1. Learn to code in some language. Any language.
Strasser begins her list urging students to learn a programming language. As the limitations of statistical packages including STATA, SAS and SPSS become increasingly apparent, empirical social scientists are beginning to learn languages such as MATLAB, R and Python. Strasser comments:
Growing amounts and diversity of data, more interdisciplinary collaborators, and increasing complexity of analyses mean that no longer can black-box models, software, and applications be used in research.
Start learning to code now so you are not behind the curve later!
2. Stop using Excel. Or at least stop ONLY using Excel.
In Excel modifying data is done without a trace. This makes documenting changes made to a dataset more difficult and prevents researchers using Excel from producing fully replicable research. Read “Potentially Problematic Excel Features” to learn more about the pitfalls of Excel.
3. Learn about how to properly care for your data.
Strasser argues researchers need to better take care of their data. Visit the DMPTool website to learn about a powerful data management tool.
4. Write a data management plan.
Although it requires an initial cost by:
[T]hinking about file organization, sample naming schemes, backup plans, and quality control measures, you can save many hours of heartache later.
5. Read Reinventing Discovery by Michael Nielsen.
Referred to as the Bible of Open Science, Reinventing Discovery: The New Era of Networked Science by Michael Nielsen:
[Is] the must-read book for anyone interested in engaging in the new era of 4th paradigm research.
The book outlines:
[T]he problems with current incentive structures in science, and the steps we should all take towards shifting the culture of research to enable more connectivity and faster progress.
6. Learn version control.
Citing Wikipedia the article states:
Version control is a system that records changes to a file or set of files over time so that you can recall specific versions later.
Version control allows researchers to revisit an earlier edition of the code and increases the transparency and reproducibility of research. For more on GitHub, a popular version control platform, read “Git/GitHub: a Primer for Researchers.”
7. Pick a way to communicate your science to the public. Then do it.
Citing “Why Scientists are seen as untrustworthy and why it matters,” Strasser emphasizes the need for researchers to communicate their research findings to the public.
8. Let everyone watch.
Consider going open. That is, do all of your science out in the public eye, so that others can see what you’re up to. One way to do this is by keeping an open notebook.
9. Get your ORCID.
ORCID stands for “Open Researcher & Contributor ID”. The ORCID Organization is an open, non-profit group working to provide a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers.
The endgame is to support the creation of a permanent, clear and unambiguous record of scholarly communication by enabling reliable attribution of authors and contributors.
10. Publish in OA journals, or make your work OA afterward.
Often academic researchers take their university provided access to academic journals for granted, but Michael White, a professor at Washington University, points out that “[M]any corporate R&D departments, municipal governments, and colleges and schools that are less well-endowed” don’t have access to expensive academic publications. To reach out to a greater audience researchers should publish their work in OA journals.
Why are we locking our work in the Ivory Tower, allowing for-profit publishers to determine who gets to read our hard-won findings?
For those interested in OA journals visit the Directory of Open Access Journals.
Strasser’s original post can be found here.