Design and Implementation of Constraints for 3D Spatial Database: Using Climate City Campus Database as an Example

Nowadays the field of geo-information is undergoing major changes, and the transition from 2D to 3D is having a major influence. A significant amount of 3D datasets are stored in the database. Experts are aware that new quality control mechanisms need to be built into the database systems in order to secure and guarantee high-performing data. Constraints are effective in providing solutions needed to avoid errors and enable maintenance of data quality. Whereas constraints for 2D geographic datasets have already been the subject of several research projects, studies into 3D geo-data constraints are largely unexplored. This thesis research discovers a new approach to model, conceptualise and implement 3D geo-constraints which can function in the database. At the outset, constraints can be formulated using natural language. As natural language is subjective and varies between individuals, expressions can be ambiguous and can easily cause confusion. So spatial constraints are abstracted using geometry that depicts the exact shape, and also topology that reveals the spatial relationship between geometries. This step makes the meaning of a constraint clearer to others. Furthermore, using standardised UML diagrams and OCL expressions, geo-constraints can be formalised to an extent that not only humans, but also machines can understand them. With model-driven architecture supported by various softwares, OCL expressions can be automatically converted to other models/executable codes (e.g. PL/SQL) just by a few clicks. And with small modifications, database triggers can be formulated to carry out constraints check. A database including various topographic objects (e.g. buildings, trees, roads, grass, water-bodies and terrains) is used as a study case to apply the discovered approach. During this research, a first attempt to formulate 3D geo-constraints in OCL has been made. These expressions can be tested and translated to other models/implementations when the OCL standard is extended with spatial types and operations. In the implementation stage, the current 3D functions in Oracle Spatial database are found to be insufficient. A new 3D function using existing 2D functions - plus additional code relating to computational geometry - has been developed by the author to bridge the gap. Based upon this function, a large group of spatial constraints which apply to objects in 3D space can be checked. Bentley Map and Python IDLE are used to test the performance of constraints as well as the visualisation of warning messages to clients. Database error messages are immediately displayed on the front-ends when a modification that does not satisfy a constraint is attempted to commit to the database. During the case study, new classes of constraints are also discovered. They are higher-level constraints, parameterised constraints, constraints allowing exceptional instances, extra-check rules to detect conflicting constraints and constraints relating to multi-scale representations.MSc GeomaticsGIS-technologyOTB Research Institute for the Built Environmen