Good Enough Open Source Practices for Data Analysis in Python

[brownsarahm]

Project Lead: @brownsarahm

Mentor: @quirksahern

Welcome to OL6, Cohort A! This issue will be used to track your project and progress during the program. Please use this checklist over the next few weeks as you start Open Leadership Training :tada:.

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Before Week 1 (Sept 11): Your first mentorship call

• [x] Complete the OLF self-assessment (online, printable). If you're a group, each teammate should complete this assessment individually. This is here to help you set your own personal goals during the program. No need to share your results, but be ready to share your thoughts with your mentor.
• [x] Make sure you know when and how you'll be meeting with your mentor.

Before Week 2 (Sept 18): First Cohort Call (Open by Design)

• [x] Complete Assignment 'Write Your Vision or Mission Statement'. Leave a comment on this issue with your draft vision statement & be ready to share this on the call.
• [x] Watch 'Mozilla & Working Open'.
• [x] Check the Syllabus for notes and connection info for all the cohort calls.

Before Week 3 (Sept 25): Mentorship call

• [x] Look up two other projects and comment on their issues with feedback on their vision statement.
• [x] Complete your Open Canvas (instructions, canvas). Comment on this issue with a link to your canvas.
• [x] Start your Roadmap. Comment on this issue with your draft Roadmap.

Before Week 4 (Oct 2): Cohort Call (Build for Understanding)

• [x] Look up two other projects and comment on their issues with feedback on their open canvas.
• [x] Pick an open license for the work you're doing during the program.
• [x] Use your canvas to start writing a README, or landing page, for your project. Link to your README in a comment on this issue.

This issue is here to help you keep track of work during the first month of the program. Please refer to the OL6 Syllabus for more detailed weekly notes and assignments past week 4.

[brownsarahm]

I’m working with scientific computing researchers and educators to develop accessible tutorial materials and minimal templates that empower researchers developing new analysis techniques to release them in formats that encourage community adoption. I'm working open to model the practices that I hope to teach. By working open, I hope to increase the impact of the templates and tutorials by encouraging learners to contribute back.

[brownsarahm]

Canvas

slightly remixed to store on github as a project to keep all of the information in one place instead of split between github and gdocs

[brownsarahm]

Road map

[quirksahern]

Hi Sarah, I've been reading your vision in the community call notes. Was thinking that you might want to add a bit about building a self-sustaining community - tweaking the last sentence. So the vision statement is more aspirational - what you are hoping the project will become. There's been a great deal of 'fun' lately re: redfining the joint Carpentries Vision Statement, you might find this thread interesting: https://github.com/carpentries/executive-council-info/issues/2

[quirksahern]

Re: your Canvas I have to admit that I intially found it a little confusing, different flow. Regarding contributors, how do you plan yo get them onboard? For the roadmap, do you have any key milestones? E.g. are there specific things that you want to achieve during Hacktoberfest or by December? These are good to breakdown and set specific deadlines for, they become the stepping stones for your road map.

[brownsarahm]

Readme (in progress)

[quirksahern]

Great read me!

Sent from my iPhone

On 29 Sep 2018, at 17:33, Sarah Brown notifications@github.com<mailto:notifications@github.com> wrote:

Readmehttps://github.com/brownsarahm/python-data-project/blob/gh-pages/README.md

— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHubhttps://github.com/MozillaFestival/open-leaders-6/issues/16#issuecomment-425657935, or mute the threadhttps://github.com/notifications/unsubscribe-auth/AFRBj3xmdR2vn1s2jkMUmL1ryJkoW9nOks5uf6DtgaJpZM4WdPEJ.

[celaus]

@brownsarahm great work - it made me feel like I can contribute something to your project :+1: As for the README, there is a dead link in there (learner profiles), but other than that, I like it.

[brownsarahm]

@celaus thanks! good catch on the link; it's fixed now.

[bebatut]

@brownsarahm I think your project is important to have sustainable research software. As @quirksahern, I was a bit confused by the flow of your canvas.

Several questions

• In Unique Value Proposition, what is the difference between hands-on and hands-on tutorial?
• In the profile of user, can you explicit what is for you "ML researchers"?
• In contributors, who do you have in mind when you say "contributors"? Maybe you could also think about having software developers.

[brownsarahm]

@bebatut thanks for the feedback. I will think about the flow a bit, but I guess I didn't see any flow in the original one, so I didn't think I was breaking anything important.

the hands/on vs hands on tutorial was a typo, more or less.

for users, I viewed the learner profiles, linked in that card as more detail. Cristina Calibration is an example of that.

[quirksahern]

Hi @brownsarahm just reading through your learner profiles, for the first learner you've mixed the gener pronouns in the text.