Approximating Accessibility of Regions from Incomplete Volunteered Data
Author: | Asghari, H., Stolberg-Larsen, J., & Züger, T. |
Published in: | CHI EA '22: CHI Conference on Human Factors in Computing Systems Extended Abstracts, 1-6 |
Year: | 2022 |
Type: | Academic articles |
DOI: | 10.1145/3491101.3519706 |
Being informed about the accessibility of neighborhoods, cities, and regions can help persons with disabilities in making travel and daily decisions. This information can also be useful and a pushing factor for supportive public policies. While accessibility mapping initiatives, such as Wheelmap.org, have enjoyed tremendous success and scale, they are still far from exhaustive, and their coverage contains biases stemming from volunteer practices. With the aid of the framework of causal statistics, we suggest approaches to adjust for these biases, with the end goal of providing helpful approximations of overall accessibility in different European geographical regions.
Visit publication |
Download Publication |

Connected HIIG researchers
Jakob Stolberg-Larsen
Ehem. Wissenschaftlicher Mitarbeiter: AI & Society Lab
Hadi Asghari, Dr.
Wissenschaftlicher Mitarbeiter: AI & Society Lab
Theresa Züger, Dr.
Forschungsgruppenleiterin Public Interest AI | AI & Society Lab