Hackathon - Data Transparency Lab 2016

The Data Transparency Lab (DTL) is a community of technologists, researchers, policymakers and industry representatives working to advance online personal data transparency through scientific research and design.It is an inter-institutional collaboration, seeking to create a global community of technologists, researchers, policymakers and industry representatives working to advance online personal data transparency through scientific research and design.DTL is supported by Telefónica.

Data Transparency Lab

A 12 hours hack day to work together on building tools that help educating users on the importance of privacy and transparency.
The Data Transparency Lab is hosting, collocated with DTL 2016 conference a 12-hours hack day. The hack day main topic is “User Education on Privacy and Transparency”. If you have any idea to help users understand why they should care about privacy and why they should demand online services to be more transparent you shouldn’t miss this event!
Prizes to be announced soon.
Find out more about Hack Ideas in our website: <A TITLE="Hackathon link" HREF="https://datatransparencylab.github.io/dtlhackday16/" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">https://datatransparencylab.github.io/dtlhackday16</A> 
<A HREF="http://dtlconferences.org/" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">http://dtlconferences.org/</A>
 
We also invite you to register to our co-located events:
DTL: <A HREF="https://dtl2016ny.eventbrite.com" TARGET="_blank" REL="noopener noreferrer">https://dtl2016ny.eventbrite.com</A>
FAT ML link: <A HREF="https://fatml2016.eventbrite.com" TARGET="_blank" REL="noopener noreferrer">https://fatml2016.eventbrite.com</A>
DAT: <A HREF="https://dat2016.eventbrite.com" TARGET="_blank" REL="noopener noreferrer">https://dat2016.eventbrite.com</A>
 
Looking forward to meeting you at Data Transparency Lab 2016. 
DTL Team

Davis Auditorium, Columbia University

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Hackathon - Data Transparency Lab 2016

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Hackathon - Data Transparency Lab 2016

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