Multi-source heterogeneous data integration analysis treatment method, system, equipment and medium

Abstract

The invention discloses a multi-source heterogeneous data integration analysis treatment method, system and device and a medium, and the method comprises the steps: obtaining multi-source heterogeneous original data, carrying out the semantic mapping through a power grid business ontology library, and carrying out the coordinate dynamic normalization through a self-adaptive conversion matrix, and obtaining standardized spatial data; carrying out spatial query, dynamic buffer area calculation and protection area grading fusion through a spatial superposition optimization algorithm, and carrying out topological relation identification and regularization processing on the power line and an external linear ground feature to obtain a spatial conflict analysis result; through a three-level conflict resolution mechanism, recognition and cooperative resolution operation of geometry, attribute and temporal conflicts are carried out, and a resolved compliance space data set is obtained; and performing governance flow driving and rule adaptation through a dynamic business rule engine to obtain a spatial data governance report. According to the method, efficient integration and intelligent treatment of spatial data in the power transmission line project are realized, the data processing timeliness is remarkably improved, and spatial conflicts are eliminated.

Description

Technical Field

[0001] This invention relates to the field of power system information technology, and in particular to a method, system, equipment and medium for integrating, analyzing and managing multi-source heterogeneous data. Background Technology

[0002] With the deepening reform of the natural resource management system and the integration and optimization of institutional functions, the management responsibilities of the former land, planning, forestry, and power departments have been gradually unified into the natural resource management system. Against this backdrop, achieving cross-departmental, cross-domain, and cross-system data fusion and business collaboration has become a core foundation for supporting the "one map" management of natural resources, project site selection and alignment, planning decisions, and administrative approvals. However, under the long-term decentralized management model, each department has developed its own independent technical system in terms of data standards, surveying benchmarks, format specifications, and storage management, accumulating a large amount of heterogeneous, isolated, and version-chaotic data resources. These historical legacy issues severely restrict the efficient utilization of data and the efficiency of business collaboration, becoming a key bottleneck that urgently needs to be addressed in the current transformation and upgrading of natural resource informatization towards intelligence and integration. Summary of the Invention

[0003] In view of the aforementioned existing problems, the present invention is proposed.

[0004] Therefore, this invention provides a method, system, device, and medium for integrating, analyzing, and governing multi-source heterogeneous data to solve the problems of existing data governance methods, such as mutually exclusive data semantics, inconsistent coordinates, diverse formats, information silos, missing associations, and delayed updates, which make it difficult to achieve effective sharing and business collaboration.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, the present invention provides a method for integrating, analyzing, and managing multi-source heterogeneous data, including: Obtain multi-source heterogeneous raw data, perform semantic mapping through the power grid business ontology library, and perform dynamic coordinate normalization through an adaptive transformation matrix to obtain standardized spatial data; Based on standardized spatial data, spatial query, dynamic buffer calculation and protection zone hierarchical fusion are performed through spatial overlay optimization algorithm, as well as topological relationship identification and regularization processing of power lines and external linear features, to obtain spatial conflict analysis results; Based on the spatial conflict analysis results, a three-level conflict resolution mechanism is used to identify and collaboratively resolve geometric, attribute, and temporal conflicts, resulting in a compliant spatial dataset after resolution. Based on the resolved compliant spatial dataset, a spatial data governance report is obtained by driving the governance process and adapting the rules through a dynamic business rule engine.

[0006] As a preferred embodiment of the multi-source heterogeneous data integration, analysis, and governance method described in this invention, the spatial overlay optimization algorithm includes: By constructing a specific spatial index structure, a fast range query can be performed on the patch data; Power-specific operators are used to calculate the safe clearance between transmission lines and ecologically sensitive areas and to integrate ecological red lines. Based on the conflict marking logic, specific areas are marked, and the avoidance layer data containing the conflict location and range is output.

[0007] The beneficial effects of this preferred technical solution are that it effectively improves the automation level and processing efficiency of multi-source spatial data fusion and conflict identification in the power line selection process, and enhances the compliance and feasibility of the planning scheme.

[0008] As a preferred embodiment of the multi-source heterogeneous data integration, analysis, and governance method described in this invention, the power-specific operator includes: The safety distance parameters around the transmission line towers are determined based on the voltage level, and a dynamic buffer zone is generated. Spatial integration processing is carried out on ecological protection areas and power facilities, and integration weights are set according to the control level of ecological protection areas to generate continuous and complete protection boundaries. Spatial overlay analysis is performed on the dynamic buffer and the fused protection boundary to identify spatial conflict areas between them.

[0009] As a preferred embodiment of the multi-source heterogeneous data integration, analysis, and governance method described in this invention, the conflict marking logic includes: When the designated area and the forest protection area have spatial overlap, and the degree of overlap exceeds the preset area threshold, it is marked as a red conflict area; When a power transmission line intersects with an ecological protection zone and the intersection angle is less than a preset angle threshold, it is marked as a yellow warning area. The intersection angle is determined by calculating the angle between the transmission line route and the normal vector of the protected area boundary, and the smallest angle is selected at multiple intersection points of the polygon as the basis for judgment.

[0010] As a preferred embodiment of the multi-source heterogeneous data integration, analysis, and governance method described in this invention, the topological relationship identification and regularization processing between power lines and external linear features includes: Spatial relationship prediction is performed on standardized power line data and external linear feature data to identify spatially intersecting sections and adjacent sections that are close to each other but do not intersect. The location of the intersection point between the power line and external linear features in space is determined by geometric calculation, and the angle between the two at the intersection point is calculated. The included angle is judged for compliance according to the power engineering design specifications. When the included angle is less than the preset angle threshold, the current intersection point is marked as a high-risk intersection point. The attribute information of high-risk intersections is included in the spatial conflict set and summarized in a unified manner with other types of conflicts to obtain the spatial conflict analysis results.

[0011] As a preferred embodiment of the multi-source heterogeneous data integration, analysis, and governance method described in this invention, the three-level conflict resolution mechanism includes: Identify geometric conflicts between transmission lines and prohibited construction zones, and perform three-dimensional spatial avoidance corrections for intersections; Compare the land category attributes of the same geographical area in different data sources, identify attribute conflicts, and assign attribute values ​​according to preset rules; Verify the update time in the data metadata, identify temporal conflicts caused by version expiration, and mark them as pending updates; The conflict tree model is used to prioritize multiple concurrent conflicts, determine the conflict processing order, and perform automatic repair operations on each conflict in the order to obtain a compliant space dataset after resolution.

[0012] The beneficial effects of this preferred technical solution are that by identifying and coordinating the processing of three types of spatial conflicts—geometric, attribute, and temporal—and combining them with a conflict tree model for priority sorting and automatic repair, it achieves the systematic resolution of multi-source power spatial data conflicts, significantly improves the automation level, processing efficiency, and compliance of data governance, and effectively ensures the accuracy and reliability of power grid planning and construction.

[0013] As a preferred embodiment of the multi-source heterogeneous data integration, analysis, and governance method described in this invention, the conflict tree model includes: Construct a tree-like decision structure with geometric conflicts, attribute conflicts, and temporal conflicts as nodes; Set the processing priority for each conflict type, with geometric conflicts having the highest priority and temporal conflicts having the lowest priority. When multiple conflicts occur simultaneously, the tree structure is traversed layer by layer according to priority, triggering the corresponding conflict resolution operation.

[0014] Secondly, the present invention provides a multi-source heterogeneous data integration, analysis and governance system, comprising: The data standardization module is used to acquire multi-source heterogeneous raw data, perform semantic mapping through the power grid business ontology library, and perform dynamic coordinate normalization through an adaptive transformation matrix to obtain standardized spatial data. The spatial conflict analysis module is used to perform spatial queries, dynamic buffer calculations and protection zone hierarchical fusion based on standardized spatial data through spatial overlay optimization algorithms, as well as topological relationship identification and regularization processing of power lines and external linear features, to obtain spatial conflict analysis results. The conflict collaborative resolution module is used to identify and collaboratively resolve geometric, attribute, and temporal conflicts based on spatial conflict analysis results through a three-level conflict resolution mechanism, resulting in a compliant spatial dataset after resolution. The governance process-driven module is used to generate a spatial data governance report by driving the governance process and adapting rules based on the dissolved compliant spatial dataset through a dynamic business rule engine.

[0015] Thirdly, the present invention provides an electronic device, comprising: Memory, used to store programs; A processor is configured to execute the computer-executable instructions, which, when executed by the processor, implement the steps of the multi-source heterogeneous data integration, analysis and governance method.

[0016] Fourthly, the present invention provides a computer-readable storage medium, comprising: when the program is executed by a processor, the steps of implementing the multi-source heterogeneous data integration, analysis and governance method.

[0017] The beneficial effects of this invention are as follows: This invention utilizes power-specific operators to dynamically calculate the safety clearance between transmission lines and ecologically sensitive areas, and integrates ecological red line classifications. This achieves the coordinated expression of power engineering constraints and ecological protection requirements, reducing the fragmentation of protected areas. Furthermore, by applying conflict marking logic to classify overlapping areas and small-angle intersections of the "three zones and three lines" into red and yellow categories, it achieves intelligent identification and risk classification early warning of spatial conflicts, improving the accuracy of route selection compliance judgment. Through a three-level conflict resolution mechanism, it identifies and collaboratively processes geometric, attribute, and temporal conflicts, and combines a conflict tree model for priority ranking and automatic repair, achieving systematic and automated resolution of multi-source heterogeneous spatial data conflicts and outputting a compliant spatial dataset. Finally, by integrating Southern Power Grid specifications into a dynamic business rule engine and supporting external rule access and automatic re-inspection, it achieves flexible configuration and continuous compliance verification of governance rules, improving the adaptability and scalability of the spatial data governance process. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein: Figure 1 This is a basic flowchart illustrating a multi-source heterogeneous data integration, analysis, and governance method provided in one embodiment of the present invention. Detailed Implementation

[0019] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0020] Example 1, referring to Figure 1 As an embodiment of the present invention, a method for integrating, analyzing, and managing multi-source heterogeneous data is provided, comprising: S100: Acquire multi-source heterogeneous raw data, perform semantic mapping through the power grid business ontology library, and perform dynamic coordinate normalization through an adaptive transformation matrix to obtain standardized spatial data; S200: Based on standardized spatial data, spatial query, dynamic buffer calculation and protection zone hierarchical fusion are performed through spatial overlay optimization algorithm, as well as topological relationship identification and regularization processing of power lines and external linear features to obtain spatial conflict analysis results; S300: Based on the spatial conflict analysis results, a three-level conflict resolution mechanism is used to identify and collaboratively resolve geometric, attribute, and temporal conflicts, resulting in a compliant spatial dataset after resolution. S400: Based on the resolved compliant spatial dataset, a spatial data governance report is obtained through a dynamic business rule engine that drives the governance process and adapts the rules.

[0021] It should be noted that existing data governance methods face a series of challenges during operation, including difficulties in merging multi-source heterogeneous data due to inconsistent coordinate systems and semantic standards; low spatial indexing efficiency that cannot support real-time queries of millions of map features; lack of a spatial analysis mechanism driven by power business rules, making it impossible to automatically identify geometric conflicts and attribute contradictions between transmission lines and ecological protection red lines and prohibited construction areas; conflict identification relies on manual interpretation and lacks quantitative marking logic, making it difficult to achieve red and yellow graded early warning; lack of systematic means to resolve differences in land use attributes and outdated metadata from different sources, leading to frequent attribute conflicts and timeliness deviations; and rigid and outdated governance rules that are difficult to dynamically adapt to constantly changing external control requirements such as land and forestry, resulting in low automation, long cycles, and weak compliance assurance capabilities in the overall governance process.

[0022] Therefore, addressing the problems of mutually exclusive data semantics, inconsistent coordinates, diverse formats, information silos, missing associations, and delayed updates in existing data governance methods, which hinder effective sharing and business collaboration, this paper proposes a collaborative technical system through steps S100-S400. This system comprises an R* tree index, power-specific operators, conflict marking logic, a three-level conflict resolution mechanism, and a dynamic business rule engine. This system achieves efficient indexing of multi-source heterogeneous spatial data, rule-driven topology fusion, hierarchical conflict identification, and automated conflict resolution. It effectively solves problems in traditional data governance such as inconsistent coordinates, semantic inconsistencies, reliance on manual conflict identification, and difficulty in collaboratively handling multiple types of conflicts. This significantly improves the automation level, processing efficiency, and compliance assurance capabilities of power engineering spatial data governance, ultimately outputting high-quality compliant spatial datasets and governance reports, providing accurate and reliable data support for intelligent site selection and alignment in the power grid.

[0023] Example 2, this is an embodiment of the present invention, which provides a method for integrating, analyzing and managing multi-source heterogeneous data based on the previous embodiment, including: In this embodiment of the application, step S100 involves acquiring multi-source heterogeneous raw data from different management departments such as land, planning, forestry, and power. The raw data includes, but is not limited to, geographic information data formats such as DWG, SHP, and GeoJSON.

[0024] In this embodiment, step S100 uses a power grid business ontology library to perform semantic mapping processing on the multi-source heterogeneous raw data. The power grid business ontology library is a knowledge model for spatial data governance in power engineering, containing semantic correspondences between power facility elements (such as poles, lines, and substations) and external geographical elements (such as ecological protection red lines, basic farmland, and forest land). Through this ontology library, field names and definitions in data from different departments are mapped to a unified semantic system, achieving semantic consistency alignment across departmental data.

[0025] In this embodiment, step S100 involves constructing an adaptive transformation matrix to dynamically normalize the data's coordinates. The adaptive transformation matrix can parse data metadata, automatically identify its coordinate system type (including WGS-84, Beijing 54 coordinate system, or CGCS2000 coordinate system), and construct corresponding coordinate transformation models based on standard transformation parameters, uniformly transforming all data to the CGCS2000 national geodetic coordinate system. After semantic mapping and coordinate normalization, a standardized spatial dataset with unified structure, consistent semantics, and the same coordinate reference is generated, providing a high-quality data foundation for subsequent spatial overlay analysis, conflict identification, and collaborative resolution.

[0026] In this embodiment of the application, the coordinate system offset correction in step S100 includes constructing an adaptive transformation matrix, performing coordinate normalization processing on multi-source data, automatically identifying and unifying different coordinate systems such as WGS-84, Beijing 54, and CGCS2000 to CGCS2000, and correcting local offsets of up to 3.2 meters.

[0027] In an optional implementation, the coordinate system offset correction in step S100 can also be achieved by selecting known high-precision GNSS measured points as control points, matching the corresponding positions in multi-source data, constructing a least-squares affine transformation model, solving for translation, rotation and scaling parameters, and performing local geometric correction on the offset patches to achieve coordinate unification.

[0028] In an optional implementation, the coordinate system offset correction in step S100 can also be achieved by constructing a graph neural network (GNN) or a convolutional neural network (CNN), inputting the geometric features and metadata of multi-source patches, training the model to learn the regional offset rules, predicting the offset vector of each patch and automatically compensating, thereby realizing end-to-end coordinate correction.

[0029] In this embodiment of the application, the semantic inconsistency handling in step S100 includes constructing a power grid business ontology library to perform semantic mapping and alignment on fields in data from different sources such as "three zones and three lines" and "forest protection areas," thereby achieving a unified expression of multi-source heterogeneous data on key concepts such as ecological protection red lines and prohibited construction areas.

[0030] In an optional implementation, the semantic inconsistency handling in step S100 can also be achieved by using models such as Word2Vec or BERT to convert the field names in each data source into vectors, calculating their cosine similarity with standard terms, and determining them as synonyms when they exceed a preset threshold, thereby achieving automatic semantic alignment without the need for ontology support.

[0031] In an optional implementation, the semantic inconsistency processing in step S100 can also perform pattern recognition on the field names in each data source by pre-setting a series of regular expression rules, such as automatically mapping the field matching ".*ecology.*red.line." to "ecological protection red line", thereby achieving fast semantic alignment based on text features.

[0032] In this embodiment of the application, the spatial overlay optimization algorithm in step S200 includes: By constructing a specific spatial index structure, a fast range query can be performed on the patch data; Power-specific operators are used to calculate the safe clearance between transmission lines and ecologically sensitive areas and to integrate ecological red lines. Based on the conflict marking logic, specific areas are marked, and the avoidance layer data containing the conflict location and range is output.

[0033] In this embodiment, the specific spatial index structure is an R-tree, whose nodes organize the map data using the Minimum Bounding Rectangle (MBR), supporting efficient insertion and range queries for millions of map patches. During index construction, a dynamic insertion optimization algorithm is introduced, prioritizing node splitting based on the least overlap and least area growth direction, avoiding the large number of empty nodes generated by traditional quadtrees under irregular map patch distributions. For the spatial relationship query requirements of linear features (such as transmission lines) and areal features (such as protected areas) commonly found in power grid planning, a spatial query mechanism based on MBR pre-screening is set up, reducing the query response time from the average of 2.4 seconds for traditional quadtrees to 0.8 seconds, improving efficiency by more than 3 times. The R-tree index supports parallel construction and incremental updates, making it suitable for scenarios with continuous access to multi-source heterogeneous data.

[0034] In this embodiment of the application, the spatial conflict detection in step S200 includes accelerating the query of millions of map patches by constructing an R* tree index, combining power-specific operators for dynamic buffer analysis and weighted Voronoi fusion, performing spatial overlay analysis on transmission lines and prohibited construction areas, identifying overlapping areas and small-angle intersections, and achieving efficient and accurate conflict detection.

[0035] In an optional implementation, spatial conflict detection in step S200 can also be achieved by dividing the study area into multi-level grid units, using quadtree structure index patches and line data, and performing spatial overlay calculations only within intersecting grids, thereby realizing rapid location and efficient detection of conflict areas.

[0036] In an optional implementation, spatial conflict detection in step S200 can also be achieved by loading transmission line and multi-source patch data into GPU memory and using CUDA to perform massive spatial overlay and cross-judgment operations in parallel, thereby achieving a second-level response for detecting millions of patch conflicts.

[0037] In this embodiment of the application, the power-specific operator in step S200 includes: The safety distance parameters around the transmission line towers are determined based on the voltage level, and a dynamic buffer zone is generated. Spatial integration processing is carried out on ecological protection areas and power facilities, and integration weights are set according to the control level of ecological protection areas to generate continuous and complete protection boundaries. Spatial overlay analysis is performed on the dynamic buffer and the fused protection boundary to identify spatial conflict areas between them.

[0038] In this embodiment, spatial fusion processing refers to a method for prioritizing the fusion of spatial boundaries between ecological protection areas and power facilities based on a weighted spatial partitioning principle. Specifically, ecological protection areas are assigned corresponding weight values ​​according to their management and control levels; the higher the management and control level, the greater the weight. Using the location of power facilities and the boundary of the ecological protection area as generators, the weighted distances from each point within the study area to different generators are calculated, and each point is assigned to the area with the smallest weighted distance, thereby forming a fusion boundary with priority differences. This method prioritizes the preservation of the spatial morphology of high-weight areas during boundary generation, effectively avoiding the problems of boundary fragmentation and overlapping after the superposition of multiple source protection areas, and generating a continuous, complete, and comprehensive protection boundary that conforms to the priority order of ecological protection. Preferably, the spatial fusion processing is implemented using a weighted Voronoi diagram algorithm, which can accurately reflect the differences in spatial influence of different management and control areas, improving the scientific nature and engineering applicability of the fusion results.

[0039] In this embodiment, the weight values ​​in the weighted Voronoi diagram are not statically set, but dynamically configured based on the protection priorities of power facilities and ecologically sensitive areas. Specifically, "substations" are assigned the highest weight of 1.0, indicating they are immovable core facilities; "Level I ecological red lines" are assigned a weight of 0.9, reflecting their high ecological protection value; "Level II ecological red lines" are assigned a weight of 0.5, reflecting moderate constraint intensity; and "basic farmland" is assigned a weight of 0.3, balancing farmland protection with engineering construction feasibility. During the fusion process, the priority order is clearly defined as [substations → Level I red lines → Level II red lines], and areas with a map patch area less than 500 m² are automatically merged to prevent geometric fragmentation caused by small patches and improve the continuity and readability of the spatial analysis results.

[0040] In this embodiment, the dynamic buffer is generated based on the following formula: Buffer = Basic safety distance + Voltage level coefficient × 5m The "basic safety distance" is 10m for 110kV lines, 15m for 220kV lines, and 20m for 500kV lines. The "voltage level coefficient" is automatically obtained by the system after identifying the line voltage level and looking up a table, with a value range of [0.8, 1.2], used to compensate for the influence of terrain undulations and meteorological conditions. "5m" is an environmental disturbance correction item, taking into account the temporary land occupation and vegetation disturbance range during construction. This dynamic buffer model supports custom parameter templates according to project type, ensuring that the safety distance calculation under different projects is compliant and adaptable.

[0041] In this embodiment of the application, the conflict marking logic in step S200 includes: When the designated area and the forest protection area have spatial overlap, and the degree of overlap exceeds the preset area threshold, it is marked as a red conflict area; When a power transmission line intersects with an ecological protection zone and the intersection angle is less than a preset angle threshold, it is marked as a yellow warning area. The intersection angle is determined by calculating the angle between the transmission line route and the normal vector of the protected area boundary, and the smallest angle is selected as the criterion at multiple intersection points of the polygon.

[0042] In this application embodiment, the designated area is the "three zones and three lines," namely, the ecological space, agricultural space, and urban space clearly delineated by the state in the national land space planning, as well as their corresponding ecological protection red lines, permanent basic farmland protection red lines, and urban development boundaries. These are important legal bases for implementing land use control and ecological protection. When this area spatially overlaps with a forest protection area, and the overlapping area exceeds a preset area threshold, it indicates a significant spatial control conflict, which may involve the dual constraints of the ecological protection red line and the forest protection scope. Therefore, it is marked as a red conflict area and strictly controlled as a prohibited construction zone to prevent power transmission line projects from illegally encroaching on important ecological function zones.

[0043] In this embodiment, the avoidance layer data generated by the conflict marking logic includes two types of spatial elements: the red area represents the "prohibited construction zone," whose attribute fields include "conflict type = overlap," "overlapping area," and "involved patch ID." When the spatial overlap area between the "three zones and three lines" and the forest protection area exceeds a preset area threshold (area > threshold 5%), a red conflict marker is triggered, generating the corresponding prohibited construction zone element. The yellow area represents the "restricted construction zone," whose attribute fields include "intersection angle," "line number," and "suggested avoidance direction." When a transmission line intersects with an ecological protection area and the minimum intersection angle is less than a preset angle threshold (angle < 30°), a yellow warning marker is triggered, generating the corresponding restricted construction zone element. All marking results are output in GeoJSON format with a unique conflict ID for subsequent use by the three-level conflict resolution module. Furthermore, this avoidance layer data supports spatial overlay with the original transmission line data to form a visualized conflict map, facilitating manual review and decision support.

[0044] In this embodiment of the application, the topological relationship identification and regularization processing between power lines and external linear features in step S200 includes: Spatial relationship prediction is performed on standardized power line data and external linear feature data to identify spatially intersecting sections and adjacent sections that are close to each other but do not intersect. The location of the intersection point between the power line and external linear features in space is determined by geometric calculation, and the angle between the two at the intersection point is calculated. The included angle is judged for compliance according to the power engineering design specifications. When the included angle is less than the preset angle threshold, the current intersection point is marked as a high-risk intersection point. The attribute information of high-risk intersections is included in the spatial conflict set and summarized in a unified manner with other types of conflicts to obtain the spatial conflict analysis results.

[0045] In this embodiment of the application, the processing adopts the improved Bentley-Ottmann algorithm to efficiently detect the spatial intersection of power lines with protected areas or external linear features, thereby improving the calculation accuracy in complex scenarios. The rule-based decision-making logic is integrated into the `validate_power_rules()` function, which contains two core rules: Cross angle ≥ 30° (return False if less than 30°); The clearance height difference is ≥15 meters (if it is less than 15 meters, it is considered a real conflict). The conflict results are processed quickly through a dynamic indexing optimization mechanism, which reduces the efficiency of detecting massive line segment-level conflicts from 6 hours to 8 minutes, demonstrating the practicality of the project. All conflict markers are accompanied by a unique conflict ID, which facilitates linkage with subsequent modules and forms a closed-loop management system.

[0046] In this embodiment of the application, the three-level conflict resolution mechanism in step S300 includes: Identify geometric conflicts between transmission lines and prohibited construction zones, and perform three-dimensional spatial avoidance corrections for intersections; Compare the land category attributes of the same geographical area in different data sources, identify attribute conflicts, and assign attribute values ​​according to preset rules; Verify the update time in the data metadata, identify temporal conflicts caused by version expiration, and mark them as pending updates; The conflict tree model is used to prioritize multiple concurrent conflicts, determine the conflict processing order, and perform automatic repair operations on each conflict in the order to obtain a compliant space dataset after resolution.

[0047] In this embodiment of the application, the conflict tree model in step S300 includes: Construct a tree-like decision structure with geometric conflicts, attribute conflicts, and temporal conflicts as nodes; Set the processing priority for each conflict type, with geometric conflicts having the highest priority and temporal conflicts having the lowest priority. When multiple conflicts occur simultaneously, the tree structure is traversed layer by layer according to priority, triggering the corresponding conflict resolution operation.

[0048] In this embodiment of the application, the conflict priority processing in step S300 includes constructing a conflict tree model with geometric conflict as the root node, attribute conflict as the intermediate node, and temporal conflict as the leaf node, and traversing layer by layer according to the priority order of "geometric conflict > attribute conflict > temporal conflict" to trigger the corresponding resolution operation, thereby realizing the orderly automatic processing of multiple types of conflicts.

[0049] In an optional implementation, the conflict priority processing in step S300 can also be achieved by assigning basic weights of 10 points, 6 points, and 3 points to geometric conflicts, attribute conflicts, and temporal conflicts, respectively, and calculating a comprehensive score in combination with factors such as conflict area and voltage level, and determining the processing order by arranging them in descending order of total score, thereby realizing the quantitative sorting and priority processing of multi-dimensional conflicts.

[0050] In an optional implementation, the conflict priority handling in step S300 can also be achieved by defining a conflict handling process in a process engine such as Drools or Activiti, setting rules such as "if there is a geometric conflict, the avoidance correction will be performed first, and then the attribute conflict handling will be entered", so as to realize the visual orchestration, condition judgment and automated scheduling of the conflict resolution process.

[0051] In this embodiment, a three-level conflict resolution mechanism is used to systematically identify and collaboratively process various conflicts generated during the fusion of power spatial data. It detects the spatial relationship between transmission lines and prohibited construction zones, which include legally binding spatial areas such as ecological protection red lines, permanent basic farmland, and forest protection zones defined by the "Three Zones and Three Lines" policy. When the transmission line path spatially overlaps with or crosses these areas, it is determined to be a geometric conflict, and a three-dimensional spatial avoidance correction process is initiated. Physical avoidance is achieved by adjusting the line's alignment or elevation, ensuring that the engineering plan meets spatial avoidance requirements.

[0052] In this embodiment of the application, a comparative analysis is performed on the problem of inconsistent land use attributes in different data sources for the same geographical area. The land use attributes refer to land use classification information published by natural resources, forestry or planning departments, such as "forest land" and "unused land". When the same plot of land is assigned different attributes in different sources of data, it is determined to be an attribute conflict. The system assigns unified values ​​to conflicting attributes according to pre-configured rules and logic to ensure that the final adopted attributes meet the compliance requirements of the national land space planning.

[0053] In this embodiment of the application, the metadata of the input data is verified, with a focus on checking its update time field. When it is found that the update time of a certain data source is significantly lagging behind the latest released version, it is determined to be a temporal conflict caused by the expiration of the version, and the data and its related elements are marked as pending update, prompting that data synchronization is required in the future to ensure the timeliness of the governance results.

[0054] In this embodiment, a conflict tree model is constructed as the decision structure for conflict resolution. This model uses geometric conflicts, attribute conflicts, and temporal conflicts as nodes, forming a tree-like logical architecture. Geometric conflicts are given the highest priority due to their direct impact on engineering feasibility, followed by attribute conflicts, while temporal conflicts, as data quality issues, are given the lowest priority. When multiple conflicts coexist, the system traverses the tree structure layer by layer according to priority, triggering corresponding automatic repair operations in sequence to ensure that critical conflicts are resolved first. Finally, after all conflicts are identified, sorted, and processed, a complete, consistent, and compliant spatial dataset is generated, serving as the foundational data output for subsequent power grid planning and design.

[0055] In this embodiment, in step S400, the dynamic business rule engine is used to transform power industry standards and specifications into configurable, scalable, and maintainable digital rule sets, enabling dynamic management of business logic during the spatial data compliance verification process. This engine supports parsing and mapping national or local power grid construction technical standards, such as the "Technical Specification for Transmission Line Design of China Southern Power Grid Company" (Q / CSG 1204043-2021), into executable rule expressions within the system in a structured manner, thereby avoiding the problems of poor flexibility and high maintenance costs caused by hard coding.

[0056] In this embodiment, rules are defined in a standardized XML format, including elements such as rule sets, individual rules, parameter configurations, exceptions, and actions. For example, in a rule set named "PowerLine_Safety," a rule with the ID "VOLTAGE_BUFFER" is defined to control the minimum safe distance between transmission lines and surrounding sensitive areas. This rule sets different minimum distances based on different voltage levels: 15 meters for 500kV lines and 10 meters for 220kV lines. The rule also includes an exception mechanism: when the slope is greater than 25°, the minimum distance is automatically multiplied by 1.5 to accommodate safety requirements in complex terrain. Such rules can be directly loaded into the system via configuration files, allowing rule changes without code modification, significantly improving system adaptability and operational efficiency.

[0057] In this embodiment, the dynamic business rule engine supports integration and real-time synchronization with external third-party rule bases. It can dynamically acquire the latest control policies and spatial constraints issued by forestry departments, natural resource management departments, and other agencies, such as forest protection areas, boundaries of ecologically sensitive areas, and permanent basic farmland. When these external rules are updated, the system can automatically identify and refresh the local rule base, ensuring that the compliance standards used in power engineering site selection and route planning are always up-to-date and meet national spatial governance requirements such as the "Three Zones and Three Lines" policy. This invention, by constructing a dynamic business rule engine based on configurable rules, achieves flexible embedding and efficient execution of power industry standards, improves the automation level and policy responsiveness of spatial data compliance analysis, and is suitable for intelligent planning and decision support scenarios in multi-source heterogeneous data environments.

[0058] Example 3, referring to Table 1, is an embodiment of the present invention. This embodiment provides a method for integrating, analyzing and managing multi-source heterogeneous data. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through specific implementation methods and implementation effects.

[0059] The specific details of this embodiment are as follows: I. Experimental Environment This embodiment constructs a multi-source heterogeneous spatial data integration, analysis, and governance system based on the actual construction needs of the Yunnan power grid's 500kV transmission line project. The hardware environment used in the experiment included: a server configured with an Intel Xeon Gold 6248R processor, 256GB of RAM, and 2TB of SSD storage; a CentOS 7.9 operating system; a GIS platform running in parallel on both ArcGIS Pro 3.0 and QGIS 3.28 platforms; and a database using PostgreSQL 14 + PostGIS 3.3 spatial extension.

[0060] The data used in the experiment came from different management departments, including land, forestry, and electricity, specifically including: 1. Three-zone, three-line data: The format is Shapefile, with a total of 1.2 million map features. The original coordinate system is CGCS2000, and there is a local coordinate offset problem (maximum offset of 3.2 meters). 2. Transmission line CAD data: The format is DWG, containing 17 layers, and there is a problem with some tower attribute fields being missing; 3. Forestry reserve data: The format is GeoJSON, with a total of 450,000 map patches. The metadata shows that the version was last updated in Q2 2023, which is 428 days older than the latest version (Q3 2024).

[0061] All data is uniformly connected to a data governance platform based on a microservice architecture. The platform integrates an R* tree index module, a power-specific operator engine, a conflict tree model, and a dynamic business rule engine, supporting automated processing orchestration and result visualization.

[0062] II. Experimental Procedure 1. Data standardization processing First, semantic alignment and coordinate normalization were performed on the multi-source heterogeneous data. The power grid business ontology library was used to semantically map key fields such as "three zones and three lines," "forest protection areas," and "line corridors," ensuring consistency in concepts like "ecological protection red lines" and "prohibited construction zones" across different departments. Subsequently, an adaptive transformation matrix was used to uniformly transform all data to the CGCS2000 coordinate system, and local corrections were performed on offset patches to eliminate coordinate deviations of up to 3.2 meters, generating a standardized spatial dataset.

[0063] 2. Spatial Overlay Optimization Analysis An R* tree spatial index was constructed to enable fast range queries on 1.2 million map patches, supporting large-scale spatial retrieval with millisecond-level response. Power-specific operators were applied for safety clearance calculation: a basic safety distance of 20 meters was set based on the line voltage level (500kV), and a dynamic buffer was generated by combining this with terrain disturbance coefficients. Simultaneously, a weighted Voronoi fusion method was used for elements such as ecological protection red lines and forest protection areas, assigning weights according to the control level (0.9 for Level 1 red lines, 0.5 for Level 2 red lines) to generate a continuous and complete comprehensive protection boundary.

[0064] 3. Conflict Identification and Marking: Spatial overlay analysis is performed on the transmission line buffer zone and the merged protection boundary to identify potential conflict areas. A hierarchical determination is then made based on the conflict marking logic. When the overlapping area between the "three zones and three lines" and the forest land protection area exceeds 5% of the total area of ​​the protection area, it is marked as a red conflict zone (prohibited construction zone). When a transmission line intersects the boundary of a protected area and the minimum included angle is less than 30°, it is marked as a yellow warning area (restricted construction area); all conflict results are output in GeoJSON format, including attribute fields such as conflict ID, type, location, area, and angle.

[0065] 4. Three-level conflict resolution Construct a conflict tree model and process them according to the priority order of "geometric conflict > attribute conflict > temporal conflict": Level 1 (Geometric Conflict): Identify sections of the route that cross ecological protection red lines, perform three-dimensional spatial avoidance correction, and adjust the route elevation or alignment; Level 2 (Attribute Conflict): Comparing the "Natural Resource Identification Land Category" with the "Land Planning Use", it was found that a certain plot of land was marked as "Forest Land" in the forestry data, but as "Unused Land" in the national land data. Based on the preset rules, it was determined to be "High Risk" and uniformly assigned the value of "Forest Land". Level 3 (Temporal Conflict): The data metadata of the forestry reserve was verified and found to be 428 days behind the latest version. It was marked as "pending update" and a data update suggestion form was generated.

[0066] 5. Dynamic rule validation and output The system invokes a dynamic business rule engine to load the safety distance rules from the Southern Power Grid Q / CSG 1204043 standard and supports real-time access to external forestry management rules. The system automatically performs rule validation, generates a final compliant spatial dataset, and outputs a governance outcome package including avoidance layers, conflict locations, and processing logs.

[0067] III. Experimental Results The method in this embodiment achieves efficient integration and intelligent management of multi-source heterogeneous spatial data involved in the 500kV line project of Yunnan Power Grid. The specific results are shown in Table 1.

[0068] Table 1 Comparison Results

[0069] Experimental results show that this method significantly improves data governance efficiency, reducing a processing task that originally required half a month of manual work to be completed automatically within 8 hours; it successfully identified and resolved all 9 spatial conflicts, avoiding the risk of rerouting due to the route crossing protected areas; and by avoiding ecologically sensitive areas in advance, it is estimated to save the project direct costs of 2.1 million yuan. The final compliant spatial dataset has been applied to the preliminary design phase of the route, supporting subsequent route optimization and environmental impact assessment.

[0070] Example 4 is an embodiment of the present invention. This embodiment differs from the first embodiment in that it provides a multi-source heterogeneous data integration, analysis and governance system.

[0071] It should be noted that the technical solution of this multi-source heterogeneous data integration, analysis and governance system is based on the same concept as the technical solution of the multi-source heterogeneous data integration, analysis and governance method described above. For details not described in detail in the technical solution of the multi-source heterogeneous data integration, analysis and governance system in this embodiment, please refer to the description of the technical solution of the multi-source heterogeneous data integration, analysis and governance method described above.

[0072] This embodiment of a multi-source heterogeneous data integration, analysis, and governance system includes: The data standardization module is used to acquire multi-source heterogeneous raw data, perform semantic mapping through the power grid business ontology library, and perform dynamic coordinate normalization through an adaptive transformation matrix to obtain standardized spatial data. The spatial conflict analysis module is used to perform spatial queries, dynamic buffer calculations and protection zone hierarchical fusion based on standardized spatial data through spatial overlay optimization algorithms, as well as topological relationship identification and regularization processing of power lines and external linear features, to obtain spatial conflict analysis results. The conflict collaborative resolution module is used to identify and collaboratively resolve geometric, attribute, and temporal conflicts based on spatial conflict analysis results through a three-level conflict resolution mechanism, resulting in a compliant spatial dataset after resolution. The governance process-driven module is used to generate a spatial data governance report by driving the governance process and adapting rules based on the dissolved compliant spatial dataset through a dynamic business rule engine.

[0073] This embodiment also provides an electronic device applicable to a multi-source heterogeneous data integration, analysis, and governance method, including: The system includes a memory and a processor. The memory stores computer-executable instructions, and the processor executes these instructions to implement a multi-source heterogeneous data integration, analysis, and governance method as proposed in the above embodiments.

[0074] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, it implements a method for integrating, analyzing and managing multi-source heterogeneous data as proposed in the above embodiments.

[0075] The storage medium proposed in this embodiment and the method for integrating, analyzing and managing multi-source heterogeneous data proposed in the above embodiments belong to the same inventive concept. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0076] Based on the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0077] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for integrating, analyzing, and managing multi-source heterogeneous data, characterized in that, include: Obtain multi-source heterogeneous raw data, perform semantic mapping through the power grid business ontology library, and perform dynamic coordinate normalization through an adaptive transformation matrix to obtain standardized spatial data; Based on standardized spatial data, spatial query, dynamic buffer calculation and protection zone hierarchical fusion are performed through spatial overlay optimization algorithm, as well as topological relationship identification and regularization processing of power lines and external linear features, to obtain spatial conflict analysis results; Based on the spatial conflict analysis results, a three-level conflict resolution mechanism is used to identify and collaboratively resolve geometric, attribute, and temporal conflicts, resulting in a compliant spatial dataset after resolution. Based on the resolved compliant spatial dataset, a spatial data governance report is obtained by driving the governance process and adapting the rules through a dynamic business rule engine.

2. The method for integrating, analyzing, and managing multi-source heterogeneous data as described in claim 1, characterized in that: The spatial overlay optimization algorithm includes: By constructing a specific spatial index structure, a fast range query can be performed on the patch data; Power-specific operators are used to calculate the safe clearance between transmission lines and ecologically sensitive areas and to integrate ecological red lines. Based on the conflict marking logic, specific areas are marked, and the avoidance layer data containing the conflict location and range is output.

3. The method for integrating, analyzing, and managing multi-source heterogeneous data as described in claim 1 or 2, characterized in that: The power-specific operator includes: The safety distance parameters around the transmission line towers are determined based on the voltage level, and a dynamic buffer zone is generated. Spatial integration processing is carried out on ecological protection areas and power facilities, and integration weights are set according to the control level of ecological protection areas to generate continuous and complete protection boundaries. Spatial overlay analysis is performed on the dynamic buffer and the fused protection boundary to identify spatial conflict areas between them.

4. The method for integrating, analyzing, and managing multi-source heterogeneous data as described in claim 3, characterized in that: The conflict marking logic includes: When the designated area and the forest protection area have spatial overlap, and the degree of overlap exceeds the preset area threshold, it is marked as a red conflict area; When a power transmission line intersects with an ecological protection zone and the intersection angle is less than a preset angle threshold, it is marked as a yellow warning area. The intersection angle is determined by calculating the angle between the transmission line route and the normal vector of the protected area boundary, and the smallest angle is selected at multiple intersection points of the polygon as the basis for judgment.

5. The method for integrating, analyzing, and managing multi-source heterogeneous data as described in claim 4, characterized in that: The identification and regularization of the topological relationship between the power lines and external linear features includes: Spatial relationship prediction is performed on standardized power line data and external linear feature data to identify spatially intersecting sections and adjacent sections that are close to each other but do not intersect. The location of the intersection point between the power line and external linear features in space is determined by geometric calculation, and the angle between the two at the intersection point is calculated. The included angle is judged for compliance according to the power engineering design specifications. When the included angle is less than the preset angle threshold, the current intersection point is marked as a high-risk intersection point. The attribute information of high-risk intersections is included in the spatial conflict set and summarized in a unified manner with other types of conflicts to obtain the spatial conflict analysis results.

6. The method for integrating, analyzing, and managing multi-source heterogeneous data as described in claim 5, characterized in that: The three-level conflict resolution mechanism includes: Identify geometric conflicts between transmission lines and prohibited construction zones, and perform three-dimensional spatial avoidance corrections for intersections; Compare the land category attributes of the same geographical area in different data sources, identify attribute conflicts, and assign attribute values ​​according to preset rules; Verify the update time in the data metadata, identify temporal conflicts caused by version expiration, and mark them as pending updates; The conflict tree model is used to prioritize multiple concurrent conflicts, determine the conflict processing order, and perform automatic repair operations on each conflict in the order to obtain a compliant space dataset after resolution.

7. The method for integrating, analyzing, and managing multi-source heterogeneous data as described in claim 6, characterized in that: The conflict tree model includes: Construct a tree-like decision structure with geometric conflicts, attribute conflicts, and temporal conflicts as nodes; Set the processing priority for each conflict type, with geometric conflicts having the highest priority and temporal conflicts having the lowest priority. When multiple conflicts occur simultaneously, the tree structure is traversed layer by layer according to priority, triggering the corresponding conflict resolution operation.

8. A multi-source heterogeneous data integration, analysis, and governance system, employing the method described in any one of claims 1-7, characterized in that, include: The data standardization module is used to acquire multi-source heterogeneous raw data, perform semantic mapping through the power grid business ontology library, and perform dynamic coordinate normalization through an adaptive transformation matrix to obtain standardized spatial data. The spatial conflict analysis module is used to perform spatial queries, dynamic buffer calculations and protection zone hierarchical fusion based on standardized spatial data through spatial overlay optimization algorithms, as well as topological relationship identification and regularization processing of power lines and external linear features, to obtain spatial conflict analysis results. The conflict collaborative resolution module is used to identify and collaboratively resolve geometric, attribute, and temporal conflicts based on spatial conflict analysis results through a three-level conflict resolution mechanism, resulting in a compliant spatial dataset after resolution. The governance process-driven module is used to generate a spatial data governance report by driving the governance process and adapting rules based on the dissolved compliant spatial dataset through a dynamic business rule engine.

9. An electronic device, characterized in that, include: Memory, used to store programs; A processor for loading the program to perform the steps of the method as claimed in any one of claims 1-7.

10. A computer-readable storage medium storing a program, characterized in that, When the program is executed by a processor, it implements the steps of the method as described in any one of claims 1-7.

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