Status: This module is currently live and freely available online.
The third release for this module is now ready, and has been published on Zenodo:
To cite this work, please use the following:
Jon Tennant; Simon Worthington; Tania Allard; Philipp Zumstein; Daniel S. Katz; Alexander Morley; Stephan Druskat; Julien Colomb; Arfon Smith; Ina Smith; Tobias Steiner; Rutger Vos; Konrad Foerstner; Heidi Seibold; Alessandro Sarretta; Abigail Cabunoc Mayes. (2018, December 4). OpenScienceMOOC/Module-5-Open-Research-Software-and-Open-Source (Version 3.0). Zenodo. http://doi.org/10.5281/zenodo.1937708.
Software and technology underpin modern science. There is an increasing demand for more sophisticated open source software, matched by an increasing willingness for researchers to openly collaborate on new tools. These developments come with a specific ethical, legal and economic challenges that impact upon research workflows. This module will introduce the necessary tools required for transforming software into something that can be openly accessed and re-used by others.
- The researcher will be able to define the characteristics of open source research software, and the ethical, legal, economic and research impact arguments for and against it.
- Based on community standards, researchers will be able to describe the quality requirements of sharing and re-using open code.
- The researcher will be able to use a range of research tools that utilise open source software.
- Individual researchers will be able to transform code designed for their personal use into code that is accessible and re-usable by others.
- Journal of Open Research Software and the Journal of Open Source Software
- Galaxy, Reproducible Research environments
- Google Compute Engine (GCE)
- Amazon Web Services (AWS), Cloud-based software environments
- Software Citation Tools, Mozilla Science Lab
- Open Science, Open Data, Open Source, Fernandes and Vos, 2017
- Choose an open source license
Research Articles and Reports
- The Future of Research in Free/Open Source Software Development, Scacchi, 2010
- The Scientific Method in Practice: Reproducibility in the Computational Sciences, Stodden, 2010
- The case for open computer programs, Ince et al., 2012
- Code Sharing Is Associated with Research Impact in Image Processing, Vandewalle, 2012
- Current issues and research trends on open-source software communities, Martinez-Torres and Diaz-Fernandez, 2013
- Ten simple rules for reproducible computational research, Sandve et al., 2013
- Practices in source code sharing in astrophysics, Shamir et al., 2013
- A systematic literature review on the barriers faced by newcomers to open source software projects, Steinmacher et al., 2014
- Knowledge sharing in open source software communities: motivations and management, Iskoujina and Roberts, 2015
- An open source pharma roadmap, Balasegaram et al., 2017
- An introduction to Rocker: Docker containers for R, Boettiger and Eddelbuettel, 2017
- Upon the Shoulders of Giants: Open-Source Hardware and Software in Analytical Chemistry, Dryden et al., 2017
- Four simple recommendations to encourage best practices in research software, Jimanez et al., 2017
- Perspectives on Reproducibility and Sustainability of Open-Source Scientific Software from Seven Years of the Dedalus Project, Oishi et al., 2018
- Good enough practices in scientific computing, Wilson et al.,2017
- The Software Sustainability Institute: Changing research software attitudes and practices
- Thinking Outside the Box: Developing Dynamic Data Visualizations for Psychology with Shiny
- A breakdown of FOSS (Free and Open Source Software) for students and researchers in academia, Lois Donnelly
- Publish your computer code: it is good enough, Nick Barnes
- Making your code citable, GitHub Guides
- FLOSS and FOSS, Richard Stallman
- (Blog post) Data visualisation apps: What they add