Towards Mobility Data Science (Vision Paper) Co-Authored by EMERALDS Scientific & Technical Coordinator
EMERALDS Scientific & Technical Coordinator Yannis Theodoridis and other project partners have co-authored a seminal paper that delves deep into the burgeoning field of mobility data science. The paper explores the complexities of collecting, analysing, and managing vast volumes of mobility data, a topic that has gained increasing importance with the proliferation of location-enabled devices.
Interdisciplinary Vision for Mobility Data Science
The paper presents an interdisciplinary vision for mobility data science, outlining a complete pipeline that includes data collection, cleaning, preprocessing, and analysis. This comprehensive framework serves as a foundational guide for researchers and practitioners, offering a structured methodology that addresses the unique challenges of mobility data.
Distinguishing Characteristics of Mobility Data
The paper makes a crucial distinction between mobility data science and general data science. It highlights that current data science systems, tools, and algorithms are not directly applicable to mobility data due to its unique spatial and temporal dimensions, high frequency of updates, and heightened privacy requirements. This differentiation enriches the academic discourse and guides practitioners in adopting more targeted approaches.
A Call to Action: Open Challenges
The paper goes beyond merely presenting the current state of the art; it serves as a clarion call to the research community. It outlines a range of open challenges that need to be tackled, urging the community to build its own mobility data science pipeline for better performance and more effective applications.