assumptions of reproducibility: what are the assumptions that make reproducibility possible. For example, recall the first project we did in this class for making reproducible code. We have to make a readme file to clearly indicate how to make instructions to regenerate the work.
tools:
During the data science faire, we will have a table to set up with monitors that can show people around the products of this class. We can show people some examples and product of the tools involved with reproducibility in the data science faire. Users are able to try on these tools, such as the ipython notebook
Goal of presenting poster during the faire:
we can introduce these tools we learned in class to people who come to the faire by showing them the work we have produced in this class using those tools.
I would suggest the following structural outline for the poster:
Introduction of reproducibility and current research focus and applications on such area
The concept of reproducibility applied in this class
The examples and tools that assist our way to make reproducible products (e.g. ipython notebook, github, vagrant, markdown …)
Using the survey results from students’ responses and make a data visualization summary graph.
Office hour (12/7/2013) summary:
I would suggest the following structural outline for the poster: