Resources for Human Mobility Research (RUSHMORE)

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.