Modern technology allows us to track essentially anything that moves, be it animals, people, vehicles, or hurricanes. As a result, many efficient computational methods have been developed to analyze movement data, including methods for similarity analysis, clustering, segmentation, classification, and pattern detection. However, movement rarely occurs in isolation and to truly understand movement data it is of paramount importance to understand the intrinsic and extrinsic factors that influence movement, such as or health conditions or motivation (intrinsic) or the (natural) environment, weather, and other surrounding entities (extrinsic). Often the data that describes these factors is available together with the tracked object data for analysis, but comparatively few computational techniques fully utilize the potential of such multifaceted data. This workshop intends to bring together researchers who are interested in developing computational techniques to analyze movement data in conjunction with other data sources that capture (some of) the factors which influence movement.

Format

Half-day workshop. One invited speaker and several contributed talks. We solicit research papers which may be preliminary, and position papers that present a vision or describe a future direction in heterogeneous movement data computation.

See the Call for papers page for more details on the submission requirements.

Important dates

Submission deadline: Monday, September 2, 2019, AoE, no extensions.

Notification: Before the end of September

Final version ready: Early October