Title: A fuzzy object relational model for the management of spatial data
Abstract: Management of GIS data presents unique problems. These include the need to: (1) Manage a wide range of differing applications data formats. (2) Bundle these formats into meaningful organizations that are driven by geospatial concerns. (3) Provide lineage and version support. (4) Provide documentation of the nature of the data and other descriptive information. (5) Maintain and keep track of meaningful relationships between sets of data.
Current industry, research and academic approaches to the problems of GIS data management can provide partial solutions to the problems found in data management. However, none of these solutions is complete. Most have strengths that are offset by the technical limitations of their underlying models, assumptions or technologies. None present a comprehensive generalized solution. This situation has created an opportunity to build a more capable and robust solution. The key to such a solution was found through the integration of multiple theories, approaches and concepts. Attempts to utilize these ideas in the past have been applied in industry and research, but none has attempted to integrate them into a comprehensive solution or solve the problems that may arise as a result of integration. The research is a major step toward providing such a solution. The key concepts and theoretical areas that this research builds on are data modeling, the use of metadata, object oriented technology and set management
The final integration manifests itself in a comprehensive architectural solution that is composed of a data model, a system model and the use of object-oriented algorithms. At the center of this architecture is a data driven methodology, a data model composed of metadata.
The data model represents the metadata relationships created as a result of shifting the management approach of managing individual data files to that of set management. This produces numerous benefits for the users of GIS data, including versions, alternative views of data, and insulation from the impacts of the introduction of new types of GIS data.
Because set management can introduce ambiguities in the selection and definition of geospatial data, this approach applies fuzzy set theory to metadata to control such problems. This is a new approach, the theoretical basis of which was Chen's definition of the role of fuzzy theory in data models. This research extended the descriptive metadata data model for sets with notations that represent both fuzzy and crisp relationships. System structure and objects are defined that support and implement this model. These components complete an architectural model that provides a robust new solution to problems currently being experienced by users of GIS data. Finally, to validate this work, a small system was built (GIS Workbench) and tested in the current laboratory environment. Testing demonstrated that the software, hence the architecture was a viable means of managing GIS data.
Publication Year: 2000
Publication Date: 2000-01-01
Language: en
Type: article
Access and Citation
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot