Data processing method and device

Abstract

The present invention discloses a data processing method and apparatus, which includes setting a data scale, analyzing and calculating interrelationships between data according to the data scale, and processing the data according to the interrelationships according to a processing method corresponding to the set processing type. Also disclosed are methods for managing and storing data according to different processing types, establishing indexes, analyzing and managing data, managing and storing data based on the indexes, displaying data, analyzing and calculating data, and progressively transmitting data. The data processing method disclosed in the embodiments of the present invention uses indexes to integrate finite and infinite, macro and micro, and complex and simple data, effectively resolving performance bottlenecks in the process of processing large amounts of data on the server side, transmission network, and client side, such as data search, reading, transmission, display, spatial relationship calculation, and spatial analysis. [Selected Figure] Figure 1

Description

[Technology Field]

[0001] This application claims priority to a Chinese patent application filed with the China Patent Administration on February 1, 2018, with application number 201810101953.5 and the title of the invention "Data Processing Method and Apparatus," and incorporates all the contents of that application. This invention relates to fields such as spatial information technology, computer graphics, virtual reality technology, and computer operating systems, and more particularly to data processing methods and apparatus. [Background technology]

[0002] Macro and micro are corresponding concepts to each other and are usually represented by scale. The scale of data can be divided into an objectively existing inherent scale and a subjectively set non-inherent scale. For example, the micro and macro of geographical research objects are based on the geographical inherent spatio-temporal scale, and the micro and macro of the perspective of geographical research are based on the geographical non-inherent spatio-temporal scale. In GIS, spatial data reflects the objectively existing inherent macro and micro, the display of electronic maps, and spatial analysis calculations embody the subjectively set non-inherent macro and micro. The conventional methods still have the problem of integration between the objectively existing inherent scale and the subjectively set non-inherent scale regarding the analysis and calculation of data structure, memory, index, and spatial relationships. For example, they cannot solve the conflict and integration between maps and data, between maps and the coordinate points of data, and further between the data bits of coordinate points. Maps have different required data at different scales, the coordinate points of the required data, and the data bits of coordinate points are different, and the conventional methods still cannot solve these problems. To solve the pressure on servers, transmission, and display caused by a large amount of spatial data, ultimately, it is necessary to preprocess spatial data using a server, first render it into a single map picture according to a specific theme style, then cut the map into grid pictures of different levels according to the pyramid structure grid, encode each level slice, and identify the unique index value of the slice. When browsing spatial data by zooming in and out on the client, the client directly calculates the corresponding slice index according to the corresponding slice index standard according to the coordinates of the current display range and sends it to the server, and the server transmits the corresponding slice data to the client for display. Although it solves the partial integration of the objectively existing inherent scale and the subjectively set non-inherent scale in the case of map display and solves the bottleneck of map display performance, other functions of the system cannot be realized, and conversely, more new bottlenecks will occur.

[0003] Resolution refers to the measurement or display of a system's ability to distinguish details. The definition of resolution issued by the National Board for the Approval of Scientific and Technological Nouns is the ability of a physical quantity to distinguish details.

[0004] With advancements in science and technology, the rapid development and widespread application of space technology, application fields based on spatial entities such as computer graphics, virtual reality, urban planning, restoration of cultural sites, animated games, computer-aided design, geographic information systems, and medical graphics are rapidly developing. As a result, data is exploding, and the compression, transmission, display, and analysis of massive amounts of data are becoming major technological bottlenecks that limit the development of these industries.

[0005] From the perspective of displaying data on a screen, the scale of the screen and the scale of the pixels are limited. Data is displayed on the pixels of an electronic screen, the number of visible pixels is limited, and one pixel can only display one piece of data at a time. In other words, the maximum amount of data that can be displayed on a screen is constant and depends only on the screen resolution, and is unrelated to the infinity of the data.

[0006] (1) The rendering process can only render the data that is ultimately visible, thus resolving the conflict between display efficiency and data volume.

[0007] (2) Transmission involves transmitting only this data to the front terminal via the network, thus resolving the conflict between network bandwidth and data volume.

[0008] (3) Reading involves reading only this data and storing it together in a single file, thereby eliminating the pressure of reading from a magnetic disk.

[0009] (4) The key point of queries is that only the data is found in the index, and the client requesting the data performs the query and search according to the index itself, the data is distributed and stored on the server according to the index entries of the index, the client searches for the data block in the data file to be read by the index, and there is no pressure on the server from data queries. Furthermore, the amount of data in the index is sufficiently small and cannot increase in proportion to the increase in the amount of data, otherwise, once a certain amount of data is reached, the network transmission of the index will become a bottleneck.

[0010] All problems can be summarized as indexing problems, and as long as the indexing problems are solved, other bottleneck problems can be solved. The indexing problems to be solved above should have all the advantages of slicing indexes, but data can be stored in a distributed manner according to spatial relationships, rather than storing the data in a distributed manner after cutting it. Indexing enables the integration of simplicity and complexity, that is, the construction, management, storage, querying, transmission, display, and analysis of any complex spatial data with simple indexing relationships.

[0011] The index solves the problem of users examining parts and wholes, macro and micro data, and analyzing and calculating data at different scales (non-inherent scales) through the integration of non-inherent and inherent scales. It can reflect the conflict between finite and infinite, namely the fusion of the data's inherent scale and a subjectively defined non-inherent scale, from the data in a macro dataset down to the smallest data bits that make up the data, by integrating non-inherent and inherent scales.

[0012] Indexes achieve a fusion of simple and complex spatial relationships between data at different scales, solving problems related to data storage, retrieval, analysis, and calculation (the issue of whether the function can be realized, for example, achieving functional separation but not cut-off storage as in conventional technology), as well as performance. Spatial relationships between data at different scales can represent both simplicity and complexity. For example, at large scales, spatial relationships between data are simple, requiring only consideration of overlapping and non-overlapping relationships, and then identifying which data to place in the index entries of the index to establish and manage sub-indexes. At small scales, spatial relationships between data can represent complex relationships such as inclusion, intersection, and tangent, and it is possible to place and manage these data directly in the index data entries without establishing and managing sub-indexes. Different data entries within the index are stored in various storage devices such as memory and hard disks as data blocks for data management, data records for database management, files, etc.

[0013] An index integrates querying, management, storage, and analytical calculations for data that corresponds to different scales within the data. For example, all forms of data, such as macrodatasets, data describing a single object (e.g., surface data), coordinate data (e.g., coordinate points that make up surface data), and microdata bits (e.g., data for each data bit that makes up coordinate data), are managed, analyzed, and calculated in an integrated manner across different scales within the index. [Overview of the Initiative] [Means for solving the problem]

[0014] In view of this, the present invention provides a data processing method and apparatus. The specific details are as follows.

[0015] A method for processing data, Set the data scale, Depending on the scale of the aforementioned data, the interrelationships between the data are analyzed and calculated. This includes processing the data according to the interrelationships in accordance with a processing method corresponding to the configured processing type.

[0016] Preferably, the data includes one or more combinations of macrodatasets, data describing a single object, coordinate data, and microdata bits. The scale of the aforementioned data is a variable that indicates the macro and micro aspects of the data; when the scale is large, the data is more macroscopic than when the scale is small, and when the scale is small, the data is more microscopic than when the scale is large.

[0017] Preferably, the scale of the data includes the spatial scale or temporal scale of the data itself.

[0018] Preferably, the scale of the data includes the scale of the observational data or the scale of the spatial data, wherein the scale of the observational data includes the magnification factor when the spatial data is displayed on a computer, and the scale of the spatial data includes the resolution of the spatial data.

[0019] Preferably, the set data scale described above includes a pre-set scale, a temporarily set scale, or a scale calculated in the data processing process.

[0020] Preferably, the relationships between the data include one or more combinations of spatial relationships, temporal relationships, and scale relationships.

[0021] Preferably, the process of processing the data according to the interrelationships, according to the processing method corresponding to the set processing type described above, is 、 different Based on the interrelationships between data on a given scale, the process involves establishing, storing, reading, transmitting, displaying, and analyzing data indexes. Or, This includes storing, reading, transmitting, displaying, and analyzing an index of the data based on different scales and the interrelationships between the data.

[0022] A method for establishing an index, analyzing, and managing data, comprising: Setting the scale of the data, Analyzing and calculating the interrelationship between data according to the scale of the data, Processing the data according to the processing method corresponding to the set processing type according to the interrelationship, and this process includes establishing an index, analyzing, and managing the data according to the interrelationship between the analyzed and calculated data.

[0023] Preferably, the set scale of the data includes a preset scale, a temporarily set scale, or a scale calculated in the data processing process, Identifying the level of the index according to the set scale of the data, Managing and searching the data according to the identified level of the index.

[0024] Preferably, the process of establishing an index, analyzing, and managing the data according to the interrelationship between the analyzed and calculated data is Continuously establishing the next-level index for the data that meets the preset index establishment conditions and the data that meets the interrelationship between the data with established indexes, Not establishing the next-level index for the data that does not meet the index establishment conditions and the data that does not meet the interrelationship between the data with established indexes.

[0025] Preferably 、 before Identifying the setting of the index establishment conditions according to the specific cases described includes conditional and unconditional cases. For example, when establishing an index for each data bit of the coordinate data, the index establishment conditions can be set.

[0026] Preferably, the pre-set index establishment conditions include a combination of one or more indicators from a predetermined data range, data volume, and number of data points.

[0027] Preferably, the data range includes the range of the data itself, or a range calculated according to the set data scale.

[0028] Preferably, the process of establishing an index and analyzing and managing the data according to the interrelationships between the analyzed and calculated data is as follows: For data that satisfies the index establishment conditions and data that satisfies the interrelationship between the data for which an index has been established, the next level index is continuously established, the next level index is managed by an index item that manages the index of the index, and the index being managed can be detected by the index item that manages the index. This includes managing data that does not satisfy the index establishment conditions and data that does not satisfy the interrelationships between indexed data using index items in the index management data, and making the data discoverable using the index items that manage the data.

[0029] Preferably, the process of establishing an index and analyzing and managing the data according to the interrelationships between the analyzed and calculated data is as follows: For data that satisfies the index establishment conditions and data that has been analyzed and calculated to have superimposed relationships between the data according to the set data scale, the next level index is continuously established. The above-mentioned next-level index corresponds to the scale of the next-level data, Setting the scale of the next level of data includes setting it by direct or indirect methods such as obtaining it by calculating the scale of the current level or by assigning it externally.

[0030] Preferably, the process of establishing an index and analyzing and managing the data according to the interrelationships between the analyzed and calculated data is: This includes continuously establishing the next level index for data that satisfies the index establishment conditions and for data that has been analyzed and calculated to superimpose coordinate points constituting spatial data onto a single point according to the scale of the set data.

[0031] Preferably, the process for establishing the index and analyzing and managing the data is: Depending on the scale of the data set, an integrated index is established for one or more combinations of the data set, data describing or representing objects, and microdatabit data. This includes using the aforementioned integrated index for data analysis and management, The analysis and management of the aforementioned data includes one or a combination of the following: data storage, querying, reading, transmission, display, analysis, and calculation of spatial relationships.

[0032] A method for managing and storing data, This includes managing and storing data according to the established index, The index of the aforementioned data is established by the method described above.

[0033] Preferably, the process for managing and storing data according to the established index is: The index items that manage the data of the aforementioned index are defined as objects that manage and store the data, and the objects that manage and store the data are defined as objects that manage and store the data in a format that includes stored data blocks, stored records, or stored files.

[0034] A method for managing and storing data, Set the data scale, Depending on the scale of the aforementioned data, the interrelationships between the data are analyzed and calculated. This includes managing and storing data according to the interrelationships between the analyzed and calculated data.

[0035] Preferably, the process for setting the scale of the data described above is: This includes setting the initial scale for data management based on the ease of understanding the relationships between data at different scales.

[0036] Preferably, the process for setting the scale of the data is: This includes setting the scale on which the data is superimposed as the initial scale for data management. The superposition of the data includes cases where all data forms one superposition, where data forms multiple superpositions, or where multiple coordinate points of a single data form a superposition.

[0037] Preferably, the process for managing and storing the data in accordance with the interrelationships between the analyzed and calculated data is as follows: The data in which the interrelationships between the aforementioned data are superimposed is defined as a data management unit. Depending on the initial scale of the aforementioned data management, a new data scale is set, In accordance with the new data scale, the interrelationships between data are analyzed and calculated, and if the relationship between data is not simply a superposition relationship, the data is used as data storage units at this scale. This includes defining data that satisfies data management conditions and whose data still overlaps as data management units in the new data scale, resetting the new data scale, and repeating the above process, Meeting the aforementioned data management conditions includes one or more combinations of the number of data, the amount of data, and the range of data. The aforementioned data range includes the data display range of the data at the new data scale.

[0038] A method of displaying data, Depending on the scale of the displayed data, the scale of the data is identified. Depending on the scale of the data, the data index is used to search for the data that needs to be displayed, and the data index is established by the method of establishing the index described above, analyzing the data, and managing it. This includes reading the data that is necessary to display the data.

[0039] Preferably, the process for determining the scale corresponding to the data, depending on the scale of the displayed data, is: This includes directly determining the scale of the data according to the scale of the data display, or determining the scale of the data by calculation according to the scale of the data display.

[0040] Preferably, depending on the scale of the data described above, the process of searching for data that needs to be displayed in the data index includes one or a combination of the following methods: The index item that manages the detected index is used as display data and displayed. The portion of the detected data corresponding to the scale of the aforementioned data is used as display data and displayed. The data bits of the detected data corresponding to the scale of the data are used as display data and displayed. The detected data is used as display data and displayed. Instead of displaying other data with overlapping relationships, one or more of the detected data are displayed as display data.

[0041] A method for analyzing and calculating data, Analysis and calculations are performed according to the index corresponding to the data, and the index corresponding to the data is established by the method of establishing the index described above, analyzing the data, and managing it. This includes performing analysis and calculations using data that corresponds to different scales within the dataset.

[0042] Preferably, the analysis and calculation include analysis and calculation related to the scale, or analysis and calculation not related to the scale. The aforementioned analysis and calculations include calculating the spatial relationships of the data, aggregation analysis, or heatmap analysis.

[0043] Preferably, the analysis and calculation process described above is: The aforementioned analysis and calculation of the scale includes performing the analysis and calculation using an index corresponding to the scale and data.

[0044] Preferably, the process for performing data analysis and calculation according to the aforementioned index is: This includes performing analysis and calculations according to the spatial relationships of the index data corresponding to different scales of data in the aforementioned index.

[0045] Preferably, the process of performing analysis and calculation according to the index corresponding to the data is: This includes identifying, through the analysis and calculation of an index, that there is a clear spatial relationship between the data, or that there is a possibility of such a spatial relationship.

[0046] Preferably, the process of performing analysis and calculation using data corresponding to different scales from the aforementioned data is 、 Ma If the analysis and calculation are performed using data with few corresponding data points at a certain scale and a small computational amount, and the analysis and calculation seek to find that there is a specific relationship between the data, then if, as a result of the analysis and calculation using the data with few corresponding data points at a certain scale and a small computational amount, there are cases where there is a possibility of a certain relationship, then it is necessary to perform further analysis and calculation using a large amount of data at a certain scale that corresponds to the data that may have a certain relationship, until the analysis and calculation clearly shows that there is a certain spatial relationship between the data.

[0047] Preferably 、 before The analysis and calculation described above includes, but is not limited to, analysis and calculation performed in cooperation with one or more parts of the system, such as the client and server sides.

[0048] Preferably 、 before The analysis and calculation described above includes, but is not limited to, performing analysis and calculation using index and macro-scale data in the client portion (not the data service side) and system edge portions, as well as performing analysis and calculation using micro-scale data and original data on the data storage side and data service side.

[0049] A method for transmitting data progressively, If you need to request incremental data, send an incremental data request, and include a request scale parameter in the request. The incremental data obtained based on the aforementioned requested scaling parameters is received, and this step is performed. The system receives incremental data obtained by analysis based on the aforementioned request scale parameter and the index scale, and the incremental data is the incremental data of the index. and / or, The system includes receiving incremental data obtained by analysis based on the aforementioned request scale parameter and the data scale, and the incremental data being incremental data. The aforementioned index is established by establishing the index described above and analyzing and managing the data.

[0050] Preferably, if the request sender has cached previously cached data, the previously cached data includes index data corresponding to the corresponding scale of the previously cached index, and / or data corresponding to the corresponding scale of the previously cached data.

[0051] Preferably, if the request sender has cached previously cached data, the specific steps are: Identify the current scale parameters, Get the highest level scale parameter corresponding to previously cached data, The system determines the relationship between the highest level scale parameter corresponding to the previously cached data and the current scale parameter to determine whether it is necessary to request the data. If necessary, it continues to execute the subsequent steps; otherwise, it terminates. Send an incremental data request, and the request includes the current scale parameter, the request scale parameter, and the corresponding highest level scale parameter from previously cached data. The system receives incremental data obtained by analyzing the aforementioned request scale parameter and the index scale parameter, and the incremental data is the index incremental data. The system receives incremental data obtained by analyzing the aforementioned request scale parameter and the data scale parameter, and the incremental data is incremental data of the data. This includes inserting the received incremental data into the previously cached data.

[0052] Preferably, the specific process of the scale parameter is The more finely the index is managed, the higher the level of the scale parameter corresponding to the index item of the microdata. The higher the data resolution, the higher the level of the scaling parameter that corresponds to the detailed data.

[0053] A method for transmitting data progressively, Receives an incremental data request, including the request scale parameter, sent from the request sender. Based on the requested scale parameter and the scale in the index, an analysis process is performed to identify index data that satisfies the incremental condition as incremental data, and / or, based on the requested scale parameter and the scale in the data, an analysis process is performed to identify data that satisfies the incremental condition as incremental data. This includes transmitting the incremental data to the request sender, The aforementioned index is established by creating the index described above and establishing a method for analyzing and managing the data.

[0054] Preferably, if the request sender has previously cached indices and data stored, the request scale parameter includes the current scale parameter and / or scale parameters corresponding to the previously cached data.

[0055] Preferably, the process for obtaining incremental data corresponding to the incremental data request is: Based on the current scale parameter in the request scale parameter, perform analysis on the index and data to obtain the current analysis results. If the aforementioned request scale parameter includes a previously cached scale parameter, the process will This includes performing analytical processing on the index and data based on previously cached scale parameters in the request scale parameters to retrieve previous analysis results. The data from the current analysis results that satisfy the incremental condition are identified as incremental data, and the specific process for this step is as follows: This includes identifying the data that is the current analysis result and not the previous analysis result as incremental data, If the aforementioned request scale parameters do not include previously cached scale parameters, the process will The current analysis results will be used as incremental data. The current scale parameter is set as the current highest level scale parameter for the incremental data. This includes sending the aforementioned incremental data to the requesting sender.

[0056] A data processing device, A scale setting unit for determining the scale of the data. Depending on the scale of the data, a data analysis unit for analyzing and calculating the interrelationships between data, It includes a data processing unit for processing the data according to the interrelationships, in accordance with a processing method corresponding to a set processing type.

[0057] A device that establishes an index and analyzes and manages data, A scale setting unit for determining the scale of the data, A data analysis unit for analyzing and calculating interrelationships between data, depending on the scale of the data, It includes an index generation unit for establishing an index based on the interrelationships between analyzed and calculated data, and for analyzing and managing the data.

[0058] A device for managing and storing data, A scale setting unit for determining the scale of data, including, but not limited to, any scale such as a pre-set scale, a temporarily set scale, or a scale calculated during the data processing process, and A data analysis unit for analyzing and calculating interrelationships between data, depending on the scale of the data, It includes a management and storage unit for managing and storing data according to the interrelationships between the analyzed and calculated data.

[0059] From the above technical proposals, it can be seen that the data processing method disclosed in this invention effectively solves performance bottleneck problems in the server side, transmission network, and client side of processes that process large amounts of data, such as data retrieval, reading, transmission, display, and calculation of spatial relationships and spatial analysis. The index solves the integration of finite and infinite, macro and micro, and complex and simple data, and the index solves the problems of data retrieval, storage, reading, transmission, display, analysis and calculation, distributed management and computation functions, and performance. [Brief explanation of the drawing]

[0060] To more clearly illustrate the embodiments of the present invention or the technical concepts in the prior art, the drawings that may be used in the description of the embodiments or the prior art are briefly described below. Of course, the drawings described below are only a few embodiments of this application, and those skilled in the art can obtain other drawings in accordance with these drawings without any creative effort. [Figure 1] This is a flowchart of a data processing method disclosed in an embodiment of the present invention. [Figure 2] This is a flowchart of a method for managing and storing data disclosed in embodiments of the present invention. [Figure 3] This is a flowchart illustrating a method for establishing an index, analyzing data, and managing it, as disclosed in the embodiments of the present invention. [Figure 4] This is a flowchart of the data display method disclosed in the embodiments of the present invention. [Figure 5] This is a flowchart of the data analysis and calculation method disclosed in the embodiments of the present invention. [Figure 6] This is a flowchart of a method for progressively transmitting data as disclosed in the embodiments of the present invention. [Figure 7] This is a flowchart of a method for progressively transmitting other data disclosed in embodiments of the present invention. [Figure 8] This is a schematic diagram of a data processing device disclosed in an embodiment of the present invention. [Figure 9] This is a schematic diagram of a device for establishing an index, analyzing data, and managing it, as disclosed in the embodiments of the present invention. [Figure 10] This is a schematic diagram of a device for managing and storing data disclosed in embodiments of the present invention. [Modes for carrying out the invention]

[0061] The technical concepts in the embodiments of the present invention are described below clearly and fully, along with the drawings of the embodiments; however, it is clear that the embodiments described are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments that a person skilled in the art could obtain based on the embodiments of the present invention without any creative effort fall within the scope of the present invention.

[0062] Real or virtual objects are represented and described by data, and such representations and descriptions have different scales. For example, the scaling of data display, screen resolution, and electronic screen (view window) all have different resolutions. When data is displayed in a view window, if the view window's resolution is limited, and the graphics drawn on the view window are relatively small, then data representing detailed parts of the data may be drawn on the same pixels. Only when the graphics drawn on the view window are relatively large can the detailed parts be displayed. In other words, the more pixels the data is filled (drawn), the higher the data resolution and the smaller the scale. The fewer pixels the data is filled (drawn), the lower the data resolution and the larger the scale. Therefore, when displaying data, it has multi-scale and multi-resolution characteristics. However, current indexes, data management, and storage do not record the multi-scale characteristics of data. Therefore, during reading, transmission, and display, all data is transmitted and displayed at once, resulting in network transmission bottlenecks and data drawing / display bottlenecks. If the data is self-adaptively simplified, a computation bottleneck occurs on the server, and the same applies to data analysis and calculation. Therefore, the present invention solves the above-mentioned technical bottleneck problem by using an index.

[0063] The data referred to in the embodiments of this application include, but are not limited to, two-dimensional data, three-dimensional data, and multi-dimensional data.

[0064] The data processing method disclosed in the embodiments of the present invention is shown in Figure 1 and includes steps S11 to S13.

[0065] In step S11, set the data scale. The aforementioned data includes, but is not limited to, all forms of data, such as macrodatasets, data describing a single object (e.g., surface data), coordinate data (e.g., coordinate points constituting surface data), and microdata bits (e.g., data for each data bit constituting coordinate data). The scale of the aforementioned data includes, but is not limited to, the spatial and temporal scales of the data itself.

[0066] The scale of the aforementioned data is a variable that indicates the macro and micro aspects of the data; when the scale is large, the data is more macroscopic than when the scale is small, and when the scale is small, the data is more microscopic than when the scale is large.

[0067] The scale of the aforementioned data includes, but is not limited to, the scale of the observational data, such as the magnification factor used when spatial data is displayed on a computer.

[0068] Spatial scale includes, but is not limited to, the resolution of spatial data.

[0069] The scale of the data set above includes, but is not limited to, any scale, such as a pre-set scale, a temporarily set scale, or a scale calculated during the data processing process.

[0070] In step S12, the interrelationships between the data are analyzed and calculated according to the scale of the data. The relationships between the aforementioned data include, but are not limited to, spatial, temporal, and scale relationships.

[0071] The spatial relationships between data at different scales can be simple or complex. For example, the spatial relationships between data at large scales are simple, requiring only consideration of overlap and non-overlapping data, while non-overlapping data simply have simple spatial relationships such as adjacency and separation.

[0072] In step S13, the data is processed according to the interrelationships in accordance with the processing method corresponding to the set processing type.

[0073] Processing the data according to the aforementioned interrelationships is It handles issues such as establishing data indexes, storing, reading, transmitting, displaying, and analyzing data based on the interrelationships between data at different scales. and / or, This includes, but is not limited to, storing, reading, transmitting, displaying, and analyzing an index of the data, based on different scales and the interrelationships between the data.

[0074] The flow of the method for managing and storing data disclosed in the embodiments of the present invention is shown in Figure 2 and includes steps S21 to S23.

[0075] In step S21, set the data scale. Set the initial scale for data management based on the ease of understanding the relationships between data at different scales.

[0076] Set the scale at which the data is superimposed as the initial scale for data management. The superposition of the aforementioned data includes, but is not limited to, various forms of superposition, such as all data forming a single superposition, data forming multiple superpositions, or multiple coordinate points of a single data forming a superposition.

[0077] In step S22, the interrelationships between the data are analyzed and calculated according to the scale of the data. The aforementioned interrelationships include, but are not limited to, various relationships such as superposition, inclusion, intersection, tangent, and separation.

[0078] In step S23, data management and storage are performed according to the interrelationships between the analyzed and calculated data. Data where the interrelationships between the data overlap are designated as data management units. A new data scale is set according to the initial scale of the aforementioned data management. Depending on the new data scale, the interrelationships between data are analyzed and calculated, and if the relationships between data are not merely superpositions, the data storage units at this scale further include, but are not limited to, data with complex interrelationships such as intersection, tangent, separation, or inclusion. Data that satisfies data management conditions and whose data still overlaps are designated as data management units in the new data scale, the new data scale is reset, and the above process is repeated, wherein the data management conditions to be satisfied include, but are not limited to, one or more combinations of data such as the number of data, the amount of data, and the range of data. The aforementioned data range includes, but is not limited to, the range of data display in the new data scale.

[0079] The flow of the method for establishing an index and analyzing and managing data as disclosed in the embodiments of the present invention is shown in Figure 3 and includes steps S31 to S3.

[0080] In step S31, the data scale is set. The aforementioned set data scale includes any scale, such as a pre-set scale, a temporarily set scale, or a scale calculated during the data processing process. The index level is determined according to the scale of the data set as described above. The data is managed and searched according to the level of the aforementioned identified index.

[0081] In step S32, the interrelationships between the data are analyzed and calculated according to the scale of the data. The relationships between the aforementioned data include, but are not limited to, spatial, temporal, and scale relationships.

[0082] The spatial relationships between data at different scales can exhibit simple or complex properties. For example, spatial relationships between data at large scales are simple, requiring only consideration of overlap and non-overlapping data. Non-overlapping data simply exhibit straightforward spatial relationships such as adjacency and separation.

[0083] In step S33, an index is established based on the interrelationships between the analyzed and calculated data, and the data is analyzed and managed.

[0084] After performing the two steps described above, the data may be processed according to the aforementioned interrelationships in accordance with the processing method corresponding to the set processing type. For example, step S33 described above is a specific embodiment of processing data according to interrelationships. The specific implementation process of steps S31 and S32 can be seen in the embodiment shown in Figure 1.

[0085] In this step, the conditions for establishing the index may be specified in advance, depending on the specific case. Specifying the index establishment conditions according to the specific cases mentioned above includes conditional and unconditional settings. For example, if an index is established for each data bit that makes up the coordinate data, then an index establishment condition can be set. The aforementioned index establishment conditions include, but are not limited to, setting a combination of one or more indicators among a certain data range, data volume, and data count as the index establishment conditions. The aforementioned data range includes, but is not limited to, the range of the data itself or the range calculated according to the set data scale.

[0086] According to pre-defined index establishment conditions, the next level index is continuously established for data that satisfies the index establishment conditions and for data that satisfies the interrelationship between the data for which an index has been established. A next-level index will not be established for data that does not satisfy the index establishment conditions, nor for data that does not satisfy the interrelationships between data for which an index has been established. For data that satisfies the index establishment conditions and data that has been analyzed and calculated to have superimposed relationships between data according to the set data scale, the next level index is continuously established. The aforementioned next-level index corresponds to the scale of the next level of data. Setting the scale of the next level of data includes, but is not limited to, setting it by direct or indirect methods such as obtaining it by calculating the scale of the current level or by external assignment.

[0087] For data that satisfies the index establishment conditions and data that satisfies the interrelationship between the data for which an index has been established, the next level index is continuously established, the next level index is managed by an index item that manages the index of the index, and the index being managed can be detected by the index item that manages the index. Data that does not satisfy the index establishment conditions and data that does not satisfy the interrelationship between indexed data are managed by an index item that manages the index data, and the data can be detected by the index item that manages the index data.

[0088] For data that satisfies the index establishment conditions, and for data that has been analyzed and calculated to superimpose the coordinate points constituting the spatial data onto a single point according to the set data scale, the next level index is continuously established.

[0089] Depending on the scale of the data set, an integrated index is established that includes, but is not limited to, a combination of, macrodataset data, data describing or representing objects, and microdatabit data (for example, 21.345, where 4 is the second data bit after the decimal point).

[0090] By using the integrated index described above for data analysis management, the data analysis management includes one or more combinations of data storage, querying, reading, transmission, display, analysis, and calculation of spatial relationships.

[0091] Analyzing and calculating interrelationships between data according to scale, establishing an index based on these scale-dependent interrelationships, and then analyzing and managing the data using the index involves solving functional and performance technical problems related to data storage, transmission, display, and analysis.

[0092] In addition to the embodiment shown in Figure 3, the method may further include the steps of setting a data scale, analyzing and calculating the interrelationships between data according to the data scale, establishing an index according to the analyzed and calculated interrelationships between data, and, after analyzing and managing the data, performing subsequent processing using the established index. The method of managing and storing data with an established index disclosed in the embodiment of the present invention is: This includes managing and storing data according to the established index.

[0093] The specific process is, The index items that manage the data of the aforementioned index are defined as units that manage and store the data, and these units manage and store the data in a format that includes, but is not limited to, storage data blocks, storage records, or storage files.

[0094] In this step, the index items that manage the data of the index are treated as management and storage objects, and the objects that manage and store the data are treated as data blocks, storage records, or storage files, and are managed and stored in various forms. The flow of the data display method disclosed in the embodiment of the present invention is shown in Figure 4 and includes steps S61 to S63.

[0095] In step S61, the scale corresponding to the data is identified according to the scale of the displayed data. The aforementioned data indices are established according to different scales, where these different scales reflect the macro and micro cases of the data itself. The scale of the displayed data also reflects the macro and micro scales of the data. Depending on the scale of the displayed data, the scale is either directly corresponding to it or calculated to correspond to a specific data scale; that is, depending on the scale of the data display, the scale corresponding to the data is directly identified, or depending on the scale of the data display, the scale corresponding to the data is determined by calculation.

[0096] In step S62, the data index is used to search for the data that needs to be displayed, according to the scale of the data. In this embodiment, the data index is established by the method shown in the embodiment in Figure 1-3.

[0097] Depending on the scale of the data, the data index searches for the data that needs to be displayed, and includes one or more of the following methods:

[0098] (1) The detected index items that manage the index are used as display data and displayed, that is, the data managed by the index items is displayed as one point on the data scale corresponding to the data display scale.

[0099] (2) The portion of the detected data corresponding to the scale of the data is used as display data and displayed. That is, the portion of the detected data can be displayed at the scale of the data corresponding to the data display scale, and the remaining data cannot be displayed due to the overlapping relationship between the data, so only the data of this portion that can be displayed can be used as display data.

[0100] (3) The data of the portion of the detected data corresponding to the scale of the data is used as display data and displayed; that is, the detected data is such that the data of a portion of the data is displayed on the scale of the data corresponding to the data display scale, and only the data of this portion of the data is used as display data.

[0101] (4) The detected data is used as display data and displayed.

[0102] (5) Using one or more of the detected data as display data in place of other data having an overlapping relationship, that is, the detected data can be displayed at a scale of the data corresponding to the data display scale, and only the data that can be displayed can be displayed as display data because only the partial data can be displayed due to the overlapping relationship between the data.

[0103] In step S63, the data that needs to be displayed is read in order to display the data. The aforementioned read includes reading from any data storage device such as memory or a hard disk.

[0104] According to step S62, for display purposes, index data that can be displayed in place of the data and data that can be displayed at the corresponding scale are read.

[0105] Embodiments of the present invention disclose a method for analyzing and calculating data, in which the analysis and calculation include analysis and calculation related to scale and analysis and calculation not related to scale. The aforementioned analysis and calculations include, but are not limited to, calculations of spatial relationships in data, aggregation analysis, and heatmap analysis.

[0106] The analysis and calculation related to the aforementioned scale are performed using the index and data corresponding to the scale. The flow of this method is shown in Figure 5 and includes steps S71 and S72.

[0107] In step S71, the analysis is performed according to the index corresponding to the data. In this embodiment, the data index is established by the method shown in the embodiment in Figure 1-3.

[0108] The analysis and calculation are performed according to the spatial relationships of the index data corresponding to different scales of data in the aforementioned index.

[0109] The analysis and calculation of the index will identify, but will not be limited to, whether there is a clear spatial relationship between the data, whether there is no clear spatial relationship, or whether there is a possibility of a spatial relationship.

[0110] The analysis and calculation of the index clearly reveals that the data have spatial relationships of separation, inclusion, and intersection. The analysis and calculation of the index suggests that there may be spatial relationships between data points such as overlap, tangent, separation, and inclusion. Further analysis and calculation to confirm the relationships between data points requires more detailed data.

[0111] The aforementioned analysis and calculation include, but are not limited to, analysis and calculation performed in cooperation with one or more parts of the system, such as the client and server sides.

[0112] The aforementioned analysis and calculation include, but are not limited to, performing analysis and calculation using index and macroscale data in the client portion, system edge portion, etc., and performing analysis and calculation using microscale data and original data on the data storage side, data service side.

[0113] In step S72, analysis and calculations are performed using data corresponding to different scales within the dataset.

[0114] Analyzing and calculating data using data corresponding to different scales involves first performing analysis and calculation using data with few corresponding data at a certain scale and a small computational cost. If this analysis and calculation seeks to find a specific relationship between the data, and if the results of the analysis and calculation using the data with few corresponding data at a certain scale and a small computational cost show that there is a possibility of a certain relationship, then it is necessary to perform further analysis and calculation using more data corresponding to the data that may have a certain relationship at a certain scale (i.e., a further microscale) until the analysis and calculation clearly shows that there is a spatial relationship between the data.

[0115] Regarding the analysis and calculation using data from the aforementioned dataset where there is little corresponding data at a certain scale and the amount of calculation is small, if the analysis and calculation results show that there are spatial relationships of separation, inclusion, and intersection between the data, then the spatial relationships of separation, inclusion, and intersection between the data are clearly established. When analyzing and calculating using data from the aforementioned dataset where there is little corresponding data at a certain scale and the calculation amount is small, if the analysis and calculation results show that there are spatial relationships between the data such as overlap, tangent, separation, and inclusion, then more detailed data is needed to further analyze and calculate and confirm the relationships between the data.

[0116] The present invention discloses a method for progressively transmitting data, the flow of which is shown in Figure 6, and includes steps S81 to S83.

[0117] In step S81, if it is necessary to request incremental data, an incremental data request is sent, and the request includes a request scale parameter. The progressive data transmission method in this embodiment is applied to the request sender, and when the request sender determines that it needs to request incremental data, it sends an incremental data request to the request receiver, and the request includes a scale parameter.

[0118] If the request sender does not have a previously cached index in memory, the request scale parameters include, but are not limited to, the current scale parameters. If the request sender has previously cached indexes stored, the request scale parameters include, but are not limited to, the current scale parameters and scale parameters corresponding to the previously cached index data. If the request sender has previously cached indices and data stored, the request scale parameters include, but are not limited to, the current scale parameter and the scale parameter corresponding to the previously cached data.

[0119] The more finely the index is managed, the higher the level of the scale parameter corresponding to the index item in the microdata. The higher the data resolution, the higher the level of the scaling parameter that corresponds to the detailed data.

[0120] If the requesting party has previously cached data, the specific steps are: Identify the current scale parameters, Get the highest level scale parameter corresponding to previously cached data, The relationship between the highest level scale parameter corresponding to the previously cached data and the current scale parameter is determined to determine whether data needs to be requested. If necessary, the subsequent steps are continued; otherwise, the process terminates. This includes sending incremental data requests, The aforementioned request includes, but is not limited to, the current scale parameter, the request scale parameter, and the corresponding highest-level scale parameter from previously cached data. The previously cached data includes index data corresponding to the corresponding scale from previously cached indexes, and data corresponding to the corresponding scale from previously cached data.

[0121] Next, incremental data obtained according to the required scaling parameters is acquired, and this step includes at least two methods. In step S82, incremental data obtained by analysis based on the requested scale parameter and the index scale parameter is received, and the incremental data is the index incremental data. The system receives incremental data obtained by analyzing the requested scale parameter and the index scale parameter. If the incremental data is index incremental data and there is previously cached index data, the system inserts the received incremental data into the previously cached index data; otherwise, it stores the received incremental data as cached data.

[0122] In step S83, incremental data obtained by analysis based on the requested scale parameter and the data scale is received, and the incremental data is incremental data of the data.

[0123] The system receives incremental data obtained by analyzing the requested scale parameter and the data scale parameter. The incremental data is an incremental version of the data, and if there is previously cached data, the received incremental data is inserted into the previously cached data; otherwise, the received incremental data is stored as cached data.

[0124] In this embodiment, incremental data may be obtained by selecting either step S82 or step S83 separately, or by using both steps simultaneously. In this embodiment, the data index is established by the method shown in the embodiment in Figure 1-3.

[0125] In the data progressive transmission method disclosed in this embodiment, when the request sender transmits an incremental data request, the request sender carries the request scale parameter in the request, and the request receiver can analyze and acquire the incremental data based on the request scale parameter. This allows the acquired incremental data to be displayed without loss, reduces the amount of data transmitted, and improves data transmission efficiency.

[0126] The method for progressively transmitting other data disclosed in this invention is applied to the incremental data request receiving side, and the flow is as follows: The system receives an incremental data request sent from the request sender, and includes a request scale parameter in the incremental data request. Based on the requested scale parameter and the scale in the index, an analysis process is performed to identify index data that satisfies the incremental condition as incremental data, and / or, based on the requested scale parameter and the scale in the data, an analysis process is performed to identify data that satisfies the incremental condition as incremental data. Finally, the process includes sending the incremental data to the request sender.

[0127] In the implementation process, the process for acquiring incremental data corresponding to an incremental data request is shown in Figure 7 and includes steps S91 to S95.

[0128] In step S91, the incremental data request sent from the request sender is received, and the request includes a request scale parameter. If the request scale parameters included in the request include previously cached scale parameters, it indicates that the request sender has previously cached data.

[0129] In step S92, analysis is performed on the index and data based on the current scale parameter in the requested scale parameter to obtain the current analysis result. The data included in the index corresponding to the current scale parameter will be considered the current analysis result. The data included in the corresponding scale, according to the current scale parameter, will be considered the current analysis result.

[0130] If the requested scale parameter includes a previously cached scale parameter, step S93 is executed; otherwise, step S94 is executed.

[0131] In step S93, analysis is performed on the index and data based on the previously cached scale parameters among the requested scale parameters to retrieve the previous analysis results. The data from the current analysis results that satisfy the incremental condition are identified as incremental data, and the specific process for this step is as follows: This includes identifying the data that is the current analysis result and not the previous analysis result as incremental data.

[0132] In step S94, the current analysis result data is used as incremental data. If the aforementioned request scale parameters do not include previously cached scale parameters, the process will This includes using the current analysis results as incremental data.

[0133] In step S95, the incremental data is sent to the requesting sender.

[0134] The current scale parameter mentioned above is set as the current highest level scale parameter for the incremental data. The aforementioned incremental data is sent to the requesting sender.

[0135] If the requesting party has previously cached data, it needs to insert the received incremental data into the previously cached data, thereby reconstructing the data, and the reconstructed data becomes the current cached data.

[0136] If the request sender does not have cached data, the request receiver, after receiving the incremental data request, analyzes the data according to the current scale parameter based on the request scale parameter, and the resulting data is incremental data. After receiving the incremental data, the request sender caches the incremental data and performs subsequent progressive transmission processing on it as previously cached data.

[0137] In this embodiment, the data index is established by the method shown in the embodiment in Figure 1-3.

[0138] The present invention also discloses a data processing device, the configuration of which is shown in Figure 8. A scale setting unit 101 for determining the scale of the data, including, but not limited to, any scale such as a pre-set scale, a temporarily set scale, or a scale calculated in the data processing process, Depending on the scale of the data, a data analysis unit 102 is provided for analyzing and calculating the interrelationships between the data, The system includes a data processing unit 103 for processing the data according to the aforementioned interrelationships using a processing method corresponding to the configured processing type.

[0139] This embodiment discloses a preferred implementation method, and its specific operating process will not be described again here, but will refer to the flow shown in one of Figures 1-7.

[0140] The present invention further discloses a device for establishing an index and analyzing and managing data, the configuration of which is shown in Figure 9. A scale setting unit 111 for determining the scale of the data, including, but not limited to, any scale such as a pre-set scale, a temporarily set scale, or a scale calculated in the data processing process, Depending on the scale of the data, a data analysis unit 112 is provided for analyzing and calculating the interrelationships between the data, An index generation unit 113 establishes an index based on the interrelationships between the analyzed and calculated data, and analyzes and manages the data. It includes an analysis management unit 114 for storing, displaying, analyzing, calculating, and progressively managing data according to the index.

[0141] Alternatively, the index generation unit 113 may be used to establish an index based on the interrelationships between the analyzed and calculated data, thereby realizing a process for analyzing and managing the data.

[0142] This embodiment discloses a preferred implementation method, and its specific operating process will not be described again here, but will refer to the flow shown in one of the Figures 3-7.

[0143] The present invention further discloses a device for managing and storing data, the configuration of which is shown in Figure 10. A scale setting unit 121 for determining the scale of the data, including, but not limited to, any scale such as a pre-set scale, a temporarily set scale, or a scale calculated in the data processing process, and Depending on the scale of the data, a data analysis unit 122 is provided for analyzing and calculating the interrelationships between the data, It includes a management and storage unit 123 for managing and storing data according to the interrelationships between the analyzed and calculated data.

[0144] This embodiment discloses a preferred implementation method, and its specific operating process will not be described again here, but will refer to the flow shown in one of Figures 1-7.

[0145] Embodiments of this application further disclose a device for managing and storing other data, which includes a management and storage unit, used in conjunction with a device for establishing an index shown in Figure 9 and analyzing and managing data, and for managing and storing data using the data index obtained by the device in Figure 9. The specific operation flow will not be described again here, as it will be explained in reference to the method embodiment described above.

[0146] The embodiments of this application further disclose a data display device, Depending on the scale of the displayed data, a scale identification unit is provided to determine the scale of the data, Depending on the scale of the data, the data index includes a search unit for finding the data that needs to be displayed, To display the data, it includes a data reading unit for reading the data that requires display.

[0147] In this embodiment, the data index is generated by a device that establishes the index shown in Figure 9 and analyzes and manages the data. The specific operating process of this data display unit will not be explained again, as it refers to the embodiment shown in Figure 4.

[0148] This application further discloses an apparatus for analyzing and calculating data, Includes analytical calculation units for performing analytical calculations based on the index corresponding to the data.

[0149] This analysis and calculation unit may be used in conjunction with the device that establishes the index shown in Figure 9 and analyzes and manages the data, and performs analysis and calculations using the index of the data obtained by the device in Figure 9. The specific operation flow will not be explained again here, as it will be explained by referring to the content corresponding to the above-described embodiment of the method.

[0150] This application further discloses a device for progressively transmitting data, which is applied to an incremental data request sender. When it is necessary to request incremental data, an incremental data request transmission unit is used to send an incremental data request, and the request includes a request scale parameter. Used to receive incremental data obtained by analysis based on the aforementioned request scale parameter and the index scale, wherein the incremental data is the incremental data of the index, and / or An incremental data receiving unit is used to receive incremental data obtained by analysis based on the requested scale parameter and the scale of the data, wherein the incremental data is incremental data of the data.

[0151] In this embodiment, the data index is generated by a device that establishes the index shown in Figure 9 and analyzes and manages the data. The specific operating process of this device will not be described again here, as it refers to the embodiment shown in Figure 6.

[0152] At the same time, this application further discloses a device for progressively transmitting other data, applicable to the incremental data receiving side. This is for receiving an incremental data request sent from the request sender, and includes an incremental data request receiver that includes a request scale parameter in the incremental data request, An incremental data identification unit performs analytical processing based on the requested scale parameter and the scale in the index to identify index data that satisfies the incremental condition as incremental data, and / or performs analytical processing based on the requested scale parameter and the scale in the data to identify data that satisfies the incremental condition as incremental data. It includes an incremental data transmission unit for transmitting the incremental data to the request sender.

[0153] In this embodiment, the data index is generated by a device that establishes the index shown in Figure 9 and analyzes and manages the data. The specific operating process of this device will not be described again here, as it refers to the embodiment shown in Figure 7.

[0154] The data processing method and apparatus disclosed in this invention may be installed in a computer, a mobile phone, or other device.

[0155] Each example in this specification is described progressively, with each example primarily describing its differences from other examples, and any identical or similar parts between examples may be referenced to one another. Since the apparatus disclosed in the examples corresponds to the methods disclosed in the examples, the description is relatively straightforward, and relevant parts can be found in the description in the Methods section.

[0156] Those skilled in the art will further understand that each exemplary unit and algorithmic step described in relation to the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination thereof, and that each exemplary component and step is generally described in the above description in terms of function in order to clearly illustrate hardware and software compatibility. Whether these functions are performed in hardware or software depends on the specific application of the technical solution and the design constraints of the solution. Those skilled in the art will be able to use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of the invention.

[0157] Steps of methods or algorithms described in relation to the embodiments disclosed herein can be carried out directly in hardware, software modules executed by a processor, or a combination thereof. The software modules may be located in random access memory (RAM), memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disks, removable disks, CD-ROMs, or any other form of storage medium known in the art.

[0158] The above description of the disclosed embodiments will enable those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the invention. Accordingly, the present invention should not be limited to these embodiments shown herein, but rather to the broadest scope overlapping with the principles and novel features disclosed herein.

Claims

1. A method for processing data, comprising: On the computer, A step of setting a scale of data, the data being used for displaying an electronic map or for spatial analysis and calculation; Analyzing and calculating correlations between the data according to the scale of the data; A step of processing the data according to the correlation according to a processing method corresponding to a set processing type, the step including establishing an index and analyzing and managing the data according to the correlation between the analyzed and calculated data; Run the command, The process of establishing an index and analyzing and managing the data according to the correlation between the analyzed and calculated data includes: Continually establishing next level indexes for data that satisfy a preset index establishment condition and data that satisfies interrelationships between the index-established data; not establishing a next level index for data that does not satisfy the index establishment conditions and the interrelationships between the data for which the indexes are established.

2. the data includes any one or more combinations of a macro data set, data describing an object, coordinate data, and micro data bits; The scale of the data is a variable that indicates the macro and micro scale of the data, 2. The method of claim 1, wherein the data is more macroscopic at larger scales than at smaller scales and more microscopic at smaller scales than at larger scales.

3. 2. The method of claim 1, wherein the scale of the data includes the spatial or temporal scale of the data itself.

4. 2. The method of claim 1, wherein the scale of the data includes a scale of observational data or a scale of spatial data, the scale of the observational data including the magnification at which the spatial data is displayed on a computer, and the scale of the spatial data including the resolution of the spatial data.

5. The method of claim 1 , wherein the interrelationships between the data include any one or a combination of a spatial relationship, a temporal relationship, and a scale relationship.

6. The process of processing the data according to the correlation in accordance with a processing method corresponding to the set processing type includes: Establishing indexes of data, storing, reading, transmitting, displaying and processing the analysis of data based on the interrelationships between data at different scales; Or, 2. The method of claim 1, further comprising the steps of: storing, reading, transmitting, displaying, and analyzing the data based on different scales and interrelationships between the data.

7. 1. A method for establishing an index and analyzing and managing data, comprising: On the computer, A step of setting a scale of data, the data being used for displaying an electronic map or for spatial analysis and calculation; Analyzing and calculating correlations between the data according to the scale of the data; a step of processing the data according to the correlation according to a processing method corresponding to a set processing type, the step including establishing an index and analyzing and managing the data according to the correlation between the analyzed and calculated data; Run the command, The process of establishing an index and analyzing and managing the data according to the correlation between the analyzed and calculated data includes: Continually establishing next level indexes for data that satisfy a preset index establishment condition and data that satisfies interrelationships between the index-established data; not establishing a next level index for data that does not satisfy the index establishment conditions and the interrelationships between the data for which the indexes are established.

8. The set data scale includes a preset scale, a temporarily set scale, or a scale calculated in a data processing process; Identifying an index level according to the scale of the set data; 8. The method of claim 7, further comprising managing and searching data according to the identified level of index.

9. The method according to claim 7 , wherein the predetermined index establishment condition includes a combination of one or more of the following indicators: a predetermined data range, a data amount, and a data number.

10. The method according to claim 9 , wherein the data range includes a range of the data itself or a range calculated according to a scale of the set data.

11. The process of establishing an index and analyzing and managing the data according to the correlation between the analyzed and calculated data includes: For data that satisfies an index establishment condition and data that satisfies a correlation between data for which an index is established, a next level index is continuously established, and the next level index is managed by an index item that manages an index of indexes, and the index managed by the index item that manages the index is detectable; The method according to claim 7, further comprising managing data that does not satisfy the index establishment conditions and data that does not satisfy the interrelationships between data for which indexes are established in index items of index management data, and making it possible to detect the data by the index items that manage the data.

12. The process of establishing an index and analyzing and managing the data according to the correlation between the analyzed and calculated data includes: Continually establish a next level index for the data that satisfies the index establishment condition and the data that is analyzed and calculated to have an overlapping relationship according to the set data scale, the next level index corresponds to a scale of the next level of data; 8. The method according to claim 7, wherein the setting of the scale of the data of the next level includes setting the scale by a method of obtaining the scale of the current level by calculation or by a method of applying the scale from outside.

13. The process of establishing an index and analyzing and managing the data according to the correlation between the analyzed and calculated data includes: The method according to claim 12, further comprising continuously establishing a next level index for data that satisfies an index establishment condition and data that is analyzed and calculated when coordinate points constituting spatial data according to the set data scale overlap one point.

14. The method process for establishing the index and analyzing and managing the data comprises: Establishing an integrated index for any one or more combinations of data of a data set, data describing or representing an object, and data of microdata bits according to the set scale of data; using the integrated index to analyze and manage data; 8. The method of claim 7, wherein the analyzing and managing of the data includes any one or more combinations of storing, querying, retrieving, transmitting, displaying, analyzing, and calculating spatial relationships of the data.

15. 1. A method for managing and storing data, comprising: On the computer, Implementing management and storage of data according to the established index; A method according to claim 7, characterized in that the index of data is established by a method according to any one of claims 7 to 14.

16. The process of managing and storing data according to the established index comprises:

16. The method of claim 15, further comprising: making an index item that manages data of the index an object that manages and stores data; and managing and storing the data in a format including a storage data block, a storage record, or a storage file.

17. 1. A method for managing and storing data, comprising: On the computer, A step of setting a scale of data, the data being used for displaying an electronic map or for spatial analysis and calculation; Analyzing and calculating correlations between the data according to the scale of the data; A step of managing and storing data according to interrelationships between the analyzed and calculated data, the step including establishing an index according to the interrelationships between the analyzed and calculated data, and managing and storing the data according to the established index; Run the command, The process of establishing an index and analyzing and managing the data according to the correlation between the analyzed and calculated data includes: Continually establishing next level indexes for data that satisfy a preset index establishment condition and data that satisfies interrelationships between the index-established data; not establishing a next level index for data that does not satisfy the index establishment conditions and the interrelationships between the data for which the indexes are established.

18. The process of scaling the data comprises:

20. The method of claim 17, further comprising setting an initial scale for data management according to the simplicity of the relationships between data at different scales.

19. The process of scaling the data comprises: Setting the scale on which the data is superimposed as an initial scale for data management; 20. The method of claim 18, wherein the superimposition of data includes all data forming one superimposition, data forming multiple superimpositions, or multiple coordinate points of one data forming a superimposition.

20. The process of managing and storing data according to the correlations between the analyzed and calculated data includes: The data having the mutual relationship of overlapping is treated as a data management unit, Set a new data scale according to the initial scale of the data management; Analyze and calculate the correlation between the data according to the new data scale, and if the correlation between the data is not a simple superposition relationship, the data is treated as a data storage unit on this scale; The data that meets the data management conditions and is still overlapped between the data is taken as a data management unit in the new data scale, and the new data scale is reset, and the above process is repeated; Satisfying the data management condition includes one or a combination of a number of data, a data amount, and a data range; 20. The method of claim 19, wherein the data range comprises a data display range of data on the new data scale.

21. 1. A method of displaying data, comprising: On the computer, determining a scale of the data in response to a scale of the displayed data; - searching for the data requiring display in an index of data according to a scale of said data, said index of data being established by a method according to any one of claims 7 to 14; reading data requiring display in order to display said data; A method comprising:

22. The process of determining a scale corresponding to the data in response to the scale of the display data includes:

22. The method of claim 21, comprising determining a scale of data directly in response to a scale of the data representation, or determining a scale of data by calculation in response to a scale of the data representation.

23. The process of searching the index of data for the data requiring display according to the scale of the data includes any one or a combination of more of the following ways: Display the index items that manage the detected indexes as display data, A portion of the detected data corresponding to the scale of the data is displayed as display data; displaying, as display data, data of a portion of the detected data corresponding to a scale of the data; The detected data is displayed as display data, 22. The method of claim 21, wherein one or more of the detected data are displayed as display data instead of other data having a superimposed relationship.

24. A method for analyzing and calculating data, comprising: On the computer, - performing an analytical calculation as a function of an index corresponding to the data, said index corresponding to the data being established by a method according to any one of claims 7 to 14; performing an analysis and calculation using data corresponding to different scales among the data; A method comprising:

25. The analytical calculation includes a scale-related analytical calculation or a scale-unrelated analytical calculation, 25. The method of claim 24, wherein the analytical calculation comprises calculating a spatial relationship of data, an aggregation analysis, or a heat map analysis.

26. The above analysis and calculation process is as follows: The method according to claim 25, wherein the analysis calculation relating to the scale includes performing the analysis calculation using an index corresponding to the scale and data.

27. The process of analyzing and calculating data according to the index is as follows:

25. The method of claim 24, comprising performing analytical calculations as a function of spatial relationships of index data corresponding to different scales of data in the index.

28. The process of performing an analysis and calculation according to an index corresponding to the data includes:

28. The method of claim 27, further comprising: determining that the analysis of the index includes determining whether the data has a definite spatial relationship or a possible spatial relationship between the data.

29. The process of performing analysis and calculation using data corresponding to different scales among the above data is as follows: The method of claim 24, wherein first, an analysis and calculation is performed using data having a small amount of corresponding data at a certain scale among the data, and the analysis and calculation is performed to determine whether there is a specific relationship between the data. If there is a data that may have a certain relationship among the results of the analysis and calculation performed using the data having a small amount of corresponding data at a certain scale among the data, it is necessary to perform further analysis and calculation using more data corresponding at a certain scale among the data that may have the certain relationship until it is determined that there is a clear spatial relationship between the data.

30. 1. A method for progressively transmitting data, comprising the steps of: On the computer, if incremental data needs to be requested, sending an incremental data request, said request including a request scale parameter; receiving incremental data obtained by analyzing the scale of the requested scale parameter and the scale of an index, the incremental data being incremental data of an index; and / or receiving incremental data obtained by analyzing the scale of the data based on the requested scale parameter and the scale of the data, the incremental data being incremental data of the data; Run the command, A method, characterized in that the index is established by a method according to any one of claims 7-14.

31. 31. The method of claim 30, wherein if the request sender is caching previously cached data, the previously cached data includes index data corresponding to a corresponding scale of the previously cached index and / or data corresponding to a corresponding scale of the previously cached data.

32. If the request sender has cached data that was previously cached, the specific steps are: Identify the current scale parameters, Get the highest-level scale parameter that corresponds to the previously cached data, determining a relationship between the highest level scale parameter corresponding to said previously cached data and said current scale parameter to determine whether data needs to be requested, and if so, continuing to execute subsequent steps, and if not, terminating; sending an incremental data request, the request including the current scale parameter and a scale parameter of a corresponding highest level of previously cached data, referred to as a requested scale parameter; receiving incremental data obtained by analyzing the requested scale parameter and the index scale parameter, the incremental data being index incremental data; receiving incremental data obtained by analyzing the scale parameter based on the requested scale parameter and the scale parameter of the data, the incremental data being incremental data of the data; 32. The method of claim 31, further comprising inserting the received incremental data into the previously cached data.

33. 1. A method for progressively transmitting data, comprising the steps of: On the computer, receiving an incremental data request sent from a request sender, the incremental data request including a request scale parameter; a step of performing an analysis process based on the requested scale parameter and the scale in the index to identify index data that satisfies an increment condition in the index as incremental data, and / or a step of performing an analysis process based on the requested scale parameter and the scale in the data to identify data that satisfies an increment condition in the data as incremental data; transmitting said incremental data to said request sender; Run the command, A method, characterized in that the index is established by a method according to any one of claims 7-14.

34. 34. The method of claim 33, wherein if the request sender has previously cached index and data stored therein, the requested scale parameters include current scale parameters and / or scale parameters corresponding to the previously cached data.

35. The process of obtaining incremental data corresponding to the incremental data request includes: Perform an analysis process on the index and data based on the current scale parameters in the request scale parameters to obtain a current analysis result; If the requested scale parameters include previously cached scale parameters, the process: performing an analytical process on the index and data based on previously cached scale parameters in the request scale parameters to obtain a previous analytical result; A specific process of identifying data that satisfies an incremental condition from the current analysis result as incremental data, and identifying data that satisfies an incremental condition from the current analysis result as incremental data, is as follows: identifying data that is the current analysis result and is not the previous analysis result as incremental data; If the requested scale parameters do not include previously cached scale parameters, the process: The data of the current analysis result is taken as incremental data, said current scale parameter being a scale parameter of a current highest level of incremental data; 34. The method of claim 33, further comprising transmitting the incremental data to a request sender.

36. A data processing device, comprising: a scale setting unit for specifying a scale of data, the data being data used for displaying an electronic map or for analyzing and calculating space; a data analysis unit for analyzing and calculating interrelationships between the data according to the scale of the data; a data processing unit for processing the data according to the correlation in accordance with a processing method corresponding to a set processing type; The data processing unit establishes an index according to the correlation between the analyzed and calculated data, and analyzes and manages the data; The process of establishing an index and analyzing and managing the data according to the correlation between the analyzed and calculated data includes: Continually establishing next level indexes for data that satisfy a preset index establishment condition and data that satisfies interrelationships between the index-established data; not establishing a next level index for data that does not satisfy an index establishment condition and for data that does not satisfy interrelationships between data for which an index has been established.

37. An apparatus for establishing an index and analyzing and managing data, comprising: a scale setting unit for specifying a scale of data, the data being used for displaying an electronic map or for analyzing and calculating space; a data analysis unit for analyzing and calculating correlations between the data according to the scale of the data; an index generating unit for establishing an index according to correlations between the analyzed and calculated data, and for analyzing and managing the data; The process of establishing an index and analyzing and managing the data according to the correlation between the analyzed and calculated data includes: Continually establishing next level indexes for data that satisfy a preset index establishment condition and data that satisfies interrelationships between the index-established data; not establishing a next level index for data that does not satisfy an index establishment condition and for data that does not satisfy interrelationships between data for which an index has been established.

38. A data management and storage device, comprising: a scale setting unit for specifying a scale of data, the data being used for displaying an electronic map or for analyzing and calculating space; a data analysis unit for analyzing and calculating correlations between the data according to the scale of the data; a management and storage unit for managing and storing data according to correlations between the analyzed and calculated data; The management and storage unit establishes an index according to the correlation between the analyzed and calculated data, analyzes and manages the data, and manages and stores the data according to the established index; The process of establishing an index and analyzing and managing the data according to the correlation between the analyzed and calculated data includes: Continually establishing next level indexes for data that satisfy a preset index establishment condition and data that satisfies interrelationships between the index-established data; not establishing a next level index for data that does not satisfy an index establishment condition and for data that does not satisfy interrelationships between data for which an index has been established.

Images