The rapidly increasing use of computers, IoT-devices, and interconnected wearables and mobile devices have given individuals, researchers, (commercial) organisations, and governments access to nearly unlimited information in the form of digital data. This personal information offers unique insights on different tiers of behaviour – individual behaviour traits, combined traits, and group behaviours as observed through a combination of data from multiple individuals.
In the context of mobile computing,
mobile and wearable devices can collect an uninterrupted stream of information
about the user’s activity, location, and e.g.,
device usage related information. Mobile devices have several built-in sensors
(e.g., accelerometer, proximity sensor, gyroscope). These mobile sensors
are primarily used by the mobile operating system to enhance the user
experience, such as app functionality or mobile device user interaction (e.g.,
vibration feedback, screen orientation detection). Other sensed
measurements (e.g., overall device
use, application choices, battery-related characteristics) can reveal
information on a user’s device usage behaviour. Information retrieved via these
sensors and further processed can further reveal associations with the users
behaviour in vivo, or daily affect, such as boredom or stress.
In this workshop, we bring together
researchers who take advantage of the proliferation of mobile devices, use these
devices as instruments for research on human activities and device usage
behaviour. We investigate new and existing methods and tools for collecting
instrumented data. We are especially interested in mobile devices, systems,
applications, methods and tools that were built to collect, augment, and explore
such rich datasets. More so, we want researchers to share their experiences,
successes, and frustrations on conducting research and analysing information
from such power and processing constrained devices to capture the state-of-the-art.
