What is it about?
In this paper, we present our position towards mobility data spaces, highlighting the idiosyncrasy of mobility data, while presenting the MobiSpaces approach that encompasses services for mobility data management and advanced mobility analytics. By exploiting MobiSpaces, mobility data providers can break the barrier of participation in data spaces thereby sharing their dataset with less hurdle, whereas data consumers can find advanced data analysis tools readily applicable on mobility data sets to extract insights and discover mobility patterns.
Featured Image
Photo by Connor Wang on Unsplash
Why is it important?
The distinguishing features of mobility data spaces relate to the idiosyncrasy of manipulation of mobility data; distributed data acquisition, imprecise data recording of spatial data, error detection and cleaning of spatiotemporal records, semantic data representation, analysis and learning of mobility patterns are just a few of the rising challenges in the mobility domain. Consequently, recent initiatives for mobility data spaces are trying to pave the way towards future mobility platforms, while also keeping up with modern research advances in mobility analytics and mobility data science.
Perspectives
As mobility plays a critical role in the global digital economy, the need for dedicated data spaces in this domain is increasingly vital. This paper presents our perspective on mobility data spaces, emphasizing the unique characteristics of mobility data. It introduces the MobiSpaces approach, which offers comprehensive services for mobility data management and advanced analytics. MobiSpaces is designed to facilitate efficient, trustworthy, and reliable data sharing across organizations and businesses, aligning with the European Union's directives for future mobility data spaces.
Ioannis Chrysakis
Netcompany-Intrasoft
Read the Original
This page is a summary of: The MobiSpaces Manifesto on Mobility Data Spaces, October 2024, ACM (Association for Computing Machinery),
DOI: 10.1145/3685651.3685654.
You can read the full text:
Contributors
The following have contributed to this page
