CN113344334A - City multi-scale comprehensive perception index system construction and query method based on ontology - Google Patents
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Abstract
The invention provides a method for constructing and inquiring a multi-scale comprehensive perception index system of a city based on an ontology, which comprises the steps of setting a top-level framework of the multi-scale comprehensive perception index system of the city, and constructing an ontology model of the multi-scale comprehensive perception index system of the city; defining basic types and elements of an index system metadata model according to the structure and content of a city multi-scale comprehensive perception index system body model, and determining the setting of an index system metadata model Schema; according to research contents and perception requirements in different fields, perception index items, perception elements and attributes of the perception index items and the perception elements under three scales of city groups, cities and blocks are collected and summarized; the method comprises the steps of constructing an example of the urban multi-scale comprehensive perception index system according to an ontology model and collected information, and realizing formalized expression of various urban multi-scale comprehensive perception index systems by establishing mapping relations between index information of the index system and each metadata field in a meta model, so as to support user query.
Description
Technical Field
The invention belongs to the technical field of sensing network information sensing, and relates to a method for constructing and inquiring a city multi-scale comprehensive sensing index system based on a body.
Background
With the rapid development of data science and technology and the promotion of urban informatization wave, the smart city becomes a new concept of urban development in the 21 st century. The smart city research based on infrastructure such as the Internet, the Internet of things and the like is based on perception data, and knowledge is found from mass data by using technologies such as cloud computing, artificial intelligence and the like, so that intelligent service is provided. However, the urban data has the characteristics of multiple types, large scale, low value density, multi-dimension space-time and the like, and is difficult to share and cooperate, which brings difficulty to subsequent data processing and use.
In order to better guide the development of work, various organizations at home and abroad develop the promotion work of the system framework in the smart city. At present, most of index systems related to smart cities focus on development and evaluation, and evaluation index systems are indispensable as identification standards of smart city construction results, but unified framework guidance is still lacked in data perception work before the evaluation index systems, and no comprehensive description system exists at present in the aspects of perception content, perception element classification, element attributes, index utilization and the like of smart cities.
The city perception index system is used for realizing quick acquisition of perception data, assisting city monitoring and management decision and improving city intellectualization level. Due to the characteristics of urban data such as space-time multi-dimension, multi-scale, multi-granularity, multi-element isomerism and the like, the current situations of numerous perception platforms and different task requirements exist, and a comprehensive perception index system for unifying perception information levels and defining the association and cooperation of perception elements and perception means is urgently needed at present, so that the requirement of urban multi-scale three-dimensional perception is supported. In the field of information science, ontologies are widely used as tools for information abstraction and knowledge description. In the face of the current situations that urban data concepts are numerous and complex, relationships between concepts and entity elements are various, attribute space-time granularity is difficult to unify and the like, the ontology is used as a formal specification of a shared concept model, and the problem of difficult information description of various metadata exists in the construction of a comprehensive perception index system. In order to solve the problems, the method for constructing the comprehensive perception index system based on the ontology emphasizes the connection among various concepts, and performs key design on the information description of the index system.
The following references are referred to herein:
[1]Allwinkle S,Cruickshank P.Creating smart-er cities:An overview[J].Journal of urban technology.2011,18(2):1-16.
[2]Alawadhi S,Aldama-Nalda A,Chourabi H,Gil-Garcia JR,Leung S,Mellouli S,et al.Building understanding of smart city initiatives[C].International conference on electronic government；2012:Springer.
[3] wangjing, Li Chao, Xiu Du Po and Danxi Guang, data-centered research review on Smart cities [ J ] computer research and development 2014(02) 239-59.
[4] The core connotation research of the smart city, namely the construction of the smart city in Shanghai as the center [ D ]. Shanghai university, 2017.
[5] Weimin, Smart City evaluation index System development review [ J ] Yangtze river jungle, 2018(30):129.
[6] Gong Jiang ya, Zhang Xiang, Sheng Jiang, Chen Cheng.
[7]Studer R,Benjamins V R.Fensel D.Knowledge engineering,principles and methods[J].Data and Knowledge Engineering,1998.25(1-2):161-197.
Disclosure of Invention
In order to meet the requirements of different users on the multi-scale three-dimensional perception of the smart city, solve the problems of unclear perception content, insufficient perception range and the like in city development and construction, and improve perception decision capability and efficiency, the invention provides a method for constructing and inquiring a city multi-scale comprehensive perception index system based on a body.
The invention provides a method for constructing a city multi-scale comprehensive perception index system based on an ontology, which mainly comprises the following steps:
step 1.2, setting a sub-theme layer and reasonably classifying the perception index items;
step 1.3, setting an index item layer and a value layer, wherein the index item layer and the value layer comprise the perception indexes collected according to the perception requirements of users, and the value layer comprises perception elements supporting the perception indexes and perception element attributes;
step 4.1, determining the perception range and perception object of each sub-theme layer;
step 4.2, collecting corresponding perception index items according to the perception range of the sub-theme layer, and determining perception elements corresponding to the content of each perception index item; classifying indexes capable of being observed, measured or calculated under each sub-theme layer according to perception content;
step 4.3, defining the attributes of the perception elements under different scales;
step 4.4, deleting redundant sensing elements and perfecting a multi-scale comprehensive sensing index system of the city;
and 5, constructing an example of the urban multi-scale comprehensive perception index system according to the ontology model and the collected information, and realizing the formal expression of various urban multi-scale comprehensive perception index systems by establishing the mapping relation between the index information of the index system and each metadata field in the meta model, thereby supporting the user query.
In step 1.1, the field of natural disasters is divided into the theme of rainstorm and waterlogging, and the field of traffic is divided into the theme of regional traffic; the ecological environment of rivers and lakes is defined as a field layer and is divided into three subjects of water environment, atmospheric environment and soil environment.
In step 1.3, the perception index items comprise single indexes and composite indexes, the single indexes are only supported by the single perception elements, and the composite indexes are obtained by calculating and processing a plurality of perception elements; when the perception task requirements of the same perception element in three scales of a city group, a city and a block are different, the attribute requirements of each perception element in the three spatial scales are listed.
In step 2, the city multi-scale comprehensive perception index system ontology model is set from top to bottom, so that the relation between concepts and concepts, between levels and levels, between concepts and examples is enhanced, the upper level comprises the lower level, and the lower level is the inheritance and subdivision of the concepts of the upper level, so that the decomposition of perception tasks is clear step by step.
And in step 3, the index system metadata comprises identification information, description information, domain information, theme information, perception index information, service information and contact information.
Furthermore, in step 4.1, the "rainstorm waterlogging" topic is divided into four sub-topics, namely a "diagnosis period", a "preparation period", a "response period" and a "recovery period"; the regional traffic theme is divided into two sub-themes of daily traffic monitoring and emergency traffic management; the molecular theme under the 'water environment' theme in the 'river and lake ecological environment' field comprises 'river water situation' and 'lake water quality', the molecular theme under the 'atmospheric environment' theme comprises 'air quality' and 'waste gas emission' and the like, and the molecular theme under the 'soil environment' theme comprises 'soil quality' and 'land utilization'.
In step 4.3, attributes such as time resolution, spatial resolution and the like of sensing elements are listed according to sensing task requirements in three scales of a city group, a city and a block, so that the corresponding sensors are guided to carry out data acquisition, and personalized solutions are provided for various sensing requirements.
In step 5, typical application scenes of 'rainstorm waterlogging', 'regional traffic', 'river and lake ecological environment' are respectively taken as examples to construct the urban multi-scale comprehensive perception index system.
On the other hand, the invention provides a city multi-scale comprehensive perception index query method based on the ontology, and index query is realized according to the city multi-scale comprehensive perception index system construction method based on the ontology.
Moreover, the query mode is query by attribute or query by relationship.
The invention has the following beneficial effects:
(1) the method comprises the steps of setting a top-level framework of a perception index system, constructing a comprehensive perception index system body model, giving application examples of typical scenes, expanding perception contents of more different application scenes by adding and perfecting theme layer and sub-theme layer examples, and enhancing the expandability and reusability of the index system.
(2) The invention provides a self-based city multi-scale comprehensive perception index query method, wherein a city multi-scale comprehensive perception index system established by the method comprises different theme scenes in multiple city fields, perception contents required by tasks in different scales are comprehensively considered according to user requirements, users are supported to carry out various query services, and a decision maker can conveniently make reasonable and effective perception decisions from the aspects of intelligent city management and assistance.
Drawings
FIG. 1 is a schematic diagram of a top-level architecture of a city multi-scale integrated perceptual index system according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of an ontology model of a city multi-scale comprehensive perception index system according to an embodiment of the invention;
FIG. 3 is a schematic diagram of overall settings of a city multiscale comprehensive perception index system Schema according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a rainstorm waterlogging multi-scale comprehensive perception index system model according to an embodiment of the invention;
FIG. 5 is a schematic diagram of a regional traffic multi-scale comprehensive perception index system model according to an embodiment of the invention;
FIG. 6 is a schematic diagram of a multi-scale comprehensive perception index system model of an ecological environment of rivers and lakes in an embodiment of the invention.
Detailed Description
For a better understanding of the present invention, the technical solutions of the present invention will be further described with reference to the accompanying drawings and specific embodiments.
The invention provides a top-level framework of an urban multi-scale comprehensive perception index system designed according to user requirements; constructing an urban multi-scale comprehensive perception index system body model, macroscopically grasping a frame, and extending downwards step by step; designing a meta model Schema according to an ontology model of a city multi-scale comprehensive perception index system, so as to facilitate expansion and reuse of more fields and application scenes; according to research contents and perception requirements in different fields, perception index items, perception elements and attributes of the perception index items and the perception elements under three scales of city groups, cities and blocks are collected and summarized; an example of the urban multi-scale comprehensive perception index system is constructed, a typical application scene of 'rainstorm waterlogging', 'regional traffic', 'river and lake ecological environment' is taken as an example for display, and formal expression of the index system is given.
The embodiment of the invention provides a method for constructing an urban multi-scale comprehensive perception index system based on a body, which takes typical application scenes of 'rainstorm waterlogging', 'regional traffic', 'river and lake ecological environment' as examples and mainly comprises the following steps:
Step 1.1, setting a 'field layer' and a 'subject layer'.
In the step, the specified range and content of the 'field layer' and the 'subject layer' are set, and the granularity of all objects in each layer of the index system is ensured to be uniform.
In the embodiment, the field of natural disasters is divided into the theme of rainstorm and waterlogging, and the field of traffic is divided into the theme of regional traffic. The granularity of the 'river and lake ecological environment' is obviously larger than that of 'rainstorm waterlogging' and 'regional traffic', from the perspective of the overall completeness of an index system, the 'river and lake ecological environment' is defined as a 'field layer', the 'river and lake ecological environment' is further refined, and three subjects of 'water environment', 'atmospheric environment' and 'soil environment' are divided, so that the granularity consistency of each object in the subject layer is ensured, the logical rationality of the index system is reflected, and the next-level subdivision is convenient.
Step 1.2, setting a sub-theme layer.
Setting a sub-theme layer, and reasonably classifying the perception index items; in specific implementation, preferably, the sub-topic layers are subdivided under the topic layer by referring to a classification mechanism in relevant standards of ITU, ISO and IEC, and all index items under each topic are effectively classified.
In the embodiment, with reference to a classification mechanism in ITU, ISO and IEC related standards, sub-topic layers are subdivided below the topic layer, so that all index items can be effectively classified conveniently. The definition of "subtopic layer" will take into account the characteristics and requirements of the subject matter from the perspective of smart city management and aid decision-making support.
And 1.3, setting an index item layer and a value layer.
During specific implementation, the step is preferably recommended to refer to relevant research documents, domestic and foreign industry standards, relevant system platform task requirements and a data dictionary, and perception indexes are collected according to user perception requirements; the "value layer" includes perceptual elements and perceptual element attributes that support perceptual metrics.
The 'index item layer' and the 'value layer' are grasped according to the perception requirements of various users such as a decision maker, a manager, the public and the like. The index item layer refers to all perception index items, including a single index and a composite index, wherein the single index is only supported by a single perception element, and the composite index is obtained by calculating and processing a plurality of perception elements. The 'value layer' comprises perception elements and attributes thereof, and perception tasks of the same perception element in three dimensions of a city group, a city and a block are required to be different, so that the attribute requirements of each perception element in the three spatial dimensions of the city group, the city and the block are listed.
And 2, constructing a city multi-scale comprehensive perception index system body model, macroscopically grasping a frame, and extending downwards step by step. According to a top-level architecture of 'field level-theme level-subtopic level-index item level-value level', an urban multi-scale comprehensive perception index system ontology model is arranged from top to bottom, and the relation between concepts and concepts, between levels and levels, between concepts and examples is enhanced.
The upper level comprises the next level, and the next level is inheritance and subdivision of concepts of the upper level, so that the decomposition of the perception task is clear step by step. Here, the perception index item includes a single index and a composite index, the value includes a perception element and an attribute thereof, and all the content serves a perception decision. As shown in fig. 2, the ontology model reserves an exploitable space for more fields and topics, facilitates updating and perfecting, and facilitates expansion and reuse in other perception tasks and application scenarios.
And 3, defining a metadata model of the index system according to the structure and the content of the city multi-scale comprehensive perception index system body model, and determining the setting of the index system metadata model Schema.
The index system metadata includes identification information, description information, domain information, topic information, perception index information, service information, and contact information, and Schema setting thereof is written in indexsystem.
Xsd defines the root element IndexSystem index system of the entire schema document.
The IndexSystem contains a container of four metadata building elements (Tag, Category, subform and Administration). The basic information source discovered by the Tag label index system provides various descriptive metadata for index system query; the Category is mainly used for inquiring a corresponding index system from the comprehensive perception theme; the SubTheme sub-theme is used for refining the requirement of comprehensive perception and corresponds to a corresponding perception index; the Administration management is mainly composed of contact information and service information. The contact information is convenient for contacting with the index system contributors, and the service information provides a service interface for the access and the calling of the index system. And each metadata component element has its corresponding element type (TagType tag type, CategoryType type, subthetetype type theme type, and administationtype management type).
Each metadata building element contains its corresponding metadata information element:
the Tag element is a sequential container containing an Identification information element Identification and a Description information element Description, wherein the Identification element (type of Identification information) is a mandatory item including a model ID and a model name, and the Description element (type of Description information) is an optional element including a Text Description.
The Category element is a sequential container containing a Field information element Field and a perceptual topic information element Theme, where the Field element is a must-select and the Theme element is a select.
There may be multiple sub-topics in one index system, so the relationship between the root element IndexSystems and SubTheme elements is one-to-many. The SubTheme element is a container containing one or more perceptual index elements, indicators, including Item index items, Value values, and attributes.
The Administration element is a container containing a Contact information element Contact and a Service information element Service, wherein the Contact element (Contact type Contact information type) comprises a Contact name, a Tel Contact phone, an Email Contact mailbox, an Address Contact Address and an Organization Contact. The Service element (ServiceType Service information type) includes a ServiceName Service name, a ServiceAddress Service address, and a ServiceDescription Service description. The Contact element and the Service element are optional elements.
In more detail, each metadata information element has its corresponding type and more detailed sub-elements.
in the embodiment, according to research contents and perception requirements of rainstorm waterlogging, regional traffic and ecological environment of rivers and lakes, perception index items, perception elements and attributes of the perception elements under three scales of cities, cities and blocks are collected and summarized.
And 4.1, determining the perception range and the perception object of each sub-theme layer.
In specific implementation, the preferred suggestion refers to ITU KPI and the classification of the existing dividing mechanism at home and abroad, considers the development and construction of the smart city, further refines the theme layer into a plurality of sub-themes from the perspective of a decision maker, and reduces the difference with the index layer.
In the examples, the "rainstorm waterlogging" topic is divided into four sub-topics "diagnosis period", "preparation period", "response period" and "recovery period"; the regional traffic theme is divided into two sub-themes of daily traffic monitoring and emergency traffic management; under the 'water environment' theme in the 'river and lake ecological environment' field, subtopics such as 'river water situation', 'lake water quality' and the like are divided, under the 'atmospheric environment' theme, subtopics such as 'air quality', 'waste gas emission' and the like are divided, and under the 'soil environment' theme, subtopics such as 'soil quality', 'land utilization' and the like are divided.
And 4.2, collecting and summarizing corresponding perception index items according to the perception range of the sub-theme layer, and combing perception elements corresponding to the perception index items.
Collecting and summarizing corresponding perception index items, and combing perception elements corresponding to the content of each perception index item; and classifying the observable, measurable and computable indexes under each sub-theme layer according to the perception content.
And 4.3, defining the perception element attributes under different scales.
In specific implementation, materials such as domestic and foreign related documents, standards, implementation schemes, technical requirements and the like and related system data dictionaries are preferably recommended to be referred, and attributes such as time resolution, spatial resolution and the like of sensing elements are listed according to sensing task requirements in three scales of urban groups, cities and blocks, so that data acquisition of corresponding sensors is guided, and personalized solutions are provided for various sensing requirements.
In the embodiment, the perceptual element attributes under three spatial scales of a city group, a city and a block are determined in the step.
Table 1 shows a rainstorm waterlogging multi-scale comprehensive perception index system.
Table 2 shows a regional traffic multiscale comprehensive perception index system
Table 3 shows a multi-scale comprehensive perception index system for ecological environment of rivers and lakes
And 4.4, deleting redundant sensing elements and perfecting a multi-scale comprehensive sensing index system of the city.
The method comprises the steps of perfecting and condensing an index system, measuring the importance of all perception index items according to perception requirements, and deleting redundant contents.
And 5, constructing an example of the urban multi-scale comprehensive perception index system according to the ontology model and the collected information, and realizing the formal expression of various urban multi-scale comprehensive perception index systems by establishing the mapping relation between the index information of the index system and each metadata field in the meta model. The meta-model of the index system can describe the connotation and the extension of various indexes in a standardized way, and when a user performs various query services, a returned result of a specific index instance can be obtained.
The index query method comprises attribute query and relation query. In the attribute query, a user can query the attribute of the element according to the perception element and obtain the attribute requirements of the element in different scale perception scenes, wherein the perception scale comprises a city group scale, a city scale and a block scale, and the attribute requirements mainly comprise spatial resolution and temporal resolution. In the query according to the relation, based on the constructed index system information and the meta-model, a user can obtain a target index and an element through SPARAL semantic query, and simultaneously obtain a node related to the index or the element according to the hierarchical structure of 'field-subject-subtopic-index item-value'. On the basis, the user can modify and process the instance file returned by the query according to the personalized requirements. Therefore, the method provides help for the expression and reuse of various urban multi-scale comprehensive perception indexes.
In the embodiment, typical application scenarios of "rainstorm and waterlogging" (as shown in fig. 4), "regional traffic" (as shown in fig. 5), and "river and lake ecological environment" (as shown in fig. 6) are respectively taken as examples for display, and a multi-scale comprehensive perception index system formalized expression of the three typical application scenarios is realized at the same time, and as shown below, a perception index system example segment of a soil environment theme is provided for reference.
The invention further provides a city multi-scale comprehensive perception index query method based on the ontology, and index query is realized according to the city multi-scale comprehensive perception index system construction method based on the ontology.
In specific implementation, a person skilled in the art can implement the automatic operation process by using a computer software technology, and a system device for implementing the method, such as a computer-readable storage medium storing a corresponding computer program according to the technical solution of the present invention and a computer device including a corresponding computer program for operating the computer program, should also be within the scope of the present invention.
In some possible embodiments, an ontology-based city multi-scale comprehensive perceptual index architecture building system is provided, which includes a processor and a memory, where the memory is used to store program instructions, and the processor is used to call the stored instructions in the memory to execute a city multi-scale comprehensive perceptual index architecture building method based on an ontology as described above.
In some possible embodiments, there is provided an ontology-based city multi-scale comprehensive perceptual index system building system, including a readable storage medium, on which a computer program is stored, and when the computer program is executed, the ontology-based city multi-scale comprehensive perceptual index system building method is implemented.
The above description is only a preferred embodiment of the present invention, and the specific implementation of the present invention is not to be considered as limited to the above embodiment, and the present invention is not limited to the above embodiment, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present invention should be considered to be within the protection scope of the present invention.
Claims (10)
1. A city multi-scale comprehensive perception index system construction method based on an ontology is characterized by comprising the following steps:
step 1, setting a top-level architecture of a city multi-scale comprehensive perception index system, comprising the following substeps,
step 1.1, setting specified ranges and contents of a 'field layer' and a 'subject layer', wherein all object granularities in each layer of an index system are uniform;
step 1.2, setting a sub-theme layer and reasonably classifying the perception index items;
step 1.3, setting an index item layer and a value layer, wherein the index item layer and the value layer comprise the perception indexes collected according to the perception requirements of users, and the value layer comprises perception elements supporting the perception indexes and perception element attributes;
step 2, constructing an ontology model of the urban multi-scale comprehensive perception index system, wherein the ontology model of the urban multi-scale comprehensive perception index system is arranged from top to bottom according to a top-level architecture of 'field level-theme level-subtopic level-index item level-value level';
step 3, defining basic types and elements of an index system metadata model according to the structure and the content of the city multi-scale comprehensive perception index system body model, and determining the arrangement of an index system metadata model Schema;
step 4, collecting and summarizing perception index items, perception elements and attributes thereof under three scales of city groups, cities and blocks according to research contents and perception requirements in different fields; the implementation process comprises the following sub-steps,
step 4.1, determining the perception range and perception object of each sub-theme layer;
step 4.2, collecting corresponding perception index items according to the perception range of the sub-theme layer, and determining perception elements corresponding to the content of each perception index item; classifying indexes capable of being observed, measured or calculated under each sub-theme layer according to perception content;
step 4.3, defining the attributes of the perception elements under different scales;
step 4.4, deleting redundant sensing elements and perfecting a multi-scale comprehensive sensing index system of the city;
and 5, constructing an example of the urban multi-scale comprehensive perception index system according to the ontology model and the collected information, and realizing the formal expression of various urban multi-scale comprehensive perception index systems by establishing the mapping relation between the index information of the index system and each metadata field in the meta model, thereby supporting the user query.
2. The method for constructing the urban multi-scale comprehensive perception index system based on the ontology according to claim 1, wherein the method comprises the following steps: step 1.1, dividing the field of natural disasters into the theme of rainstorm and waterlogging, and dividing the field of traffic into the theme of regional traffic; the ecological environment of rivers and lakes is defined as a field layer and is divided into three subjects of water environment, atmospheric environment and soil environment.
3. The method for constructing the urban multi-scale comprehensive perception index system based on the ontology according to claim 1, wherein the method comprises the following steps: in the step 1.3, the perception index items comprise single indexes and composite indexes, the single indexes are only supported by a single perception element, and the composite indexes are obtained by calculating and processing a plurality of perception elements; when the perception task requirements of the same perception element in three scales of a city group, a city and a block are different, the attribute requirements of each perception element in the three spatial scales are listed.
4. The method for constructing the urban multi-scale comprehensive perception index system based on the ontology according to claim 1, wherein the method comprises the following steps: in the step 2, the ontology model of the urban multi-scale comprehensive perception index system is arranged from top to bottom, so that the relation between concepts and concepts, between levels and levels, between concepts and examples is enhanced, the upper level comprises the lower level, and the lower level is the inheritance and subdivision of the concepts of the upper level, so that the decomposition of perception tasks is clear step by step.
5. The method for constructing the urban multi-scale comprehensive perception index system based on the ontology according to claim 1, wherein the method comprises the following steps: in step 3, the metadata of the index system comprises identification information, description information, field information, theme information, perception index information, service information and contact information.
6. The method for constructing the urban multi-scale comprehensive perception index system based on the ontology according to claim 1, wherein the method comprises the following steps: in step 4.1, the theme of rainstorm waterlogging is divided into four sub-themes of diagnosis period, preparation period, response period and recovery period; the regional traffic theme is divided into two sub-themes of daily traffic monitoring and emergency traffic management; the molecular theme under the 'water environment' theme in the 'river and lake ecological environment' field comprises 'river water situation' and 'lake water quality', the molecular theme under the 'atmospheric environment' theme comprises 'air quality' and 'waste gas emission' and the like, and the molecular theme under the 'soil environment' theme comprises 'soil quality' and 'land utilization'.
7. The method for constructing the urban multi-scale comprehensive perception index system based on the ontology according to claim 1, wherein the method comprises the following steps: in step 4.3, attributes such as time resolution, space resolution and the like of sensing elements are listed according to sensing task requirements in three scales of a city group, a city and a block, so that the corresponding sensors are guided to carry out data acquisition, and personalized solutions are provided for various sensing requirements.
8. The method for constructing an ontology-based urban multi-scale comprehensive perception index system as claimed in claim 1, 2, 3, 4, 5, 6 or 7, wherein: in the step 5, typical application scenes of 'rainstorm waterlogging', 'regional traffic' and 'river and lake ecological environment' are respectively taken as examples to construct the urban multi-scale comprehensive perception index system.
9. A city multi-scale comprehensive perception index query method based on ontology is characterized in that: the ontology-based urban multi-scale comprehensive perception index system construction method according to claims 1-8, achieving index query.
10. The ontology-based urban multi-scale comprehensive perception index query method according to claim 9, wherein: the query mode is query by attribute or query by relation.
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