#OpenDataDay: let's explore data on computer repairs

I wonder if some of the fault types are the most useful. E.g., ‘Liquid damage - Needs new keyboard’ that fits under a ‘keyboard’ fault, however to classify the type of problems that happen, I’d find ‘liquid damage’ more useful, with keyboard replacement as a solution.

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That’s an interesting question. We have a Data Quality Index (DQI) sheet at the VEEEERRY end of that spreadsheet, that explains how we score data.

On some level, it’s up to our discretion to decide how “technically representative” an LCA is. And some priority is given to the “temporal representativeness” (or “freshness”) of the data. But perhaps once we have more data about the ages of devices brought to events, this can be changed. For example, we might find that hifi components are an average of 15 years old.

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Hey @Becky_Miller, here you go:

:paintbrush: Colour palette

:laptop: Illustrations of components, devices & tools

And

:spiral_notepad: Our full branding guide is here

I’ll add these to Janet’s post above

Very good point - there’s limits in the current suggested list of problems for categorisation. As part of today’s work, we’re also learning about this, and will consider alternatives/better categories

@neil , it would be great to have location on the devices_all.csv

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We’ve come across an interesting question: is it worth categorising solutions in case a repair was not completed? Ie. it was identified that a laptop requires replacing RAM, the solution could be “Advised”, or also “Need to replace”. Based on discussions at the event, we need to clarify what’s the purpose of categorising solutions, then decide whether to do so just for “Fixed” items, or for all.

I’ve tried topic modelling and not been impressed with the results. The text comments appear to be too short for the topics to be meaningful. Instead, here’s a more basic but still automated tagging of key words for laptops:

keyword_tagging

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Is this for all categories, including tablets?

I know the lack of text is frustrating, having similar problems with tablets. (I think we may need to create some kind of real-time alert to users/admins when text comments are too poor @neil @james.)

But this aggregate data is quite interesting when compared with tablets as a category, as we have proportionately more problems with screens and ports/connectors. (Perhaps ports/connectors are not picked up by this modelling?)

This causes me to wonder… are tablets are simply treated as such physically disposable products that people don’t even keep them long enough to experience “slow/software/boot” obsolescence issues.

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.

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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:

https://pads.therestartproject.org/p/DataDive

We’ve confirmed with @Elena (attending in person) that this will be for a follow-up to the event

Added a quick pivot of @Janet’s fault categorisations to the Tablets sheet

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.

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Here’s the keyword tagging for all categories. There may be some scope to improve for desktops and tablets:

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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)

categiries_repair_status

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Thanks everyone for the session yesterday. I’ve tidied-up my code for sharing, so on that and some other ideas:

  • 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)

  • 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

  • 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

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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.