Uploaded on 2016-04-26 by MonserratJ

Visible information: great number of bikes in a crowded street full of restaurants and tourists (I know it's not the best picture, but bare with me). Invisible information: - let''s suppose these bikes are part of a bike share program which requires the users to have a card/ID. From this ID we can know the age and home addresses of the users. Thanks to the bike share program, and its pick up and drop off points, we can learn more about these bikers' lifestyles: where do they go, at what time... Bike traffic as well as other specific information disaggregated by age or sex, like in the examples provided in the videos. - this is also a crowded street with stores and restaurants. I was thinking of information that can be provided by mobile phones and credit cards. Again, we can count on details like age, sex, home address, typical spending of people. See where they go. How far they are willing to travel to get to the shops, how often they go there, etc. This information could help when deciding what types of store to open in the area or to decide the target population of the stores, how many parking (or bike) spots we would need, etc. [1]: https://edxuploads.s3.amazonaws.com/14616941024061242.jpg