Yes, I’ve taken all this into account – the visualisation is very rough (I set the thresholds so I’d get a nice balance of red, yellow and green markers).

There’s a bunch of things I’d do to complete the visualisation:

- Use the notations as a way of categorising the bacteria levels like you sugguest
- Visually include the actual assessment quality rankings
- Explain what the bacteria do to us
- Include some history about England’s bathing water
- Compare a cup of water/london’s sewage system bacteria levels so people understand what level of bacteria is being talked about…

Yes – getting 500 items back from the API was like taking a bite out of a cake and finding out it’s moist.

Nice work. I don’t know where you set your thresholds of High, Medium, Low etc. But if you want to be selective in your API calls you can used the notations on the sample classifications. For weekly in-season assessment:

eg: http://environment.data.gov.uk/doc/bathing-water?latestSampleAssessment.sampleClassification.complianceCodeNotation=G 

or for annual compliance assessments:

http://environment.data.gov.uk/doc/bathing-water?latestComplianceAssessment.complianceClassification.complianceCodeNotation=G

Code notations go: G, I, F, C, N (Higher/Excellent, Minimum/Good, Fail/Poor, Closed and Not-Assessed respectively).

Bet you liked being able to get 500 plus items at a shot

Stuart

Could you provide some more specificity as to how you got the RaphaelJS to process JSON data?

Interested in a similar initiative and having trouble wrapping my head around how to be process the results of the SPARQL query and continue to leverage the linked data API in the result set.