# 2021 Q3 review / Q4 planning meeting

October 14

Session 1: 11AM-12PM PST
Session 2: 1PM-2PM PST

Participants:

- David
- Julian
- Kristina
- Chris
- Jessica

## Homework

* Update and Score previous quarter OKRs
* [2021 Q3 OKRs](https://docs.google.com/spreadsheets/d/1nGV8z5ozEZv6qjrummr-q_PrzAMDLmVbRHnRyDrtEEM/edit#gid=607562223)
* Draft next quarter OKRs
* [2021 Q4 OKRs](https://docs.google.com/spreadsheets/d/1n8Y1Zv-hkZZLHGwBaBSomaK-YnAfEbpGjm2QcEMKdKY/edit#gid=844680069)
* [Guide: Set goals with OKRs](https://rework.withgoogle.com/guides/set-goals-with-okrs/steps/introduction/)
* Review
* [notes from previous quarter(s)](https://osf.io/tzmhp/wiki/OKRs%20%26%20Quarterly%20Reviews/)
* Link above includes homework
* Suggest topics [here](https://forms.gle/aSp2FYjEiicAVndSA) or below
* Create a presentation

## Agenda

* 11:00-11:45 Welcome and Overview of the Day, State of the Group
* 11:45-12:00 Discussion
* 12:00-12:30 Break
* 12:30-13:15 Individual Presentations (~15min ea)
* Major accomplishments
* What went well, what didn't
* Plans for next quarter
* Add links to presentations here:
* [Chris](https://docs.google.com/presentation/d/1pev2m6Yp4BCzzUQkOV66Mb7FQICpmXQfrhu1FfMabBw/edit#slide=id.p)
* [Kristina](https://docs.google.com/presentation/d/17da2kgTZzyQ_EF7gxDBh1-XFd09QweAqFyXkUFZXO58/edit#slide=id.gf5eafe1f9f_0_0)
* [Julian](https://drive.google.com/file/d/1ZgRvHd3JQ6LmRmldbAstKNHyRzNME_0n/view?usp=sharing)
* [Jessica - TODO]()
* 13:15-13:30 Closing discussion

## Notes

* Incubator project products
* (Public) GitHub repository
* DOI from archived data and code, e.g., Zenodo or ReDATA
* Publication (optional but encouraged)
* Post-incubator assessments
* How did the project go?
* Managing expectations about how to collaborate, e.g., authorship
* Followup work on [roles and responsibilities spreadsheet](https://docs.google.com/spreadsheets/d/1N95GgtAgvpQ9PhpiYwqWYewWu-FOzeIoQxzX2oldUuk/edit#gid=0)

## Discussion Topics / Parking Lot

* How are our processes working?
* [x] Toggl
* everyone is ok w/ it; key thing is to be able to report time with some defensible level of accuracy.
* [ ] Incubator
* [ ] TODO create a checklist
* how to define 'done'
* repository ownership - if one doesn't exist - we create, they fork?
* [x] authorship - expectations and responsibilites?
* review incubator project wiki
* How to convey each project's purpose and output clearly to anyone: Adding tile for each project once it's done to the group's website? Blog post from report?
* blog post w/ incubator tag; then we could have a page that lines these up
* [x] Office Hours
* What to do about non-ALVSCE folks showing up?
* Add example questions to office hours page that we can/have addressed?
* Splitting off from Coffee & Code?
* [ ] TODO add a clearly space for DIAG in rezbaz; don't hang out in the default entryway.
* Splitting to 1h ea Tues / Thurs
* [ ] TODO Change hours to Tues 9-10 AM + by appointment
* No split; but people in town encouraged to attend hacky hour on Thursdays.
* Sprint review - start Monday standup earlier?
* Elevator pitches for our groups aimed at different audiences, e.g., PI vs software engineer vs ecology grad student
* Sharing questions to entire group instead of private messaging
* Reproducibility and Data Science Skills for Ecologists
* teaching + research enhancement; reuse curriculum
* BRIDGES students, Susan Washko from SNRE, ENVS
* Have registration; cap at 10-15 people. Ask participants to commit to attending 80%
* Make recordings available privately just to students, in order to make participants feel more comfortable about asking questions
* SEEDS was 2h, Tu/Th for one month
* 1/week for 2h over 8 weeks?
* could add follow ups?
* make az-digitalag/organization private?
* yes
* Julian's list of things
* can help fix / automate tedious stuff
* Teaching
* SQL, APIs,
* Pandas + plotting
* teaching Planet labs, NEON materials
* Carpentries materials; python for earth and environmental scientists https://carpentries-lab.github.io/python-aos-lesson/
* Python for R users, and vice versa. Or, how to read Python/R.
* What are the awesome things about Python? What about R?
* Best practices part II (beyond carpentries)
* What scientists can learn from programmers, and what programmers can learn from scientists
* Testing; hypothesis automated testing
* Type annotations - what it is and how to do it
* Continuous analysis (GitHub actions, GitLab CI)
* Static analysis
* Immutable values
* Pure functions
* Good naming conventions (for variables, files, functions, modules, etc.)