Ian Ozsvald: Keynote at EuroPython 2018 on “Citizen Science”

I’ve just had the privilege of giving my first keynote at EuroPython (and my second keynote this year), I’ve just spoken on “Citizen Science”. I gave a talk aimed at engineers showing examples of projects around healthcare and humanitarian topics using Python that make the world a better place. The main point was “gather your data, draw graphs, start to ask questions” – this is something that anyone can do:

EuroPython crowd for my keynote

NOTE that this write-up will evolve over a few days, I have to add the source code and other links later.

In the talk I covered 4 short stories and then gave a live demo of a Jupyter Lab to graph some audience-collected data:

• Gorjan’s talk on Macedonian awful-air-quality from PyDataAmsterdam 2018
• My talks on solving Sneeze Diagnosis given at PyDataLondon 2017, ODSC 2017 and elsewhere
• Anna’s talk on improving baby-delivery healthcare from PyDataWarsaw 2017
• Dirk’s talk on saving Orangutangs with Drones from PyDataAmsterdam 2017
• Jupyter Lab demo on “guessing my dog’s weight” to crowd-source guesses which we investigate using a Lab

The goal of the live demo was to a) collect data (before and after showing photos of my dog) and b) show some interesting results that come out of graphing the results using histograms so that c) everyone realises that drawing graphs of their own data is possible and perhaps is something they too can try.

The slides are here .

Here’s some output. Approximately 440 people participated in the two single-answer surveys. The first (poor-information estimate) is “What’s the weight of my dog in kg when you know nothing about the dog?” and the second (good-information estimate) is “The same, but now you’ve seen 8+ pictures of my dog”.

With poor information folk tended to go for the round numbers (see the spikes at 15, 20, 30, 35, 40). After the photos the variance reduced (the talk used more graphs to show this), which is what I wanted to see. Ada’s actual weight is 17kg so the “wisdom of the crowds” estimate was off, but not terribly so and since this wasn’t a dog-fanciers crowd, that’s hardly surprising!

Ian applies Data Science as an AI/Data Scientist for companies inModelInsightand in his, sign-up for. He also founded the image and text annotation API

, lives in London and is a consumer of fine coffees.