Research On Seamless Integration Technology Of Distributed Heterogeneous Spatial Data Based On Data Center Patterns

After many years of accumulation and development, the national spatial information infrastructure (NSII) of our country has reached a great scale, and provided massive spatial information resources for the national construction, social development and public services. However, with the widely development of network-based applications and the continuous improvement of it's requirement, the application of these spatial information resources also encountered some issues requiring urgent solutions, the key performance of these issues is that the integrated use of these spatial information resources is in a lower level. At the same time, spatial data interoperability technology has improved; the cooperative processing technology of distributed GIS has also been studied deeply; spatial data mining and information fusion technologies are becoming mature day by day. All of these provide new approach to solve the problems mentioned above. At present, a large number of geographical distributed data collection stations can share their own spatial data resources "in its own position"; spatial information between different level of government departments, enterprises and institutions are exchanged frequently; a wide range of new system patterns have been proposed to deal with distributed heterogeneous spatial data in an integrated way. In this situation, although the "information island" has been broken up in a certain extent, but the integrated use of distributed heterogeneous spatial data is still far from "seamless", the reason is that, for the seamless integration of spatial data, there is no a clear concept definition, technology is not blameless, and there is no a prototype system, and so on.On the other hand, in various application areas of GIS some spatial data center systems have appeared to manage spatial information resources. These systems have some similar patterns, they are, (1) be able to manage distributed heterogeneous spatial data resources in a unify and concentrate portal form; (2) widely use multi-level catalogue resource manager as the means of resource management; spatial data, non-spatial data and other resources can be grouped with a variety of themes and their order; (3) be able to organize into multi-level data centers cluster with the connection ability to the higher and lower level of data centers, and data can be exchange between all levels; (4) it's important to accumulate and reuse GIS functions, and sometimes has the abilities to reorganize the application system as soon as the requirement is changed. However, these spatial data center systems are almost simply put all kinds of spatial data and non-spatial data together to simplify the management process, and does not concern to integrate the data resource in a seamless and consistent way, that is all data resources can be geo-referenced using a unique spatial reference. Through the extension of data center model by introducing the concept, theory and technical methods of spatial data seamless integration, data center pattern will be upgrated into a feasible distributed heterogeneous spatial data seamless integration pattern, and then the existing spatial data center system can be prepared as prototype system.In this paper, combining with a task of National 863 Project, named "The technology research and software development of distributed heterogeneous spatial data seamless integration which supports incremental update", it focuses on to research and design a seamless integration framework for distributed heterogeneous spatial data, to set up a clear definition of this problem, to list out the design requirements of the framework, to analysis the key components of the framework, and to find out the implementation approach of these key components. On this groundwork, the paper also discusses and solves some key issues, such as the edit and update of seamless integrated spatial data, consistency maintenance methods, and query processing and query optimization techniques. Specifically the research works are as follows:(1) Retrospect to the development and actuality of distributed heterogeneous spatial data integration technology, pointing out that the direction is seamless integration and advanced fusion, deeply studing on the widely used concerned technologies, such as geographic information sharing and interoperability, maps joint, map conflation, spatial data fusion. Analysising the use scope of each technology, and any of them is half-baked for seamless integration. Considering the characteristics of distributed heterogeneous spatial data, the research work of seamless GIS, seamless spatial database, distributed GIS, and distributed multi-spatial database at home and abroad are introduced and discussed. It also summarizes the main kinds of existing spatial data center based spatial data integration patterns at home and abroad, pointing out the feasibility and necessity of these pattern to integrate spatial data seamlessly.(2) Setting up a complete conceptual model of seamless integration of spatial data. Studing various viewpoints of this problem, and the connection between these viewpoints, proposing the multi-layered semantic seamless integration model, pointing out that the seamless integration of spatial data is multi-level, multi-angle "stand-alone single-layer single-map"-liked transparent access and transparent application of distributed heterogeneous spatial data, and it's a systematic and comprehensive platform. Researching on various spatial data seam problems, especially the seams come from distributed heterogeneous environment. Analysising the cognition and modeling process of people to the real world geographic objects, pointing out that the continuity cracks and catabolizes of information in the transformation from the real world to the geo-feature set world is the reason of the seam, and proposing the idea of reverting the continuity and consistency back into the information. Focusing on the top-level user view of seamless integration, the concept of a seamless integrated system model, data location and description of resources, and data containers seamless integration, these work provide the foundation of the research and design of the integrated framework and prototype system.(3) By analyzing the reqirements from operating environment, distributed heterogeneous data processing, data integration and management, uncertainty, automated and intelligent, the paper points out that the seamless integration of spatial data is a systematic project need to meet a wide range of harsh conditions, and proposes the design principle of seamless integration system. Deeply analysising the spatial data center architecture and its general patterns, and discussing the feasibility to realize seamless integration framework based on the patterns of spatial data center. It researches and designs out a seamless integration system architecture, focusing on the key components, such as the framework, global catalogue system, global spatial index, multi-layer intelligent middleware, and so on.(4) Studing the version management mechanism of seamless integration framework. Proving that based on this mechanism a variety of seamless spatial queries can be done using the set difference operation in a high-performance manner. The seamless integration archive mechanism is proposed to improve the performance. Distributed heterogeneous spatial data register mechanism is studied and designed; the data cleaning pre-processing meathod is used to set up the initial seamless version of the data. Based on the data's initial seamless version, the maintenance of topological relationship and seamless characteristic in the process of data editing and updating can be done with the consistency maintenance measures, and can make ensure the data always in validate status.(5) Studing the query process of seamless integration spatial data, and its optimization. The general process data query is studied firstly, and then elaborating in detail on the implementation steps of concrete data query types. Analysising the key influencing factors in seamless query processing cost model, and provides research guidance for seamless data query optimization. It focuses on the research of some important optimization meathods, such as query processing compaction, the use of equivalent effectiveness mechanisms to reduce the volume of seamless computing, the use of data cache, and so on.(6) Researching on implementation of the distributed heterogeneous spatial data seamless integration prototype system. The key components of spatial data center related with seamless integration are extended and enhanced, and the basic functional needs are achieved through the data center fuction building mechanism. Through the practical application of the prototype system in the foundation geographic information database integration project, the feasibility and effectiveness of the technologies are verified.