2021-04-23, 16:30–17:00, Track 1
Focusing on human mobility data, the trackintel framework (https://github.com/mie-lab/trackintel) provides functionalities for mobility data modeling, quality enhancement, data integration, performing quantitative analysis and mining tasks, and visualizing the data and/or analyzing results.
The trackintel framework structures human movement into hierarchical units (i.e., positionfixes, triplegs/stages, trips and tours), and provides functionality to generate everything starting from the raw tracking data. It also provides functions for a complete mobility data processing pipeline:
- Preprocessing (filtering, outlier detection, imputation of missing values, quality assessment, data aggregation)
- Contextual Augmentation (map matching, trajectory algebra-based context addition)
- Analysis (extraction of mobility metrics, preferences, systematic mobility)
- Visualization and Communication (generation of maps, charts)
In this talk, we will introduce you to the most important functionalities of the trackintel framework. Moreover, using real-world tracking data, we will provide typical use-cases for different mobility data processing tasks, revealing the usefulness of the framework.