Mingqiang Guo

A Geospatial Information Grid Framework for Geological Survey.

The use of digital information in geological fields is becoming very important. Thus, informatization in geological surveys should not stagnate as a result of the level of data accumulation. The integration and sharing of distributed, multi-source, heterogeneous geological information is an open problem in geological domains. Applications and services use geological spatial data with many features, including being cross-region and cross-domain and requiring real-time updating. As a result of these features, desktop and web-based geographic information systems (GISs) experience difficulties in meeting the demand for geological spatial information. To facilitate the real-time sharing of data and services in distributed environments, a GIS platform that is open, integrative, reconfigurable, reusable and elastic would represent an indispensable tool. The purpose of this paper is to develop a geological cloud-computing platform for integrating and sharing geological information based on a cloud architecture. Thus, the geological cloud-computing platform defines geological ontology semantics; designs a standard geological information framework and a standard resource integration model; builds a peer-to-peer node management mechanism; achieves the description, organization, discovery, computing and integration of the distributed resources; and provides the distributed spatial meta service, the spatial information catalog service, the multi-mode geological data service and the spatial data interoperation service. The geological survey information cloud-computing platform has been implemented, and based on the platform, some geological data services and geological processing services were developed. Furthermore, an iron mine resource forecast and an evaluation service is introduced in this paper.

A spatially adaptive decomposition approach for parallel vector data visualization of polylines and polygons

With the wide adoption of big spatial data and the emergence of CyberGIS, the nontrivial computational intensity introduced by massive amount of data poses great challenges to the performance of vector map visualization. The parallel computing technologies provide promising solutions to such problems. Evenly decomposing the visualization task into multiple subtasks is one of the key issues in parallel visualization of vector data. This study focuses on the decomposition of polyline and polygon data for parallel visualization. Two key factors impacting the computational intensity were identified: the number of features and the number of vertices of each feature. The computational intensity transform functions (CITFs) were constructed based on the linear relationships between the factors and the computing time. The computational intensity grid (CIG) can then be constructed using the CITFs to represent the spatial distribution of computational intensity. A noninterlaced continuous space-filling curve is used to group the lattices of CIG into multiple sub-domains such that each sub-domain entails the same amount of computational intensity as others. The experiments demonstrated that the approach proposed in this paper was able to effectively estimate and spatially represent the computational intensity of visualizing polylines and polygons. Compared with the regular domain decomposition methods, the new approach generated much more balanced decomposition of computational intensity for parallel visualization and achieved near-linear speedups, especially when the data is greatly heterogeneously distributed in space.

Design and implementation of a distributed web service directory in SOA-oriented urban spatial information sharing platform

Web service directory is an important component of SOA-oriented urban spatial information sharing platform. The current UDDI and UDDI-based UBR have been poorly used actually. One the one hand, the business services of urban spatial information sharing platform have some characteristics such as diversity, complexity and security, so the increase of web services make the maintenance of UBR become very difficult. On the other hand, because there is no corresponding exchanging and connecting mechanism among the private services registry libraries, it results in the new services island among each UGIS. Aiming at the problems mentioned above, the paper designs and implements a distributed web service directory in SOA-oriented urban spatial information sharing platform. According to the characteristics of urban spatial information sharing services, through distributed portal service directory and node service directory, it can reasonably organize private or semi-private services registered libraries and easily implement mutually communications among them. It can transfer the business services to all UGIS information node service directory, avoid the implementation bottleneck and the difficulties of information maintenance which caused by the centralized model and improve the SOA-based application services availabilities.

A Knowledge-Driven Geospatially Enabled Framework for Geological Big Data

Geologic survey procedures accumulate large volumes of structured and unstructured data. Fully exploiting the knowledge and information that are included in geological big data and improving the accessibility of large volumes of data are important endeavors. In this paper, which is based on the architecture of the geological survey information cloud-computing platform (GSICCP) and big-data-related technologies, we split geologic unstructured data into fragments and extract multi-dimensional features via geological domain ontology. These fragments are reorganized into a NoSQL (Not Only SQL) database, and then associations between the fragments are added. A specific class of geological questions was analyzed and transformed into workflow tasks according to the predefined rules and associations between fragments to identify spatial information and unstructured content. We establish a knowledge-driven geologic survey information smart-service platform (GSISSP) based on previous work, and we detail a study case for our research. The study case shows that all the content that has known relationships or semantic associations can be mined with the assistance of multiple ontologies, thereby improving the accuracy and comprehensiveness of geological information discovery.

An efficient data organization and scheduling strategy for accelerating large vector data rendering

Rendering large volumes of vector data is computationally intensive and therefore time consuming, leading to lower efficiency and poorer interactive experience. Graphics processing units (GPUs) are powerful tools in data parallel processing but lie idle most of the time. In this study, we propose an approach to improve the performance of vector data rendering by using the parallel computing capability of many-core GPUs. Vertex transformation, largely a mathematical calculation that does not require communication with the host storage device, is a time-consuming procedure because all coordinates of each vector feature need to be transformed to screen vertices. Use of a GPU enables optimization of a general-purpose mathematical calculation, enabling the procedure to be executed in parallel on a many-core GPU and optimized effectively. This study mainly focuses on: (1) an organization and storage strategy for vector data based on equal pitch alignment, which can adapt to the GPUs calculating characteristics; (2) a paging-coalescing transfer and memory access strategy for vector data between the CPU and the GPU; and (3) a balancing allocation strategy to take full advantage of all processing cores of the GPU. Experimental results demonstrate that the approach proposed can significantly improve the efficiency of vector data rendering.

The Architecture of SOA-oriented Urban Spatial Information Sharing Platform

In order to break the bulwark and eliminate the information isolated island in UGIS, the architecture of SOA-oriented urban spatial information platform is proposed. The SOA-oriented urban spatial information management and service architecture is designed and the key technologies are discussed in detail. The architecture is based on service and adopts the convenient and widely used SOA. It contains five logical structures, which are application layer, spatial information publishing layer, and spatial information service layer, spatial information supporting layer, the basic supporting layer. Through the five layers and the key technologies in them, the architecture can connect the computing, data and software resources which distributed in each urban department and accept users’ access requirements by web portal everywhere. The key technologies of ontology-based urban spatial information semantic sharing model and the urban spatial information dynamic aggregation model are discussed in detail. The architecture can solve the interoperability problem of multi-source systems and give a guide theory model and implement scheme for the urban spatial information sharing.

Active Grid Node Metadata Directory Service Synchronization Mechanism: Take the Case of the China Geological Survey Information Grid Platform

With the wide application of spatial information grid, how to solve the data synchronization has become a current research focus in spatial information grid. Because of the confidentiality and specificity of spatial data, it needs each grid node can only have their own data. When one grid node wants to use the data in another one, it must obey the principle of using the data without owning the data. Therefore, the establishment of the grid node metadata directory is an effective way to realize the spatial datas integration and sharing. There are two main technical difficulties in grid data synchronization currently. The one is poor data security and the other is not able to implement real-time synchronization. Aiming at the two problems, after studied the current mainstream data synchronization techniques, we proposed an active grid node metadata directory service synchronization mechanism. The mechanism releases all kinds of allowed sharing data in the source nodes through the form of metadata directory and uses services to implement the metadatas transformation and synchronization among different grid nodes. Each node in the grid environment uses the message queue mechanism to monitor the spatial data changes themselves, and uploads these changes to metadata directory to implement the active synchronous updates with the metadata upload tool. In this mechanism, each grid node cannot only be the source data nodes providing synchronous metadata, but also be the target data nodes accepting the synchronous updates. It allows multiple source data nodes and a number of target data nodes existence at the same time. Therefore, the synchronization mechanism can implement double-ways metadata real-time synchronization among grid nodes. This synchronization mechanism has been successfully applied to the China geological survey information grid platform and achieved very good actual operation results.

Distributed Real-Time Organization and Scheduling Strategy of Massive Grid Data

In order to solve the two deficiencies in existing massive grid data organization and scheduling: the lack of a universal distributed management method;time-consuming and complex pre-cutting processes, a new strategy is proposed in this paper. It abandons the whole pre-cutting processes in the traditional way.From the view of high efficiency, the new strategy integrates the pre-cutting method and real-time buffer mechanism. In lower map levels, the data can beorganized by the pre-cutting technique, but it is organized by real-time buffer mechanism in higher map levels. We represent the strategy in detail by a concrete example. The empirical results shows that the new strategy can effectively solve the two deficiencies above and implements a class of problems with massive grid data distributed real-time organization and scheduling.

Metadata Extended Model Based On Geological Domain Ontology

The current metadata modeling techniques can not meet the needs of knowledge conception expression, knowledge organization, and metadata semantic consistency in geological domain. This paper introduces ontology and integrates this theory to geological domain metadata modeling. It adopts the first order logic equivalent algorithm and defines the metadata extended model as a quaternion group which is consists of geological term set, geological term definition set, attribute definition set and instance set. It also provides the formal description of each set. Finally the five steps for building geological domain metadata extended model are given. The result presents that this model not only provides the content standards for geological domain knowledge representation and knowledge organization, but also provides the basis for geological domain multi-source data and historical data integration and application in semantic consistency.