JP3809985B2 - Attribute data management method - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a point data management method in an information system that handles graphics, and more particularly, to an attribute data management method for managing a plurality of attribute information related to graphics on a map in a geographic information system.
[0002]
[Prior art]
A geographic information system (GIS) is a system for appropriately managing and efficiently using geographical information, and has been used for various purposes such as fixed asset management and city planning support.
In many conventional GIS, in order to manage a plurality of related attribute data groups collectively, an identifier (ID) having a common value such as an address code and a graphic number on a map is previously described in the attribute data. “Label management”, that is, “relationship explicit type” data structure / system structure has been used.
FIG. 11 shows an example of a label management type resident information system, in which attribute information is created as a tabular database according to type, and these are integrated and used.
Here, “◯ △” (1102), which is the ID of the house graphic 1101, is given as a common identifier to all the attribute data related to a certain house and is explicitly associated.
Therefore, when referring to house information, data having the same ID “◯ △” is searched from the address database 1103 and the resident database 1104 by simple ID match determination, so that efficient data extraction / integrated use is possible. Yes (1105).
[0003]
Generally, a distributed map database (for example, Japanese Patent Application Laid-Open No. 5-20365) constructed in a planned manner is often constructed as a related explicit database with high data utilization efficiency because an association identifier can be prepared in advance.
However, while data utilization efficiency is good, there is a restriction on data creation in which an identifier for association must be created. Another problem is that it is difficult to cope with changes in the relationship between data.
For example, in a system that uses an address code as a common identifier, if there is a change in the address system, such as “Implementation of block-type residence display”, the identifier of all data in the corresponding area must be corrected. Depending on complicated data correction processing, inconsistencies between data may occur. In addition, if the address system collapses, such as “immediately after the Great East Japan Earthquake,” the data itself becomes difficult to use.
[0004]
On the other hand, there is also a method of expressing a plurality of related attribute data groups as “attribute point data having a positional relationship” and using a “related-implicit” data structure / system structure for managing the relationship according to the position.
111 in FIG. 1 is an example of a resident information system of a positional relationship management type.
Unlike the label management example described above, the resident point data 112 and the address point data 103 do not have a common identifier. However, due to the positional relationship of being included in the same house graphic 104, it is possible to extract related point data groups using graphic analysis with a large amount of calculation such as inclusion determination and refer to the house information collectively (113). ).
That is, there is an advantage that attribute information in map data that is not associated in advance at the time of data creation / use can be integrated / used, such as completely different types of map data. Moreover, there is no difficulty in dealing with the relationship change, which is a problem in the label management system.
However, on the contrary, there is a problem that calculation processing is required every time data is used, which is inefficient.
[0005]
[Problems to be solved by the invention]
There has been a lot of research on distributed management of map databases, but there has been a great deal of research on how to geographically integrate decentralized data again, link them appropriately, and present them efficiently to users. It has not been studied much.
In order to respond flexibly and efficiently to various situations such as the integration of completely different types of map databases, data is managed by positional relationship during creation / integration, while explicitly associated by a common identifier when used. It is more convenient to have the data.
However, the former has a problem that the processing efficiency when using data is poor, and the latter has a problem that the system lacks flexibility in changing data.
[0006]
The purpose of the present invention is to reduce the calculation processing when using related implicit data, and to manage the change in the relationship in related explicit data appropriately. To provide management technology.
[0007]
[Means for Solving the Problems]
In order to solve the above problems, the present invention provides:
An attribute data management method in an information system for managing attribute data related to a closed area on a map using map data,
Creating the attribute data as attribute point data having position coordinates located in the closed region, associating the attribute point data with the closed region,
Change the coordinate value of the position coordinates of all the attribute point data belonging to the same closed region to the same coordinate value as a coordinate key, associate all the attribute point data belonging to the same closed region as an attribute point data group,
During attribute search, the first attribute point data is extracted by determining whether or not the input search coordinate value is within the closed region, and thereafter the same coordinates as the coordinate key of the extracted attribute point data are extracted. By extracting and extracting attribute point data having a key, attribute data related to the input coordinate value for search is searched at high speed.
[0008]
In addition, an attribute data management method in an information system that uses map data to manage attribute data having a relationship with a figure such as a point or a line on a map,
Creating the attribute data as attribute point data having position coordinates located within a certain distance from the graphic, and associating the attribute point data with the graphic;
The coordinate values of the position coordinates of all the attribute point data associated with the same graphic are used as the coordinate values of the constituent points constituting the graphic, and all the attribute point data belonging to the same graphic are associated as the attribute point data group. ,
At the time of attribute search, the attribute value data related to the input figure can be searched at a high speed by extracting the attribute point data by matching the coordinate value of the figure configuration point of the input figure and the position coordinate of the attribute point data. Like to do.
[0009]
Further, the attribute point data group associated with each other is continuously registered in the point data file,
At the time of attribute search, after searching the first attribute point data, the corresponding data group is extracted continuously only by the coordinate value match determination, the end of the search is determined by detecting the coordinate value mismatch, and the related attribute data To search fast.
[0010]
When managing the attribute point data that cannot change the coordinate values of the position coordinates of all the attribute point data belonging to the same closed region to the same coordinate value, A search position coordinate field is newly provided, and the coordinate value of the search position coordinate of the field is set to the same coordinate value as a coordinate key.
[0011]
When managing attribute point data that cannot change the coordinate values of the position coordinates of all the attribute point data associated with the same graphic to the coordinate values of the constituent points constituting the graphic, the attribute points A second search position coordinate field is newly provided in the data, and the coordinate value of the search position coordinate in the field is used as the coordinate value of the constituent points constituting the figure.
[0012]
Further, individual management flag information indicating whether or not attribute point data is associated is set in the attribute point data, the attribute point data is registered in the point data file, and all the individual management of the registered attribute point data is performed. Set management flag information indicating whether or not the flag information is valid in the point data file,
At the time of attribute search, if the management flag information is valid, an inclusion determination is made as to whether or not the input search coordinate value is within the closed region, and the first attribute point data is extracted. Perform a match determination process to match and extract attribute point data with the same coordinate key as the coordinate key of the attribute point data,
If the management flag information is invalid, it is determined whether or not the position coordinates of the attribute point data for which the individual management flag information is invalid belong to a closed region, and if it belongs, the association is performed to validate the individual management flag information. , When all the individual management flag information is validated and the management flag information is validated, the match determination process is performed,
By referring to the management flag information, related attribute data is searched at high speed.
[0013]
Further, individual management flag information indicating whether or not attribute point data is associated is set in the attribute point data, the attribute point data is registered in the point data file, and all the individual management of the registered attribute point data is performed. Set management flag information indicating whether or not the flag information is valid in the point data file,
At the time of attribute search, if the management flag information is valid, a match determination process is performed to perform a match determination between the coordinate value of the figure configuration point of the input graphic and the position coordinate of the attribute point data and extract the attribute point data,
If the management flag information is invalid, it is determined whether or not the position coordinates of the attribute point data for which the individual management flag information is invalid are associated with a figure. And when all the individual management flag information is enabled and the management flag information is enabled, the match determination process is performed.
By referring to the management flag information, related attribute data is searched at high speed.
[0014]
Moreover, the time information when attribute data exists in the attribute point data is described,
The time information is used as a determination material, the attribute point data group existing in a certain period is associated, and the related attribute data is searched at high speed, so that statistical information on a certain period and space is acquired at high speed. .
[0015]
DETAILED DESCRIPTION OF THE INVENTION
Hereinafter, an embodiment of the present invention will be described in detail with reference to FIGS.
First, the outline of the association processing in the present invention will be described with reference to FIGS.
FIG. 3 shows an example of determination processing by the positional relationship analysis determination function.
301 is a state of the inclusion determination process.
Using the surface determination graphic 302, an inclusion determination 303 is performed as to whether or not scattered points are included in the determination graphic 302 (inside or outside).
The four internal determination point data 304 shown in black are determined as a point data group (305), and the four external determination point data 306 shown in white are determined not to belong to the point data group.
[0016]
Reference numeral 311 denotes a state of the distance determination process.
Using the line determination graphic 312, a distance determination 313 is performed to determine whether scattered points are within the distance x from the determination graphic 312 (whether they are near or far).
The four near-determination point data 314 indicated by black is determined as a point data group (315), and it is determined that the four far-determination point data 316 indicated by white do not belong to the point data group.
[0017]
FIG. 4 shows an example of explicit association of point data groups by the association data description function.
Reference numeral 401 denotes a state of association using a point graphic.
Using the point association guide 402, the coordinate value of the association guide 402 is assigned as a common identifier to the three points to be associated point data 403 shown in white (404).
Reference numeral 411 denotes a state of association using line figure composing points.
Using the line association guide 412, the coordinate values of the constituent points of the association guide 412 are assigned as common identifiers to the four points to be associated point data 413 shown in white (414), and the associated point data 415 shown in black And
The point data that has undergone the above-described processes is hereinafter referred to as associated point data or associated points.
[0018]
The point data includes the “graphic centroid point” (for example, the centroid point of the Kokubunji city administrative boundary figure on the map) that has meaning in the original coordinate values, Alternatively, there are two types such as “representative points” that need only be inside a certain region.
In this embodiment, assuming the former, as shown in the file format of FIG. 9 to be described later, the representative point is entered separately from the original coordinate field (908 to 910 in FIG. 9) (the true position is entered). Although an example (detailed in FIG. 9) in which the second search coordinate field (914, 915 in FIG. 9) is provided is shown, in the latter case, a new coordinate value (for example, the above representative point) ) Can also be given. The true position is a position indicated by the original coordinate value.
Further, in the present embodiment, an example is shown in which attribute point data having three-dimensional solid information is associated by giving the same coordinate value for two-dimensional coordinates, but the same coordinate value can also be given for three-dimensional coordinates.
Furthermore, as shown in FIG. 9 to be described later, when the point data exists across a plurality of files, it is possible to describe / manage the situation in which the relation is clearly specified using the overall management flag.
Although FIG. 4 shows an example in which graphic data such as points and lines is used as an association guide, in addition to graphic composing points, graphic centroid points, centroid points of multiple data points, specific points (address representative points, national census) It is also possible to use a graphic center point).
Similarly, regarding the description method of association, IDs other than coordinates are assigned, a reference INDEX indicating a point data group is created / held, a pointer to the next data is assigned to each point data, and points in a plurality of files For data groups, various methods can be used, such as creating an integrated file in which the data groups are grouped, or using it as a temporary integrated file.
[0019]
As described above, by using the processing functions shown in FIGS. 3 and 4 in combination, the relationship of the related implicit data group (data group that is not associated) described later in FIG. It is possible to construct a system that can flexibly deal with various situations such as integration of distributed databases and manual input of data.
In addition, by associating and describing data groups as necessary, appropriate information can be quickly gathered and presented to the user.
Furthermore, by using “location coordinates” which is the basis of geographic information as a common identifier, data can be shared between systems with greatly different design concepts.
[0020]
FIG. 1 is a diagram for explaining the concept of the present invention.
Reference numeral 101 denotes a data image and a screen image of an associated explicit type system in which point data is associated. The associated points are called association explicit points, resident point data is shown as an example of the association explicit point group 102, address point data is shown as an example of the association guide 103, and house surface data is shown as an example of the determination graphic 104.
The related explicit point group 102 is explicitly associated by assigning the coordinate value of the association guide 103 as a common identifier by the association processing function described above with reference to FIGS.
For example, when referring to information about a certain house, each individual management flag for each point located in the house (which will be described later with reference to FIG. 9, point data is associated with point data in a point data file which is a point data file). If the individual management flag indicating whether or not it has been assigned is associated, and if the individual management flag is valid, it is associated, and if it is invalid, it indicates that it is not associated.) It is found that they are related, and the related explicit point cloud correspondence processing function 105 is selected and executed.
The point data group can be extracted efficiently only by the coordinate matching determination process suitable for the related explicit type data format, and the information can be collectively displayed with a few procedures.
[0021]
On the other hand, 111 is a data image and a screen image of the related implicit system.
Points not associated with each other are referred to as related suggestion points, resident point data is shown as an example of the related suggestion point group 112, address point data is shown as an example of the association guide 103, and house surface data is shown as an example of the determination graphic 104.
For example, when referring to information about a certain house, it can be seen that the point data group is not explicitly associated with each other because the management flag for each point located in the house is invalid. Select and execute.
Since inclusion determination is performed for each piece of point data and a positional relationship of being included in the house figure is extracted, integrated processing of a distributed map database that cannot be associated in advance is possible although processing time is required.
[0022]
In FIG. 1, an example of inclusion determination using house surface data is shown as the determination graphic 302, but other than those that exist within a radius r from a certain point, grouping by clustering from the distribution of point data itself, determination by attribute, It is also possible to use a determination method such as
[0023]
Next, a data structure example of the point data file and the management information file will be described with reference to FIG.
The point data file 900 (for example, a resident point data file) includes a header portion 901 and a list of data portions 907 relating to each point. There are as many data portions 907 as the number of data points.
(Header part 901)
A management flag 902 indicates whether the association processing for the entire point data file is valid or invalid.
Reference numeral 903 denotes time information at the time of executing the association process, reference numeral 904 denotes a data type of the determination graphic used for the association process (for example, a house frame), reference numeral 905 denotes a data type of the association guide used for the association process (for example, address representative point). ), 906 stores the number of point data registered in the point data file.
(Data part 907)
The original coordinate fields 908, 909, and 910 store the true position coordinate value of the point data (the true position is the position indicated by the original coordinate value), 911 stores the data generation time, and 912 stores the data disappearance time.
Reference numeral 913 denotes an individual management flag, which indicates whether or not the point data of this data portion is associated.
Second search coordinate fields 914 and 915 are second search coordinate values (coordinate values of address representative points, etc.) obtained by association processing, and 916 is a point already associated with the same search coordinate value. Stores the total number of data.
Finally, attribute data (for example, a person's name) is stored in 917.
[0024]
The management information file 920 is a file for managing the entire plurality of point data files, and collectively manages the header portion 921 indicating the association information over the entire plurality of point data files and the information of each point data file. It consists of a list of data parts 927. There are as many data portions 927 as the number of point data files.
(Header portion 921)
Reference numeral 922 denotes an overall management flag, which indicates whether or not the association processing is effective for all point data files.
923 is time information at the time of executing the entire association process, 924 is the data type of the determination graphic used for the entire association process, 925 is the data type of the association guide used for the entire association process, and 926 is the management information Stores the number of data (number of point data files).
(Data part 927)
928 stores the type of point data (for example, resident point data, address representative point data, etc.).
Reference numeral 929 indicates whether the process of associating the point data is for all the point data files or the point data file alone.
Reference numerals 930, 931, 932, and 933 represent the header data 902, 903, 904, and 905 of the point data.
[0025]
According to the above data structure, when the addition / correction of point data occurs after the association processing, efficiency can be achieved by executing the association processing only on the point data.
That is, when adding / modifying data, the overall management flag 922 of the management information file 920, the management flag 930 of the file including the point data, the management flag 902 of the point data file, the individual management flag 913, and the above flags are operated and invalidated. Turn into.
When the association process is performed again, if the overall management flag 922 of the management information file 920 is invalid, a point data file in which the management flag 930 is invalid is searched, and the individual management flag 913 is selected from the point data file. Association processing such as graphic analysis can be performed only on invalid point data.
In addition, for the management information of the local government system, the department name in charge, the location of the department in charge (machine name, file name), the association process is either all sections / single, the time information (association process execution date and time information) It is also possible to hold association data (use data, determination method, coordinate guide data) and the like.
[0026]
FIG. 2 shows an example of the functional configuration of the present invention.
The positional relationship analysis determination function 201 calculates a positional relationship between point data by graphic analysis such as inclusion determination and distance determination.
Data obtained from the relationship is described in a format that allows identification of members of the same point data group, such as a common identifier (coordinate key (second search coordinate value, etc.)) given by the association data description function 202 And are explicitly associated.
The functions of these 201 and 202 are as described with reference to FIGS.
The data correction / addition / integration processing function 204 changes data.
The flag / management information processing function 203 receives the results of the association data description function 202 and the data correction / addition / integration processing function 204, switches the validity / invalidity of each flag, and simultaneously records the data status in the management information file. To do.
The flag / management information determination function 205 refers to the management flag of the management information file and the data to be processed. If it is valid, the related explicit point cloud correspondence processing function 206 is used. If it is invalid, the related implicit point cloud correspondence processing function 207 is used. Select and call.
[0027]
Here, the feature of the present invention is that a related explicit point group corresponding processing function with high processing efficiency, such as matching determination, is explicitly performed for a point data group that is explicitly associated by referring to a management flag or a management information file, For point data groups that are not associated with the data, by appropriately selecting and executing a process such as a related implied point group processing function that can handle various forms of data by inclusion determination, etc. It is to enable the construction of a flexible system that has the characteristics of “/ integration / management” and “efficient use”.
[0028]
In addition, the association process occupying an important position in the present invention is realized by a combination of three functions of a positional relationship analysis determination function 201, an association data description function 202, and a flag / management information processing function 203.
The management information file is checked at the time of the association request from the user, or when the management flag is invalid, etc., by calling 201, it is automatically associated without bothering the user. A map database can be constructed.
Further, by combining the positional relationship analysis determination function 201, the association data description function 202, and the data correction / addition / integration processing function 204, a common coordinate value can be obtained in advance when the user performs data correction or addition by manual input. It is also possible to adopt a system that inputs directly related data, such as pulling data into.
[0029]
Next, the data search / display procedure will be described in detail with reference to FIGS. 5, 6, 7, and 8.
FIG. 5 is an example of a flowchart showing the overall flow of data search / display.
When there is a geographical search request from a user by specifying a location on the screen, first, input coordinates are initialized by the user's specification (S501: S means “step”).
Next, a search for a surface figure including input coordinates is started (S502). The search for the surface graphic including the input coordinates is performed on another file (for example, a file related to a house frame).
User designation is accepted as to which type of drawing is searched (S503), surface graphic data in the specified file is selected (S504), and it is determined by graphic analysis whether the input coordinates are included in the surface graphic (S504). S505).
If it is included, a surface figure to be searched is determined (S506).
Next, the search for the point data group included in the surface graphic is started for the point data file (S507).
[0030]
Here, the validity / invalidity of the overall management flag of the management information file is determined (S508), and A (related explicit point cloud correspondence processing function) and B (related implicit point cloud correspondence processing function) are selected and processed. Details of the processing procedure of these functions will be described with reference to FIGS.
Information on the point data group obtained as a result of the search is displayed together for presentation to the user (S509) (S510).
In S509 and S510, the point data group is classified according to the type / content of the attribute, and information on the number of constituent points obtained as a result is displayed, or the point data group is displayed as a single point when displaying a small scale. It is possible to apply such as.
As described above, by setting and using the overall management flag (S508), it is possible to select and execute the related explicit point cloud corresponding processing function with high processing efficiency and the related implicit point cloud corresponding processing function that can handle various types of data. It is possible to build a system that combines high speed and flexibility.
[0031]
FIG. 6 is an example of a flowchart of the related explicit point cloud corresponding processing function.
This is because the analysis of the point data is used only for the first point data detection included in the figure, and after that, the point data group that is explicitly associated can be efficiently identified by performing a simple match of the point data coordinate values. This is a flow of processing to search for and register the result in the search result table.
An association guide point data file is selected (S601), and all the points in the file are selected (S602), and it is determined whether or not the search coordinate values are included in the surface figure to be searched (S603). As a result, the inclusive point of the first surface graphic retrieved first is stored as a “target point” (S604).
Thereafter, another point data file is selected (S605), and for all the points in the file (S606), it is determined whether the search coordinates have the same value as the target point (S607). Registers the result in the search result table (S608).
[0032]
FIG. 7 is an example of a flowchart of the related implied point group correspondence processing function.
This is a process of searching for point data that is implicitly associated with the positional relationship by graphic analysis called face and point inclusion determination while determining the management flag and registering the result in the search result table. It is a flow.
First, a management information file is selected (S701), and for all data portions in the file (S702), it is determined whether the management flag is valid or invalid (S703).
When the management flag is valid, that is, when all the point data in the point data file indicated by the management flag is explicitly associated, the corresponding point data file is selected (S704), and all the points in the file are selected (S705). ), Process C described later is called.
[0033]
Also, when the management flag is invalid, that is, when only some of the point data in the point data file indicated by the management flag is explicitly associated, or when all the point data is not explicitly associated The point data file to be selected is selected (S706), and it is determined whether the individual management flag is valid or invalid for all point data in the file (S707) (S708).
When the individual management flag is valid, that is, when the point data is associated with other point data, a process C described later is called.
[0034]
When the individual management flag is invalid, that is, when the point data is not associated at all, it is determined whether or not the point data is included in the surface figure to be searched (S709). The result is registered in the search result table (S710). The registration result is reflected in the point data file. That is, the individual management flag of the corresponding data part of the point data file is validated, and the search coordinate value is set.
[0035]
In the process C, when a part of related explicit data is mixed, a point data group can be searched using a common identifier (here, the same coordinate value).
First, it is checked whether or not the target point included in the inclusion determination target graphic is already stored (S711). If the target point is already stored, the coordinate value for searching the point data and the target point coordinate value are determined to match ( S712), if they match, the result is registered in the search result table (S713). If the target point is not yet stored, it is determined whether or not the point data is included in the surface figure to be searched (S714), and if it is included, it is stored as the target point (S715).
[0036]
Here, according to the present invention, when the relational implied type and each management flag are invalid, the relation between data can be extracted by determining the inclusion relation between the points and the faces.
For this reason, it is possible to collectively handle data that has been related but has been separated, such as manual input of data by manual operation of a mouse or the like, and data registration in a situation where past history cannot be referred to such as in an emergency.
In addition, by adding an individual management flag to each point data, even if there is a point that has been added / modified after the association process, only the point data can be determined to be included by referring to the individual management flag. This eliminates the need to re-execute the association process, and can greatly improve the efficiency.
[0037]
As described above, in the method of FIG. 6, compared with the method of FIG. 7, the number of times of performing graphic analysis for obtaining the inclusion relation between points and faces in step 603 is reduced until the first target point is found.
Further, after the target point search, it is only necessary to follow the association identifier in step 607 (determining whether a point matches a point), the calculation processing amount can be greatly reduced, and high-speed processing is possible.
Therefore, it is possible to construct a system with high response performance to the user.
[0038]
FIG. 8 is an example of a flowchart of association processing.
Here, a method of explicitly associating by using the inclusion determination by the surface graphic for the positional relationship determination and giving the same coordinate value to the point data from which the relationship is extracted as a result will be described.
First, with respect to graphic data used for positional relationship analysis determination (S801), designation of the determination surface graphic (S802) and association guide point type (S803) from the user is accepted.
Subsequently, a temporary table of point data to be included is created (S805) for all the determination surface graphics (S804).
Here, the determination of the point group included in each surface graphic is the same as the point data group search procedure by the method of FIG.
Further, the coordinate value of the barycentric point is calculated for each surface figure (S806), and is additionally described in the previously obtained temporary table (S807).
[0039]
For all point data groups in the temporary table (S808), if there is only one associated guide point in each point data group (S809), the coordinate value of the associated guide point in the search coordinates of all point data (S810).
Otherwise, there are two or more association guide points or there are point data groups without association guides, so instead of the association guide points, give the coordinate value of the barycentric point of the judgment surface figure in the temporary table (S811).
Finally, a point data file and a management information file are selected (S812), both management flags are validated (S813), and at the same time, a record of the execution time of the association process is described in the management information file (S814). .
[0040]
As a result of the above processing, instead of performing complicated association extraction processing such as graphic analysis every time data is used, the association processing results can be described and retained, and high-speed processing can be realized for later use Can do.
[0041]
As described above, by using the procedures of FIGS. 5, 6, 7, and 8, the management flag and the management information file are referred to, and the point data group that is explicitly associated has a processing efficiency such as matching determination. Appropriate selection of processing such as a good related explicit point cloud correspondence processing function and a related implicit point cloud correspondence processing function that can handle various types of data by inclusion determination etc. for point data groups that are not explicitly related By executing this, it is possible to construct an elastic system having the characteristics of “flexible data input / integration / management” and “efficient use”.
[0042]
FIG. 10 shows an example of a method of using time information of a figure for determination and collecting point data groups existing in a space in a certain period and providing them as statistical information.
The statistical information acquisition / provision function 1001 searches for all point data included in the determination graphic 1002.
Here, the time information possessed by the point data is determined, and the 1997 resident data 1003 is a target of processing, and the 1997 non-resident data 1004 is not a target of processing.
The resident data is assigned the same coordinate value 1005 such as an address representative point, and the association processing 1006 is explicitly performed.
That is, the statistical information is information in which attribute data is integrated by location / time. By collecting the point data group according to the present invention, the user can easily acquire / display the statistical information 1007.
Here, according to the present invention, since related attribute point data can be explicitly collected, statistical processing is performed in advance, and statistical information associated with address representative points is prepared and provided as information. Is also possible.
[0043]
【The invention's effect】
According to the present invention, completely different map data can be integrated and used by sharing data between distributed map databases.
It also manages point data groups that are entered without being explicitly associated, such as manual data entry using a mouse or the like, or data registration in situations where past history cannot be referenced, such as in an emergency. Integrated use is possible.
That is, it is possible to increase the flexibility related to data input and database integration work and to reduce restrictions on database / system construction.
Further, according to the present invention, it is possible to efficiently handle and combine both the data types of the related explicit point data group and the related implicit type point data group, and efficiently present appropriately associated information to the user. It becomes possible.
In addition, since processing suitable for the data form can be selected and executed, a system with high response performance to the user can be realized by increasing data processing speed by reducing the amount of calculation.
[Brief description of the drawings]
FIG. 1 is a diagram for explaining the concept of the present invention.
FIG. 2 is a diagram illustrating an example of a functional configuration according to the present invention.
FIG. 3 is a diagram illustrating an example of determination processing by a positional relationship analysis determination function according to the present invention.
FIG. 4 is a diagram illustrating an example of explicit association processing of point data groups by an association data description function according to the present invention.
FIG. 5 is a flowchart showing an example of a data search / display procedure in the present invention.
FIG. 6 is a flowchart showing an example of a procedure of a related explicit point cloud corresponding processing function in the present invention.
FIG. 7 is a flowchart showing an example of a procedure of a related implicit point group correspondence processing function in the present invention.
FIG. 8 is a flowchart showing an example of an association processing procedure in the present invention.
FIG. 9 is a diagram showing an example of data structures of a point data file and a management information file in the present invention.
FIG. 10 is a conceptual diagram of a data management method using time information in the present invention.
FIG. 11 is a diagram for explaining the concept of a conventional system.

Claims (8)

An attribute data management method in an information system for managing attribute data related to a closed area on a map using map data,
Creating the attribute data as attribute point data having position coordinates located in the closed region, associating the attribute point data with the closed region,
Change the coordinate value of the position coordinates of all the attribute point data belonging to the same closed region to the same coordinate value as a coordinate key, associate all the attribute point data belonging to the same closed region as an attribute point data group,
During attribute search, the first attribute point data is extracted by determining whether or not the input search coordinate value is within the closed region, and thereafter the same coordinates as the coordinate key of the extracted attribute point data are extracted. by extracting attribute point data having a key match determination, the attribute data managing method characterized by search attribute data associated with the input search for coordinate values. Map data graphic of points and straight lines on the map using a (hereinafter, referred figures) and an attribute data management method in an information system for managing attribute data having a relationship with,
Creating the attribute data as attribute point data having position coordinates located within a certain distance from the graphic, and associating the attribute point data with the graphic;
The coordinate values of the position coordinates of all the attribute point data associated with the same graphic are used as the coordinate values of the constituent points constituting the graphic, and all the attribute point data belonging to the same graphic are associated as the attribute point data group. ,
When searching for attributes, search for attribute data related to the input figure by extracting the attribute point data by determining the coordinates of the coordinates of the figure's constituent points of the input figure and the position coordinates of the attribute point data. Attribute data management method characterized by In the attribute data management method according to claim 1 or 2,
Continuously register the associated attribute point data group in the point data file;
At the time of attribute search, after searching the first attribute point data, the corresponding data group is extracted continuously only by the coordinate value match determination, the end of the search is determined by detecting the coordinate value mismatch, and the related attribute data attribute data management method, characterized by search for. The attribute data management method according to claim 1,
When managing the attribute point data that cannot change the coordinate values of the position coordinates of all the attribute point data belonging to the same closed region to the same coordinate value, the attribute point data is used for a second search. An attribute data management method characterized in that a position coordinate field is newly provided, and the coordinate value of the position coordinate for search in the field is set to the same coordinate value as a coordinate key. In the attribute data management method according to claim 2,
When managing the attribute point data that cannot change the coordinate values of the position coordinates of all the attribute point data associated with the same graphic to the coordinate values of the constituent points constituting the graphic, the attribute point data An attribute data management method characterized in that a second search position coordinate field is newly provided, and the coordinate value of the search position coordinate in the field is used as the coordinate value of a constituent point constituting the figure. The attribute data management method according to claim 1,
Individual management flag information indicating whether or not attribute point data is associated is set in the attribute point data, the attribute point data is registered in the point data file, and all the individual management flag information of the registered attribute point data Management flag information indicating whether or not is valid in the point data file,
At the time of attribute search, if the management flag information is valid, an inclusion determination is made as to whether or not the input search coordinate value is within the closed region, and the first attribute point data is extracted. Perform a match determination process to match and extract attribute point data with the same coordinate key as the coordinate key of the attribute point data,
If the management flag information is invalid, it is determined whether or not the position coordinates of the attribute point data for which the individual management flag information is invalid belong to a closed region, and if it belongs, the association is performed to validate the individual management flag information. , When all the individual management flag information is validated and the management flag information is validated, the match determination process is performed,
Attribute data management method, characterized by search the associated attribute data by referring to the management flag information. In the attribute data management method according to claim 2,
Individual management flag information indicating whether or not attribute point data is associated is set in the attribute point data, the attribute point data is registered in the point data file, and all the individual management flag information of the registered attribute point data Management flag information indicating whether or not is valid in the point data file,
At the time of attribute search, if the management flag information is valid, a match determination process is performed to perform a match determination between the coordinate value of the figure configuration point of the input graphic and the position coordinate of the attribute point data and extract the attribute point data,
If the management flag information is invalid, it is determined whether or not the position coordinates of the attribute point data for which the individual management flag information is invalid are associated with a figure. And when all the individual management flag information is enabled and the management flag information is enabled, the match determination process is performed.
Attribute data management method, characterized by search the associated attribute data by referring to the management flag information. In the attribute data management method according to claim 1 or 2,
Describe time information in which attribute data exists in the attribute point data,
Using time information as a determination material, associating the attribute point data group exists in a certain period of time, by search the associated attribute data, attribute data, characterized in that get the statistics for a period of time and space Management method.

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