IA369Z - Reproducibility in Computational Research
(Reprodutibilidade em Pesquisa Computacional)
First Semester 2020
(Reprodutibilidade em Pesquisa Computacional)
First Semester 2020
Profa. Leticia Rittner (lrittner @ dca . fee . unicamp . br) - room 314-A
Schedule: Wednesday - 14 to 18 hs - room - FE12
Latest news
Classes starts on March 11th. Materials and assignments will be soon available in Google Classroom.
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
More information will be available soon.
