Chapter 4 Better science in less time

Better science is less time is science that is more efficient, reproducible, open, inclusive, and kind. There are growing examples of better science in less time in environmental and Earth science, and beyond. Here are a few examples to showcase what is possible and being done by the community.

Slides that have been presented during Champions Program Cohort Calls:

Here we also introduce the Pathway document that teams will develop throughout the Champions program. The Pathway is based on Table 1 in Lowndes et al. 2017, and helps teams deliberately identify data workflow practices and next steps to facilitate efficiency and open culture in terms of reproduciblity, collaboration, communication, and culture.

4.1 Ocean Health Index: behind the scenes

Some key points to discuss from Lowndes et al. 2017, Nature Ecology & Evolution: Our path to better science in less time using open data science tools:

  • Reproducibility & communication enabled by open tooling
  • Shared practices are useful beyond shared projects

If you’re interested in more overview of the OHI setup, see this 2017 talk (25 mins): OHI Better science in less time

4.1.1 OHI pathway

  • Motivated by necessity
  • Reimagined by possibility and community
  • Done incrementally!
  • Yes: it’s an investment.
  • Also yes: huge, enduring payoff for (your) science

4.1.2 Reproducibility & communication enabled by open tooling

RMarkdown to reimagine data analysis and communication. RMarkdown combines analyses & figures together, rendered to your reporting output of choice.

An example:

  • Website built with R/RMarkdown & Github
  • You can get started too: (1-hour tutorial)

4.1.3 Shared workflows not only useful for shared projects

  • OHI team: we identified as a team & prioritized helping each other
    • We work on many different projects
    • Use same workflows, share feedback, can think together across projects
  • Shared conventions reduce friction & cognitive load
    • Common ground, easier to talk about, easier to ask for help
    • You don’t need to design everything from scratch

And, critically:

  • It’s about increasing efficiency and reproducibility and open science.
  • But it is also about increasing participation and inclusion.
  • Consider diversity, equity, and inclusion in your daily practices.
  • How you work and onboard others to your projects is a DEI issue.

4.2 Examples in the wild: environmental science

4.3 Further resources

4.3.1 Not so standard deviation podcast

Parker & Peng
Great discussions about data concepts and “in the wild”
Episode 9: Spreadsheet drama

4.3.2 Practical computing for biologists

Haddock & Dunn
Software & computing concepts already on your computer
Chapter 2: Regular expressions