Dopplr as you all know is a great travel service – You fill in the cities you are going to travel to and every six months you are sent a wonderful automated travel report visualising your travel data in a very clear way.
The time taken to add your ‘data’ to Dopplr is something you really don’t mind as the benefits outweigh the ‘cost’.
What if you could record data about anything and visualise this in a personal report?
Daytum was created as a way for Nicholas to store all of this information. You sign into site and add a ‘thing’ with an ‘amount’ – cigarette : 1
This then gets logged into the system with a timestamp and as you smoke you keep updating the site. A mobile twitter interface is thankfully on hand as updating your data via a website is a chore upon a chore. Now you just have to tweet your ‘thing’ with your ‘amount. A similar system called your.flowing.data created by Nathan Yau is entirely built on top of twitter to store your data.
These are systems for the committed – You have to be in the mindset to fire off a tweet to record that thing.
Can objects we naturally interact with start to share the data they store?
The Wifi body scale is automated and is single minded in what it records.
Another great example is the Sleep Cycle iphone app – It is an alarm clock that wakes you up when you are in the lightest part of your sleep cycle. It does this by monitoring how you are moving while you sleep – the phone accelerometer registers your motion and figures out the best point you can wake up. Aside from sleeping better, the app produces a variety of graphs to help you understand your sleep cycle.
So can we automate the collection of any data without changing our normal behaviour?
Poyozo could be the development that does this ->
Poyozo gives you your own data back by downloading the information you’re currently giving to the web on to your own computer. You can opt-in to importing your data from Facebook, Twitter, Foursquare, Last.fm, Google Calendar, any email service, any RSS feed, Flickr, Wesabe, Listit, Skydeck, Dopplr, your Firefox browsing history, the local weather, and your location, allowing you to access all of this personal data as easily as the companies that run these services can.
So if we could be generating our own automated annual Feltron reports. What insights could they offer? Could they offer insights into our behaviour and moods
I was having a lovely lunch time chat with Mike Stenhouse about this very subject – He has been exploring a lot of these ways to visualise connections between data at trampoline systems and also in his own time. He started explain some of the prototypes he had built, gave some brilliant examples i’d never heard of and we chewed over some other random scenarios.
Did you gain weight one week (wifi scales) because you ate at a certain restaurant (foursquare) or you went on a business trip (dopplr). Were you sad at work one day (twitter), listening to incredibly depressing music (last.fm) and searching for a new job (bookmarks) and buying something to cheer youself (purchases). Could the report then identity that you were the happiest on a certain day or offer some insight into why.
Would be eventually be drowning in data from our lives and eventually be finding patterns with no meaning? Maybe so, but I for one would love to try it and see.