Method for establishing non-material cultural heritage space-time database

Abstract

The application discloses a method for establishing a non-material cultural heritage space-time database, characterized in that, a basic space-time database is first established to arrange time events of the non-material cultural heritage, then a transmission space-time database is established to analyze space information such as a spatial distribution dispersion degree of the non-material cultural heritage at a transmission destination, a spatial transmission distribution feature of the transmission destination and a spatial action feature of the transmission destination, and then a chronicle space-time database is jointly constructed through the space information and the time events. Thus, the relevant chronicle theme information is associated with basic geographic elements, the non-material cultural heritage landscape pattern described in the chronicle can be presented, and the space-time process of cultural transmission and diffusion can be excavated.

Description

[Technical Field]

[0001] This invention relates to the field of database creation methods, and specifically to a method for creating a spatiotemporal database of intangible cultural heritage. [Background Technology]

[0002] As intangible cultural heritage receives increasing attention, research findings are becoming more abundant, and cultural databases have been established in many fields. Based on the study of literature, it has been found that existing cultural databases mainly fall into two categories: cultural databases with local characteristics and thematic databases. However, data models for collecting, storing, and processing cultural data information in terms of time and space are still relatively few. [Summary of the Invention]

[0003] The purpose of this invention is to solve the problems in the background art and provide a method for establishing a spatiotemporal database of intangible cultural heritage.

[0004] The above-mentioned technical objective of the present invention is achieved through the following technical solution:

[0005] A method for establishing a spatiotemporal database of intangible cultural heritage involves first establishing a basic spatiotemporal database to organize the temporal events of intangible cultural heritage, then establishing a dissemination spatiotemporal database to analyze the spatial data such as the spatial dispersion of intangible cultural heritage in dissemination destinations, the spatial dissemination distribution characteristics of dissemination destinations, and the spatial role characteristics of dissemination destinations, and finally constructing a chronological spatiotemporal database of major events by linking spatial data with temporal events.

[0006] This invention establishes a spatiotemporal database of intangible cultural heritage based on spatiotemporal database theory, combining the characteristics of the database with the target user group for research. For a spatiotemporal database based on chronological data, it is even more crucial to grasp the data characteristics; the time points, time periods, location information, and inheritance relationships contained in the chronology are the core considerations of the model. In the organization of attribute data, it is necessary to maintain the original state of the data as much as possible while removing data redundancy to facilitate user querying and research. In the organization of spatiotemporal data, the key is to integrate temporal and spatial information. A location may have multiple time points, and a single time point may have multiple spatial points, i.e., a "one-to-many" relationship. Therefore, temporal and spatial data are stored separately to avoid data clutter.

[0007] The basic spatiotemporal database includes information such as name, event content, time, location, audience, and topic type.

[0008] The propagation spatiotemporal database includes the degree of dispersion of the spatial distribution of propagation destinations, the spatial propagation distribution characteristics of propagation destinations, and the spatial action characteristics of propagation destinations.

[0009] In addition to having attribute fields that include dissemination events, location information, dissemination forms, and dissemination subjects, it is also necessary to clarify the spatial distribution characteristics of intangible cultural heritage in the dissemination destinations and jointly construct a spatiotemporal database of major events through the connection between spatial data and temporal events.

[0010] From a cultural geography perspective, a spatiotemporal database is constructed by selecting a specific time period and considering dimensions such as time, space, audience, and theme. Through the collection, classification, and extraction of basic data (time information extraction, spatial information extraction, and information from different themes), factors related to dissemination paths and influence intensity are identified, establishing a spatiotemporal database for dissemination. This provides support for spatial pattern analysis of intangible cultural heritage diffusion and facilitates model building from a cultural geography research perspective.

[0011] Preferably, ArcGIS spatial analysis tools are used, and the spatial autocorrelation index method is selected to describe the spatial distribution dispersion of the propagation destination; the spatial propagation distribution characteristics of the propagation destination are quantitatively analyzed using the standard error ellipse analysis method, kernel density estimation and other methods; and the spatial action characteristics of the propagation destination city are analyzed through the spatial action function of the propagation destination, thereby establishing a spatiotemporal database.

[0012] Preferably, a spatiotemporal database is established based on the global spatial autocorrelation index method to describe the distribution of intangible cultural heritage dissemination destination city elements. The distribution types are uniform, random, and clustered. The spatial distribution can be quantitatively determined by the Moran's I value of spatial autocorrelation.

[0013] The global spatial autocorrelation index method represents the degree of similarity between points that are spatially adjacent or neighboring. It can determine the spatial clustering characteristics of target points. The calculation formula is as follows:

[0014]

[0015] In the formula: x i x j These represent the number of destination cities in regions i and j, respectively; x is the mean; w ij is a spatial vector matrix, which defines the spatial relationships within the region; n is the total number of samples from the destination cities for the propagation.

[0016] When Moran's I value is positive and significant, the regions exhibit a clustered distribution; conversely, when it is negative, they exhibit a discrete distribution.

[0017] The larger the I value, the higher the degree of spatial autocorrelation. Its value distribution range is [-1, 1]. To test the significance of its spatial distribution correlation, the study uses the Z test. If the Z value is greater than the distribution range, it shows significant clustering, and if it is less than the distribution range, it shows regional dispersion.

[0018] Preferably, standard error elliptic analysis, also known as "directional distribution," is used to analyze the distribution relationships, expansion relationships, and distribution patterns of urban points in the spread of intangible cultural heritage. The major and minor axes of the ellipse represent the directions with the most and least spread, respectively, and the area of ​​the ellipse can represent the discreteness of the spread degree. Combining the central distribution with time-segmented distribution, a distribution model of intangible cultural heritage destination cities is established as follows:

[0019]

[0020] In the formula, u δ The distribution coefficient of destination cities for propagation; δ u denoted as , where is the standard deviation of acceptance levels in each city; u is the average acceptance level in each city; u i Let represent the acceptance level of the i-th city; n is the number of cities.

[0021] In order to analyze the current distribution of destination cities for the dissemination of intangible cultural heritage and explore its spatial characteristics, it is necessary to study its spatial effects. As the distance increases, the intensity of spatial interaction continuously weakens, exhibiting a distance decay effect.

[0022] At the macro and agglomeration levels, assuming other variables remain relatively stable, the role of space is mainly reflected in the relationship between culture and distance.

[0023] The propagation destination space action function can be expressed by the following formula:

[0024]

[0025] In the formula, k is a constant coefficient; G ij P represents the spatial interaction between destinations i and j. i and P j The node attraction between the two regions; d ij Let F(d) be the distance between locations i and j in pixels; ij ) is the distance decay function.

[0026] Compared with the prior art, the beneficial effects of the present invention are:

[0027] 1. This invention establishes a basic spatiotemporal database to organize the temporal events of intangible cultural heritage (ICH). Then, it establishes a dissemination spatiotemporal database to analyze spatial data such as the spatial distribution dispersion length, spatial distribution characteristics, and spatial role characteristics of ICH in dissemination destinations. Finally, by combining spatial data with the connection to temporal events, a chronological spatiotemporal database of major events is constructed. This links relevant chronological thematic information with basic geographical elements, revealing the ICH cultural landscape patterns described by the chronology, exploring the spatiotemporal process of cultural dissemination and diffusion, providing support for spatial pattern analysis of ICH cultural diffusion, and facilitating model building from a cultural geography research perspective.

[0028] 2. This invention uses standard error ellipse analysis to analyze the distribution relationships, expansion relationships, and distribution patterns of urban points of intangible cultural heritage dissemination. The major and minor axes of the ellipse represent the directions of the most and least dissemination, respectively, and the area of ​​the ellipse can represent the discreteness of the degree of dissemination.

[0029] 3. This invention analyzes the current distribution of cities as destinations for communication by examining the communication destination action function, explores its spatial action characteristics, and reflects the correlation between culture and distance. [Attached Image Description]

[0030] Figure 1 This is an overall schematic diagram of the present invention.

Implementation Method

[0031] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention.

[0032] This embodiment provides a method for establishing a spatiotemporal database of intangible cultural heritage, such as... Figure 1 As shown, a basic spatiotemporal database is first established to organize the temporal events of intangible cultural heritage. Then, a dissemination spatiotemporal database is established to analyze the spatial information such as the spatial dispersion of intangible cultural heritage in the dissemination destination, the spatial dissemination distribution characteristics of the dissemination destination, and the spatial role characteristics of the dissemination destination. Finally, a chronological spatiotemporal database of major events is constructed by combining spatial information with the connection with temporal events.

[0033] Using ArcGIS spatial analysis tools, the spatial autocorrelation index method was selected to describe the spatial distribution dispersion of propagation destinations; the standard error ellipse analysis method was used to quantitatively analyze the spatial propagation distribution characteristics of propagation destinations; and the spatial action characteristics of propagation destinations were analyzed through the spatial action function of propagation destinations.

[0034] A spatiotemporal database was established based on the global spatial autocorrelation index method to describe the distribution of intangible cultural heritage dissemination destination city elements. The distribution types are uniform, random, and clustered. The spatial distribution can be quantitatively determined by Moran's I value of spatial autocorrelation.

[0035] The global spatial autocorrelation index method represents the degree of similarity between points that are spatially adjacent or neighboring. It can determine the spatial clustering characteristics of target points. The calculation formula is as follows:

[0036]

[0037] In the formula: x i x j These represent the number of destination cities in regions i and j, respectively; x is the mean; w ij is a spatial vector matrix, which defines the spatial relationships within the region; n is the total number of samples from the destination cities for the propagation.

[0038] When Moran's I value is positive and significant, the regions exhibit a clustered distribution; conversely, when it is negative, they exhibit a discrete distribution.

[0039] The larger the I value, the higher the degree of spatial autocorrelation. Its value distribution range is [-1, 1]. To test the significance of its spatial distribution correlation, the study uses the Z test. If the Z value is greater than the distribution range, it shows significant clustering, and if it is less than the distribution range, it shows regional dispersion.

[0040] The standard error elliptic analysis method was used to analyze the urban points of intangible cultural heritage dissemination. Standard error elliptic analysis can be used to analyze the distribution relationships, expansion relationships, and distribution patterns of urban points. The major and minor axes of the ellipse represent the directions of maximum and minimum dissemination, respectively, and the area of ​​the ellipse represents the discreteness of the dissemination degree. A distribution model of intangible cultural heritage dissemination destination cities was established by combining the central distribution with time-series analysis as follows:

[0041]

[0042] In the formula, u δ The distribution coefficient of destination cities for propagation; δ u denoted as , where is the standard deviation of acceptance levels in each city; u is the average acceptance level in each city; u i Let represent the acceptance level of the i-th city; n is the number of cities.

[0043] The propagation destination space action function can be expressed by the following formula:

[0044]

[0045] In the formula, k is a constant coefficient; G ijP represents the spatial interaction between destinations i and j. i and P j The node attraction between the two regions; d ij Let F(d) be the distance between locations i and j in pixels; ij ) is the distance decay function.

[0046] The data in this study mainly includes the number of cities and their geographical coordinates as destinations for the dissemination of intangible cultural heritage, as well as the time, methods, and source groups of dissemination. This type of data was mainly obtained from biographies of various individuals, newspaper articles, periodicals, and by contacting relevant cultural institutions at home and abroad. Spatial data was obtained from Natural Earth Data.

[0047] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for establishing a spatiotemporal database of intangible cultural heritage, characterized in that, First, a basic spatiotemporal database is established to organize the temporal events of intangible cultural heritage. Then, a dissemination spatiotemporal database is established to analyze the spatial data such as the spatial distribution dispersion of intangible cultural heritage in the dissemination destination, the spatial dissemination distribution characteristics of the dissemination destination, and the spatial role characteristics of the dissemination destination. Finally, a chronological spatiotemporal database of major events is constructed by combining spatial information with the connection with temporal events. Using ArcGIS spatial analysis tools, the spatial autocorrelation index method was selected to describe the spatial distribution dispersion of propagation destinations; the standard error ellipse analysis method was used to quantitatively analyze the spatial propagation distribution characteristics of propagation destinations; and the spatial action characteristics of propagation destinations were analyzed through the spatial action function of propagation destinations. A spatiotemporal database was established based on the global spatial autocorrelation index method to describe the distribution of intangible cultural heritage dissemination destination city elements. The distribution types are uniform, random and clustered. The spatial distribution is quantitatively determined by the Moran's I value of spatial autocorrelation. The global spatial autocorrelation index method represents the degree of similarity between points that are spatially adjacent or neighboring, and is used to determine the spatial clustering characteristics of target points. The calculation formula is as follows: ； In the formula: , These represent the number of destination cities for propagation in regions i and j, respectively. The mean; is a spatial vector matrix, which defines the spatial relationships within the region; n is the total number of samples from the destination cities of the propagation. When Moran's I value is positive and significant, the regions exhibit a clustered distribution; conversely, they exhibit a discrete distribution. The larger the Moran's I value, the higher the degree of spatial autocorrelation. Its value distribution range is [-1, 1]. To test the significance of its spatial distribution correlation, the study uses the Z test. If the Z value is greater than the distribution range, it shows significant clustering; otherwise, the regions are dispersed. The standard error elliptic analysis method was used to analyze the urban points of intangible cultural heritage dissemination. This method is employed to analyze the distribution relationships, expansion relationships, and distribution patterns of these urban points. The major and minor axes of the ellipse represent the directions of maximum and minimum dissemination, respectively, and the area of ​​the ellipse represents the dispersion of the dissemination degree. Based on the central distribution and time-segmented analysis, a distribution model of intangible cultural heritage dissemination destination cities was established as follows: ； In the formula, To disseminate the distribution coefficient of destination cities; The standard deviation of acceptance levels in each city; This represents the average acceptance level across all cities. For the first The acceptance level in each city; n is the number of cities; The propagation destination space action function is expressed by the following formula: ； In the formula, k is a constant coefficient; This represents the spatial interaction between destinations i and j. and To enhance the attractiveness of nodes in both regions; The distance in pixels between locations i and j; This is the distance decay function.

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