#OpenDataDay: let's explore data on computer repairs


Hi everyone,

And welcome to our first data dive into the repair data collected at community repair events. The Restart Project’s recently reached an important milestone: open data on 10,000 repairs collected at events part of our network.

As part of the growing movement for the Right to repair, we’re now collaborating with EU partners to ensure that insights from the data can influence future policy to make products more repairable.

This first event focuses on data on computer repairs, as in the coming year there will be a revision of EU ecodesign regulation about computers, and therefore an opportunity to use insights from over 2,200 repairs of desktops, laptops and tablets to push for longer-lasting, repairable devices.

How to get started?
To post comments on this thread and be in touch with others in real-time, we’re asking you to register to our online community if you haven’t yet. While registering, please choose “Data volunteering” as one of the skills. When you’re finished with the registration, please return to this thread. (You may be asked to log in again, just click log in and you should be all set.) In case you’re stuck with registration, email us for help at tech@therestartproject.org

We’ll soon add new posts to this thread highlighting key activities, and we ask you to :speech_balloon: join the discussion throughout the day, sharing your findings, questions and ideas here

And don’t forget to have fun! :grinning:

Summary of Open Data Day 2019

:speech_balloon: Step 1: Join the discussion

Get involved in the conversation throughout the day!

Throughout the day, we’ll all post our findings here and help each other out with any issues.

If you’re not registered in our online community yet, see the post above in order to get registered and get posting in the thread! (And if you get chance, why not also introduce yourself in our community welcome thread?)


:hammer_and_wrench: Step 2: Dive into the data

Whether it’s visualisation, advanced text analysis, answering simple questions, or building charts and graphs and asking what-ifs, here are some ideas of how you can investigate the data.

Whichever you choose, we’ll help you get set up. If you’re not sure what to do, just drop a question into the thread. Don’t forget to post your ideas in the thread and team up with others if you’d like to collaborate!

Here’s are some options for things to work on:

  • :desktop_computer::computer: Option 1: Help categorise the faults we’ve seen in computers
  • :woman_mage::man_artist: Option 2: Play with the data (plots, visualisations, inforgraphics, get creative!)
  • :chart_with_upwards_trend::bar_chart: Option 3: Answer freeform questions and what-ifs
  • :female_detective::male_detective: Option 4: Use your search-fu and help us research

When you have an idea what you’re going to work on, please add yourself to the roll call.


:computer::desktop_computer: Option 1: Help categorise the faults we’ve seen in computers

We want to investigate what problems and faults we commonly encounter in the computers and tablets we see at our events.

The data we collect on problems and solutions is currently recorded in free text - so we’d like to systematically categorise the faults in order to further analyse it.

We have two ways of doing this - choose the one you like!

Click for more info

Manual categorisation

It’s still hard to beat people-powered classification for accuracy. In this task, you will read through the information that Restarters have recorded about a repair, and from the text provided categorise the type of problem that we faced and the solution that we used to solve it.

We have 5 spreadsheets for this:

Automatic categorisation

Manually categorisation is usually accurate, but also quite laborious. Tool-based textual analysis could provide a much quicker method for categorising problems and solutions. If you think you’ve cracked it, we can match the results up with the manual work to verify accuracy.

Some tools you might like to try:


:woman_mage::man_artist: Option 2: Play with the data (plots, visualisations, infographics, get creative!)

If you’re a wizard with data, have an idea you’d like to explore, or just want to get creative with an infographic or visualisation, here’s raw CSVs of the data and to have a dive into it yourself:

(And, don’t forget, when we’ve completed the problem categorisation in Option 1… we want to visualise that information, too!)

Click for some ideas of tools you could use

Here are some ideas for free data visualisation tools you can try:

  • RAWgraphs (build graphs and inforgraphics from CSV files, no account required)
  • Infogram (build infographics, requires free account)
  • d3.js (requires coding knowledge)
  • any other suggestions? add them to the thread!


:chart_with_upwards_trend: :bar_chart: Option 3: Answer freeform questions and what-ifs

For asking and answering freeform questions and what-ifs, you can use our tool Metabase. If you’re good with charts and graphs this is a good option and let’s you play with the data through a graphical interface. (Alternatively, if you want a quick way to run SQL queries and visualise them, you can do that in Metabase.)

To get started, here are some questions that members of the Restarters community would already like to know the answer to: Exploring our repair data - what do you want to know?

Click for info on using Metabase


:female_detective::male_detective: Option 4: Use your search-fu and help us research

If you’re a whiz with a search engine and digging up information, here are a couple of pieces of valuable research you could get stuck into:

  • Finding lifecycle assessment data on computers
    • We report on the environmental impact of Restarters’ repairs
    • We calculate this using life-cycle assessment (LCA) data
    • LCA data is sometimes hard to come by - but we can find it in documents online and pull out the relevant information
  • Verifying known brands
    • For the brands that we have had recorded in our database, help us verify those which are genuine by finding links online that prove the brand names existence


Step 3: Have fun and share your findings!

Let’s all share our findings with each other throughout the day.

Uploading images :woman_artist: :man_artist:

For any images and visualisations you have, you can upload them straight into this thread. Just create a Reply and press the image button (or you can copy paste the image straight in).

Sharing files

If there’s any other data files you need to upload, please feel free to share them here (note: requires a Google account to upload - if you’d prefer to share elsewhere, please go ahead and link to the download in this thread).


Roll call

Edit this post and add your username (e.g. @neil) here so we all have an idea of what everyone is working on:

Click to see the roll call

Option 1: Help categorise the faults we’ve seen in computers

I’ll categorise manually row by row

Ideally, two people per sheet - one starts at the top, one starts at the bottom! (But laptops medium has a lot of records - we’ll need more people on that one.)

Desktop PCs

Laptop small

  • @ugo
  • …add yourself!

Laptops medium

Laptops large

  • …add yourself!


  • @Janet - update - made my way through all of the problem part, but :rotating_light: need help with solutions :rotating_light:

I’ll try to categorise automatically

Option 2: Play with the data (plots, visualisations, infographics, get creative!)

  • …add yourself!

Option 3: Answer freeform questions and what-ifs

  • …add yourself!

Option 4: Use your search-fu and help us research


I’m working on something completely different!

  • add yourself!

pinned #12


Also just noting that we have an album of good laptop photos, for use by datavizzers

The free fonts we tend to use are Asap and Permanent Marker.

Here’s our :paintbrush: Colour palette, some :laptop: Illustrations of components, devices & tools and also our :spiral_notepad: full branding guide.


Hello all! We’ll getting started in London now - if you’re joining us online, why not say hello here!


Just wondering what the difference between fault_type and fault_category is. Here’s an example of how it’s confusing me - Row 19 on the Tablets sheet

On the category I have the option for “firmware” but on type I have nothing that helps me out


:wave: from sunny Nottingham :bow_and_arrow:


Hi all from the South London Maker Festival! This may be ambitious but I’ll be attempting to combine the hackathon with a Restart Party at the festival, by working on visualisation with visitors to the festival. Updates to follow.


The fault_types are taken from a third party report and are not comprehensive, if you don’t find one that matches anything then enter a new fault type


Sorry everyone, especially @Steve_Cook: my sinusitis has come back & I’m going to have to spend some time inhaling steam & lying down.

I’ll try to dive into some data later on if I can.


Hi everyone, at Newspeak House we’re 13 people at the moment. We had a slightly slow start going through all that’s on offer. People are diving in the data now. Has anyone else joined remotely?


fault categories are simply umbrella terms for fault types but there is no actual relationship between the values in each list


Just in case anyone wants even more data, I’ve just uploaded an excel from http://www.wastedataflow.org/. This includes waste and recycling by UK borough by quarter (London sample only) and includes total estimates for Electronic waste in tonnes.