Using visual analytics to detect problems in datasets collected from photo-sharing services

Datasets that are collected for research often contain millions of records and may carry hidden pitfalls that are hard to detect. This work demonstrates how visual analytics can be used for identifying problems in the spatial distribution of crawled photographic data in different datasets: Picasa Web Albums, Panoramio, Flickr and Geograph, chosen to be potential data sources for ongoing doctoral research. This poster summary describes a number of problems found in the datasets using visual analytics and suggests that greater attention should be paid to assessing the quality of data gathered from user-generated photographic content. This work is the first part of a three-year PhD project aimed at producing a pedestrian-routing system that can suggest attractive pathways extracted from user-generated photographic content.