_champion.qmd

# Be a champion for open science {#champion} *in development...* ## Objectives and Resources To provide resources for you to promote good practices for open and reproducible science in your communities and institutions. ## Three messages If there are 3 things to communicate to others after this workshop, I think they would be: **1. Data science is a discipline that can improve your analyses** - There are concepts, theory, and tools for thinking about and working with data. - Your study system is not unique when it comes to data, and accepting this will speed up your analyses. *This helps your science:* - Think deliberately about data: when you distinguish data questions from research questions, you'll learn how and who to ask for help - Save heartache: you don’t have to reinvent the wheel - Save time: when you expect there’s a better way to do what you are doing, you'll find the solution faster. Focus on the science. **2. Open data science tools exist** - Data science tools that enable open science are game-changing for analysis, collaboration and communication. - Open science is "the concept of transparency at all stages of the research process, coupled with free and open access to data, code, and papers" ([Hampton et al. 2015](http://onlinelibrary.wiley.com/doi/10.1890/ES14-00402.1/abstract))) *This helps your science:* - Have confidence in your analyses from this traceable, reusable record - Save time through automation, thinking ahead of your immediate task, reduced bookkeeping, and collaboration - Take advantage of convenient access: working openly online is like having an extended memory **3. Learn these tools with collaborators and community (redefined):** - Your most important collaborator is Future You. - Community should also be beyond the colleagues in your field. - Learn from, with, and for others. *This helps your science:* - If you learn to talk about your data, you'll find solutions faster. - Build confidence: these skills are transferable beyond your science. - Be empathetic and inclusive and build a network of allies ## Build community Join existing communities locally and online, and start local chapters with friends! Some ideas: - [Mozilla Study Groups](https://science.mozilla.org/programs/studygroups) Example: [Eco-data-science](http://eco-data-science.github.io/). Also see ([Steven et al. 2018](https://www.biorxiv.org/content/early/2018/02/15/265421)) - [RLadies](https://rladies.org/). Example: [RLadies Santa Barbara](https://www.meetup.com/rladies-santa-barbara/) These meetups can be for skill-sharing, showcasing how people work, or building community so you can troubleshoot together. They can be an informal "hacky hour" at a cafe or pub!