During the beginning of the semester a keen discussion started. The public was shocked by the uncovering of Peter Warden and Alasdair Allan which discovered that apple was tracking user movements and saved them iPhone for an unlimited time. Especially in Germany, which is always a bit paranoid in terms of data gathering and tracking of individuals, a discussion about privacy and self determination broke out. Instead of generating new negative scenarios, we rather tried to use the gathered information in a positive way. Hence we designed a rating and recommendation system that helps people to find hidden, interesting or lovely spots in unknown surroundings like a new city. Furthermore, users can compare their impressions and self conceived map of their way with the real tracking results on a geographic map.
Field of ApplicationPrimarily, LiquidData is a research project. On one hand it was an experiment for smartphone and multitouch table communication. On the other hand we wanted to challenge our daily use of the massive data we gather or produce and how we deal with them. Personal data tracking is already part of our everyday life and it seems that we can not stop this process, or can we? Should we rather manage how to deal with it to use it for our own purpose? LiquiData is questioning these paradoxes of our privacy requests and the wish to share personal information on social media.
Although, our intention was the experiment in interaction and to discuss this topic and the practical use of the project. For instances it could be used in different kinds of navigation or tourist information systems.
The hotel lobby
One of the possible scenarios could be a hotel lobby where people return daily from their trips through the city with lots of photos and impressions. Now they see their way through the city and where they have been today if they »spill out« their movement profile. With the locations on the table they are able to tag them or observe how their paths differs from other guest. In addition, the user can add comments to the location on the table to recommend or warn of a specific spot. All of the data that has been loaded on the table can be a source of inspiration for the next trips.
The smartphone functions as primary interaction device. The movement profile automatically recorded by many devices, as well as geo-located photos, are transferred to the table and displayed at their positions on the map. All the data is being transmitted by swiping it of the phone to the table.
SnapperThe Snapper is the element that connects the smartphone to the multi touch table. It draws lines from the phone to the places. These locations can be browsed by rotating the smartphone. The amount of connected locations can be controlled by the circle around the Snapper.
LocationsThe locations represent public spots such as restaurants, bars, clubs, etc. that were in the radius of the user. The glyph visually encodes the various content types, with the size of the bubbles representing the amount of comments, photos and ratings for the location.
Circle navigationThe radial navigation is displayed after tapping a location on the table. This element enables to browse through comments, photos and ratings by dragging the scroll bar around the circle.
TableThe multitouch table is the central medium for the data. Every geographical information and every manual information as photos, comments and ratings are collected on the table. A user without a smartphone can passively browse through all the data to use it as a recommendation device. The dark map is hardly visible at the beginning. The data that a user loads on the table unveils the parts where the user has been. We used a liquid metaphor to make both the interaction easy to understand as well as to attract users by the playfulness of its behavior.
The prototype was developed with the Microsoft Surface I. The programming environment Processing was used for the entire application. The aesthetic and behavior of the liquid was done with the libraries GLGraphics and toxiclibs. The multitouch gestures works with the TUIO library. All the map functions and visualizations works because of Till Nagel’s Unfolding Library and TileMill. For guides on implementing TileMill with Processing, we highly recommend the Tutorial on Till Nagel’s website or this quick tutorial.