Extract User-Generated Content from Spatial Data Provision Services

User-generated content and voluntary data are valuable information sources commonly used in many fields to derive new knowledge, guide decision processing, or tailor recommendations. Acquiring such data from a typical data provision service is not trivial, because several limitations arise from legal, commercial, and technological points of view. A data consumption application needs to be carefully designed in order to extract a consistent and meaningful picture of the available data, particularly when it is subject to budget constraints. This paper provides a comprehensive discussion and formalization of the topic, focusing on a specific problem found in many spatial services: detecting sites located in a specific area of interest, subject to a limited budget. Moreover, a solution is presented which is based on an incremental interactive algorithm with tailored data structures and parallel optimizations.