As researchers at GIUZ, we face challenges such as ensuring we can reproduce our own work and deciding how and what to share with the greater community. Some groups or individuals might already have developed their own ways of dealing with these challenges, others might be less aware of them. To collectively tackle these challenges and to profit from knowledge already existing at GIUZ across group boundaries, we are offering a 2-day workshop including speakers, hands-on sessions, and opportunities to exchange ideas and best practices on the theme of reproducible research.
Opening keynote on reproducible research by Dr. Edzer Pebesma from the University of Münster (Tuesday Sept 13, 10:00 - 11:00, room G85). Open to the public.
Second day keynote on data handling by Dr. Peter Fornaro from the University of Basel (Wednesday Sept 14, 9:00 - 10:00, room G85). Open to the public.
Hands-on computer-based sessions on versioning and collaboration. Open to workshop participants only.
Short talks by GIUZ (Geographical Institute at the University of Zurich) group representatives on best practices, challenges, and personal experiences. Open to workshop participants only.
This workshop has been made possible thanks to InnoPool funding from the GIUZ.
This tutorial in the context of the Reproducible Research Workshop provides you with the first steps on how to use Git with R and RStudio. (The tutorial was originally created on GitHub and hosted here.) Objectives of this tutorial: Set up and install Git Set up Git in RStudio Create new Git project in RStudio Clone/fork an existing project from GitHub Make some commits to your own project. Motivation R in combination with the distributed version control system Git provides a convenient setup to make your research project reproducible.
This tutorial in the context of the Reproducible Research Workshop provides you with the first steps on how to use Git with the Eclipse IDE. Eclipse is heavily used to program in Java, as well as in other languages like C++, and even Python (via PyDev). (The tutorial was originally created on GitHub and hosted here.) Objectives of this tutorial: Set up and install Eclipse with EGit, and get a GitHub account Clone/fork an existing project from GitHub and import it into Eclipse Commit changes to a file in the GitHub project from Eclipse Part 1: Installation and setup To get started you need the following software installed on your computer: Eclipse, and EGit.
This tutorial in the context of the Reproducible Research Workshop provides you with the first steps on how to write publications in R. Objectives of this tutorial: Installation and setup of R, RStudio and Miktex Load a template project to RStudio (or fork it from GitHub, see part 4 of the Git with RStudio tutorial) Generate an example report as an HTML, Word or $\LaTeX$ (Latex) document Generate a sample publication Prepare a publication for use in Overleaf Motivation Wouldn’t it be great to combine analysis, data, results, plots, bibliography and text all together and later on regenerate a report or publication with the click of one button?
This tutorial in the context of the Reproducible Research Workshop provides you with the first steps on how to write publications in Overleaf. Objectives of this tutorial: Subscribe to Overleaf Create a new Latex project in Overleaf Save your Overleaf project to your local computer Share your project with colleagues Motivation Overleaf is an online LaTeX editor with integrated real-time preview. It allows you to collaborate with your co-authors who can review, comment, and edit the document.
Reproducible Research keynote:
Intro to versioning:
Reproducible Research short talks:
Data Handling keynote:
Data Handling short talks:
Coursera course: Reproducible Research: Free online course, assuming some knowledge or R, focused on concepts of Reproducible Research, R, RStudio, using R markdown files for sharable analyses. Taught by Dr. Roger Peng.
Report Writing for Data Science in R: Textbook for the Coursera course, by Dr. Roger Peng.
rOpenSci: Building R packages for reproducible research - “Transforming science through open data”.
Open Science Framework: An end-to-end solution for open and reproducible research, with integrated versioning, data hosting, and more.
Elsevier: Sharing Research Data: Presents several options for sharing your research data.
Mendeley Data: Platform to share research data in a citable, secure way; from Mendeley, primarily known for their reference managing software.
c4science: Infrastructure for scientific code co-creation, curation, sharing and testing; emphasis on Swiss Universities.
figshare: Data sharing publication platform.
Software carpentry: Lessons/workshops to teach skills for research computing, including R for Reproducible Scientific Analysis.
Pweave: Scientific report generator and literate programming tool for Python.
101 innovations in scholarly communication: Poster on the changing research workflow, including tools and tool-chains.
Tuesday, September 13th 2016
09:30 – 10:00 : Welcome and Introduction [Y03-G85]
10:00 – 11:00 : Dr. Edzer Pebesma reproducible research keynote [Y03-G85]
11:00 - 11:20 : coffee break [Y25-H38]
11:20 – 12:45 : Short talks from GIUZ groups, with discussion [Y25-H92]
13:45 – 14:45 : Versioning talk by Dr. Moritz Neun [Y25-H92]
14:45 - 15:00 : coffee break [Y25-H38]
15:00 – 17:00 : Versioning tools hands-on session (with demo and tutorials for Git, Eclipse/EGit, RStudio) [Y25-J9/10]
Wednesday, September 14th 2016
09:00 – 10:00 : Dr. Peter Fornaro data handling keynote [Y03-G85]
10:00 - 10:30 : coffee break [Y25-H38]
10:30 – 12:30 : Short talks from GIUZ groups, with discussion [Y25-H92]
13:30 – 15:30 : Collaboration and data sharing practical (with demo and tutorials for Overleaf and publication writing in R) [Y25-J9/10]
15:30 - 15:45 : coffee break [Y25-H38]
15:45 – 16:40 : Reproducible research mingling [Y25-H92]
16:40 - 17:00 : Closing session [Y25-H92]
17:00 : Apéro [Y25-L11]
Get in touch with the workshop organizers:
Pia Bereuter, Elise Acheson, Felix Morsdorf, Manuela Brunner, Annina Michel.
E-mail: first.last@geo.uzh.ch
(replace ‘first’ and ‘last’ with the desired contact’s name above)