CN111324683A - Data management method for unified coding of space-time and elements - Google Patents
Data management method for unified coding of space-time and elements Download PDFInfo
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Abstract
The invention discloses a data management method for space-time and element unified coding, which comprises the following steps: carrying out spatial feature extraction on input data, carrying out spatial coding and establishing a unit conforming to the spatial feature of the input data; performing time characteristic extraction on input data, performing time coding and establishing a unit conforming to the time characteristic of the input data; performing element feature extraction on input data, performing element coding and establishing a unit conforming to the element characteristics of the input data; a multi-level indexing mechanism for retrieval is constructed. According to the invention, a set of coding model with characteristic change attenuation is constructed by combining space-time and element information, so that a data management method for comprehensively planning geographic space, large-span time and multiple elements is effectively realized.
Description
Technical Field
The invention particularly relates to a data management method for unified coding of space-time and elements.
Background
At present, various information systems access a large amount of data, and in order to more accurately, more completely, more quickly and more accurately dig out deep-level connotations from the massive data and realize the conversion of the data to information and knowledge, data management and data organization are required to be carried out according to the thought of big data.
At present, data management mechanisms considering geographic information are attracting attention of all parties, and a great deal of force is invested to carry out theoretical innovation and technical innovation, but the data management mechanisms mainly focus on planar geographic grids or upwards expand or extend a certain height layer on the basis of platform grids, and the method is relatively suitable for storage and analysis of near-ground or near-space data, but as shown in fig. 1, due to the surface curvature of the earth and the irregularity of the shape of the earth, the method has the defects that a far-empty area can deform and spatial features such as area and volume cannot be truly reflected, and accordingly, the defects of data storage, management or analysis, even deviation or errors can be caused. In addition, current research also mainly focuses on geospatial coding, and the consideration of time has not yet formed a complete solution, limiting the application space of the method. Meanwhile, the current research results mainly focus on theoretical research, more is to establish standards, and the technical practice is not deep enough.
Disclosure of Invention
The purpose of the invention is as follows: in order to overcome the defects in the prior art, the method provides a data management method for uniformly coding space-time and elements, and the method is based on a uniform space-time standard and an element classification rule, firstly, various types of data are planned to form a common data exchange format, secondly, a space cube capable of being split according to requirements is established, the space cube is organized into a proper volume space according to the space characteristics of the data, and finally, secondary and tertiary indexes are respectively established according to the time attributes and the element attributes of the data to support and realize the progressive retrieval and analysis of the data.
The technical scheme is as follows: in order to achieve the above object, the present invention provides a data management method for unified coding of space-time and elements, comprising the following steps:
s1: establishing a space cube, performing space feature extraction on input data, performing space coding and establishing a unit conforming to the space feature of the input data;
s2: performing time characteristic extraction on input data, performing time coding and establishing a unit conforming to the time characteristic of the input data;
s3: performing element feature extraction on input data, performing element coding and establishing a unit conforming to the element characteristics of the input data;
s4: a multi-level indexing mechanism for retrieval is constructed.
Further, the step S1 is specifically:
step S1-1: and (3) carrying out spatial feature extraction: according to the input data characteristics, decomposing the description information to obtain the position information, establishing a spatial metadata model, and representing in a triple form to obtain the spatial position information of the data, including longitude and latitude positions and heights, and simultaneously expanding the recording vector of the attitude information for recording a direction angle, a roll angle and a pitch angle;
step S1-2: determining a space unit: the position information obtained in step S1-1 is recorded as longitude Lng and latitude Lat, and the altitude is Alt, and the position and altitude are converted into cube cells of different precisions according to the tomographic pattern of the space cube.
Further, the step S2 is specifically: according to the input data characteristics, time description information is decomposed, position information is obtained, and a space metadata model is established.
Further, the step S3 is specifically:
step S3-1: decomposing the composition elements of various data objects, and carrying out clustering and classifying operations;
step S3-2: carrying out unique code editing in the clustering process of the entity, namely setting a Key which uniquely represents the class of elements, and carrying out unique Value domain editing on the classified attribute elements, namely setting a Value which uniquely represents the class of domains;
step S3-3: encoding the entities according to keys generated by clustering and Value generated by classification;
further, the step S4 is specifically: and (4) performing multi-element combination on the space ID, the time ID and the element ID generated in the steps S1-S3 to generate a logic address set IDSet capable of being indexed rapidly.
According to the invention, a space cube dividing method is introduced firstly, and the space of different height layers exists in an equal volume form through a scene management model similar to an octree, so that the problem of inconsistent data representation volume caused by the earth maze is solved better. Meanwhile, on the basis, a characteristic change model with space, time and element attenuation in sequence is constructed, information coding is realized in a multi-dimensional index mode on the basis of the attenuation model, and the coding mechanism can be rapidly tested in practice.
The invention constructs a set of coding models with characteristic change attenuation by combining space-time and element information, and effectively realizes a data management method for comprehensively planning geographic space, large-span time and multiple elements. Based on the method, the method is beneficial to realizing the natural association and mining analysis of the data, and meanwhile, the multi-level index mechanism also effectively solves the problems of difficult storage, difficult management and difficult retrieval of mass data.
Has the advantages that: compared with the prior art, the invention has the following advantages:
1. by the octree fission of the cube, a space data container with equal volume and area can be generated to support the natural association of various data.
2. By the unified coding of space, time and elements, the rapid marking and context understanding of data are realized.
3. And a multi-level index mechanism is constructed, so that efficient retrieval is realized.
Drawings
FIG. 1 is a schematic view of a conventional planar grid organization;
FIG. 2 is a flow chart of the operation of the present invention;
FIG. 3 is a schematic representation of the spatial cube organization of the present invention;
FIG. 4 is a schematic diagram of a three-level indexing architecture of the present invention;
FIG. 5 is a process illustrative diagram of the present invention;
FIG. 6 is a diagram of the IDSet logical address set;
FIG. 7 is a diagram of an addressing mechanism for hierarchical indexing.
Detailed Description
The invention is further elucidated with reference to the drawings and the embodiments.
As shown in fig. 2 and 5, the present invention provides a data management method for coding space-time and elements uniformly, comprising the following steps:
1) planning various types of data to form a common data exchange format, as shown in fig. 3, establishing a space cube which can be split according to requirements, extracting spatial features of input data, and establishing a unit which accords with the spatial features of the space cube:
1-1) carrying out feature extraction: according to the input data characteristics, the description information is decomposed, the position information is obtained, a spatial metadata model is established and is characterized in a triple form, the spatial position information of the data is mainly obtained and comprises longitude and latitude positions and heights, meanwhile, the recording vector of the attitude information is expanded and is used for recording a direction angle, a roll angle and a pitch angle, and the vector is beneficial to developing data analysis of collision detection, track conflict and motion trend.
1-2) determining spatial units: the position information obtained in step 1-1 is recorded as longitude Lng and latitude Lat, and the altitude is Alt. And converting the position and the height into cubic units with different precisions according to the established chromatographic mode of the space cube. Generally, the description information of each cube unit includes latitude and longitude ranges, height layers, the volume of the cube, and the like; in order to better realize the search of the cubic unit, a set of complete unit naming method is established in the embodiment, which mainly takes the latitude and longitude range and the space height range as references, and the designated space unit can be quickly located through the naming method. The value of the space unit is a 64-bit integer value, the first 32 bits of which represent altitude information, the following 16 bits of which represent longitude information, and the last 16 bits of which represent latitude information. Recording the number CubicCellID of the space unit, calculating to obtain a column number CCLng according to the longitude Lng, calculating to obtain CCLat according to the latitude Lat, and calculating to obtain CCAlt according to the altitude, wherein the calculation process is as follows:
noting the side length CubicEdgeLength of the original cube 2 ═ 2 (world radius + ExSpace), wherein the world radius is 6378137 m, the ExSpace is the space expansion according to the requirement, and the length of the cube is 50000 m;
generally, the processing level LayerID corresponding to the size of an original cube is 1, the LayerID value is accumulated along with the subdivision of the level, the value range can be flexibly set according to the engineering requirement, and the value range of the value is 1 to 10 in the patent;
CubicSize＝CubicEdgeLenght*pow(1/2,LayerID)，
CCLng＝(int)((180+Lng)/CubicSize)，
CCLat＝(int)((90+Lat)/CubicSize)，
CCAlt＝(int)((Alt+CubicEdgeLength)/CubicSize)，
in the above formula, Pow represents the power of the second parameter corresponding to the first parameter in the parentheses, and int represents rounding the value;
the unique identification of the geospatial is named:
CubicCellID ═ (__ int64) (CCAlt 0X100000000+ CCLng 0X10000+ CCLat), __ int64 represents a 64-bit integer, and 0X represents a 16-bit system;
the variable volume and size capability of the spatial coding can support data organization and analysis application in different application modes, such as activity range analysis, diffusion area analysis, regional hotspot analysis, buffer area analysis and the like.
2) Time feature extraction is carried out on input data, time coding is carried out, and a unit which accords with the time characteristic is established:
according to the input data characteristics, time description information is decomposed, position information is obtained, and a spatial metadata model is established:
the data were normalized in terms of time YYYY, MM, DD, HH, TT, SS, where YYY represents year, MM represents month, DD represents day, HH represents minute, TT represents minute, and SS represents second. And when the time ID number is CubicCellTID, the following steps are carried out:
CubicCellTID＝(__int64)(YY*0x10000000000000000+MM*0x1000000000000+DD*0x100000000+HH*0x10000+TT*0x100+SS)；
the time coding variable-duration capability can support year, month, day, week, hour, minute and second as units, and can develop data organization and analysis application, such as K-line analysis, frequency analysis, time domain analysis and the like.
3) Performing element feature extraction on input data, performing element coding, and establishing a unit conforming to the element characteristics:
3-1) decomposing the constituent elements of various data objects, and carrying out clustering and classifying operations, wherein the clustering mainly focuses on entities with the same characteristics into one object, if an entity 'airplane' exists, one characteristic of the entity can be clustered into 'country', and the classification divides the value of the entity, and the value of the country element of the entity 'airplane' can be divided into China, America or other countries. In engineering practice, the specific clustering and classification method can be set according to requirements;
3-2) unique code editing is carried out in the clustering process of the entity, namely, a unique Key capable of representing the type of elements is set, unique Value domain editing is carried out on the classified attribute elements, namely, a unique Value capable of representing the type of domain is set, and the unique code and the relationship of the entity can be conveniently generated in the subsequent process of processing the Value pair of the Key and the Value in the step;
3-3) encoding the entity according to Key generated by clustering and Value generated by classification, recording the encoding as FactorID, and then:
FactorID＝(__int64)(Key*0x10000000000000000+Value)
in this process, in order to implement scalability of Key and Value, the sub-Key is adopted in this embodimenti、ValueiIt is similar to a multi-level index:
4) A three-level index mechanism for retrieval is constructed, specifically as shown in fig. 4, and includes a spatial index, a temporal index, and an element index, and the specific construction process is as follows:
performing multi-component combination on the CubicCellID, the CubicCellTID and the FactorID generated in the previous step to generate a logic address set IDset capable of being quickly indexed, wherein the representation is specifically shown in FIG. 6;
as can be seen from fig. 6, IDset is composed of 160 proportional bits, and at most 64 bits can be processed by the current general computer, and in order to solve the 160 coding and calculation problem, a hierarchical indexing addressing mechanism is particularly established, as shown in fig. 7;
in fig. 7, IDSet is referred to as a logical address set or a logical address space of data, and the logical address space of data may be one-dimensional, where the logical addresses are limited to be arranged in order from 0; or two or more dimensional, where the entire data set is divided into segments, each segment having a different segment number, and the addresses within the segments start at 0. When retrieving data, the entire set of address spaces will be loaded into the data integrated management space, and in order to ensure correct retrieval of data, the logical addresses of the data must be translated into actual physical addresses, a task known as address translation or relocation.
Claims (5)
1. A data management method for unified coding of space-time and elements is characterized in that: the method comprises the following steps:
s1: establishing a space cube, performing space feature extraction on input data, performing space coding and establishing a unit conforming to the space feature of the input data;
s2: performing time characteristic extraction on input data, performing time coding and establishing a unit conforming to the time characteristic of the input data;
s3: performing element feature extraction on input data, performing element coding and establishing a unit conforming to the element characteristics of the input data;
s4: a multi-level indexing mechanism for retrieval is constructed.
2. The method for managing data of spatio-temporal and element unified coding according to claim 1, wherein: the step S1 specifically includes:
step S1-1: and (3) carrying out spatial feature extraction: according to the input data characteristics, decomposing the description information to obtain the position information, establishing a spatial metadata model, and representing in a triple form to obtain the spatial position information of the data, including longitude and latitude positions and heights, and simultaneously expanding the recording vector of the attitude information for recording a direction angle, a roll angle and a pitch angle;
step S1-2: determining a space unit: the position information obtained in step S1-1 is recorded as longitude Lng and latitude Lat, and the altitude is Alt, and the position and altitude are converted into cube cells of different precisions according to the tomographic pattern of the space cube.
3. The method for managing data of spatio-temporal and element unified coding according to claim 1, wherein: the step S2 specifically includes: according to the input data characteristics, time description information is decomposed, position information is obtained, and a space metadata model is established.
4. The method for managing data of spatio-temporal and element unified coding according to claim 1, wherein: the step S3 specifically includes:
step S3-1: decomposing the composition elements of various data objects, and carrying out clustering and classifying operations;
step S3-2: carrying out unique code editing in the clustering process of the entity, namely setting a Key which uniquely represents the class of elements, and carrying out unique Value domain editing on the classified attribute elements, namely setting a Value which uniquely represents the class of domains;
step S3-3: and encoding the entity according to the Key generated by clustering and the Value generated by classification.
5. The method for managing data of spatio-temporal and element unified coding according to claim 1, wherein: the step S4 specifically includes: and (4) performing multi-element combination on the space ID, the time ID and the element ID generated in the steps S1-S3 to generate a logic address set IDSet capable of being indexed rapidly.
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