MobSciData Factory addresses the scientific and technological challenges of exploiting mobility data related to the movement of people and goods by enabling the secure, interoperable, and privacy-compliant collection, sharing, processing, and analysis of heterogeneous data. The project adopts an integrated approach combining data, methods, and infrastructure to improve the accessibility, quality, traceability, and governance of mobility data, in support of reproducible research and informed decision-making for sustainable mobility.
Objectives
The primary objective of MobSciData Factory is to design and deploy a shared and non-fragmented platform for mobility data storage, processing, and scientific sharing. This platform will provide access to inventoried, gathered, and acquired mobility data from both homogeneous and heterogeneous sources, at scale. More specifically, MobSciData Factory aims to:
1. Improve access to mobility data
Facilitate secure and transparent access to heterogeneous mobility datasets by documenting their origin, quality, context, and governance.
2. Develop open and reproducible methods
Design and share open-source tools and methods for processing, calibrating, enriching, and analysing multi-source mobility data.
3. Ensure data quality and traceability
Guarantee data lineage and reproducibility by documenting the full data life cycle, from collection to final exploitatio
4. Deploy a secure and interoperable platform
Provide a cloud-based, privacy-compliant infrastructure enabling scalable data sharing and distributed processing for the scientific community.
Scientific and Technological Challenges
To achieve these objectives, the consortium will face several key scientific and technological challenges.
Challenge 1 – Data accessibility, gathering, and acquisition:
Mobility data often raise significant privacy and governance concerns, which limit access for the scientific community. Restricted access to real-world mobility data impacts research reproducibility, limits the generality of results, and slows scientific progress. In addition, data acquisition by academic actors is resource-intensive and often results in limited, homogeneous, and non-scalable datasets. MobSciData Factory addresses this challenge by facilitating shared access to heterogeneous mobility data sources within a controlled and transparent framework.
Challenge 2 – Data quality, representativity, and traceability:
Mobility data are highly dependent on their collection context and methods. However, many existing datasets lack sufficient documentation regarding their lineage, collection conditions, and spatiotemporal coverage, which complicates their interpretation and reuse. The project places particular emphasis on data traceability by recording contextual, technical, and methodological information associated with data collection and processing, thereby improving data quality assessment and representativity.
Challenge 3 – Data processing, enrichment, and multi-source exploitation:
Existing approaches to mobility data processing are often fragmented, poorly documented, and difficult to reuse or combine. Processing multi-source mobility data further increases complexity due to differences in data nature, scale, and collection conditions. MobSciData Factory aims to overcome these limitations by developing unified, modular, and interoperable methods and tools covering the full data pipeline, including calibration, fusion, enhancement, validation, and exploitation.
Challenge 4 – Centralized and interoperable support platform:
Scientific infrastructures for data and tool sharing are currently fragmented and governed by independent entities, limiting their interoperability and usability. This fragmentation hinders reproducibility, repeatability, and collaboration within the scientific community. MobSciData Factory addresses this challenge by designing a centralized, cloud-based platform that supports secure data sharing, distributed processing, and interoperable tool deployment, while respecting data sovereignty and privacy requirements.
Toward a unified mobility data ecosystem
By addressing these challenges jointly, MobSciData Factory aims to establish a coherent and sustainable mobility data ecosystem that supports open science, interoperability, and long-term scientific collaboration. The project ultimately seeks to accelerate mobility research and contribute to the development of data-driven strategies for more sustainable mobility systems.