Naturally, we are working on the problem of gender-neutral toilets! Our project wiki page is here: CrowdPee.
As mentioned before, the official public toilets in Zürich are non-gendered (apart from urinals), but we want to get lots more information. One dataset that caught our eye was the list of licensed premises. We're going to use that list as a starter set and collect data on their toilets in two ways:
- Using crawlers to find contact details for these establishments, and emailing them to ask.
- Using Twitter / Flickr / etc. bots to find geotagged updates from their locations, and asking people to fill out a quick questionnaire about their toilets.
|CrowdPee data collection diagram|
Since the locations we're targeting are places that sell alcohol, we will probably mostly be approaching people who are out enjoying themselves. Vincent proposed that the questionnaire should be as short and as fun to fill out as possible, with pictures rather than radio buttons (he hates radio buttons!) and easy to complete on a phone. It could also be useful to give something back to the user when they complete a questionnaire ... a picture / video / joke / voucher / something else? What's more, since we are anticipating that people will be answering our questions on smartphones, why not have them upload a photo of the toilets at the same time? David pointed out that the photo and questionnaire would have to be sent separately, since a webpage cannot communicate with a smartphone camera. Something to think about.
We will also need to make a database to store the returned information, and of course, the more questionnaires that are filled out for a venue, the more reliable the data will be. To keep things simple for the responders, we agreed to limit ourselves to the following questions:
- Are the toilets unisex, or gendered?
- Safe2pee.org distinguishes between 'genderfree' and 'single stall or locking'. Maybe we should too?
- Accessibility can be much more nuanced than this, of course. Is this too simplified?
- David suggested this question, an important consideration.
We have started work on the Twitter bot, using Tweepy and with Will Thompson's fewerror bot as a handy base. Our code is here. So far, we can identify tweets within about 500 metres of a known restaurant in Zürich. The next step will be making a questionnaire for them to visit. We might need help with the design, as none of us are artists!