CN102902782A - Mass multisource heterogeneous spatial information data seamless integration management method - Google Patents
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Abstract
The invention discloses a mass multisource heterogeneous spatial information data seamless integration management method. The method comprises the steps of: building a distributed seamless integration conceptual model, and under the distributed heterogeneous spatial data seamless integration environment, using a multi-layer intelligent middleware system to build a cross-platform, exchangeable, safe and reliable spatial data management system which supports a heterogeneous database, the distributed computation and the cooperative services. According to the method provided by the invention, normalized sharing and low-level integration of the geographic information resource are realized, the data utilization rate is increased, and further the information timeliness and the working efficiency are improved.
Description
Technical field
The present invention relates to the integrated harmless management method of the multi-source heterogeneous spatial information data seamless of technical field, particularly a kind of magnanimity of geography information spatial data management.
Background technology
Integrated and the fusion of multi-source information is a large hot issue in Earth Information Science field, and this three aspects: of characteristics of the feature of its meaning and necessity and Earth Information itself, acquisition means feature, the information processing platform or system is closely linked.Yet in the reality, owing to lacking the standard base data, the multiple dimensioned property of data multi-semantic meaning, multi-space and expression, the complicated variety of data acquisition means, caused the generation of multi-source heterogeneous spatial data, on the one hand be the mass data of the different-format that enriches, being people on the other hand can not satisfy the demand of data.Also proposed now some correlation theories and carried out the data-switching of different-format, but the process of conversion is complicated, expends time in and human resources, and easy drop-out.Also need to carry out the research of data integration from the data sharing meaning, and the GIS application needs the data of integrated multiple data sources and different-format just can finish.
The development experience of spatial data is seamless integrated theory and method the seamless stage such as integrated of the spatial data under the splicing of traditional GIS map sheet, Seamless GIS, seamless space database, distributed GIS, Distributed Multi-Spatial Database, the distributed heterogeneous environment, present similar course to the development of GIS itself, namely from the unit to the multimachine, from network to distributed, from the isomorphism to the isomery.As far back as the eighties in 20th century, some international scholars just take the lead in having begun about the senior integrated research of spatial data, and the aspect such as integrated of the multiple representation of, GIS spatial data integrated at the GIS spatial data and multiple dimensioned, multiresolution spatial data has produced numerous theoretical results.ARCGIS can support the effective integrated storage administration of unified database of multi-data source, multi-scale, multi-time Scales data, the unified performance of multi-source, multi-scale, multi-time Scales data, figure, image, DEM, attribute form, the integrated demonstration of planning text and real-time many conditional attributes, the space querying ability of multi-data source have realized the seamless integrated of grid and demonstration.
Domestic scholars has also been done correlative study in this field.The slit aspect that spatial data produces under the distributed heterogeneous environment considers, the research of present seamless fusion mainly comprises the following aspects: l) how much and multiattribute seamless fusion between many map sheets border; 2) the seamless fusion of data representation (vector, grid, TIN etc.); 3) multi-Scale Data is seamless integrated; 4) many projections and coordinate system is seamless integrated etc.About how much and multiattribute seamless control fusion between many map sheets border, the propositions such as Wang Hui reach continuously so that mass data is used in logic by setting up the splicing relation between figure block boundary key element, and have furtherd investigate the splicing strategy of various form elements.The seamless integrated research of multi-Scale Data is a focus, and Wang Yanmin, Li Deren etc. propose a kind of hierarchical layered partition type multi-scale scheme, have developed the multi-scale model according to the map making integrated approach.Ai Tinghua points out to realize that continuous yardstick expresses, and is faced with at present to divide suitable engineer's scale and change granularity, data capacity and minimize, take into account the key issue such as consider semantic feature, operation response speed is real-time and horizontal data representation is consistent.Seamless integration problem with regard to many projections and coordinate system, Hu Peng etc. point out, " seamless space database " problem is actually the space basic problems on mathematics of geographical space, point out to abandon the geographical space that Euclidean space really is unified in the geographical space of GIS geoscience, fundamentally cancellation " seamless space database " problem.Li Aiqin etc. have designed a kind of Morton of improvement code " classification 4 quadrants diffusion quadtree coding " scheme and have carried out seamless management and the spatial index of geodata, and inquired in detail the seamless organization of multi-scale data, but the tissue of focused data but not legacy data is integrated.The main seamless process problem of paying close attention to image data such as Wang Mi, data structure, spatial index and the scheduling mechanism of large-scale image database have been realized, and studied multiresolution, multi-data source, multiband, multidate image data tissue, and the band of striding of image data is dispatched and flow display.Also there are some scholars to think to lay particular emphasis on for spatial data seamless integrated integrated, and seamlessly refer to indiscriminate access mode to distributed heterogeneous spatial data source.Having proposed the seamless integrated technology of a kind of multi-source Spatial Data (SIMS) such as Song Guanfu etc. comes implementation space data sharing and multi-format spatial data integrated, SIMS shields the difference of various data source dedicated engine by Virtual Spatial data Engine, the direct access to the several data form is provided.
Comparatively speaking, distributed heterogeneous spatial data seamless integrated to spatial data require relatively low, but all data might not possess global feature, also might repeat or redundancy in spatial dimension, and this has just caused the difficulty on the seamless integration realization.On the other hand since distributed heterogeneous spatial data in space, attribute, special topic, topology, semanteme, data representation, yardstick, the time slit factor aspect phase, projection and coordinate system etc. influence each other, fusion method with regard to independent a kind of slit has had certain research, how to consider these slits, can intactly be blended in still needs in the distributed Magnanimity spatial-database to explore further.The seamless integrated technology of spatial data is in fact a kind of data fusion method, should consider the integrated and transparent interoperability to distributed isomeric data, and multiple means of spatial data being carried out fusion treatment also will be provided.In sum, the seamless integrated research of Driven Heterogeneous Geographic Data Set rests on theoretical research stage mostly, does not also reach practical, still needs to do a large amount of work.
Domestic a lot of GIS manufacturer has also turned to sight following that very commercioganic spatial data is integrated technical, such as hypergraph SuperMAP, middle ground MAPGIS etc., supported data format conversion, OGC interoperability standard and middleware direct control isotype.With abroad comparing, most researchs are all round the integrated management technology of multi-source heterogeneous spatial data, and have obtained application in the GIS software platform, truly senior integrated and merge available product and occur not yet.
Particularly for field of traffic, often relate to numerous contents such as the land used of population, national economy data, all kinds of city plannings and scale, link length grade and the traffic capacity, the volume of traffic, traffic, traffic zone, basic surveying and mapping data, satellite remote sensing date, geologic prospect data, running fix data.Geographic Information System is to process the effective tool of these spatial datas (geometric attribute) and attribute data (non-geometric attribute), in the urgent need to set up a kind of can seamless integrated multiple necessary data, realize exchanges data, data sharing and have the system of powerful graphics process, geographical simulation, analytic function, support secondary development, thoroughly change conventional management system information processing mode, to satisfy people's various demands.
Summary of the invention
Technical matters to be solved by this invention is, not enough for prior art, provide the multi-source heterogeneous spatial information data seamless of a kind of magnanimity integrated harmless management method, change " information island " state of the current geographic information resources of all departments, promote interdepartmental geography information to share; Improve the data utilization rate; Promote information timeliness and work efficiency.
For solving the problems of the technologies described above, the technical solution adopted in the present invention is: the integrated harmless management method of the multi-source heterogeneous spatial information data seamless of a kind of magnanimity steps of the method are:
1) input data volume spatial information data huge, that distribute from several data sources, strange land;
2) make up the global resource catalogue, form the overall virtual view of resource under the distributed computing environment, this overall situation virtual view comprises data resource accumulation layer, Resource TOC layer, scheduling of resource layer, access interface layer, two-way communication between each layer from bottom to up successively;
3) judge the spatial information data layout, if raster data then is divided into it regular data block, use the distributed file system storage; If vector data then uses the storage of OGC simple data model, adopt the R-Tree piecemeal; For each data block is distributed unique ID, indicate spatial dimension;
4) will cut apart the concrete data block that obtains after finishing evenly is deployed on each node of each layer of Resource TOC;
5) copy ISO seven layer network agreements, define seamless integrated concept model, performing step 2) in the seamless storage of data block; Described seamless integrated concept model is followed successively by seamless virtual graph layer, elementary factor class layer, key element layer, factor data collection layer from bottom to up;
6) input call the spatial data querying command, in step 2) in data block in carry out seamless distributed query;
7) a plurality of seamless result set that seamless distributed query is obtained carries out seamless process and merges;
8) utilize wavelet transformation to realize the transmission of data block;
9) result is called in demonstration.
In the described step 7), utilizing multi-layer intelligent middleware system that seamless result set is carried out seamless process merges, described multi-layer intelligent middleware system comprises data middleware, version middleware, Distributed Query Processing middleware, seamless integration middleware, described data middleware carries out gapless distribution inquiry to described data block, described version middleware is communicated by letter with described data middleware, described Distributed Query Processing middleware is communicated by letter with described version middleware, described seamless integration middleware is communicated by letter with described Distributed Query Processing middleware, and generates seamless result set.
The multi-source heterogeneous concrete index of magnanimity among the present invention is large according to the source data amount, the strange land distributes, and data model has uncertainty and isomerism in semanteme, expression-form, environment for use.
Compared with prior art, the beneficial effect that the present invention has is: the invention solves the geographic information resources standardization and share and low-level integration problem, by data integration, can change " information island " state of the current geographic information resources of all departments, " on the spot " that solved the massive spatial data resource shares and problem of complex utilization, based on the integrated multi-data source Task-decomposing mechanism problem of implementation of effectiveness, based on the associated treatment problem between the multisystem in function warehouse, make the integrated of distributed heterogeneous spatial data reached efficient, practical degree can satisfy the demand that conglomerate is used; Promote interdepartmental geography information to share Effective Raise scientific management and level of decision-making.
Description of drawings
Fig. 1 is one embodiment of the invention process flow diagram;
Fig. 2 is one embodiment of the invention overall situation virtual view structural representation;
Fig. 3 is the seamless integrated concept model of one embodiment of the invention schematic diagram;
Fig. 4 is one embodiment of the invention multi-layer intelligent middleware system schematic diagram.
Embodiment
As shown in Figure 1, the method step of one embodiment of the invention is as follows:
1) input data volume spatial information data huge, that distribute from several data sources, strange land;
2) make up global resource catalogue (such as Fig. 2), form the overall virtual view of resource under the distributed computing environment, this overall situation virtual view comprises data resource accumulation layer, Resource TOC layer, scheduling of resource layer, access interface layer from bottom to up successively, in twos communication between each layer; The realization of global resource catalogue to discovery, tissue, the management of mass data, is accessed and locating query the unified of space information resources in the distributed data base by the data resource access Interface realization under distributed network environment simultaneously;
3) judge the spatial information data layout, if raster data then is divided into it regular data block, use the distributed file system storage; If vector data then uses the storage of OGC simple data model, adopt the R-Tree piecemeal; For each data block is distributed unique ID, so that the identification copy is described by its spatial dimension (x_min, y_min, x_max, y_max) simultaneously, indicate spatial dimension; For vector data, Local map layer usage space database is stored with OGC elementary factor class model, and for each data item is distributed unique ID, be convenient to quick indexing, also adopt simultaneously its spatial dimension (x_min, y_min, x_max, y_max) describe, so just can the spatial index of vector data and raster data is unified.And for the data item at Resource TOC place, the ground floor of each Nodes R tree index is uploaded to the Resource TOC place, thereby the global index of implementation space data;
4) will cut apart the concrete data block that obtains after finishing evenly is deployed on each node of each layer of Resource TOC;
5) copy ISO seven layer network agreements, define seamless integrated concept model (see figure 3), realize 2) in the seamless storage of data block; Described seamless integrated concept model is followed successively by seamless virtual graph layer, elementary factor class layer, key element layer, factor data collection layer from bottom to up;
6) input call the spatial data querying command, 2) in data block in carry out seamless distributed query;
7) a plurality of seamless result set that seamless distributed query is obtained carries out seamless process and merges;
8) utilize wavelet transformation to realize the transmission of data block; At first, at data sending terminal raw image data is decomposed into a series of small echo, then these small echos is carried out separately compression coding and transmission, receiving end reconfigures out original image after receiving data, sharpness progressively becomes more clear from the most coarse beginning in anabolic process.Above-mentioned progressive transmission mechanism has improved data transfer efficient greatly, considers the repeatedly decoding of receiving end, and reconstructed operation shows image, uses the GPU computing and improves the image regeneration rate;
9) result is called in demonstration.
As shown in Figure 3, seamless integrated concept model is decomposed into factor data collection, key element, elementary factor class, the several level of seamless virtual graph layer with distributed spatial database, and the function of each layer is as follows:
4.1) the factor data collection.Seamless integrated conceptual model at first from conceptive be the factor data collection with multi-source heterogeneous data abstraction, thereby the difference that causes of the distributed and isomerism of screen factor certificate in form.The factor data collection is one group of spatial data with similar theme with same frame of reference, such as the various types of traffic data layers that comprise highway, railway, water route etc., is the basis of the compound utilization of implementation space data multi-mode.Seamless query results provides the result data management to distributed seamless query task.
4.2) key element.Key element is that the geometry of factor data collection and attribute information are described, and wherein geometric element comprises that point, line, surface, mixing etc. are several.
4.3) the elementary factor class.The elementary factor class is that space reference system, partial indexes, rule, the topological relation to key element defines.Process by integrated and seamless process, the elementary factor class adopts unified attribute structure, and a plurality of elementary factor class data that are distributed on the different node are conceptualized as an elementary factor class.
4.4) seamless virtual graph layer.Seamless virtual graph layer is a kind of special elementary factor figure layer, and the seamless integrated management to the spatial data that satisfies the constraint conditions such as same same period of history of yardstick of same type is provided.The virtual graph layer is managed the similar atural object data with zone adjacency, region overlapping attribute by subgraph layer catalogue and map sheet catalogue; The attribute of virtual graph layer is defined by unified attribute structure, and is mapped in each similar atural object data attribute separately and goes; The subdata that the virtual graph layer decides inquiry to relate to by global index.
The design of conceptual model is to realize the seamless integrated basis of distributed heterogeneous spatial data.The present invention adopts the URL of definition data resource, and realizing location and the description of data resource by the seamless integrated required basic metadata model of standard, the guiding by several levels such as server, geographical data bank, type of directory, data realizes the conversion between URL and the data resource operand.
As shown in Figure 4, utilizing multi-layer intelligent middleware system that seamless result set is carried out seamless process merges, described multi-layer intelligent middleware system comprises data middleware, version middleware, Distributed Query Processing middleware, seamless integration middleware, described data middleware carries out gapless distribution inquiry to described data block, described version middleware is communicated by letter with described data middleware, described Distributed Query Processing middleware is communicated by letter with described version middleware, and described seamless integration middleware is communicated by letter with described Distributed Query Processing middleware, seamless result set.
Seamless integration middleware provides a plurality of result set seamless processes that each distributed subquery is obtained to merge, at least comprise the inquiry to the incremental data storehouse in the subquery result set, then utilize the status information of version to reject deficiency of data, the seamless process of implementation space data merges.Seamless Integration Services provides the maintenance function to seamless integrated coherency state, and the topological consistency maintenance and the seamless feature that are included in seamless integrated data editor and the renewal process are safeguarded, and the seamless process in adopting off-line editing mechanism process is safeguarded.Multi-layer intelligent middleware system comprises:
5.1) seamless integration middleware.Query requests is at first received by the some inquiry services in the integration framework, pre-service (inquire about validity checking, daily record, set up task agent) through this service, query requests is submitted to seamless integration middleware, and this middleware mainly is responsible for the generation of seamless result set;
5.2) the Distributed Query Processing middleware.Seamless integration middleware does not carry out too much processing to query requests, but this request is mail to the Distributed Query Processing middleware of lower floor; This layer Middleware implementation set up a plurality of distributed subquery tasks to the decomposition of task;
5.3) data middleware.The Distributed Query Processing middleware mails to these distributed subquery requests other data middleware, and this a little request arrives the data middleware layer the most at last, at the data middleware layer, carries out real inquiry for each specific heterogeneous data source;
5.4) the projection middleware.The result data burst that inquires is reversed all middlewares of sending into query requests forward process, carries out additional processing, such as the projection middleware;
5.5) the version middleware.Result data penetrates global space index middleware, arrives at last seamless integration middleware.In seamless integration middleware, data communication device is crossed version mechanism and is realized the seamless process processing.Version mechanism and filing mechanism be implementation space data seamless chemical combination and and the gordian technique of seamlessness maintenance, on Intelligent Multi layer middleware system, by this edition middleware is provided, manage version incremental data storehouse in the mode consistent with other data source; Content constantly increases when the incremental data storehouse, can also utilize filing mechanism, the distributed data storage of the trend of the times in each network node, the performance of enhancement system in seamless process merges.
In middleware architecture, some middleware is processed (forward) to query express, some middleware is processed (oppositely) to results expression, and seamless query script significantly shows the distribution processor process of query requests and integrated assimilation processing procedure to Query Result.
The present invention adopts multilayer middleware and " embedding-combination " formula framework, has reacted the intelligent of this individual system, and has supported many-sided extendability.Can support new data source type by developing new middleware; By embedding the middleware of specific function, expanding system is to the processing power of spatial data.
Traffic information data is comprehensive and complicacy because of it, and is distributed in different traffic information systems, finishes different traffic administrations and control function, has the characteristics of isomery, level.The below illustrates as an example of traffic data example and utilizes the present invention to carry out the seamless integrated management method of the multi-source heterogeneous traffic data of magnanimity.
1) the traffic feature category is set up.With traffic information data abstract be following a few class: (1) geo-spatial data.Mainly comprise the data such as topomap, orthography, earth control, elevation, traffic, water system, administrative division, block, buildings and public land deeds; (2) basic document data.Comprise the land use statistics data, socioeconomic status data, natural situation data.(3) transport need (OD survey) data.The origin-destination survey data that comprise resident trip, urban floating population trip survey data, flow of goods enquiry data, motor vehicle origin-destination survey data, passenger-cargo stream origin-destination survey data of transport hub, bicycle origin-destination survey data etc.(4) means of transportation data.Comprise highway data such as link length, road net, highway section, with one voice, parking lot etc., urban public transport data such as bus-route network, circuit, the field etc. of standing, urban outbound traffic hinge data.(5) function division.Comprise the function divisions such as Highways ' shopping centre, residential block, greenbelt.(6) current situation of traffic enquiry data.Comprise the volume of traffic, the data such as the handling capacity of passengers of each circuit bus and motor vehicle speed.In addition, the typing of city road network structural drawing and traffic pattern is with corresponding figure layer vector quantization and to be changed over to by MapInfo be corresponding graphical format file.
2) make up traffic key element Resource TOC.By data cleansing, change type, the attribute of original traffic data into above-mentioned traffic factor kind, by defining seamless integrated data organization regulation, generate the bibliographic structure that directly in data center's directory tree view, to show, and on the node of directory tree according to type binding function or the treatment scheme of data, make up the Resource TOC of traffic remote sensing mass data, form the overall virtual directory of resource under the distributed computing environment, set up seamless virtual graph layer.The global dictionary system is the multilayer structured management to metadatabase, and metadata is by the logging data of metadata input device.
3) realize that the traffic data seamless process is integrated.Adopt seamless process Data Cleaning Method dynamic calculation topology to realize that topology is seamless, realize that respectively other editor of key element level and topological relation are safeguarded and for the topological consistency maintenance of interpolation, renewal and the deletion of whole map sheet, realize that the huge traffic data seamless process is integrated.The below is established as example with the road topology relation, and road is one of the most basic traffic key element of transportation network, is the physical support of all transport information.The intersection point of road axis is defined as junction node.The geological information of road is take intersection node as starting point, other data are as association, continuous point coordinate string provides under the setting coordinate system, because the track is to the dependence of road, and the overlapping characteristic of geological information between the two, by the forward and reverse lane width in the attribute information and number of lanes calculating the result is described as the side-play amount with respect to road, reduce spatial data redundant, the consistency maintenance work between minimizing and the spatial data has also realized that the Feature Dependence between road and track concerns and the space topological incidence relation.The planar data such as parking lot are the key factors that affects urban inner and interurban communication transportation, can be divided into two kinds such as the parking lot data, and a kind of is static data, and direct correlation space geometry data are such as parking lot numbering, affiliated road etc.Another kind is dynamic data, and namely the remaining berth of parking lot real-time empty situation is associated with the parking lot numbering, is distinguished as the storage file name with real-time acquisition time.Describe its geometric position with point, the static attribute data are such as numbering and so on related geometric data.Dynamic traffic flow data and data collection point numbering link, and are distinguished as the storage file name with real-time acquisition time.By said process, realize tissue, storage, the management of various traffic key elements, and with the time, how related empty data are.
4) seamless process inquiry.Respectively by setting up the R-tree model, the line discipline piecemeal of going forward side by side is by following process implementation seamless process inquiry: l) obtain segment that inquiry relates to number according to query region with vector data and raster data; 2) in the segment that obtains, search point, line, surface data judge whether in the query region of user's appointment; 3) find out in user's query region and with the point, line, surface target that user's query region intersects, according to the graph data of these point, line, surface targets, search for corresponding attribute splicing table data, set up the index of attribute splicing table; 4) in the index of attribute splicing table, find out all targets, divide and extract corresponding target geometric data in the segment that is clipped to related objective, carry out the splicing of whole atural object.
5) huge traffic data shows and transmission.The main data transmission of being responsible between sharing service platform and other application systems of traffic data transmission, here mainly adopt the network progressive transmission method of spatial data, specifically refer to the application at the multi-scale expression of net environment traffic data, namely detailed expression and the transition process under the large scale expressed in the summary of spatial data under the small scale.By will be each time the detailed information of abbreviation record.Raw data is organized as the set of a certain summary expression and a series of details increments.On the basis of expressing at summary, according to certain rules to the stack of details increment, get final product the progressive transmission of implementation space data.
6) realize data interoperation by middleware Technology at last.Achievable middleware comprises data middleware, projection middleware, Distributed Query Processing middleware.Middleware joins in the system by login mechanism.In the Input Process of spatial data, need pre-defined geodata source, the server section of geodata source corresponding data resource URL positioning mark, system provides information service according to services request and search access right for the client.Use WSDL to describe service by the Web service system between each traffic information system, use the UDDI issue and search service, when service requester acquisition request data, services, at first need to access the log-on message of this service to the UDDI registry, then access the WSDL document of this service, and generation native object, thereby the interoperability between the realization system.System data interoperability middleware can be supported Shapefile, Coverage, Access, ArcSDE and the data sources such as Large-scale Relational Database Oracle and SQLServer of ArcGIS, also supports simultaneously the Driven Heterogeneous Geographic Data Set sources such as OracleSpatial, MAPINFO, AUTOCAD, MAPGIS6x.
Claims (2)
1. the multi-source heterogeneous spatial information data seamless of a magnanimity integrated management method is characterized in that, steps of the method are:
1) input data volume spatial information data huge, that distribute from several data sources, strange land;
2) make up the global resource catalogue, form the overall virtual view of resource under the distributed computing environment, this overall situation virtual view comprises data resource accumulation layer, Resource TOC layer, scheduling of resource layer, access interface layer, two-way communication between each layer from bottom to up successively;
3) judge the spatial information data layout, if raster data then is divided into it regular data block, use the distributed file system storage; If vector data then uses the storage of OGC simple data model, adopt the R-Tree piecemeal; For each data block is distributed unique ID, indicate spatial dimension;
4) will cut apart the concrete data block that obtains after finishing evenly is deployed on each node of each layer of Resource TOC;
5) copy ISO seven layer network agreements, define seamless integrated concept model, performing step 2) in the seamless storage of data block; Described seamless integrated concept model is followed successively by seamless virtual graph layer, elementary factor class layer, key element layer, factor data collection layer from bottom to up;
6) input call the spatial data querying command, in step 2) in data block in carry out seamless distributed query;
7) a plurality of seamless result set that seamless distributed query is obtained carries out seamless process and merges;
8) utilize wavelet transformation to realize the transmission of data block;
9) result is called in demonstration.
2. the seamless integrated harmless management method of magnanimity multi-source heterogeneous spatial data according to claim 1, it is characterized in that, in the described step 7), utilizing multi-layer intelligent middleware system that seamless result set is carried out seamless process merges, described multi-layer intelligent middleware system comprises data middleware, the version middleware, the Distributed Query Processing middleware, seamless integration middleware, described data middleware carries out gapless distribution inquiry to described data block, described version middleware is communicated by letter with described data middleware, described Distributed Query Processing middleware is communicated by letter with described version middleware, described seamless integration middleware is communicated by letter with described Distributed Query Processing middleware, and generates seamless result set.
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