Chapter 2 Introduction

We do rigorous quantitative science to support decision-making for living marine resource management. We conduct our work using Open Data Science principles, emphasizing scientific excellence (not perfection) that is transparent, reproducible, collaborative, and ethical. We aim to make our methods and results available and support ongoing learning.
Our quantitative work is based on statistical thinking, using evidence-based approaches to compare among alternatives for models and management options.

See the next chapter for more detail on our lab culture and philosophy. We are motivated heavily by the following two papers - which provide a blueprint for how we think about the way we do our work.

Lowndes, J.S.S., Best, B.D., Scarborough, C., Afflerbach, J.C., Frazier, M.R., O’Hara, C.C., Jiang, N. and Halpern, B.S., 2017. Our path to better science in less time using open data science tools. Nature ecology & evolution, 1(6), pp.1-7.

Wilson, G., Bryan, J., Cranston, K., Kitzes, J., Nederbragt, L. and Teal, T.K., 2017. Good enough practices in scientific computing. PLoS computational biology, 13(6), p.e1005510.

[To come: recommended reading list]

2.1 How we meet

Currently, we meet virtually by Zoom for weekly lab meetings, individual meetings with Gavin, and our Shut Up and Write session.
We use Googledocs to set agendas, record decisions made, and outline action items during meetings. Each lab member has their own google doc for their 1:1 meetings with Gavin. Prior to each meeting, create your agenda for that meeting there.

2.2 How we give feedback

Feedback, both giving and receiving it, is an important aspect of our lab. Most of the feedback we give and receive is when giving and attending practice talks. We expect feedback to be supportive but constructive.

This resource from UBC does a really great job of outlining the main points of how to give and receive feedback.

2.3 How we share things (and send them to Gavin)

It is useful to have standard ways of sharing things. These don’t always have to be followed but are a useful guide and will make things easier. When sending material to someone, always make sure to describe what you are sending and try to make it as easy as possible for them to help you.

Taking a project-based approach to organizing your work makes it easier to share and solicit feedback from others, as things tend to be self-contained. Try to keep only 1 working instance of material, and use some form of version control to facilitate this (see recommendations in Wilson et. al paper linked above).

Project management tools in Github are a good way to record and document questions on analyses. Use ‘Issues’ on github repositories for project-related tasks and problems. Alternatively, make use of a GoogleDoc for each project to record this history, much like you would a lab notebook.

Code: can be shared via Github repositories, or via a dedicated Google Drive folder. For specific questions on problems, please try to create a minimal reproducible example. Ensure that others can run and interact with the material being shared.

Writing: Preferably via GoogleDoc, R Markdown, or Overleaf, but MS Word documents can also be shared. Google docs are particularly useful for collaborative writing, and have the advantage of there only ever being one version (as opposed to files that are sent around via email). Word documents should always have your last name as the first part of the file name (e.g. please no “mythesis.doc”).

We also share our insitutional knowledge through our lab-chat github ‘issues’ repository. This is community-driven troubleshooting resource, contribute!

We maintain a lab Google Drive folder for lab publications, presentations, photos, CVs, etc. Please make use of these so that others in the lab can make fair use of our work.