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Quantified Self: Where to start ? 3 года назад


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Quantified Self: Where to start ?

For this session, we bring you three individual use cases on how to get started with data collection for Quantified Self. Each mini talk will last approximately 15 minutes and will be followed by a 15 minute Q&A at the End 0:00 Introductions 5:40 Tim: Everything your phone knows about you If you’re reading this you're likely doing it on your phone. It turns out our phones collect a lot of data passively about our habits and given that most of what we do can make its way through your phone, I’ll explore how much data and what data can be extracted from your phone using mostly passive collection methods. 22:52 Ellie: Health & Sports Data Description: Whilst there are so many things collecting data about your daily movements, moods, steps - how do you actually access them all, and more importantly analyse them? I’ll show you how to access the data from your phone, Strava, and Garmin devices and what to do with these data sources once you have them to get a full picture of your health/ activities to analyse. 36:56 Jenny: Fitbit Sleep Data Description: If you own a Fitbit then you’ll know that it’s constantly collecting all kinds of data about you that you can view in the app. As data geeks, this isn’t enough, we want the ability to extract this data and play with it ourselves! Luckily there’s an API for that and we’ll talk through how to get access to all your historical sleeping data. 51:48 Questions: Links https://exiftool.org http://files.tableaujunkie.com/fitbit...   / strava   https://dev.fitbit.com/apps https://darksky.net/forecast/40.7127,... https://support.google.com/docs/answe... https://www.strava.com/account http://connect.garmin.com/signin https://dev.fitbit.com/build/referenc... ---------------------------------------------------------------------------------------------------- Want more information about us? Head over to theinformationlab.co.uk Want to see more of our events? Head over to til.bi/talkdata to find out more ----------------------------------------------------------------------------------------------------

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