RUSHMORE - Resources for Human Mobility Research

• Applicants: Professorin Dr. Elena Demidova; Professor Dr. Stefan Dietze; Dr. Simon Gottschalk; Dr. Benjamin Zapilko
• Subject Area: Data Management, Data-Intensive Systems, Computer Science Methods in Business Informatics ; Empirical Social Research
• Term: since 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 547610252

Mobility data and its analysis play an essential role for a wide variety of stakeholders from research to address different tasks, e.g., study social inequalities, build traffic prediction models, and support infrastructure decisions. Several challenges exist specifically relevant in the context of mobility data; for example, such data is often limited to specific regions and time frames. To still enable analyses and to generalize from these datasets, the synthetic generation of data and the development and provision of transferable models are important prerequisites. With RUSHMORE, we plan to provide such datasets and develop new methods and a search prototype for human mobility research. Further, we plan to perform in-depth evaluations and infer best practices for developing data services that offer mobility data and metadata to interested data consumers according to the FAIR principles. In detail, we aim at addressing the following objectives: (i) facilitating multidisciplinary research regarding a variety of use cases by providing open and FAIR access to a wide range of mobility-related data and models; (ii) engaging the research community in widespread sharing and reuse of mobility data to facilitate interdisciplinary research; (iii) closing data gaps and addressing sparsity and costliness of mobility data through representative synthetic data and machine learning models generated out of established and comparable datasets.

• DFG Programme: Research data and software (Scientific Library Services and Information Systems)