This is just laptops, not tablets nor desktops, but I can easily re-run. On the blank entries: the sort-of-good-news is that 338 of the 479 blanks are all from one restart group.
That was one of our hypotheses - the alert would however often only work if people who were actually involved with the repair were entering the data
Depends what you mean by “work” - if it helps subtly reinforce the importance of the text comments for next time, it will have worked IMHO.
In case anyone was using it: moved chat out of the thread, as it was difficult to use in the thread - open it up in a separate tab to access it:
Quick field report from South London Maker Festival - VEEERY busy here, lots of interest in Restart and the live repairs being done; I’ve been talking people through the impact data using Metabase to visualise.
Here’s the keyword tagging for all categories. There may be some scope to improve for desktops and tablets:
Thanks so much everyone for all your contributions - we’ll write up our key findings from today, and we look forward to keeping you involved with our work on data analysis pushing for the Right to repair. Stay in touch, and more soon (we’re cleaning up the space at Newspeak House then heading to the pub)
Thanks everyone for the session yesterday. I’ve tidied-up my code for sharing, so on that and some other ideas:
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The code is now in the google docs folder: the restart_open_data_day.html file is for sharing code and outputs, and the restart_open_data_day.Rmd file generates the html. You’ll need to download the html to a local drive to view properly (preview on docs won’t render fully)
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On data collection, I was wondering if a tagging system would be easier for repairers than a free text field. They could pick a ‘primary tag’ from a list and then add ‘secondary tags’ if appropriate. Not sure if that would be too much of a change in approach
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I mentioned to Neil the option of using Kaggle as a platform for further analysis. The main benefit is having the code, computation and outputs hosted in one place. You’d need to check whether the small print was acceptable from a data licence point of view. It’s best known for the ‘competitions’ section but you can use the ‘datasets’ section for less formal collaboration and data exploration
A competition example
And a dataset example
How do you add a skill if you’re already registered? I don’t see it at all.
I would just be interested to know what are the commonest items we have coming in, which are the commonest fixable, and the commonest unfixable.
Thanks @Elena! If you would be happy to share the source for the underlying Jupyter notebook, I will add it to our analytics repo.
You should see it at the bottom of your ‘Edit Profile’ page @philip, in Restarters. If you click in the list of Skills, you will be able to add new.
We can definitely answer that Philip. For now I’ll just link an existing question we already have in Metabase that includes that data, but we can visualise it differently if you need:
Thanks all to everyone who participated on Saturday!
@Elena @Becky_Miller @Julie_Vaccalluzzo @Steve_Cook @Monique @james @isabel @neil @Janet @Panda @ugo @Tom_Wagstaff @Lewis_Crouch @Eunice
(Please do let me know if I’ve missed anyone off)
It was a great event, and we really appreciate all your enthusiasm and contributions on the day. Photos have been uploaded here: https://drive.google.com/drive/folders/1f4dqMhczjxeenYH-0dIYTGLEhhwymwp7
For everyone who wanted to stay involved after the day: we have a dedicated category on repair data - it would be great to keep the discussion going there. I’ll post a summary of our Open Data Day event there soon.
We are also planning to hold future data events - keep your eyes peeled!
Hackathon you can bring your dataset if you want someone to work on it?
Thanks @Elena, looks interesting! I’d certainly be interested in going to this and taking our data along. Do you think our data would fit into a competition at Kaggle or one of the other sites listed? ( I don’t know much about how those sites work - but @Lewis_Crouch mentioned Kaggle on ODD.)
Kaggle and similar are best for predictive modelling e.g. predict which products can be repaired based on product info and user comment. For you the best one may be https://www.drivendata.org/ or similar?
DataKind maybe?
Depends on what you want. In a hackathon you can ask people to do specific stuff that’s not predictive modeling, as you did in your hackathon.
Get in touch with Alex who runs this hackathon (send him a message on meetup). He also runs Kaggle and some other meetups.
He will help you.
https://www.meetup.com/en-AU/London-Data-Science-Workshop/events/259759725/?isFirstPublish=true