Discussion sessions are a fundamental part of the Collaborations Workshop and help people work on solving shared problems and learn about new ideas.
This year we have various categories of discussion topics which will be listed online. These include:
The following questions will be run before, during and after the workshop. You can tweet and answer using our special hashtag - #CW14repro - and by linking to longer articles.
- What is reproducible research?
- How does your domain support reproducibility?
- What programming languages are best suited for reproducible research and why?
When discussing these questions or linking to relevant materials, the #CW14strat hashtag needs to be used.
- How do you know your research is reproducible?
- How do you use software tools to make your work reproducible?
- How best to encourage people to adopt reproducibility?
- How should researchers be trained in producing reproducible research?
- How does reproducibility fit in with incomplete, scattered or flawed data?
- Is engineering for long-term reproducible research a good thing idea, and why?
- What is and should be the role of code review in research?
- Are research software engineers doomed to obsoletion, and why?
- What should research dissemination models look like in the future (how do we get beyond the publication)?
The hashtag for this topic is #CW14manage and can be used to address the following questions:
- What software tools or development infrastructures help researchers achieve reproducible research?
- Are notebook/labbooks style tools, such as IPython Notebook or Labtrove, useful tools to improve reproducibility?
- Which aspects of reproducibility are most important for assessing research?
- How do we publish research in a reproducible manner when GUI tools are used ?
- What is the best way to train producers of good software documentation, and why is this important?
- How do we improve bad software?
- What problems should Recomputation.org address?
- Is successful research that uses excellent software testing practices really possible?
- What are the best practices for domain-based and institutional data management for supporting reproducible research ?
- What is the minimum standard of quality for research software that we should expect?
- How do you match users with developers of research software?
- How might a public repository of knowledge benefit the research community and aide reproducibility?
- How do you make a case for funding a full-time software developer in RCUK and EU funding calls?
Lastly, those who'd like to discuss issues related to best practice in software reproducibility can discuss this via the #CW14pract hashtag.
- How are tools such as Github, iPython Notebook and RStudio being used to practice reproducible science?
- Does software such as Sweave or KnitR allow people to produce reproducible outputs or just replicable ones?
- What data visualisation tools are used in research and how does their use relate to reproducibility?
- How do you construct reproducible analysis after using standard research processes?
- How do good software development practices aide reproducible research?
- How can automatic provisioning of software and applications aid reproducibility?
- Are ontologies useful in producing reproducible research?
- What’s the best way to access domain specific resources and is this reproducible?
- What programming languages, language features and paradigms support reproducibility?
- How do we completely describe a piece of code, so that it will be executable not only today or next year, but in a hundred years' time as well?
- What are the current must-use standards for publishing and reproducible research?
Suggest a topic
If you have a topic you would like discussed at the Collaborations Workshop 2014 (CW14) please contact us by email.
Note - discussion topics above are mostly based on suggestions from those registered to attend CW14.