[Open-Science-de] Save the date: GO FAIR Personal Health Train Implementation Network German Chapter Workshop, 12/02/2019, Berlin

[go-fair]

Save the date: GO FAIR Personal Health Train Implementation Network German Chapter Workshop on 12th February 2019, Berlin 

Register here: https://www.go-fair.org/registration-workshop-pht-german-chapter/

The GO FAIR Germany initiative invites researchers, care providers, technology developers, industry, standard organizations and policy makers to join the Personal Health Train (PHT) implementation network. 

The international PHT initiative aims to increase the use of existing biomedical data for research into personalised health & medicine, preventive medicine, and value-based healthcare. The approach is also adopted by other domains such as agriculture.

The GO FAIR PHT implementation network develops concepts, technologies and reference implementations to allow communities reusing their privacy sensitive data in an innovative way. As current German members of the network, we explore use cases from the medical informatics initiative consortia and develop proof of concept solutions. 

Now the GO FAIR International Support and Coordination Office establishes a German PHT chapter. The office will support all activities that enable the building of a PHT implementation  network in Germany. Stakeholders from Germany are invited to actively join the network and collaboratively work on future solutions for the PHT German chapter.

The aim of the German chapter is to discuss specific needs and use cases as well as strategies to achieve sustainable solutions on a national level. The MII projects, NFDI research infrastructures, and other communities that share data are welcome to bring their own challenges.

Join our workshop to explore this novel data reuse approach and be part of it.


What is the PHT: 
The PHT is a novel privacy-preserving approach to utilize distributed data and is based on the principle of "data resides where it belongs to, analytics meets data to harvest desired outcomes". In this analogy, train stations represent data repositories that provide computational abilities to execute tasks. The trains are the data analytics tasks such as data mining algorithms, applications or queries which are sent to relevant stations to be executed in a safe environment. The train does not leave the station with data that is privacy-protected. 

Who can benefit from it: 
Any community or organization who wants to utilize privacy sensitive data for any other purposes can benefit from the PHT approach, such as 
. industry and researchers to develop data analytic solutions, 
. data infrastructures and service providers to create a new value chain by selling access to data
. Researchers, care providers to benefit from data driven solutions, 
. Organizations, distributed system to monitor quality and asses effectiveness 
. Citizens to be empowered deciding who can use their data

How can I contribute: 
You can contribute the implementation network by bringing your use cases and identifying your needs; discussing technologies, solutions and standards; outlining a vision of reusing data beyond the boundaries of institutions or consortia; and more.


Organizer:
GO FAIR Support and Coordination Office, ZBW - Leibniz Information Centre for Economics, Neuer Jungfernstieg 21, 20354 Hamburg

Organization Committee: 
Oya Beyan, Oliver Kohlbacher, Stefan Decker, Matthias Löbe, Toralf Kirsten, Holger Stenzhorn, Monika Linne

Venue
TMF-Geschäftsstelle, Charlottenstraße 42/Dorotheenstraße, 10117 Berlin

Date: 12 February 2019  | 11:00 - ca. 17:30 o'clock

Contact Persons:

GO FAIR Germany
Monika Linne
go-fair at zbw.eu

PHT Implementation Network
Dr. Oya Beyan
beyan at fit.fraunhofer.de

Please register here: https://www.go-fair.org/registration-workshop-pht-german-chapter/