IMPORTANT DATES for this Course
   Deadline for applications: June 16th, 2017
   Course date: June 21st - 23rd 2017

Course description

In an age of increasingly complex and data-intensive, collaborative scientific practices, scandals of irreproducibility, and a growing societal ethos of transparency and accountability, a new paradigm has arisen: Open Science. In this three day course, we will introduce to you the three organizing principles and practices that undergird this paradigm:
Open Access scholarly publishing
Open Source software development
Open Data integration and sharing
For this, we will be introducing a set of technologies and ways of using them. The reasonable expectation is that the participants will feel empowered and start using them for the above purposes in a highly productive way. The use-cases that we will be working on are going to be based on bioinformatics, but the principles are very broadly applicable to other fields. You do not need to have any particular programming or otherwise computational experience beyond what is normally required from a scientist in graduate school and beyond, i.e., you should not be afraid of interacting with a computer and editing simple text files.
 

Target Audience
Researchers and Students in all sectors of Biomedicine.

Pre-course Reading
W S Noble. 2009. A Quick Guide to Organizing Computational Biology Projects. PLoS Comput Biol 5(7): e1000424 https://doi.org/10.1371/journal.pcbi.1000424
E M Hart et al. 2016. Ten Simple Rules for Digital Data Storage. PLoS Comput Biol 12(10): e1005097 https://doi.org/10.1371/journal.pcbi.1005097
P E Bourne et al. 2017. Ten simple rules to consider regarding preprint submission 13(5): e1005473. https://doi.org/10.1371/journal.pcbi.1005473