TY - GEN
T1 - Push-based Spatial Crowdsourcing for Enriching Semantic Tags in OpenStreetMap
AU - Gummidi, Bhuvan
AU - Pedersen, Torben Bach
AU - Xie, Xike
AU - Zimányi, Esteban
N1 - Conference code: 27th
PY - 2019/11/8
Y1 - 2019/11/8
N2 - OpenStreetMap (OSM) is a popular community-driven mapping platform with voluntary contributions from (amateur) cartographers. However, it is a difficult process for the cartographer to identify the areas where she can best contribute to OSM. Furthermore, the current OSM spatial entities are missing many tags; for example, top three road network tags, Name, Source, and Surface, are available only for the 10% of the total road segments. Our paper aims to improve the quantity and quality of the road network tags by actively pushing the nearest road segments for the cartographer to be mapped. We propose a push-based spatial crowdsourcing method to achieve this objective, and validate it by focusing on road segments in OSM. Specifically, we formally define the batch-based maximum road segment task assignment problem and suggest methods based on heuristics like travel distance and road segment task grouping. Finally, our experimental evaluation verify the applicability of our assignment solutions by comparing the resulting number of assigned tasks. With regard to the number of assigned road segments, our junctions-based and road segment-based heuristic methods, outperform the baseline methods by five and two times, respectively.
AB - OpenStreetMap (OSM) is a popular community-driven mapping platform with voluntary contributions from (amateur) cartographers. However, it is a difficult process for the cartographer to identify the areas where she can best contribute to OSM. Furthermore, the current OSM spatial entities are missing many tags; for example, top three road network tags, Name, Source, and Surface, are available only for the 10% of the total road segments. Our paper aims to improve the quantity and quality of the road network tags by actively pushing the nearest road segments for the cartographer to be mapped. We propose a push-based spatial crowdsourcing method to achieve this objective, and validate it by focusing on road segments in OSM. Specifically, we formally define the batch-based maximum road segment task assignment problem and suggest methods based on heuristics like travel distance and road segment task grouping. Finally, our experimental evaluation verify the applicability of our assignment solutions by comparing the resulting number of assigned tasks. With regard to the number of assigned road segments, our junctions-based and road segment-based heuristic methods, outperform the baseline methods by five and two times, respectively.
KW - OpenStreetMap
KW - Task Assignment
KW - Spatial Crowdsourcing
KW - Semantic Tags
KW - Road Network
U2 - 10.1145/3347146.3359365
DO - 10.1145/3347146.3359365
M3 - Article in proceeding
SP - 532
EP - 535
BT - Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
A2 - Banaei-Kashani, Farnoush
A2 - Trajcevski, Goce
A2 - Guting, Ralf Hartmut
A2 - Kulik, Lars
A2 - Newsam, Shawn
PB - Association for Computing Machinery
T2 - International Conference on Advances in Geographic Information Systems
Y2 - 5 November 2019 through 8 November 2019
ER -