Can you fixme? An intrinsic classification of contributor-identified spatial data issues using topic models
Rajesh Chittor Sundaram, Elham Naghizade, Renata Borovica-Gajic, Martin Tomko
INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE | TAYLOR & FRANCIS LTD | Published : 2021
Assessing OpenStreetMap (OSM) data quality against authoritative data sources may not always be viable. This is primarily because of the multi-dimensional nature and heterogeneity of the maps, yet the activity is pivotal for targeted data cleansing and quality enhancement undertakings in these data sets. A salient facet of OSM, allowing contributors to flag potential problems encountered during the mapping process, is the FIXME tag. In this article, we examine and discuss OSM data quality through the vast expanse of issues (knowledge) documented via FIXME. We present a classification and analysis of these quality issues, exposed as topic models and grounded in the ISO-19157 standard, across ..View full abstract
Awarded by Australian Research Council
This research was supported by the Australian Research Council [ARC DP170100153].