7. - Authors are not paid for papers they publish!
- Editorial board (often) receives no monetary compensation
for reviewing.
- Research projects are (mostly) publicly funded.
- Public Institutions have to pay to access research
articles.
Doing research: Literature review
- Content created by research scientists. عندككة؟فلو
هامانجمشَهمكفن
We need a solution, please!!!!
8. Doing research: Literature review
OPEN ACCESS(OA) *: “literature is digital, online,
free of charge, and free of most copyright and
licensing restrictions”.
*Suber, P. Open Access; MIT Press: Cambridge, MA, USA, 2012; Chapter 1.
Available online: http://mitpress.mit.edu/books/open-access
9. Doing research: Literature review
Cost of Open Access publishing:
*Table4: H. Morrison, J. Salhab, A. Calvé-Genest, and T. Horava, “Open Access Article Processing
Charges: DOAJ survey May 2014,” Publications, vol. 3, no. 1, pp. 1–16, 2015.
10. Doing research: Literature review
Golden Open Access*: peer-reviewed journals that conduct
peer-reviewing and often charges authors for publication.
*Suber, P. Knoweldge Unbound; MIT Press: Cambridge, MA, USA,2016;
https://mitpress.mit.edu/books/knowledge-unbound
2 types of OA:
Green Open Access*: repositories that host pre-prints or
free to access. (e.g.: ArXiv).
11. Doing research: Literature review
Open Access criticism:
- “Double dipping”: charging both subscriptions and OA, a business model
adopted by some Hybrid Access Journals.
- Watering-down science by encouraging low-quality science publication
(predatory Open Access publishers: Pay to Publish).
- Misinterpretation of research findings.
12. Doing research: Literature review
Checklist:
✓ Research papers
- [locked item, proceed to unlock]
- [locked item, proceed to unlock]
The Student is happy!
14. Doing research: Experimentation
- Research studies require data collection and analysis for hypotheses testing
and the investigation of novel methods.
- Research equipment is expensive, requires maintenance and upgrades.
- Laboratories budget cannot afford access to multiple commercial datasets.
- يالالماتريلحقروطار
15. Doing research: Data
OPEN DATA*: “Open Data is research data that is freely available on the
internet permitting any user to download, copy, analyze, re-process,
pass to software or use for any other purpose without financial, legal, or
technical barriers other than those inseparable from gaining access to the
internet itself.”
* https://sparcopen.org/open-data/
16. Doing research: Data
Open Data repositories
- Community driven
project.
- Public data sources in
30 subjects :
● Agriculture
● Biology
● Climate + Weather
● EarthScience
● Economics
● ....
https://github.com/awesomedata/awesome-public-datasets
17. Doing research: Data
Open Data repositories
- EU funded project.
- General purpose OA
repository:
○ Up to 50 GB of free
space per dataset.
○ All research output
accepted.
https://zenodo.org
18. Doing research: Data
Open Data criticism:
The Skeptic
- Gaining profit from the labour of scientists.
- Privacy concerns.
- Misinterpretation and misuse of shared data.
21. Doing research: Software for Data Analysis
- Proprietary research software licenses are expensive.
- Reinventing the wheel : re-implementing data analysis
methods minimizes time dedicated to significant
research.
- Software developers shortage in research
laboratories.
22. Doing research: Source code
OPEN SOURCE*: “programmers or users can read,
modify and redistribute the source code of a piece of
software.”
*F. Pereira, “The Need for Open Source Software in Machine Learning,” vol. 8, pp. 2443–2466, 2007.
23. Doing research: Source code
Open Source Software licence
F. Pereira, “The Need for Open Source Software in Machine Learning,” vol. 8, pp. 2443–2466, 2007.
24. Doing research: Source code
Open Source hosting services
- Control Version System (CVS) based services :
- Github, Gitlab, BitBucket.
- Private hosts:
- Institutions dedicated servers: this-uni.edu/lab/repo/project
- Research oriented : RunMyCode
- Allows to share source code and data associated
with a research publication
25. Doing research: Source code
Open Source for science
- Python programming language ecosystem
26. Doing research: Source code
Open Source scientific computing environment
- Anaconda : open source freemium scientific Python distribution
includes:
- Python 2.x & 3.x interpreters + package manager.
- +1,000 Anaconda-curated and community packages.
- IDEs: Jupyter, Spyder, Rstudio.
- +6 million users.
27. Doing research: Source code
Sponsoring Open Source
NumFocus (Nonprofit organization) :
- Provides fiscal sponsorship for Open
source scientific data projects.
- Sponsored by : IBM, Microsoft,
Bloomberg, Anaconda, Intel, ...
- 21 projects sponsored (so far).
28. Doing research: Source code
Open Source criticism:
The Skeptic
- Software companies benefits Open Source
software with 0 costs and 0 compensation.
- Bad documentation and weak support.
- Issues with Open Source licenses compatibility.
29. Doing research: Data analysis
Checklist:
✓ Research papers
✓ Dataset
✓ Source code
The Student is happy!
32. Open Science
S. Bartling and S. Friesike, “Open Science :One Term, Five Schools of Thought”, Opening Science The Evolving Guide on How the Int
Changing Research, Collaboration and Scholarly Publishing. 2014.
34. Open Science
Reproducibility, what for ?
*Hugo Larochelle, “Some Opinions on Reproducibility in ML”,Reproducibility Workshop, ICML 2017.
- Validating research findings : “If it isn’t reproducible, it might just as well not exist!”.*
- Accelerating novel research discoveries by reducing the time spent on reproducing
experiments.
- Measuring the impact of papers beyond citations.
- Overcoming the replication crisis and fight against research misconducts (eg: p-
hacking).
35. Open Science
Moabb (Mother of All Brain-Computer Interface Benchmarks):
Open Science Project: (Work in progress)
- BCI Benchmarking tool: Compare
different BCI algorithms for different
EEG Paradigms on different datasets.
- Created by NeuroTechX community.
- Based on Python Open Source
packages: MNE, Scikit-learn, ...