CN106909645A - A kind of space-time data organization of unity method of expansible definition - Google Patents
A kind of space-time data organization of unity method of expansible definition Download PDFInfo
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- CN106909645A CN106909645A CN201710092427.2A CN201710092427A CN106909645A CN 106909645 A CN106909645 A CN 106909645A CN 201710092427 A CN201710092427 A CN 201710092427A CN 106909645 A CN106909645 A CN 106909645A
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Abstract
A kind of space-time data organization of unity method of expansible definition, comprises the following steps：Step A：According to high score space-time data signature analysis, the metadata abstract model of self adaptation extension is set up；Step B：The grid coding and weave connection of high score metadata and solid data；Step C：Expansible high score spatial-temporal data model based on GML specifications, for the self-defined multiple GML document schems of form in different pieces of information source, realizes the integrated high score space-time data interface of GML forms；And step D：The metadata and solid data organization modeling of the expansible definition of the Visual Implementation.
Description
Technical field
The present invention relates to time-space data analysis field, more particularly to a kind of space-time data organization of unity side of expansible definition
Method.
Background technology
Current high score System information construction is faced with data type complexity, miscellaneous problem, Various types of data product
Many with originating, data volume is big, and updating decision, structuring, unstructured data are simultaneously deposited, and the generation of real time data holds random, scattered
Or the features such as pulsed, a large amount of pulseds that traditional data tissue cannot adapt to data pour in storage read-write pressure and the appearance brought
Amount scaling concern.Simultaneously with system continuous extension with it is perfect, also have new data type and data form entered into
In system, this is the organization of unity management of high score space-time data with very big challenge.The mode of existing multi-source data integration is big
Cause has three kinds：Data Format Transform pattern, data interoperation pattern, Direct data access pattern, but still it is faced with information
Source is complicated, manage the incompatible bottleneck problem of various, data form.
Metadata is the feature and attribute for being specifically used to describe data, is also referred to as the data on data, makes number
Standardization is reached according to processing, the standardization of the data resource that advances science, so as to strengthen data exchange and share, this is above-mentioned to solve
Challenge provides an important feasible way.But existing metadata standard, it is impossible to adapt to multi-source heterogeneous high score space-time data
Dynamic expansion, organization of unity and management.At present, OpenGIS alliance (open GIS consortium, OGC) has created at it
Public geographic model (OGC abstract norms) on the basis of, by encapsulating geography information and its attribute, formulated and met geographical space
XML (extensible Markup Language) (extensible markup language, XML) superset-geographical indication of data tissue characteristic
Language (geography markup language, GML), and have become actual Net Geographic Spatial Data exchange mark
It is accurate.GML is a kind of metadata definition language of very useful GIS data, and the metadata organization for being directed to GIS data has elder generation
Its advantage.
Existing high score space-time data is not only remote sensing and GIS data, it is necessary to the characteristics of considering other data types.
Under unified geo-spatial framework benchmark, it is considered to the metadata specification of integration construct, eliminate and shielding metadata and data
Stylistic difference.The advantage of GML is used for reference, carrying out model in the form of metadata and entity represents, the model has Gao Kekuo
Malleability, breaks through the limitation of the metadata organization of expansible definition, meets the management to new other genre metadatas for adding.Realize
The self-organizing of data.Data management and maintenance tool are provided, dynamic scalable capacity is realized to each isomerous multi-source high score space-time number
According to unified management.
The content of the invention
In view of the problem that existing scheme is present, in order to overcome the shortcomings of above-mentioned prior art, the present invention proposes one
Plant the space-time data organization of unity method of expansible definition.
According to an aspect of the invention, there is provided a kind of space-time data organization of unity method of expansible definition, including
Following steps：Step A：According to high score space-time data signature analysis, the metadata abstract model of self adaptation extension is set up；Step B：
The grid coding and weave connection of high score metadata and solid data；Step C：Expansible high score space-time number based on GML specifications
According to tissue, for the self-defined multiple GML document schems of form in different pieces of information source, the integrated high score space-time of GML forms is realized
Data-interface；And step D：The metadata and solid data organization modeling of the expansible definition of the Visual Implementation.
From above-mentioned technical proposal as can be seen that the invention has the advantages that：
Using the dynamic scalable metadata schema defined based on general character and personal characteristics can to different type high score when
Empty data carry out Unify legislation.The personality attributes of data are supported to inherit and derive between self-defined extension, data type, realize
The dynamic expansion of multi-source heterogeneous data, organization of unity and management.
High score spatio-temporal data types are more and be difficult to be managed collectively and merge, it is stipulated that unified coding rule, and utilize GML
Data form is integrated.
Editor, the extension to all kinds of metadata and solid data are completed, using the succession between data and generalization, is led to
Realize the management of the Life cycle such as structure, editor, modification, the extension of high score Spatio-Temporal Data Model for Spatial with crossing the formal intuition of GUI.
Brief description of the drawings
Fig. 1 is the schematic flow sheet of the space-time data organization of unity method of the expansible definition of the embodiment of the present invention；
Fig. 2 is the metadata schema figure of expansible definition；
Fig. 3 is the schematic flow sheet of Fig. 1 steps A；
Fig. 4 is the schematic flow sheet of Fig. 1 steps B；
Fig. 5 is the schematic flow sheet of Fig. 4 steps C；
Fig. 6 is GML data file integrated flow schematic diagrames in Fig. 1 steps C；
Fig. 7 is the schematic flow sheet of step D in Fig. 1；
Fig. 8 is solid data establishment, editing interface figure in Fig. 1 steps D.
Specific embodiment
Certain embodiments of the invention will be done with reference to appended accompanying drawing in rear and more comprehensively describe to property, some of them but not complete
The embodiment in portion will be illustrated.In fact, various embodiments of the present invention can be realized in many different forms, and should not be construed
To be limited to this several illustrated embodiment；Relatively, there is provided these embodiments cause that the present invention meets applicable legal requirement.
In this manual, following is explanation for describing the various embodiments of the principle of the invention, should not be with any
Mode is construed to the scope of limitation invention.Referring to the drawings described below is used to help comprehensive understanding by claim and its equivalent
The exemplary embodiment of the invention that thing is limited.It is described below to help understand including various details, but these details should
Think what is be merely exemplary.Therefore, it will be appreciated by those of ordinary skill in the art that not departing from scope and spirit of the present invention
In the case of, embodiment described herein can be made various changes and modifications.Additionally, for clarity and brevity,
Eliminate the description of known function and structure.Additionally, running through accompanying drawing, same reference numerals are used for identity function and operation.
To make the object, technical solutions and advantages of the present invention become more apparent, below in conjunction with specific embodiment, and reference
Accompanying drawing, the present invention is described in more detail.
The invention provides a kind of high score space-time data organization of unity method of expansible definition, referred in unified space-time
Under framework, Unify legislation is carried out to the general character attribute of different types of data using metadata, solve diversiform data and be difficult unification
Management and the problem of fusion.Fig. 1 is the stream of the high score space-time data organization of unity method of expansible definition in the embodiment of the present invention
Journey, as shown in figure 1, the high score space-time data organization of unity method of expansible definition is comprised the following steps：
Step A：According to high score space-time data signature analysis, the metadata abstract model of self adaptation extension is set up.
Solve the problems, such as that polymorphic type high score space-time data is difficult to be managed collectively and fusion, as shown in Figure 2.To image, numerical value,
The space-time datas such as Space Product, unstructured data, extract word description and other information.All kinds of general character attributes are extracted, is also carried
Expansible feature is taken as personality attributes, uniform data is carried out abstract.Unified access, data correlation and Classification Management are provided.
This step specifically includes following steps, as shown in Figure 3：
Sub-step A1：High score data signature analysis；
Metadata for the universal product, professional treatment product, emergent application product carries out organization of unity, by data lattice
The minutias such as formula, quality, processing method and acquisition methods are divided into general character and individual character.
Sub-step A2：The general character attribute of different type high score space-time data is described；
Under unified space-time reference frame, all the sensors data, intermediate result data for the treatment of etc. needed for covering will
The general character attribute of different type high score space-time data is described, for belonging to data structured and destructuring in common information
Part, the metadata form of constituting criterion carries out storage management data form storage in the form of database table.
Sub-step A3：Support the self-defined extension of data personality attributes.
Dynamically draw on metadata abstract model and connect, data type is supported to inherit and derived from, and realizes the organization of unity of data.
Data input for not meeting form needs to realize the unification of data form by formatting import tool, it is ensured that automatically process
It is ageing.
Step B：The grid coding and weave connection of high score metadata and solid data.
On the basis of abstract model description, Dynamic Geographic grid coding is carried out to high score space-time data, to metadata and reality
Body is configured, edited, multidimensional association.
In this step, Dynamic Geographic grid coding is the grid chi required for being determined by the dense degree of destination object
Degree, such as sparse place of atural object only need to coarse grid, and refined net memory space and non-space number are then pressed in the intensive place of atural object
According to raising locus effectiveness of retrieval.This step specifically includes following steps, as shown in Figure 4：
Sub-step B1：Metadata and solid data dynamic grid are encoded；
Loading area map, the whole world, the whole country are divided into the net of different thicknesses level by different longitude and latitude sizing grids
Lattice, the grid of each level covers relation in scope with levels, with certain rule to spatial data structure hierarchical coding.
Dynamic adjustment map scaling, geographical space positioning and geographical feature description is associated, using grid units as basic
Resolution ratio, control is in the error range for allowing.Be conducive to input image search condition (frame select or polygon selection region) with
And subsequent result sequence.
Sub-step B2：Define expansible metadata organization model, associated metadata and solid data.
Association content includes：
A) association in time：The incidence relation set up in time attribute dimension between earth observation data, including time category
Property association, the time close on association, time interval association, temporal calculation associate etc..Data time attribute can not be null value, time category
Property storage format, data type by HZB/GF 4008-2014 specify perform.
B) space correlation：Incidence relation between setting up data in the space attribute dimension of data, including spatial neighbor
Association, space are subordinate to association, spatial operation association etc..Data space attribute can not be null value, the storage format of space attribute, number
Performed according to type peace HZB/GF 4008-2014 regulations.
C) object association：The incidence relation set up according to object of observation between data, including object is classification associated, object is subordinate to
Category association, object tag association, characteristics of objects association, the association of object electromagnetic property etc..Data can not include earth object.
D) relevance：The content included according to data carries out the association between data, it will usually with characteristic vector
Form represents the content of data, including semantic feature vector, color feature vector, shape eigenvectors, Text eigenvector, letter
Number characteristic vector etc..
Data correlation rule is defined, time, space, object are classified as the base attribute of associated data, the pass of data
Connection relation can be defined as such as the five-tuple of formula (1)
S=<ARt,ARs,ARo,TF,SF> (1)
Wherein, ARt, ARs, ARo are one group of correlation rules, one group of logical deduction by reasoning rule can be expressed as, for example, by condition
X is derived and is asserted Y, represented with X → Y.ARt is the correlation rule of time dimension, and ARs is the correlation rule of Spatial Dimension, and ARo is
Correlation rule based on object of observation.TF is temporal characteristics, such as the life cycle of data, time marking etc., and SF is space characteristics,
Such as the locus of data, regional extent etc..By Bayesian learning, complete the renewal of association relation model, introduce sequence number n with
ΘnThe state of incidence relation between the remotely-sensed data of expression current procedures n, with Xn={ x1,x2…xnCurrent data set is represented, with P
(Θ0) represent correlation model original state probability measure, it is assumed that XnData are separate in collection, then have posterior probability
Wherein, P (Θn) represent the prior probability without training data, P (Xn) represent the training data to be observed
Prior probability, P (Xn|Θn) represent and assume ΘnData X is observed in the case of establishmentnProbability.In view of the mutual of data
Independence, then have P (xn|Xn-1,Θn)=P (xn,Θn), P (xn|Xn-1) be normaliztion constant, then haveFollowing formula can be obtained：
Conditional probability P (xn|Θn) represent Current observation data xnLikelihood score, P (Θn|Xn-1) represent current learning procedure
Prior probability, and as n=1 the prior probability be probability P (Θ0).Aposterior knowledge according to each study is obtained down
The priori for once learning, so as to be made up of the state renewal process of Infinite Cyclic Knowledge delivery.It is expressed as：
So far a transfer process for recursive form is formed, study and the renewal process of incidence relation state is illustrated.
Step C：The expansible high score spatial-temporal data model based on GML specifications is realized, for the form in different pieces of information source
The outline (Schema) of self-defined some GML documents, realizes the integrated high score space-time data interface of GML forms.
With the increase of data type, position of the combing new type data in data taxonomic hierarchies, to new type data
Definition is extended, is quickly generated.In this step, high score spatial-temporal data model is realized by way of database, specific bag
Following steps are included, as shown in Figure 5：
Sub-step C1：The metadata of high score space-time data is read first.High score space-time data may be from same number
According to source, it is also possible to from different data sources.In heterogeneous platform, it is multi-party to there is data representation, data content etc. in each data source
The difference in face, realizes metadata uniform format.
Sub-step C2：According to data quality control condition, judge whether data meet the requirements, read high score space-time data reality
Body.
Sub-step C3：Using quality conversion function, the structure of document, mark, element, attribute defined in GML Schema
Deng metadata information, the difference of data representation is effectively reflected, each Schema is bound together, to the data of GML documents
Information integration reforms into transparent.
Sub-step C4：Schema can be realized by XSLT in XML (Extensible Stylesheet Language Transformations) and XPath technologies
Binding, complete data file it is integrated, realize high score space-time data organization of unity, integration realization block diagram is illustrated in fig. 6 shown below.
Step D：The metadata and solid data organization modeling of the expansible definition of the Visual Implementation, including：Metadata type
Definition, solid data definition, data edition and extension.
This step includes following sub-step, as shown in Figure 7：
Sub-step D1：Metadata type definition and extension to object of observation.
During the metadata modeling for defining grammer expansible, user can create, edit-modify and delete all kinds of metadata
Type and metadata.Metadata type definition module is responsible for defining metadata type, and the metadata of same type has identical
Data structure and management service mode.Function includes creating metadata type；Editing meta-data type；Delete metadata type；
Object metadata is defined；Observe the metadata definition of data.The extension of metadata definition can be divided into two aspects：It is top-down
Data derive and bottom-up data generaliza-tion.The expansible metadata modeling for defining grammer realizes the dynamic of metadata definition
It is expansible；The extension of object metadata definition.
Sub-step D2：Solid data definition and extension to object of observation.
Data entity is created under metadata type node.Solid data definition module is responsible for preview and checks metadata, wound
Build solid data, edit substance data delete solid data, and data are imported and derived, it is integrated and extend solid data type
Attribute structure.The expansible solid data for defining grammer is created, editing interface is illustrated in fig. 8 shown below.
Sub-step D3：The editor of high score Spatio-Temporal Data Model for Spatial, extension and manage.
New data organization model is realized by way of database, with the structure of the formal intuition ground implementation model of GUI, compiled
Volume, modification, show existing metadata type, solid data, metadata relationship, derive expansible definition metadata type and
Solid data tissue model.
So far, the space-time data organization of unity method introduction of the expansible definition in the present invention is finished.
The process or method described in accompanying drawing above can be by including hardware (for example, circuit, special logic etc.), solid
Part, software (for example, the software being carried in non-transient computer-readable media), or both the treatment logic of combination hold
OK.Although describing process or method according to some order operations above, however, it is to be understood that some described operation energy
Performed with different order.Additionally, concurrently rather than certain operations can be sequentially performed.
It should be noted that in accompanying drawing or specification text, the implementation for not illustrating or describing is affiliated technology
Form known to a person of ordinary skill in the art, is not described in detail in field.Additionally, the above-mentioned definition to each element and method is simultaneously
Various concrete structures, shape or the mode mentioned in embodiment are not limited only to, those of ordinary skill in the art can carry out letter to it
Singly change or replace, for example：
(1) quality control conditions and quality control function in step C can have other forms.
(2) the metadata organization management module in step D is realized only being replaced with corresponding function.
Particular embodiments described above, has been carried out further in detail to the purpose of the present invention, technical scheme and beneficial effect
Describe in detail bright, it should be understood that the foregoing is only specific embodiment of the invention, be not intended to limit the invention, it is all
Within the spirit and principles in the present invention, any modification, equivalent substitution and improvements done etc. should be included in protection of the invention
Within the scope of.
Claims (7)
1. a kind of space-time data organization of unity method of expansible definition, it is characterised in that comprise the following steps：
Step A：According to high score space-time data signature analysis, the metadata abstract model of self adaptation extension is set up；
Step B：The grid coding and weave connection of high score metadata and solid data；
Step C：Expansible high score spatial-temporal data model based on GML specifications, the form for different pieces of information source is self-defined more
The outline of individual GML documents, realizes the integrated high score space-time data interface of GML forms；And
Step D：The metadata and solid data organization modeling of the expansible definition of the Visual Implementation.
2. space-time data organization of unity method according to claim 1, it is characterised in that step A includes：
Sub-step A1：High score data signature analysis；
Sub-step A2：The general character attribute of different type high score space-time data is described；And
Sub-step A3：Support the self-defined extension of data personality attributes.
3. space-time data organization of unity method according to claim 1, it is characterised in that step B includes：
Sub-step B1：Metadata and solid data dynamic grid are encoded；And
Sub-step B2：Define expansible metadata organization model, associated metadata and solid data.
4. space-time data organization of unity method according to claim 3, it is characterised in that the association includes that the time closes
Connection, space correlation, object association and/or relevance.
5. space-time data organization of unity method according to claim 4, it is characterised in that the pass of metadata and solid data
The five-tuple of connection relation such as following formula：
S=<ARt,ARs,ARo,TF,SF>
Wherein, ARt, ARs, ARo are one group of correlation rules, can be expressed as one group of logical deduction by reasoning rule, and ARt is time dimension
Correlation rule, ARs is the correlation rule of Spatial Dimension, and ARo is the correlation rule based on object of observation, and TF is temporal characteristics, SF
It is space characteristics.
6. space-time data organization of unity method according to claim 1, it is characterised in that step C includes：
Sub-step C1：Read the metadata of high score space-time data；
Sub-step C2：According to data quality control condition, judge whether data meet the requirements, read high score space-time data entity；
Sub-step C3：Using quality conversion function, the metadata information defined in GML Schema；And
Sub-step C4：The binding of Schema is realized by XSLT and XPath technologies in XML.
7. space-time data organization of unity method according to claim 1, it is characterised in that step D includes：
Sub-step D1：Metadata type definition and extension to object of observation；
Sub-step D2：Solid data definition and extension to object of observation；And
Sub-step D3：The editor of high score Spatio-Temporal Data Model for Spatial, extension and manage.
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