishment and
operation of data trusts. Preliminary findings were presented during the
meeting then refined as participants and co-authors identified relevant
literature and contributed to this manuscript.
  Results: Twelve (12) minimum specification requirements (min specs) for data
trusts were identified. The foundational min spec is that data trusts must meet
all legal requirements, including legal authority to collect, hold or share
data. In addition, there was agreement that data trusts must have (i) an
accountable governing body which ensures the data trust advances its stated
purpose and is transparent, (ii) comprehensive data management including
responsible parties and clear processes for the collection, storage, access,
disclosure and use of data, (iii) training and accountability requirements for
all data users and (iv) ongoing public and stakeholder engagement.
  Conclusion / Implications: Based on a review of the literature and advice
from participants from 15 Canadian organizations/initiatives, practical
guidance in the form of twelve min specs for data trusts were agreed on. Public
engagement and continued exchange of insights and experience is recommended on
this evolving topic.
