Abstract
This dissertation combines both novel methodological work as well as high-quality scientific software development for mobility data science. It presents novel methods enabling movement data exploration that scale to massive datasets, describes the development of a novel open source scientific Python library for EDA of movement data (MovingPandas), and proposes the first structured EDA protocol for movement data.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of Mobile Data Management (MDM) 2024 |
| Pages | 325 - 327 |
| ISBN (Electronic) | 979-8-3503-7455-1 |
| DOIs | |
| Publication status | Published - 2024 |
| Event | 25th IEEE International Conference on Mobile Data Management - Brussels, Belgium Duration: 24 Jun 2024 → 27 Jun 2024 https://mdm2024.github.io/ |
Conference
| Conference | 25th IEEE International Conference on Mobile Data Management |
|---|---|
| Abbreviated title | MDM 2024 |
| Country/Territory | Belgium |
| City | Brussels |
| Period | 24/06/24 → 27/06/24 |
| Internet address |
Research Field
- Multimodal Analytics
Keywords
- Spatial data science
- Mobility data
- mobility data science
Fingerprint
Dive into the research topics of 'Exploratory Analysis of Massive Movement Data'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver