Too many times I have had the experience of being in a room where researchers or data scientists are talking about their results or methods in words that are not really understandable or meaningful to the rest of the room. Sometimes this is necessary as the situation is truly technical, but a lot of the time the use of complicated jargon can be a defence mechanism or an unnecessary status move. It's possible to talk about data in words that are digestible and relevant when we actually want to.

This month we're fulfilling a decades-long dream of mine; with the release of our online Data Speak Decoder. 

We've identified three types of data speak decoding: technical terms that are useful explained in a non-technical way, data terms that are needlessly confusing which usually have plainer or more specific alternatives, and lastly data terms with multiple meanings which can cause misunderstanding.

We're just starting to build the decoder and would love your help choosing the next terms to decode.

Find the Decoder here.

When I was a kid, one of the most important dates circled on my calendar was Amnesty Day at my local library. On these days, I could return my mountain of overdue books and have the late fees forgiven. Data Science needs a place to offer the same opportunity to learn from our mistakes without penalties or judgement. 

The We All Count Data Amnesty Salons are a place to share anonymous stories about what went wrong in your data projects, alert people to mistakes you’ve made in the past, and ask questions you might be embarrassed about. They are a judgement-free zone where we can all improve together.

Hosted by Heather Krause, the Salons are live-streamed and you can submit stories and questions in advance via our anonymous link (above) or by emailing Heather; or you can join the live discussion on the day! Unless your mistake is, like, career-endingly bad, in which case we DEFINITELY want to hear it, but I’d submit it anonymously. The best (and by best we mean worst) data gaff of each salon goes in the Data Amnesty Hall of Fame – a place to celebrate the difficulty and frequent absurdity of the world of Data Science. It’s part of our commitment to Demystify, Democratize and Demonstrate Data for Equity.