Sharing linked data sets for research: Results from a deliberative public engagement event in British Columbia, Canada

12:00 noon to 1:00pm PST | All sessions will be delivered live and online via the Gotowebinar system.

This webinar is part of the Power of Population Data Science Series

Information is increasingly digitized, and researchers desire access to an increasing variety and depth of data to answers questions that can serve the public good. This talk will describe the methods and results of a public deliberation event held in April 2018 on the acceptability of sharing of linked data for research. The event brought together 23 members of the public over two weekends.

Public deliberations differ from public consultations and other forms of public engagement (e.g., surveys, focus groups) by the depth and length of the discussions. The purpose of deliberation is not consensus of opinion, but instead statements or recommendations that members of the public believe appropriate given the diversity of opinions and values in British Columbia.

Participants developed and voted on 19 policy-relevant statements relating to:

  • The governance of linked datasets
  • Security and review process for releasing linked datasets
  • Responsibilities of Data Stewards and researchers
  • Public involvement

Generally, participants were supportive of research using linked data because of the value they can provide to society. Participants desire efficiency for researchers, as long as there are adequate protections in place around security and privacy of the data.

View original IJPDS article at: https://ijpds.org/article/view/1103

Watch recorded presentation below.
 

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Speaker

Jack Teng Jack Teng was the project manager for the Using Personal Data for Research public deliberation. He helped manage public engagement at PopData.

He completed his doctorate degree at the University of British Columbia in the interdisciplinary department of Resource Management and Environmental Studies. He has a background in qualitative and quantitative research.

 

 

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