Did you ever:
- had to go back to the regression code you wrote months ago to replicate a table that a referee wants slightly different and been unable to trace how in hell it was created in the first place?
- think that it would be nice if you could easily access the code for that relevant paper whose results do not make much sense?
- suffer from a disk failure and lost some of your files because no backup was in place?
- argue with co-authors which document version was the latest? Then this workshop might be of interest to you.
From a less individual perspective, a recent controversy over a Harvard study shows that there is clearly a need for more transparency and better practices in the way research in the social sciences is carried out. At the same time, government institutions and universities are also progressively pushing for a more open and reproducibility-prone policy in the way publicly funded research is made available.
Despite this recognized relevance, relative complexity and wide interest, it is strange that virtually no training is provided on workflow design and choice of appropriate tools. Students and researchers in the social sciences typically receive no guidance as to why or how they should adopt habits that favor the open science principles in their research activity. Therefore, in this workshop, we cover the main ideas behind a well-designed workflow with openness, transparency and reproducibility in mind, and will provide an introductory, hands-on, overview of a set of free tools that have been designed with such values in mind.
We do not aim to get to every detail of each tool and package. Instead, we aim to give a gentle introduction, to provide further material and to place them in the appropriate context. Specific emphasis will be put on how certain tools contribute to building a coherent open workflow and how they relate to other tools. The main areas we will review are: mark-up languages such as
LaTeX , typesetting system, reference managers, particularly those open and free such as
Bibtex which are compatible with
LaTeX, conversion tools such as
Pandoc, open environments for statistical computing such as or
Python, version control systems such as and back-up solutions. At the end of the workshop, participants should be able to reproduce a paper of their own and make it available in an open form applying the concepts and tools introduced.