February 2021 – CYBERMOSAIC

After attending a talk on data visualisation I was reflecting on the work of John Snow and the early use of data visualisation via mapping in 1854. John produced maps showing the location of water pumps and the prevalence of the disease cholera which was causing many deaths at the time. By plotting the number of deaths as bars at their geographic location and also the locations of water pumps a pattern emerged. In particular it was noted that around a pump in Broad Street Soho, there were a high number of deaths. Also at a brewery where workers had access to a private water supply there were less deaths. Up to that point the disease was thought to be spread through the air. By careful data collection, generating useful maps and gaining insight from the story they told, it was possible to trace the infection sources to poor water quality. Subsequent action taken directly from the data mapping saved numerous lives.

Disease mapping and the efforts of the track and trace app are the latest version of this effort of match disease data with geolocation. With Covid-19 infection data available for every postcode in the UK, what are todays Broad Street water pumps and Soho brewery equivalents? Interestingly one of the services still in use during the lockdowns that also require human contact are ATM’s and cashpoints. It just so happens that both google maps and most of the banks provide this information via API’s. An interesting question is therefore, are there ATM and Covid-19 hotspots? Is there a relationship between the location and use of cashpoints and Covid19 transmission? Are some machines cleaned more frequently than others and does this matter? Are there any other services from which mapping data and Covid-19 infections can draw unexpected but useful insight?

To start the experiment the first step is to collect the data. For me that looks like accessing API’s:

NHS Developer Portal

https://developer.api.nhs.uk/coronavirus

Banking API’s

https://developer.lloydsbank.com/

https://developer.santander.co.uk/sanuk/external/atms

https://developer.barclays.com/catalogue

The next step is to play around with these. If the most dangerous ATM in the country can be found you’ll at least know whether to take one or two bottles of hand sanitiser with you the next time you use cash (if indeed you ever need to again!!!).

I attended a seminar today in which the role of identity was discussed in the context of gender. It was the first time I learnt the correct definition of gender vs. sex and gained an appreciation of how online and offline identity might play a role in peoples very personal journeys.

During the questions another interesting topic came up – if we had a general AI, what gender would it be?

As more of our lives and even our identities move on line, it occurred to me that protection of a persons online identities may have a safety implication, if not a privacy one. So as an exercise, the following links have been collated for me to share to those who ask for them: