IA369Z - Reproducibility in Computational Research
(Reprodutibilidade em Pesquisa Computacional)
First Semester 2017
(Reprodutibilidade em Pesquisa Computacional)
First Semester 2017
Profa. Leticia Rittner (lrittner @ dca . fee . unicamp . br) - room 314-A
Schedule Wednesday/Friday - 8 to 10 hs - room - PE35
Short syllabus
The purpose of this course is to study the concepts and tools behind the communication of modern data analyzes in a reproducible way. Topics such as ethical aspects of research and data management, e-Science and Open Science, literate computing tools, evidence-based data analysis, benchmarking in research and organization, and management of workflow will be addressed. During the course, students will learn and test platforms and languages that allow you to compile snippets of code embedded in documents, allow you to write and publish executable documents, and organize your data analysis to be reproducible and accessible by your peers. At the end of the course, students will use all they learned and the tools they have tested to prepare a reproducible research paper.
Bibliography
- 1. Beveridge, W., "The art of scientific investigation",
- 2. Peng RD (2011) Reproducible research in computational science. Science 334: 1226?1227. doi: 10.1126/science.1213847
- 3. Crocker J, Cooper ML (2011) Addressing scientific fraud. Science 334: 1182. doi: 10.1126/science.1216775
- 4. Barnes, N. Publish your computer code: it is good enough. Nature. 467, (2010), 753
- 5. Munafò, MM., et al. "A manifesto for reproducible science." Nature Human Behaviour 1 (2017): 0021.
- 6. Sandve, G. et al. "Ten simple rules for reproducible computational research." PLoS computational biology 9.10 (2013): e1003285.
Students projects
Here you can find some very interest material that the students prepared during the semester. Beside a reproducible paper, each student produced a diary of "Best pratices in Reproducible Research". Check them out:
