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Leeds Data Mill
The document discusses the CKAN framework, highlighting its widespread adoption by over 30 national governments and 100 local installations, along with 500,000 raw datasets available. It also mentions Datapress as an application providing turnkey cloud hosting and features such as the CKAN API and data sharing community initiatives. The content emphasizes a simple data-flow model versus a real-world data flow model.
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Leeds Data Mill
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- 6. • CKAN isa Framework • 30+ National Governments • 100+ Local Installs • 500k+ Raw Datasets
- 7. • DataPress isan App • Turnkey cloud hosting • DCAT, CKAN API • Data sharing community
- 9. • Citizen Dashboard •Driven by API • Released open source
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- 13. Real-World Data FlowModel
Editor's Notes
- #2 • Hi there, my name is Tom Rees ◦ I’m a programmer and sort of an Open Data Hacker ◦ I run a tech startup in London called DataPress ◦ If you’ve ever done any publishing or blogging with WordPress, you can think of DataPress as being like WordPress for data. ◦ We run data portals and data catalogues, helping companies and councils to organise and publish their data so people can get to it and re-use it
- #3 • So story number 1. Cast your minds back... ◦ The year is 1854, the place is London ◦ This bridge didn’t begin construction until 1886, but there aren’t any photographs from 1854, so this is from the Sherlock movie. It’s to get you in the mood. ◦ PEOPLE ARE DYING MYSERIOUSLY ◦ There is a miasma in the air, causing people to get sick and die ◦ Britains top medics and priests can’t solve the mystery ◦ It appears to be killing at random...
- #4 • They didn’t need a doctor, they needed a Data Scientist ◦ In this case, the hero of the story is John Snow, or “Jon Snooooo”. ◦ He took a different approach to solving this problem. ◦ He went around afflicted areas, knocking on doors, creating a list of outbreaks. ▪ They were somewhat naive. We now know that they were crowdsourcing a geospatial dataset.
- #5 • Snow and his team began to cross-reference this dataset with other available sources. ◦ Again this is naive, he was wireframing application mashups. ◦ They tried various types of correlation in this research. ▪ Weather. ▪ Migration patterns. ▪ Transport. ▪ It was basically a hackathon ◦ And they stumbled on a perfect fit. The London Water supply lines.
- #6 • In the end, despite there being no conclusive test to detect the infection... ◦ They worked out that this outbreak was Cholera ◦ Contracted from this pump handle ◦ A Soho water pump. ◦ With a pub named after Jon. ◦ Steps were taken, lives were saved ◦ Because as data scientists, that’s what we do. Humble work, but we save lives. ◦ There was no single resource or dataset which solved the problem for Snow. ◦ The moral of the story is that much more incredible things happen when sharing data and connecting the dots.