09:00-10:00 - Sünje Dallmeier-Tiessen, Scientific Information Service, CERN

Data citation best practices:  http://best-practices.dataverse.org/data-citation/
To complement the discussion on "trusted" versus "certified" data repositories: "Recommended versus Certified Repositories: Mind the Gap":  https://datascience.codata.org/article/10.5334/dsj-2017-042/
Reproducibility: same result with same data.
Reusability: people can use the data to go further (CERN shared a lot of data that has been used for other studies). 
Repurposability: data in a format that can be easily reused in different contexts for different purposes
"advantage of data repurposability: it can better meet reporting needs, data quality needs, will tend to use standardized formats, etc." (http://svn.red-bean.com/repos/producingoss/trunk/notes.org)
Replicability: same result with alike datasets.
Useful sites: http://researchdata.epfl.ch, http://re3data.orghttps://www.pangaea.de/

10:30-11:30 - Marta Teperek, Cambridge Big Data

slides: https://zenodo.org/record/997313#.WctsVMgjG70
CC0 images: http://pixabay.com
People are ready to do open science if there is a benefit for them (selfishness):

11:30-12:30 Lucia Prieto, UNIL Neurosciences and TReND in Africa

Making your own equipment can save you money, but also time!
Open makes designs improve with time
Basic electronics:
Arduino microcontrollers: https://www.arduino.cc
Raspberry Pi computers: https://www.raspberrypi.org
Repositories of open hardware projects:
Instructables:    http://www.instructables.com/howto/pcr/