Geology and mineral resources field ontology model construction method and system based on use case driving

Abstract

The application relates to the technical field of ontology construction, and particularly discloses a case-driven geological mineral field ontology model construction method and system. The application establishes a Ningxia geological mineral panoramic case library based on Ningxia geological mineral full-service-chain original service cases; extracts an ontology modeling meta-linguistic set from the cases in the panoramic case library; obtains a Ningxia geological mineral OWL ontology through reuse screening, characteristic expansion and formalization based on the ontology modeling meta-linguistic set and a general geological ontology; performs case executable verification and data consistency verification based on the Ningxia geological mineral OWL ontology, actual geological data and the cases in the panoramic case library, and obtains an ontology that passes the double-closed-loop verification; arranges and delivers the ontology that passes the double-closed-loop verification, marks a source case ID for each ontology element, generates a case-ontology traceability table, and then outputs a complete ontology delivery package. The application effectively improves the executability and traceability of the ontology model.

Description

Technical Field

[0001] This invention relates to the field of ontology construction technology, and in particular to a method and system for constructing ontology models in the geological and mineral resources field based on use case-driven approaches. Background Technology

[0002] In the field of geology and mineral resources, with the explosive growth of geological exploration data and the continuous convergence of multi-source heterogeneous data, building accurate and efficient geological and mineral ontology models has become a core prerequisite for achieving unified management of geological data, in-depth knowledge mining, and intelligent decision support.

[0003] A method for constructing an ontology model in the field of geology and mineral resources is proposed as follows: The application purpose and disciplinary scope of the ontology are clearly defined; knowledge is collected through research of field literature, technical specifications, and geological reports, in-depth interviews with field experts to extract their concepts and rules, and analysis of the structure of existing databases; core concepts within the field are listed; hierarchical relationships between concepts are defined; the attributes of each concept and the logical relationships between concepts are defined in detail; specific instances are filled in and relevant data is supplemented; formal coding is performed using languages ​​such as OWL, and logical consistency is checked using an inference engine; after passing the check, the ontology model for the field of geology and mineral resources is output.

[0004] The existing method is based on the seven-step approach, which is a classic paradigm for domain ontology construction. There are comprehensive guidelines to follow, providing a clear starting point for the project. In addition, it makes full use of the tacit knowledge of experts. The model is collaboratively constructed by domain experts and knowledge engineers, and its classification system and logical relationships are very rigorous.

[0005] However, existing methods also have some drawbacks: First, they lack traceability. It's difficult to trace the origins of a concept or rule within the ontology, which expert proposed it, and in what scenario, hindering knowledge updates and iterations. Second, knowledge acquisition faces bottlenecks, heavily relying on the time and effort of a few experts. The knowledge source is singular and highly subjective, making it difficult to cover all business scenarios. Third, a semantic gap exists; there's a distance between the abstract concepts of experts and the operational practices of frontline business personnel, potentially leading to a theoretically correct but practically unusable ontology. Therefore, further optimization of existing methods is still needed. Summary of the Invention

[0006] This invention addresses the problems of poor traceability, bottlenecks in knowledge acquisition, and semantic gaps in the background technology by proposing a method and system for constructing ontology models in the geological and mineral resources field based on use case-driven approaches.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a use case-driven ontology model construction method for the geological and mineral resources domain, comprising the following steps:

[0008] Step 1: Conduct structured collection of original business use cases across the entire business chain of Ningxia Geology and Mineral Resources, and establish a panoramic use case library for Ningxia Geology and Mineral Resources based on the structured collection results;

[0009] Step 2: Extract classes, implicit classes, relationships, and attributes from the use cases in the panoramic use case library using a four-step method; extract axioms based on business rules; extract instances based on use case scenarios; detect conceptual conflicts between different use cases; arbitrate based on use cases with higher weights; and output a set of ontology modeling metaphrases.

[0010] Step 3: Obtain the set of ontology modeling meta-terms and the general geological ontology. After reuse filtering, feature expansion and formalization, the Ningxia Geological and Mineral Resources OWL ontology is obtained.

[0011] Step 4: Based on the Ningxia Geological and Mineral Resources OWL ontology, actual geological data, and use cases in the panoramic use case library, use a 3D geological modeling system to verify the executability of use cases and the consistency of data, and output an ontology that has passed both closed-loop verifications.

[0012] Step 5: Organize the deliverables for the ontology that has passed the double closed-loop verification, mark the source use case ID for each ontology element, generate the use case-ontology traceability table, and then output the complete ontology delivery package.

[0013] Step 6: For the newly added Ningxia geological business use cases, first execute Step 1 to complete the structured data collection and add the collected use cases to the Ningxia Geological and Mineral Panorama Use Case Library. Then execute Steps 2 to 5 in sequence. Finally, output the updated OWL ontology, the updated use case-ontology traceability table, and the synchronously updated Ningxia Geological and Mineral Panorama Use Case Library.

[0014] To achieve the above objectives, the present invention provides the following technical solution: a use case-driven ontology model construction system for the geological and mineral resources field, including a use case library building module, a meta-arbitration module, an ontology construction module, a dual closed-loop verification module, a delivery and organization module, and an iterative update module;

[0015] The use case library building module performs structured collection of original business use cases from the entire business chain of Ningxia Geology and Mineral Resources, and establishes a panoramic use case library for Ningxia Geology and Mineral Resources based on the structured collection results.

[0016] The meta-arbitration module extracts classes, implicit classes, relationships, and attributes from the use cases in the panoramic use case library using a four-step method, extracts axioms based on business rules, extracts instances based on use case scenarios, detects conceptual conflicts between different use cases, arbitrates the use cases with higher weights, and outputs a set of ontology modeling meta-terms.

[0017] The ontology construction module obtains the ontology modeling meta-language set and the general geological ontology. After reuse filtering, feature expansion and formalization, the Ningxia Geological and Mineral Resources OWL ontology is obtained.

[0018] The dual-loop verification module is based on the Ningxia Geology and Mineral Resources OWL ontology, actual geological data, and use cases in the panoramic use case library. It uses a 3D geological modeling system to verify the executability of use cases and the consistency of data, and outputs an ontology that has passed both dual-loop verifications.

[0019] The delivery processing module processes the deliverables of the ontology that has passed the dual closed-loop verification, marks the source use case ID for each ontology element, generates a use case-ontology traceability table, and then outputs the complete ontology delivery package.

[0020] For newly added Ningxia geological business use cases, the iterative update module first completes structured data collection and adds the collected use cases to the Ningxia Geological and Mineral Panorama Use Case Library. Then, it sequentially executes meta-arbitration, ontology construction, double closed-loop verification, and delivery organization. Finally, it outputs the updated OWL ontology, the updated use case-ontology traceability table, and the synchronously updated Ningxia Geological and Mineral Panorama Use Case Library.

[0021] Compared with the prior art, the present invention has at least one of the following beneficial technical effects:

[0022] First, to address the issue of poor traceability in existing technologies, this invention marks the source use case ID for each ontology element in step five, generating a use case-ontology traceability table. All classes, relations, attributes, axioms, and instances in the ontology are marked with their source use case IDs, which makes the legislative intent of the ontology clear and traceable, greatly facilitating subsequent maintenance, review, and evolution, and ensuring extremely strong traceability.

[0023] Secondly, to address the bottleneck in acquiring existing technical knowledge, this invention sets up a use case arbitration step in step two. Conflict detection is performed on the candidate class set, implicit class set, implicit relation set, attribute set, explicit relation set, axiom set, and instance set. The definitions of the same concept in different use cases are compared to obtain a conflict list. The conflict list and the weight labels of each use case are retrieved. For each conflict, the use case definition with the higher weight is selected as the final definition. If the weights are the same, the resource exploration class use case takes priority. If the weights are the same and both belong to the resource exploration class or not, the use case with the more detailed definition takes priority. The arbitration-free meta-word set is output. This transforms subjective expert debate into objective business decision-making, making the knowledge sources broader and closer to reality, effectively improving the executability of the ontology model.

[0024] Third, to address the semantic gap issue in existing technologies, this invention sets up a first step: to collect original business use cases from the entire business chain of Ningxia Geology and Mineral Resources in a structured manner. Based on the structured collection results, a panoramic use case library of Ningxia Geology and Mineral Resources is established. This ensures that the ontology directly originates from real business operations and data flow processes, representing the context most familiar to business personnel, effectively avoiding the semantic gap. The ontology model is strongly correlated with front-line business use cases, ensuring that the final OWL ontology accurately reflects business needs, achieving a high degree of alignment between business and technology. Attached Figure Description

[0025] Figure 1 A step-by-step diagram illustrating the method for constructing an ontology model in the geological and mineral resources field based on use case-driven approaches;

[0026] Figure 2 Construct a system module connection diagram for an ontology model in the geological and mineral resources domain based on use case-driven architecture. Detailed Implementation

[0027] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0028] like Figure 1 As shown, this embodiment provides a method for constructing an ontology model in the geological and mineral resources field based on use case-driven approaches, including the following steps:

[0029] Step 1: Conduct structured collection of original business use cases across the entire business chain of Ningxia Geology and Mineral Resources, and establish a panoramic use case library for Ningxia Geology and Mineral Resources based on the structured collection results;

[0030] Step 2: Extract classes, implicit classes, relationships, and attributes from the use cases in the panoramic use case library using a four-step method; extract axioms based on business rules; extract instances based on use case scenarios; detect conceptual conflicts between different use cases; arbitrate based on use cases with higher weights; and output a set of ontology modeling metaphrases.

[0031] Step 3: Obtain the set of ontology modeling meta-terms and the general geological ontology. After reuse filtering, feature expansion and formalization, the Ningxia Geological and Mineral Resources OWL ontology is obtained.

[0032] Step 4: Based on the Ningxia Geological and Mineral Resources OWL ontology, actual geological data, and use cases in the panoramic use case library, use a 3D geological modeling system to verify the executability of use cases and the consistency of data, and output an ontology that has passed both closed-loop verifications.

[0033] Step 5: Organize the deliverables for the ontology that has passed the double closed-loop verification, mark the source use case ID for each ontology element, generate the use case-ontology traceability table, and then output the complete ontology delivery package.

[0034] Step 6: For the newly added Ningxia geological business use cases, first execute Step 1 to complete the structured data collection and add the collected use cases to the Ningxia Geological and Mineral Panorama Use Case Library. Then execute Steps 2 to 5 in sequence. Finally, output the updated OWL ontology, the updated use case-ontology traceability table, and the synchronously updated Ningxia Geological and Mineral Panorama Use Case Library.

[0035] Furthermore, the original business use cases of the Ningxia Geological and Mineral Resources full business chain include use case name, participants, main process, branch process, abnormal process, preconditions, postconditions, and business rules.

[0036] The structured data collection process involves confirming whether the information contained in the original business use cases of the entire business chain of Ningxia Geology and Mineral Resources is complete. If the information is complete, the use case is retained; if it is incomplete, the use case is removed.

[0037] The Ningxia geological and mineral panoramic use case library established based on structured acquisition results includes:

[0038] Each use case collected through structured data acquisition is assigned a weight tag and named in the format of use case name-time-weight;

[0039] All named use cases are categorized into five sets: resource exploration, mine management, disaster prevention, environmental protection, and data services.

[0040] A panoramic use case library for Ningxia's geology and mineral resources is established, which contains the five category sets.

[0041] Specifically, in this embodiment, the structured data collection involves confirming whether the information contained in the original business use cases of the Ningxia Geological and Mineral Resources full business chain is complete. This means confirming whether all original business use cases of the Ningxia Geological and Mineral Resources full business chain contain the use case name, participants, main process, branch process, abnormal process, preconditions, postconditions, and business rules. If all of these are present, the information contained in the original business use cases of the Ningxia Geological and Mineral Resources full business chain is considered complete; otherwise, the information contained in the original business use cases of the Ningxia Geological and Mineral Resources full business chain is considered incomplete.

[0042] In this embodiment, it should be specifically noted that the weight label reflects the contribution and business importance of the use case to the ontology construction, and can be set based on a two-dimensional standard of business frequency and business irreplaceability. The business frequency refers to the number of times the use case is executed annually in the actual business of Ningxia Geology and Mineral Resources. The business irreplaceability refers to whether the use case is a necessary process for Ningxia Geology and Mineral Resources. When the business frequency of the use case is greater than or equal to 10 times / year and the business irreplaceability is non-replaceable, either condition is met, and the use case is determined to be a core use case, with its weight label being core. When the business frequency of the use case is greater than or equal to 3 times / year and the business irreplaceability is partially replaceable, either condition is met, and the use case is determined to be an important use case, with its weight label being important. When the business frequency of the use case is less than or equal to 2 times / year and the business irreplaceability is completely replaceable, either condition is met, and the use case is determined to be a general use case, with its weight label being general.

[0043] In this embodiment, the specific execution flow for adding weight tags to each use case acquired through structured data collection is as follows:

[0044] Collect original use case lists (including use case names, categories, and brief descriptions) from the task books of ongoing or completed projects of the Ningxia Basic Geological Survey Institute, the annual work plan of the Ningxia Geological Environment Monitoring Station, or the business process documents of the Ningxia Department of Natural Resources' Mine Management System.

[0045] Two to three people from the Ningxia Basic Geological Survey Institute or Geological Environment Monitoring Station were selected as business experts to score each use case based on business frequency and business irreplaceability. The business frequency was scored as 1 / 2 / 3, with 1 point for a business frequency of less than or equal to 2 times / year, 2 points for a business frequency of greater than or equal to 3 times / year, and 3 points for a business frequency of greater than or equal to 10 times / year. The business irreplaceability was scored as 1 / 2 / 3, with 1 point for a business that was completely replaceable, 2 points for a business that was partially replaceable, and 3 points for a business that was completely irreplaceable.

[0046] Compare the frequency score and the substitution score given by the business experts. If the difference in frequency scores is less than or equal to 0.5, the experts' frequency scores are considered to be consistent, and the average of the frequency scores is directly used for subsequent calculations. If the difference in substitution scores is less than or equal to 0.5, the experts' substitution scores are considered to be consistent, and the average of the substitution scores is directly used for subsequent calculations. If the difference in frequency scores is greater than 0.5, the experts' frequency scores are considered to be inconsistent, and the use case is transferred to the arbitrator to determine the frequency score. The inconsistent use case is automatically promoted to weight level 3. If the difference in substitution scores is greater than 0.5, the experts' substitution scores are considered to be inconsistent, and the use case is transferred to the arbitrator to determine the substitution score.

[0047] The ontology engineer performs weight calculation and labeling. If the frequency score plus the substitution score is greater than or equal to 5, the weight level is 3 and the weight is labeled as core. If the frequency score plus the substitution score is greater than or equal to 3, the weight level is 2 and the weight is labeled as important. If the frequency score plus the substitution score is less than or equal to 2, the weight level is 1 and the weight is labeled as general. For divergent test cases, no weight calculation is performed. The divergent test cases are automatically promoted to weight level 3 and the weight is labeled as core.

[0048] Add a weight label to each use case collected through structured data.

[0049] In this embodiment, it should be specifically noted that, for resource exploration use cases, the weighting of the 3D geological model construction and resource reserve estimation of a mining area in the Helan Mountain coalfield is marked as core; the weighting of the rapid resource evaluation of a mining cluster in Ningxia is marked as important; and the weighting of the exploration record of a single mining point is marked as general. For mine management use cases, the weighting of the dynamic management of ore bodies within a depth of 1200m in a mining cluster in Ningxia is marked as core; the weighting of daily mine safety inspections is marked as important; and the weighting of equipment ledger management is marked as general. For disaster prevention use cases, the weighting of the geological disaster classification evaluation and prediction in Ningxia mines is marked as core; the weighting of surface deformation monitoring is marked as important; and the weighting of historical disaster archive query is marked as general. For environmental protection use cases, the weighting of groundwater resource management and pollution diffusion simulation in Ningxia is marked as core; the weighting of soil pollution investigation is marked as important; and the weighting of data export from a single monitoring point is marked as general. For data service use cases, the integrated query of multi-source heterogeneous geological data (1000+ documents) is marked as core, the online browsing of geological maps is marked as important, and the conversion of a single data format is marked as general.

[0050] Furthermore, the extraction of classes, implicit classes, relationships, and attributes from the use cases in the panoramic use case library based on the four-step method, the extraction of axioms based on business rules, and the extraction of instances based on use case scenarios include the following steps:

[0051] Candidate nouns are filtered from the entire use case text, technical products are removed, and geological entities are retained to obtain a set of candidate classes.

[0052] The verbs and their subjects and objects are fully screened from the use case text. The process classes are analyzed by reverse deducing the verbs to obtain a set of implicit classes. Based on the reverse deduction of the verb subject-object pairs, the set of implicit relationships is obtained.

[0053] Extract constraint parameters from the business rules of the use case, bind them as attributes of the class, and generate an attribute set;

[0054] Retrieve the interaction descriptions of entities in the use case scenario, establish explicit relationships based on the spatial and logical interactions between entities, and generate a set of explicit relationships;

[0055] Extract constraints from business rules, formalize them into axioms, and generate a set of axioms;

[0056] Retrieve specific data from the main flow, branch flow, and exception flow of the test case, extract instances from the specific values ​​of the test case scenario, and generate an instance set.

[0057] Specifically, this embodiment requires clarification of the original example text for core sampling from borehole A in mine area A. The text describes core sampling conducted in mine area A, with a drilling depth of 500 meters. The collected cores contain granite, shale, and copper-bearing veins. Technician Zhang San numbered and recorded the cores and sent the samples to the laboratory for copper content testing. The test results showed a copper content of 2.3%. A copper content greater than 1% is considered mining-worthy. The cores must be stored in a temperature- and humidity-controlled sample library, with the temperature maintained between 15 and 25°C.

[0058] The process of extracting classes, implicit classes, relationships, and attributes using a four-step method, extracting axioms based on business rules, and extracting instances based on use case scenarios includes the following steps:

[0059] Candidate terms are filtered from the full text of the use case text. The selected candidate terms include mining area A, borehole, core, granite, shale, copper-bearing vein, technician, sample, laboratory, sample library, and number. Among them, mining area A, borehole, core, granite, shale, copper-bearing vein, and sample are geological entities and are retained and included in the candidate class set.

[0060] The verbs and their subjects and objects are fully filtered from the use case text. The filtered verbs include collection, inclusion, detection, judgment, and storage. The subject and object of collection are technician and core, and the reverse process class is core collection process. The reverse relationship is technician - collection - core. The subject and object of inclusion are core and granite, shale, and copper-bearing vein. The reverse process class is lithological composition process. The reverse relationship is core - inclusion - granite, shale, and copper-bearing vein. The subject and object of detection are laboratory and copper content. The reverse process class is copper content detection process. The reverse relationship is laboratory - detection - copper content. The subject and object of judgment are copper content and mining value. The reverse process class is value judgment process. The reverse relationship is copper content - judgment - mining value. The subject and object of storage are core and sample library. The reverse process class is core storage process. The reverse relationship is core - stored in - sample library. The reverse process class is included in the implicit class set, and the reverse relationship is included in the implicit relationship set.

[0061] The constraint parameters are extracted from the business rules of the use cases. The constraint parameters include 500 meters, 2.3%, 1%, constant temperature and humidity, and 15~25℃. The 500-meter binding class is drilling, and the attribute is depth. The 2.3% binding class is sample, and the attribute is copper content. The 1% binding class is sample, and the attribute is copper content threshold. The constant temperature and humidity binding class is sample library, and the attribute is temperature and humidity requirement. The 15~25℃ binding class is sample library, and the attribute is temperature range. The binding classes, attributes, and constraint parameters are included in the attribute set accordingly.

[0062] Retrieve the interaction descriptions of entities in the use case scenario. The interaction descriptions include: rock cores are stored in a sample library; copper-bearing veins exist in rock cores; if the copper content is greater than 1%, it has mining value; and granite, shale, and copper-bearing veins are components of rock cores. Rock cores being stored in a sample library is a spatial interaction, with the explicit relationship being "rock cores are stored in a sample library." Copper-bearing veins existing in rock cores is a spatial interaction, with the explicit relationship being "copper-bearing veins are assigned to rock cores." If the copper content is greater than 1%, it has mining value, with the explicit relationship being "copper content > 1% implies mining value." Granite, shale, and copper-bearing veins being components of rock cores is a spatial interaction, with the explicit relationship being "granite, shale, and copper-bearing veins are components of rock cores." Generate the explicit relationships and include them in the explicit relationship set.

[0063] The constraints are extracted from the business rules. These constraints include: if the copper content is greater than 1%, it is considered to have mining value; the core must be stored in a constant temperature and humidity sample library; and the temperature must be controlled between 15 and 25°C. These constraints are formalized into axioms: if the copper content is >1%, it has mining value; the core is stored in a constant temperature and humidity sample library; and the sample library temperature is ∈ [15°C, 25°C]. These axioms are then incorporated into the axiom set.

[0064] Retrieve specific data from the main process, branch processes, and exception processes of the test case. The main process includes drilling in mine area A, collecting rock cores, and obtaining test results. The specific data for drilling in mine area A is mine area A, borehole D-001, and the instance is mine area A, borehole D-001. The specific data for collecting rock cores is samples containing granite G-01, shale S-02, and copper vein C-03, and the instance is samples containing granite G-01, shale S-02, and copper vein C-03. The specific data for the test results is copper content of 2.3%, and the instance is sample instance - copper 2.3%. The branch process is the judgment result, and the specific data for the judgment result is 2.3% > 1%, therefore it has mining value, and the instance is judgment instance - has mining value. The exception process is temperature exceeding the standard, and the specific data for temperature exceeding the standard is temperature 30℃, therefore it is unqualified, and the instance is exception instance - temperature exceeding the standard. The generated instance is added to the instance set.

[0065] Furthermore, the process of detecting conceptual conflicts between different use cases, arbitrating based on the use case with the highest weight, and outputting a set of ontology modeling metaphrases includes the following steps:

[0066] Conflict detection is performed on the candidate class set, implicit class set, implicit relation set, attribute set, explicit relation set, axiom set, and instance set. The definition of the same concept in different use cases is compared to obtain a conflict list, which includes conflicting concepts, conflicting use case pairs, and conflicting content.

[0067] Retrieve the conflict list and the weight tags of each use case. For each conflict, select the use case definition with the higher weight as the final definition. If the weights are the same, take priority for resource exploration use cases. If the weights are the same and both belong to resource exploration use cases or do not belong to resource exploration use cases, take priority for more detailed use cases. Output the set of conflict-free metaphrases after arbitration.

[0068] For the set of conflict-free metaphrases, merge the extraction results of all use cases, remove duplicate metaphrases, and retain the unique definition after arbitration to obtain the set of ontology modeling metaphrases.

[0069] In this embodiment, it is specifically necessary to explain the original use case text for landslide monitoring borehole construction. The text states: A monitoring borehole, 30 meters deep, is installed in landslide B to install displacement sensors. The borehole is cemented, and the core sample is stored as a construction record in a dry, well-ventilated archive room with the room temperature controlled between 5 and 35°C. An early warning is triggered if the displacement rate exceeds 5 mm / day.

[0070] Based on the four-step method for extracting classes, implicit classes, relationships, and attributes, and based on business rules for extracting axioms and use case scenarios for extracting instances, the specific extraction process is consistent with the extraction process for core samples from borehole A in mine area. Therefore, the extracted candidate class set is landslide body B, monitoring borehole, and core sample. The extracted implicit class set is the monitoring borehole deployment process, displacement sensor installation process, cement cementing process, core sample preservation process, temperature control process, and early warning triggering process. The extracted implicit relationship set is: technician-deployment-monitoring borehole, technician-installation-displacement sensor, cement-filling-monitoring borehole, core sample-preservation-archive room, room temperature-controlled at 5~35℃, displacement rate-trigger-early warning. The attribute set is monitoring... Drilling depth = 30 meters, displacement rate - early warning threshold = 5 mm / day, archive room - temperature range = [5℃, 35℃], archive room - humidity requirement = dry and ventilated; the explicit relationship set is that the displacement sensor is installed in the monitoring borehole, the core is stored in the archive room, the displacement rate > 5 mm / day triggers the early warning, and the monitoring borehole is filled with cement; the axiom set is that the early warning is triggered when the displacement rate > 5 mm / day, the core is stored in the dry and ventilated archive room, and the archive room temperature ∈ [5℃, 35℃]; the instance set is landslide body B, monitoring borehole M-001, displacement sensor S-001, cement instance C-20260610, core instance R-001, early warning instance - trigger, and abnormal instance - advanced early warning.

[0071] Core collection from borehole A in mining area is a resource exploration use case, with a weight of 0.9. Borehole construction for landslide monitoring is a geological hazard use case, with a weight of 0.6.

[0072] A set-by-set comparison was performed on the candidate class set, implicit class set, implicit relation set, attribute set, explicit relation set, axiom set, and instance set extracted from the core collection of borehole A in mining area and the construction of boreholes for landslide monitoring. For the core in the candidate class set, the former use case was defined as a geological object containing minerals, while the latter use case was defined as a construction record carrier; the definitions were inconsistent, hence a conflict. For the borehole and monitoring borehole in the candidate class set, the former was defined as a geological engineering entity, while the latter was defined as a sensor installation channel; the definitions were inconsistent, hence a conflict. For the borehole process and deployment process in the implicit class set, the former was defined as the core collection process, while the latter was defined as the sensor installation process; the definitions were inconsistent, hence a conflict. For the borehole depth in the attribute set, the former use case was defined as 500 meters, while the latter use case was defined as 30 meters; the definitions were inconsistent, hence a conflict. Regarding the storage temperature range in the attribute set, the first use case defines it as [15, 25℃], while the second use case defines it as [5, 35℃]. The definitions are inconsistent, hence a conflict. Regarding the storage humidity requirement in the attribute set, the first use case defines it as constant temperature and humidity, while the second use case defines it as dry and ventilated. The definitions are inconsistent, hence a conflict. Regarding the core storage constraint in the explicit relation set, the first use case defines it as stored in a constant temperature and humidity sample library, while the second use case defines it as stored in a dry and ventilated archive room. The definitions are inconsistent, hence a conflict. Regarding the temperature constraint in the axiom set, the first use case defines it as temperature ∈ [15℃, 25℃], while the second use case defines it as temperature ∈ [5℃, 35℃]. The definitions are inconsistent, hence a conflict. Regarding the storage constraint in the axiom set, the first use case defines it as constant temperature and humidity, while the second use case defines it as dry and ventilated. The definitions are inconsistent, hence a conflict. The conflict information is integrated to obtain a conflict list. The conflict concepts in the conflict list include core samples and boreholes in the candidate class set, the drilling process in the implicit class set, the borehole depth, storage temperature range, and storage humidity requirements in the attribute set, core storage constraints in the explicit relation set, and temperature constraints and storage constraints in the axiom set. The conflict use case in the conflict list is the core sample collection from borehole A in the mining area and the drilling construction for landslide monitoring. The conflict content in the conflict list includes the core sample, borehole, drilling process, borehole depth, storage temperature range, storage humidity requirements, core storage constraints, temperature constraints, and the definition of storage constraints in the two use cases.

[0073] Retrieve the conflict list and the weight labels of each use case. For each conflict, select the use case definition with the highest weight as the final definition. Since the weight of core collection from borehole A in mine area is 0.9 and the weight of borehole construction for landslide monitoring is 0.6, the conflict list is based on the definition of core collection from borehole A in mine area as the final definition. Output the set of conflict-free metawords after arbitration.

[0074] The set of conflict-free candidate classes after arbitration is: {Mining Area A, Borehole, Core, Granite, Shale, Copper-bearing Vein, Sample, Landslide B, Monitoring Borehole}; the set of conflict-free implicit classes after arbitration is: {Core collection process, Lithological composition process, Copper content detection process, Valuation process, Core preservation process, Monitoring borehole layout process, Displacement sensor installation process, Cement cementing process, Temperature control process, Early warning triggering process}; the set of conflict-free implicit relationships after arbitration is: {Technician-Collection-Core, Core-Contains-Granite, Shale, Copper-bearing Vein, Laboratory-Detection-Copper Content}. Copper content - determination - mining value, core - stored in - sample library, technician - deployment - monitoring borehole, technician - installation - displacement sensor, cement - filling - monitoring borehole, core - stored in - archive room, room temperature - controlled at 5~35℃, displacement rate - trigger - early warning}; The set of conflict-free attributes after arbitration is: { borehole - depth = 500 meters, sample - copper content = 2.3%, sample - copper content threshold = 1%, sample library - temperature range = [15, 25℃], sample library - humidity requirement = constant, displacement rate - early warning threshold = 5 mm / day, archive room - temperature range =[5,35℃],Archives room-humidity requirement=dry and ventilated}; The set of conflict-free explicit relations after arbitration is: {Core - stored in -sample library, copper-bearing vein - hosted in -core, copper content > 1% - pulled out - has mining value, granite, shale, copper-bearing vein - composed of -core, displacement sensor - installed in -monitoring borehole, core - stored in -archives room, displacement rate > 5mm / day - pulled out - triggers early warning, cement - fills -monitoring borehole}; The set of conflict-free axioms after arbitration is: {Copper content > 1% has mining value, core stored in constant temperature and humidity sample library, sample library Temperature ∈ [15, 25℃], displacement rate > 5 mm / day triggers an early warning, core samples are stored in a dry and ventilated archive room, archive room temperature ∈ [5, 35℃]}; the set of conflict-free instances after arbitration is: {mining area A, borehole D-001, granite G-01, shale S-02, copper-bearing vein C-03, sample instance - copper 2.3%, judgment instance - mining value, landslide body B, monitoring borehole M-001, displacement sensor S-001, cement instance C-20260610, core instance R-001, early warning instance - triggered, anomaly instance - advanced early warning}.

[0075] Furthermore, the reuse screening includes the following steps:

[0076] Traverse the candidate classes in the ontology modeling meta-language set, and search for classes with the same name or synonyms in the general geological ontology one by one. Output reusable classes and classes to be defined. The reusable classes are classes that already exist in the general geological ontology, and the classes to be defined are classes that do not exist in the general geological ontology.

[0077] Traverse the implicit classes in the ontology modeling meta-language set, search for process classes with the same name or synonym in the general geological ontology, and output reusable process classes and undefined process classes. The reusable process classes are process classes that already exist in the general geological ontology, and the undefined process classes are process classes that do not exist in the general geological ontology.

[0078] The explicit and implicit relations in the meta-language set of ontology modeling are traversed. Existing relations are retrieved in the general ontology. Reusable relations and undefined relations are output. The reusable relations are existing relations in the general geological ontology. The undefined relations are relations unique to the geological and mineral resources field of Ningxia.

[0079] Traverse the attributes in the set of meta-elements for ontology modeling, retrieve existing attributes in the general ontology, and output reusable attributes and attributes to be expanded. The reusable attributes are existing attributes in the general geological ontology, and the attributes to be expanded are attributes unique to the geological and mineral resources field of Ningxia.

[0080] Traverse the axioms in the set of meta-languages ​​for ontology modeling, retrieve existing constraints in the general ontology, and output reusable axioms and axioms to be supplemented. The reusable axioms are existing constraints in the general geological ontology, and the axioms to be supplemented are constraints unique to the geological and mineral resources field in Ningxia.

[0081] Traverse the instances in the ontology modeling meta-language set, retrieve existing instances in the general ontology, and output reusable instances and Ningxia-specific instances. The reusable instances are existing instances in the general geological ontology, and the Ningxia-specific instances are instances unique to the field of geology and mineral resources in Ningxia.

[0082] The integrated output reuse filtering results include reusable classes and undefined classes, reusable process classes and undefined process classes, reusable relations and undefined relations, reusable attributes and attributes to be extended, reusable axioms and axioms to be supplemented, as well as reusable instances and Ningxia-specific instances.

[0083] Furthermore, the feature extension includes the following steps:

[0084] For the definition class, based on the arbitration definition in the meta-language set, the hierarchical structure of the class is supplemented to obtain the hierarchical tree of Ningxia characteristic classes;

[0085] For defining process classes, based on the arbitration definition in the meta-language set, the triggering conditions and input / output of the process classes are supplemented to obtain the process class definition with Ningxia characteristics;

[0086] To define the relation, based on the explicit and implicit relations in the meta-language set, we define the starting point class, the ending point class, and the features to obtain the Ningxia-specific relation definition;

[0087] For extended attributes, based on the attributes and axioms in the meta-language set, the specific type and range of attribute values ​​are bound to obtain the Ningxia-specific attribute definition;

[0088] For supplementary axioms, based on the axioms in the set of meta-languages, they are formalized into constraints usable by OWL, resulting in axioms with Ningxia characteristics.

[0089] For instances unique to Ningxia, individuals are created and assigned values ​​based on instances in the metaword set to obtain instances unique to Ningxia;

[0090] Integrate the unique extended results and reusable information to output the extended complete concept set, which includes classes, relations, attributes, axioms and instances.

[0091] Furthermore, the formalization is an improved formalization of Methodology;

[0092] The formalization of the improved Methodology includes the following steps:

[0093] The expanded complete set of concepts, after determining the ontology name, version, and namespace, generates the ontology specification document;

[0094] Organize the class hierarchy, relationship network, process classes and their interaction with entity classes to generate a conceptual model diagram;

[0095] The conceptual model is converted into OWL syntax to obtain an OWL file;

[0096] The reused general ontology fragments are merged with the extended Ningxia-specific fragments to obtain the merged OWL file;

[0097] Consistency was tested using an inference engine, and the axiom derivation was verified to obtain an evaluation report and a revised Ningxia Geological and Mineral OWL ontology.

[0098] Furthermore, the executability verification of the use case includes:

[0099] Import the OWL ontology into the 3D geological modeling system, select test cases one by one from the panoramic test case library for simulation execution, and check whether the concept coverage, relation completeness, reasoning accuracy and modeling completeness all meet expectations during the test case execution process. If they all meet expectations, the test case execution verification is deemed to have passed; otherwise, the test case execution verification is deemed to have failed. The test case execution verification report is fed back to step three, the ontology is corrected and then re-verified.

[0100] The data consistency verification includes:

[0101] The actual geological data is mapped to classes and instances of the OWL ontology. Each axiom constraint of the ontology is checked to see if it is violated by the actual data. If there is no conflict and the data can be correctly classified by the ontology, the data consistency verification is passed. If there is a conflict, a list of conflicting data is generated and fed back to step three. The ontology is corrected and then re-verified.

[0102] Specifically, in this embodiment, the concept coverage rate is the ratio of the number of use case concepts existing in the ontology to the total number of concepts involved in the use cases; a concept coverage rate greater than or equal to 0.95 is considered to meet expectations. The relation completeness rate is the ratio of the number of relations existing in the ontology and correctly connected to the total number of relations involved in the use cases; a relation completeness rate greater than or equal to 0.95 is considered to meet expectations. The reasoning accuracy rate is the ratio of the number of correct axiom derivations to the total number of reasoning operations; a reasoning accuracy rate of 1 is considered to meet expectations. The modeling completeness rate is the ratio of the number of entity classes that meet the modeling conditions to the minimum number of entity classes required for modeling; a modeling completeness rate greater than or equal to 0.95 is considered to meet expectations.

[0103] In this embodiment, it should be specifically noted that the sorting of deliverables includes the following steps:

[0104] According to the Methodology specification, the ontology is split into TBox and ABox, and TBox files and ABox files are output. The TBox includes classes, relations, attributes and axioms, and the ABox includes instances.

[0105] Unify the namespace prefix for TBox and ABox files, generate the ontology header declaration, and standardize the OWL file;

[0106] Extract concept coverage, relation completeness, reasoning accuracy, and modeling completeness as a summary of validation metrics;

[0107] Output the standardized ontology and validation metrics after processing.

[0108] Furthermore, the step of tagging the source use case ID for each ontology element and generating the use case-ontology traceability table includes the following steps:

[0109] Iterate through all classes in the ontology, retrieve the use case ID of the first occurrence of the concept in the panoramic use case library, mark it as the source use case, and output each class and the source use case ID;

[0110] Traverse all relationships in the ontology, retrieve the first occurrence of the use case ID of the relationship in the panoramic use case library, mark it as the source use case, and output each relationship and the source use case ID;

[0111] Iterate through all attributes in the ontology, retrieve the first occurrence of the use case ID of the attribute in the panoramic use case library, mark it as the source use case, and output each attribute and the source use case ID;

[0112] Traverse all axioms in the ontology, retrieve the use case ID of the first occurrence of the requirement corresponding to the axiom in the panoramic use case library, mark it as the source use case, and output each axiom and the source use case ID;

[0113] Traverse all instances in the ontology, retrieve the use case ID of the first occurrence of the instance in the panoramic use case library, mark it as the source use case, and output each instance and the source use case ID;

[0114] Summarize all the tagging results and generate traceability tables in two directions: use case ID-ontology element and ontology element-use case ID. Generate use case-ontology traceability table.

[0115] Output the ontology and use cases with source tags – ontology traceability table.

[0116] In this embodiment, it should be specifically noted that the use case-ontology traceability table includes ontology elements, element types, source use case IDs, and use case names.

[0117] In this embodiment, it should be specifically noted that the generation of the complete ontology delivery package includes:

[0118] The standardized OWL file, use case-ontology traceability table, verification metrics, use case executability verification report, and data consistency verification report are merged and packaged to obtain the initial draft of the delivery package;

[0119] A delivery document is generated based on the initial draft of the delivery package. The delivery document includes an ontology description, a traceability table usage guide, and verification conclusions.

[0120] Package the initial draft of the delivery package and the delivery documents to generate a complete ontology delivery package.

[0121] In this embodiment, it should be noted that the preset values ​​and weights used are selected based on actual needs, and no specific value restrictions are imposed here.

[0122] like Figure 2 As shown, this embodiment provides a use case-driven ontology model construction system for the geological and mineral resources field, including a use case library building module, a meta-arbitration module, an ontology construction module, a dual closed-loop verification module, a delivery and organization module, and an iterative update module.

[0123] The use case library building module performs structured collection of original business use cases from the entire business chain of Ningxia Geology and Mineral Resources, and establishes a panoramic use case library for Ningxia Geology and Mineral Resources based on the structured collection results.

[0124] The meta-arbitration module extracts classes, implicit classes, relationships, and attributes from the use cases in the panoramic use case library using a four-step method, extracts axioms based on business rules, extracts instances based on use case scenarios, detects conceptual conflicts between different use cases, arbitrates the use cases with higher weights, and outputs a set of ontology modeling meta-terms.

[0125] The ontology construction module obtains the ontology modeling meta-language set and the general geological ontology. After reuse filtering, feature expansion and formalization, the Ningxia Geological and Mineral Resources OWL ontology is obtained.

[0126] The dual-loop verification module is based on the Ningxia Geology and Mineral Resources OWL ontology, actual geological data, and use cases in the panoramic use case library. It uses a 3D geological modeling system to verify the executability of use cases and the consistency of data, and outputs an ontology that has passed both dual-loop verifications.

[0127] The delivery processing module processes the deliverables of the ontology that has passed the dual closed-loop verification, marks the source use case ID for each ontology element, generates a use case-ontology traceability table, and then outputs the complete ontology delivery package.

[0128] For newly added Ningxia geological business use cases, the iterative update module first completes structured data collection and adds the collected use cases to the Ningxia Geological and Mineral Panorama Use Case Library. Then, it sequentially executes meta-arbitration, ontology construction, double closed-loop verification, and delivery organization. Finally, it outputs the updated OWL ontology, the updated use case-ontology traceability table, and the synchronously updated Ningxia Geological and Mineral Panorama Use Case Library.

[0129] Specifically, in this embodiment, the system also includes a Ningxia geological and mineral panoramic use case library and a cloud database. The Ningxia geological and mineral panoramic use case library is used to structurally store Ningxia geological and mineral panoramic use cases, and the cloud database is used to store data information of each module of the system.

[0130] In this embodiment, it should be specifically noted that the use case library building module is connected to the meta-language arbitration module, the dual-loop verification module, and the iterative update module. The meta-language arbitration module, the ontology building module, the dual-loop verification module, and the delivery organization module are connected sequentially. The dual-loop verification module is connected to the ontology building module, and the iterative update module is connected to the use case library building module. All modules in the system are connected to the cloud database.

[0131] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for constructing an ontology model in the geological and mineral resources field based on use case-driven approaches, characterized in that: Includes the following steps: Step 1: Conduct structured collection of original business use cases across the entire business chain of Ningxia Geology and Mineral Resources, and establish a panoramic use case library for Ningxia Geology and Mineral Resources based on the structured collection results; Step 2: Extract classes, implicit classes, relationships, and attributes from the use cases in the panoramic use case library using a four-step method; extract axioms based on business rules; extract instances based on use case scenarios; detect conceptual conflicts between different use cases; arbitrate based on use cases with higher weights; and output a set of ontology modeling metaphrases. Step 3: Obtain the set of ontology modeling meta-terms and the general geological ontology. After reuse filtering, feature expansion and formalization, the Ningxia Geological and Mineral Resources OWL ontology is obtained. Step 4: Based on the Ningxia Geological and Mineral Resources OWL ontology, actual geological data, and use cases in the panoramic use case library, use a 3D geological modeling system to verify the executability of use cases and the consistency of data, and output an ontology that has passed both closed-loop verifications. Step 5: Organize the deliverables for the ontology that has passed the double closed-loop verification, mark the source use case ID for each ontology element, generate the use case-ontology traceability table, and then output the complete ontology delivery package. Step 6: For the newly added Ningxia geological business use cases, first execute Step 1 to complete the structured data collection and add the collected use cases to the Ningxia Geological and Mineral Panorama Use Case Library. Then execute Steps 2 to 5 in sequence. Finally, output the updated OWL ontology, the updated use case-ontology traceability table, and the synchronously updated Ningxia Geological and Mineral Panorama Use Case Library.

2. The method for constructing an ontology model in the geological and mineral resources field based on use case-driven approach according to claim 1, characterized in that, The original business use cases of the Ningxia Geological and Mineral Resources full business chain include use case name, participants, main process, branch process, abnormal process, preconditions, postconditions, and business rules. The structured data collection process involves confirming whether the information contained in the original business use cases of the entire business chain of Ningxia Geology and Mineral Resources is complete. If the information is complete, the use case is retained; if it is incomplete, the use case is removed. The Ningxia geological and mineral panoramic use case library established based on structured acquisition results includes: Each use case collected through structured data acquisition is assigned a weight tag and named in the format of use case name-time-weight; All named use cases are categorized into five sets: resource exploration, mine management, disaster prevention, environmental protection, and data services. A panoramic use case library for Ningxia's geology and mineral resources is established, which contains the five category sets.

3. The method for constructing an ontology model in the geological and mineral resources field based on use case-driven approach according to claim 1, characterized in that, The process of extracting classes, implicit classes, relationships, and attributes from the use cases in the panoramic use case library based on a four-step method, extracting axioms based on business rules, and extracting instances based on use case scenarios includes the following steps: Candidate nouns are filtered from the entire use case text, technical products are removed, and geological entities are retained to obtain a set of candidate classes. The verbs and their subjects and objects are fully screened from the use case text. The process classes are analyzed by reverse deducing the verbs to obtain a set of implicit classes. Based on the reverse deduction of the verb subject-object pairs, the set of implicit relationships is obtained. Extract constraint parameters from the business rules of the use case, bind them as attributes of the class, and generate an attribute set; Retrieve the interaction descriptions of entities in the use case scenario, establish explicit relationships based on the spatial and logical interactions between entities, and generate a set of explicit relationships; Extract constraints from business rules, formalize them into axioms, and generate a set of axioms; Retrieve specific data from the main flow, branch flow, and exception flow of the test case, extract instances from the specific values ​​of the test case scenario, and generate an instance set.

4. The method for constructing an ontology model in the geological and mineral resources field based on use case driving as described in claim 3, characterized in that, The process of detecting conceptual conflicts between different use cases, arbitrating based on the use case with the highest weight, and outputting a set of ontology modeling metaphrases includes the following steps: Conflict detection is performed on the candidate class set, implicit class set, implicit relation set, attribute set, explicit relation set, axiom set, and instance set. The definition of the same concept in different use cases is compared to obtain a conflict list, which includes conflicting concepts, conflicting use case pairs, and conflicting content. Retrieve the conflict list and the weight tags of each use case. For each conflict, select the use case definition with the higher weight as the final definition. If the weights are the same, take priority for resource exploration use cases. If the weights are the same and both belong to resource exploration use cases or do not belong to resource exploration use cases, take priority for more detailed use cases. Output the set of conflict-free metaphrases after arbitration. For the set of conflict-free metaphrases, merge the extraction results of all use cases, remove duplicate metaphrases, and retain the unique definition after arbitration to obtain the set of ontology modeling metaphrases.

5. The method for constructing an ontology model in the geological and mineral resources field based on use case-driven approach according to claim 1, characterized in that, The reuse screening includes the following steps: Traverse the candidate classes in the ontology modeling meta-language set, and search for classes with the same name or synonyms in the general geological ontology one by one. Output reusable classes and classes to be defined. The reusable classes are classes that already exist in the general geological ontology, and the classes to be defined are classes that do not exist in the general geological ontology. Traverse the implicit classes in the ontology modeling meta-language set, search for process classes with the same name or synonym in the general geological ontology, and output reusable process classes and undefined process classes. The reusable process classes are process classes that already exist in the general geological ontology, and the undefined process classes are process classes that do not exist in the general geological ontology. The explicit and implicit relations in the meta-language set of ontology modeling are traversed. Existing relations are retrieved in the general ontology. Reusable relations and undefined relations are output. The reusable relations are existing relations in the general geological ontology. The undefined relations are relations unique to the geological and mineral resources field of Ningxia. Traverse the attributes in the set of meta-elements for ontology modeling, retrieve existing attributes in the general ontology, and output reusable attributes and attributes to be expanded. The reusable attributes are existing attributes in the general geological ontology, and the attributes to be expanded are attributes unique to the geological and mineral resources field of Ningxia. Traverse the axioms in the set of meta-languages ​​for ontology modeling, retrieve existing constraints in the general ontology, and output reusable axioms and axioms to be supplemented. The reusable axioms are existing constraints in the general geological ontology, and the axioms to be supplemented are constraints unique to the geological and mineral resources field in Ningxia. Traverse the instances in the ontology modeling meta-language set, retrieve existing instances in the general ontology, and output reusable instances and Ningxia-specific instances. The reusable instances are existing instances in the general geological ontology, and the Ningxia-specific instances are instances unique to the field of geology and mineral resources in Ningxia. The integrated output reuse filtering results include reusable classes and undefined classes, reusable process classes and undefined process classes, reusable relations and undefined relations, reusable attributes and attributes to be extended, reusable axioms and axioms to be supplemented, as well as reusable instances and Ningxia-specific instances.

6. The method for constructing an ontology model in the geological and mineral resources field based on use case driving as described in claim 5, characterized in that, The feature extension includes the following steps: For the definition class, based on the arbitration definition in the meta-language set, the hierarchical structure of the class is supplemented to obtain the hierarchical tree of Ningxia characteristic classes; For defining process classes, based on the arbitration definition in the meta-language set, the triggering conditions and input / output of the process classes are supplemented to obtain the process class definition with Ningxia characteristics; To define the relation, based on the explicit and implicit relations in the meta-language set, we define the starting point class, the ending point class, and the features to obtain the Ningxia-specific relation definition; For extended attributes, based on the attributes and axioms in the meta-language set, the specific type and range of attribute values ​​are bound to obtain the Ningxia-specific attribute definition; For supplementary axioms, based on the axioms in the set of meta-languages, they are formalized into constraints usable by OWL, resulting in axioms with Ningxia characteristics. For instances unique to Ningxia, individuals are created and assigned values ​​based on instances in the metaword set to obtain instances unique to Ningxia; Integrate the unique extended results and reusable information to output the extended complete concept set, which includes classes, relations, attributes, axioms and instances.

7. The method for constructing an ontology model in the geological and mineral resources field based on use case-driven approach according to claim 6, characterized in that, The formalization is an improved formalization of Methodology; The formalization of the improved Methodology includes the following steps: The expanded complete set of concepts, after determining the ontology name, version, and namespace, generates the ontology specification document; Organize the class hierarchy, relationship network, process classes and their interaction with entity classes to generate a conceptual model diagram; The conceptual model is converted into OWL syntax to obtain an OWL file; The reused general ontology fragments are merged with the extended Ningxia-specific fragments to obtain the merged OWL file; Consistency was tested using an inference engine, and the axiom derivation was verified to obtain an evaluation report and a revised Ningxia Geological and Mineral OWL ontology.

8. The method for constructing an ontology model in the geological and mineral resources field based on use case-driven approach according to claim 1, characterized in that, The executability verification of the use cases includes: Import the OWL ontology into the 3D geological modeling system, select test cases one by one from the panoramic test case library for simulation execution, and check whether the concept coverage, relation completeness, reasoning accuracy and modeling completeness all meet expectations during the test case execution process. If they all meet expectations, the test case execution verification is deemed to have passed; otherwise, the test case execution verification is deemed to have failed. The test case execution verification report is fed back to step three, the ontology is corrected and then re-verified. The data consistency verification includes: The actual geological data is mapped to classes and instances of the OWL ontology. Each axiom constraint of the ontology is checked to see if it is violated by the actual data. If there is no conflict and the data can be correctly classified by the ontology, the data consistency verification is passed. If there is a conflict, a list of conflicting data is generated and fed back to step three. The ontology is corrected and then re-verified.

9. The method for constructing an ontology model in the geological and mineral resources field based on use case-driven approach according to claim 1, characterized in that, The process of marking each ontology element with a source use case ID and generating a use case-ontology traceability table includes the following steps: Iterate through all classes in the ontology, retrieve the use case ID of the first occurrence of the concept in the panoramic use case library, mark it as the source use case, and output each class and the source use case ID; Traverse all relationships in the ontology, retrieve the first occurrence of the use case ID of the relationship in the panoramic use case library, mark it as the source use case, and output each relationship and the source use case ID; Iterate through all attributes in the ontology, retrieve the first occurrence of the use case ID of the attribute in the panoramic use case library, mark it as the source use case, and output each attribute and the source use case ID; Traverse all axioms in the ontology, retrieve the use case ID of the first occurrence of the requirement corresponding to the axiom in the panoramic use case library, mark it as the source use case, and output each axiom and the source use case ID; Traverse all instances in the ontology, retrieve the use case ID of the first occurrence of the instance in the panoramic use case library, mark it as the source use case, and output each instance and the source use case ID; Summarize all the tagging results and generate traceability tables in two directions: use case ID-ontology element and ontology element-use case ID. Generate use case-ontology traceability table. Output the ontology and use cases with source tags – ontology traceability table.

10. A use case-driven ontology model construction system for the geological and mineral resources domain, employing the use case-driven ontology model construction method for the geological and mineral resources domain as described in any one of claims 1-9, characterized in that, It includes a use case library building module, a meta-arbitration module, an ontology construction module, a dual-loop verification module, a delivery organization module, and an iterative update module; The use case library building module performs structured collection of original business use cases from the entire business chain of Ningxia Geology and Mineral Resources, and establishes a panoramic use case library for Ningxia Geology and Mineral Resources based on the structured collection results. The meta-arbitration module extracts classes, implicit classes, relationships, and attributes from the use cases in the panoramic use case library using a four-step method, extracts axioms based on business rules, extracts instances based on use case scenarios, detects conceptual conflicts between different use cases, arbitrates the use cases with higher weights, and outputs a set of ontology modeling meta-terms. The ontology construction module obtains the ontology modeling meta-language set and the general geological ontology. After reuse filtering, feature expansion and formalization, the Ningxia Geological and Mineral Resources OWL ontology is obtained. The dual-loop verification module is based on the Ningxia Geology and Mineral Resources OWL ontology, actual geological data, and use cases in the panoramic use case library. It uses a 3D geological modeling system to verify the executability of use cases and the consistency of data, and outputs an ontology that has passed both dual-loop verifications. The delivery processing module processes the deliverables of the ontology that has passed the dual closed-loop verification, marks the source use case ID for each ontology element, generates a use case-ontology traceability table, and then outputs the complete ontology delivery package. For newly added Ningxia geological business use cases, the iterative update module first completes structured data collection and adds the collected use cases to the Ningxia Geological and Mineral Panorama Use Case Library. Then, it sequentially executes meta-arbitration, ontology construction, double closed-loop verification, and delivery organization. Finally, it outputs the updated OWL ontology, the updated use case-ontology traceability table, and the synchronously updated Ningxia Geological and Mineral Panorama Use Case Library.

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