Το work with title Spatiotemporal graph queries on geographic databases under a conceptual abstraction scale by Partsinevelos Panagiotis, Papadakis Konstantinos, Makantasis Konstantinos is licensed under Creative Commons Attribution 4.0 International
Bibliographic Citation
Partsinevelos P., Papadakis, K., and Makantasis, K., (2013), Spatiotemporal graph queries on geographic databases under a conceptual abstraction scale,
Geo-spatial Information Science, Taylor and Francis, 01/2014; 17(2). DOI: 10.1080/10095020.2014.915482
https://doi.org/ 10.1080/10095020.2014.915482
Visual queries assist non-expert users to extract information from spatial databases in an intuitive and natural approach, making Geographic information systems comprehensive and efficient for a wide range of applications. A common visual means of querying takes the form of drawings or graphs, under which many spatial ambiguity and translation errors rise. In this study, common query attributes extracted from user graphs such as spatial topology, size, cardinality, and proximity are regarded under a conceptual moderation scheme. Thus, the system/user may concentrate on various conceptual combinations of information. Furthermore, time is incorporated to support spatiotemporal queries for changing scenes and moving objects. Arbitrary, relative, and absolute scaling is possible according to the data-set and application at hand. The theoretic approach is implemented under a prototype user interface system, called ShapeController. Under this prototype, a user may extract scene-based relations in an automatically inferred fashion, or include single object-oriented relations when all possible relations seem redundant. Finally, a natural language description of the query is extracted upon which the user may select the desired query relations. Experimentation on a spatial database demonstrates the concepts of predefined draw objects, scaling relaxation, conceptual abstraction, and scene, object- and textual-oriented transitions that promote query expressiveness and restrain ambiguities.