Public pages

Welcome to the wiki for data and model analysis!

Data and model analysis @ SRC

This section collects hints and tricks for how to use our in-house technical resources for doing data and model analysis. The page is currently maintained by the SESLINK group and is constantly updated through our weekly Monday meetings ("Nut cracking - 2 pm, room 238").

• Visualization techniques - collection of links from R and Jupyter to produce figures, infographics, ...
• Git version control for paper, data analysis and modeling projects
• NetLogo tips and tricks for designing simulation experiments
• R tips and tricks for statistical analysis
• Gunvor - how to access our computation server
• Jupyter Notebooks on Gunvor
• Linux tips and tricks - how to work with shell commands
• Running simulations in the cloud - just in case Gunvor is not your friend, you might want to consider run heavy analyses somewhere
• Available software at SU and SRC
• Technical documentation - about external servers
• Bibliometric analysis - different tools and strategies

You have not found what you were looking for? Contact Ingo or Romina to help you further!

Potential upcoming topics

• Quality assurance
  • improve collaboration
  • improve reproducibility, example from "Better science in less time"
  • making assumptions visible (e.g. underlying maps)

• Qualitative Comparative Analysis
  • Zuzana

• How to get 'big data'?
  • from behind paywals?
  • how to deal with that data later on? (when you need to make it available, open access ...)
  • licenses
  • platforms, portals (e.g. on SU where you can get a doi)
  • open data surveys
  • SND - swedish data service

Literature

• Good enough practices in scientific computing Wilson et al. 2017

Tutorials

• Plotting with python
• Designing models in NetLogo

Send us your favourite training websites and cheat sheetes!