CN114492379A - Digital standard meta-model based on semantics and application method thereof - Google Patents

Abstract

The invention relates to a digital standard meta-model based on semantics and an application method thereof, wherein the meta-model comprises three parts of data contents, namely a DSS general ontology, technical description data and structure and data constraint, which are established based on a unified semantic framework, and semantic elements in the unified semantic framework comprise a DSS composition class, a DSS object relationship, a DSS object attribute and a DSS object instance; the DSS is grouped into classes, including a primary class and a secondary class, for generalizing concepts. The invention realizes the content expression of standard elements based on uniform semantics, automatically reads, understands and processes DSS through a computer, realizes the automatic comparison between DSS models or DSS instances, automatically judges the conformity of products or processes and batch products, and performs inference decision and automatic control based on DSS; through a registration, reference and inheritance mechanism, the sharing and reuse of standard elements are realized, and the efficiency of digital design and standard system revision and standard implementation benefit are improved.

Description

Digital standard meta-model based on semantics and application method thereof

Technical Field

The invention relates to the application of semantic technology in the standardization field, and also relates to quality management and demand engineering technology, in particular to a digital standard meta-model based on semantics and an application method thereof.

Background

The standard is an important basis for product design production and test acceptance. The standard in the traditional form generally refers to a standard document (which is written based on natural language and uses paper as a common carrier, or is converted into a digital form in a computer after being scanned) for human reading and understanding, the standard document mainly consists of elements such as a preamble, a range, a term definition and the like, and the text structure of the standard document is mostly chapters, sections, bars, items and the like.

With the advent and development of computer technology, and in particular computer graphics, Standards have been developed in more and more fields for the main purpose of computer reading, understanding and processing, such Standards being referred to as Digital Standards & Specifications (DSS) for short. The fields of use of the digitization standard include: digital design and manufacture, software testing, artificial intelligence, automatic control, knowledge management, and the like.

The existing technical scheme for digitalizing the standard (index standard document) to form the digital form standard mainly comprises the following steps:

according to the first scheme, standard elements (including technical indexes) are segmented and extracted, XML is used for carrying out structured expression to form a structured template as a digital form standard, and then different mode files (Schema) are established (configured) to check the format of the standard elements so as to realize the structuring and query retrieval of the standard contents and the technical indexes.

And in the second scheme, based on a structured template formed by the standard document or the first scheme, the element ternary group data contained in the template is extracted, and a corresponding knowledge graph is established as a digital form standard so as to realize the query of standard contents and associated objects with various entity relationships.

Compared with the digital standard, the digital form standard obtained by adopting the scheme has the following defects:

1. the digital form standard lacks complete and unified standard element semantic relation, has no clear and unified verification rule and/or judgment rule, and is difficult to realize automatic obtaining of a conformance result;

2. the requirement in the digital form standard has the defect of incomplete structural information, and the defect is usually represented by that related premises or product grades are not structured and associated in the requirement, so that the automatic obtaining of a conformance result under the same premises or product grades cannot be ensured;

for example: the requirement for the melting point of the product in the digital format standard, without structuring and correlating the relevant preconditions "atmospheric conditions tested", may result in the requirement being misused or the compliance results based on the requirement being invalid;

another example is: in the digital form standard, for products with grading and grading requirements, structuring and association of corresponding requirements are not carried out according to product grades, so that risks of mistakenly comparing and judging products with different grades are caused, and automatic grading and grading of the products are difficult to accurately support;

3. when multiple reference relationships exist between digital form standards, the requirement in the digital form standard is ambiguous and the inheritance and reuse of the requirement cannot be accurately realized as the complexity of the reference relationships increases.

The information disclosed in this background section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.

Disclosure of Invention

Aiming at the defects in the prior art, the invention aims to provide a digital standard meta-model based on semantics and an application method thereof, wherein the digital standard meta-model realizes the content expression of standard elements based on unified semantics, automatically reads, understands and processes DSS through a computer, realizes the automatic comparison between DSS models or DSS instances, automatically judges the conformity of products or processes and batch products, and performs inference decision and automatic control based on DSS; through registration, citation and inheritance mechanisms, the sharing and reuse of standard elements are realized, the efficiency of digital design and standard system revision and the standard implementation benefit are improved, and the method is suitable for various application occasions of digital standards, in particular to the digital application of product standards and technical specifications.

In order to achieve the purpose, the invention adopts the technical scheme that:

the invention provides a semantic-based digital standard meta-model (referred to as meta-model for short) for assisting in building a DSS model (digital standard model) or a DSS instance (digital standard instance), which comprises three parts of data contents, namely a DSS general ontology, technical description data, structure and data constraint, built based on a unified semantic framework, as shown in FIG. 1, wherein:

the unified semantic framework is expressed by adopting a principal and predicate object (SPO) triple format, and semantic elements of the unified semantic framework comprise a DSS (direct sequence spread spectrum) composition class, a DSS object relationship, a DSS object attribute and a DSS object instance;

the DSS object instance is a DSS component class, a DSS object relationship, or a DSS object attribute instance, an expression format of the DSS object instance is preset in the meta-model, and the DSS object instance is generated only when the DSS model is generated based on the meta-model or generated based on the DSS model, for example, the DSS model of an automatic beverage filling process is generated based on the meta-model, the automatic beverage filling process being one DSS object instance of a core topic;

in the predicate SPO triplet, the DSS object relationship is located in a predicate P part, and specifically includes: the relationship among the sub-components, the relationship hasPart, the type relationship type, the attribute relationship hasProperty, the value relationship hasValue, the component relationship consistsOf, the component logic, the relationship aimAT, the conformity relationship conformTo, the requirement relationship hasRequirement, the core subject relationship hasCoreSubject, and the like;

the DSS general ontology comprises a DSS basic concept (class), an object relation, common DSS object attributes, a basic axiom and a function and a metering unit ontology;

further, when a specific domain is determined, the DSS common ontology includes a domain ontology corresponding to the specific domain;

the method and steps for establishing the DSS general ontology and the domain ontology can be implemented according to the prior art and are not detailed;

the technical description data comprises requirements, rules and meta-model self attribute data;

the structure and data constraints comprise related constraints on DSS general ontology and technical description data, the related constraints comprise data type, value range and cardinality constraints, and the structure and data constraints can be implemented according to the prior art and are not detailed.

On the basis of the above technical solution, as shown in fig. 2, the DSS forms a class for generalizing concepts, which specifically includes: a primary class and a secondary class;

the main classes include: core subject, core attribute, related subject, related attribute, requirement and decision item; the secondary classes include: rules, conditions, condition sets, statements, preconditions, results, execution terms.

On the basis of the technical scheme, as shown in fig. 3, the core theme (coresubmit), which corresponds to the standardized object in the standard document and is unique in a DSS model or DSS instance, is classified into a product-class core theme, a process-class core theme and other core-class themes according to types; for example, the product core theme may be a watch, the process core theme may be an automatic beverage filling process, and the other core themes may be water environment, risk conditions, health evaluation, and the like;

-said core attributes (coreAttribute) corresponding to DSS object attributes owned by core topics, a core topic having at least one core attribute; for example, the product class core theme may have two core attributes of product net weight and product color, and the process class core theme may have two core attributes of process start time and process total time consumption;

as shown in fig. 3, the related topic (RelevantSubject) corresponds to related factors that may affect core attributes, where a core attribute has at least one related topic, and the related factors that may affect the core attributes include environment, device, method, and/or person, etc.; for example, when the core attribute is the melting point of the product, relevant factors influencing the core attribute include a test site in environmental factors and a test method in method factors;

-said correlation attributes (RelevantAttribute), which correspond to DSS object attributes owned by the correlation topics, for constituting a required premise, a correlation topic having at least one correlation attribute; for example, the related theme is that there may be three related attributes of temperature, humidity, atmospheric pressure when the environment, there may be two related attributes of micrometer precision, voltmeter range when the related theme is the apparatus;

as shown in fig. 3, the core attribute and the related attribute are uniformly attributed to a topic attribute (topic attribute) in the meta-model, the topic attribute is managed as a class object in the DSS model or the DSS instance, the topic attribute is associated with the test method, and the type of the topic attribute is divided into a quantitative attribute, a qualitative attribute, and an identification attribute, where:

examples of quantitative attributes are as follows: mass (absolute magnitude), altitude (relative magnitude), heating time (relative magnitude), product yield (ratio) of the object;

examples of qualitative attributes are as follows: whether the seat has a heating function or not and whether the automobile paint surface is scratched or not are judged by 1 and 0;

examples of identifying attributes are as follows: employee ID (numeric), achievement ranking (numeric), car color (character), company address (character);

as shown in fig. 5, the condition set (ConditionSet) includes m components related by element relationship, m is greater than or equal to 1, the component is a condition or condition set, the element logic of the condition set is and or, and the logic result of the condition set is obtained by the operation of each component in the condition set according to the element logic; namely: the component in the condition group can only have one condition or only one condition group, and also can be a plurality of conditions and/or condition groups, and the condition groups can form nesting; for example: in the example shown in fig. 5, the condition group 1 includes 3 components related by an element relationship, namely, a condition 1, a condition 2, and a condition group 2, where each component is related by an element relationship to the condition group 1, and each component (referring to the condition 1, the condition 2, and the condition group 2) in the condition group 1 obtains a logical result of the condition group after performing an element logical operation, where the element logical is "and" or "; the components and constituent logic in condition set 2 are not shown;

the Condition (Condition) is constituted by a statement, the statement being true, the logical result of the Condition being 1, the statement being false, the logical result of the Condition being 0;

as shown in fig. 6, the Statement (Statement) is used for describing things, the semantics of which are equivalent to Statement sentences of natural language, and the Statement (Statement) is constructed in a triple format, and specifically includes:

a first triple for expressing a subject part, wherein the associated object is the subject part, and the associated relation is the main relation (hasSubject);

a second triple for expressing a predicate part, wherein the associated object is a "predicate part", and the associated relationship is a "predicate relationship (hasPredicate)";

a third triple for expressing an object part, wherein the associated object is an object part, and the associated relationship is a guest relationship (hasObject);

the predicate portion of the statement may take on any of the following values: greater than, less than, not greater than, not less than, equal to, assign, include, exist;

as shown in fig. 3 and 4, the Requirement (Requirement) includes a precondition and at least one validation rule, and when the logic result of the precondition is true, the compliance result of the Requirement is obtained according to the validation rule; the requirement has a necessity attribute, and is used for setting the requirement as any one of a mandatory requirement, a recommended requirement and an optional requirement according to the attribute, and the necessity attribute can be used for realizing judgment control in a reference or judgment rule;

one requirement is associated with only one core attribute by a targeting relationship and one core attribute is associated with at least one requirement by a targeting relationship, i.e.: core attributes and requirements are associated by aiming at the relationship, one core attribute can be associated with a plurality of requirements, but one requirement is associated with only one core attribute;

as shown in fig. 4, the precondition (Prerequisite) is a condition set in which the logic of the component is default to "and", and a logic result of the precondition is obtained by performing logical operation on each component in the condition set according to the component; for example: fig. 4 illustrates a premise that when n is 3, three conditions and one condition group are included, and then each component in the condition group is a condition 1, a condition 2, a condition 3, and a condition group 1, the logic of the component is default to "and", and the logic result of the premise is obtained after each component in the condition group is operated according to the logic of the component; it should be noted that the condition set defaults to and only when taken as a precondition, that is: the premise is a set of conditions that satisfy a specific rule that means that the constituent logic defaults to (can only be) and;

as shown in FIG. 3, the statements in the set of conditions that make up the premise, all of their (meaning statements) subject parts come from related attributes; for example as shown in fig. 7:

the statement that the environmental temperature is equal to 24 ℃ constitutes a condition 1, the statement that the subject part is the environmental temperature, the statement that the environmental temperature is a relevant attribute, the statement that the predicate part is equal to, the statement that the object part is 24, the measurement unit of the object part is obtained by inheriting the measurement unit of the super class of the temperature by the environmental temperature, and the measurement unit body in the DSS general body specifies that the measurement unit of the temperature is the temperature;

statement that "atmospheric pressure is less than 105 kPa" constitutes condition 2, the statement has a subject portion of atmospheric pressure, which is a related attribute, a statement has a predicate portion of "less than", and an object portion of 105, the measurement unit of the object portion is obtained by inheriting the measurement unit of the excess type "pressure" from the atmospheric pressure, and the measurement unit body in the DSS common body specifies that the measurement unit of the "pressure" is kPa;

the two conditions can form a condition group, when the logic of the component of the condition group is AND, the condition group 'environment temperature is equal to 24 ℃ (and) atmospheric pressure is less than 105 kPa' forms a precondition 1;

as shown in fig. 4, the validation rule (ValidationRule) is composed of a set of conditions, a result, and an execution item, the result is a set of statements about compliance, the execution item is a set of statements about actions, when the set of conditions is true, the statements about compliance are valid, and the actions included in the statements about actions are executed; the execution items are optional contents, and the condition group and the result are optional contents;

in another alternative embodiment, the validation rule (ValidationRule), consisting of a value range, a result and an execution term, the statement on compliance is valid when the value range is satisfied, the action contained in the statement on action is executed; the execution item is optional content, and the value range and the result are necessary content; this embodiment may be preferred;

the value Range (Range) represents the value Range allowed by the theme property, and the value Range is a Range value or a point value:

as an alternative embodiment, the results may be reduced from the statements to a compliance and its corresponding values; for example: the result is 'the conformity result of the apple fruit diameter requirement is-conformity', because the requirement indicates that the target is 'the apple fruit diameter', the result can be directly expressed by the triple < rule 1: the conformity result: conformity > or < rule 1: the conformity 1>, wherein the rule 1 is the conformity verification rule about the apple fruit diameter requirement;

as shown in fig. 8, the Decision item (Decision) includes at least one Decision rule (Decision rule), and the Decision item associates the Decision item with the relationship and obtains an overall compliance result of the Decision item according to the Decision rule;

the decision-making item may be any one of: the conformity of the standard, the conformity of the product, the conformity of the batch product and the conformity of the product grade;

as shown in fig. 8, the decision rule (DecisionRule) is the same as the validation rule (ValidationRule); the difference between the two is that the specific values of the condition group and the target of the result are different, specifically:

the subject part of the condition in the verification rule must be a core attribute, and the subject part of the condition in the judgment rule is a compliance result of requirements related to decision items; for example:

the method comprises the following steps that verification rules for judging whether apples are superior products are possible to be multiple, wherein one verification rule is that the requirements of the superior products are met when the diameter of the apples is 95-105 mm, the subject part is the core attribute of the diameter of the apples, and each verification rule can form a required conformance result;

the decision item at this moment is the conformity of the superior apple product, the judgment rule is that when the total number of the non-conformity of the detected apple to all the requirements of the superior apple product is 0, the detected apple is judged to be the superior apple product, the judgment rule is used for obtaining the overall conformity result of the decision item, and the subject part is the total number of the non-conformity of all the requirements related to the decision item 'the conformity of the superior apple product';

verifying the conformity of the result in the rule aiming at the object as a requirement, and judging the integral conformity of the result in the rule aiming at the object as a decision item;

the validation Rule (ValidationRule) and the predicate Rule (DecisionRule) are collectively attributed to rules (Rule) in a secondary class in the meta-model.

On the basis of the above-mentioned semantic-based digital standard meta-model, as shown in fig. 9, the present invention further provides an application method of the semantic-based digital standard meta-model, where the application method is used for generating a target DSS based on a reference source, and the application method includes the following steps:

step S901, selecting a reference source, and referring to a DSS general ontology in the reference source;

when the target DSS to be generated is a DSS model, the reference source selects a DSS meta model; for example: the target DSS to be generated is a watch DSS model, and the selected DSS meta model is the general specification of the timing device DSS;

when the target DSS to be generated is a DSS instance, selecting a DSS model according to the reference source; the DSS instance means that the DSS is already a specific standard or detailed specification, such as: the target DSS to be generated is the mechanical watch standard of a specific model of a specific brand of a specific manufacturer, and the selected DSS model is the mechanical watch DSS general standard of the manufacturer;

step S902, establishing a core theme and a core attribute;

determining a main class related to a core theme of the target DSS through a theme and attribute establishing unit, and establishing the core theme of the target DSS as a new subclass under a super class by taking the main class related to the core theme of the target DSS as the super class in the cited DSS general ontology;

furthermore, when the core theme of the target DSS is a product class core theme or a process class core theme, establishing a physical component of the core theme, wherein the physical component is associated with the core theme through a sub-element relationship, and the physical component comprises a part or a sub-process; establishing an abstract component of the core theme, wherein the abstract component is associated with the core theme through a component relation and comprises functions, interfaces, structures, characteristics and the like;

after the core theme is established, acquiring the core attribute owned by the core theme through the theme and attribute establishing unit, wherein the core attribute is from inheritance of the super-class owned DSS object attribute on one hand, and from a newly added DSS object attribute on the other hand, and the core attribute is associated with the core theme and inherits the metering unit from the metering unit body in the DSS general body;

step S903, establishing a related theme and related attributes;

acquiring core attributes of the target DSS through a theme and attribute establishing unit, acquiring relevant factors influencing the core attributes, and establishing relevant themes one by one according to the relevant factors;

after the related subject is established, acquiring related attributes owned by the related subject through a subject and attribute establishing unit, wherein the related attributes are from inheritance of the super-class owned DSS object attributes on one hand and from newly added DSS object attributes on the other hand, and the related attributes are associated with the related subject and inherit the metering units from the metering unit bodies in the DSS general bodies;

step S904, establishing requirements item by item;

acquiring core attributes of the target DSS through a requirement establishing unit, establishing requirements for the core attributes one by one, establishing a precondition first, establishing a verification rule item by item and setting a necessity attribute finally when establishing the requirements; as an alternative embodiment, the method further comprises setting a weight coefficient for the requirement;

further, the concrete steps of establishing the premise are as follows:

establishing a condition group of which the component logic defaults to AND, and determining components included in the condition group, wherein when the components are conditions, subject parts of the conditions are all from related attributes, and when the components are condition groups, repeating the step until a nested structure of the condition groups is completed;

further, the specific steps of establishing the verification rule are as follows:

determining condition groups, results and execution items in the verification rules in sequence, and then completing the establishment of the verification rules;

or, sequentially determining a value range, a result and an execution item in the verification rule, and then completing the establishment of the verification rule;

step S905, establishing a decision item;

when the decision item is established, a target DSS is obtained through a decision item establishing unit, the decision item is determined according to the purpose of the target DSS, all requirements associated with the decision item are determined, and a judgment rule is established according to all the requirements;

further, the specific steps for determining all requirements associated with a decision item are as follows:

determining all involved core attributes according to decision items;

determining all requirements involved according to all core attributes;

further, the specific steps of establishing the decision rule according to all the requirements are as follows:

determining condition groups, results and execution items in the judgment rules in sequence, and then finishing the establishment of the judgment rules;

or, sequentially determining the value range, the result and the execution item in the judgment rule, and then completing the establishment of the judgment rule.

On the basis of the above technical solution, as shown in fig. 9, the method further includes the following steps:

step S906, determining the self attribute data of the target DSS, determining a general ontology element and identifying;

the self attribute data at least comprises a name, identification information, a version and a creator;

determining and identifying the newly added and registered universal body elements or determining and identifying the revised and referred universal body elements according to the specific requirements of submitting a registration application or submitting a revision application to a management organization;

step S907, defining structure and data constraints;

using SHACL or RDFS (RDF schema) or OWL to complete defining structure and data constraint;

the SHACL is a data constraint language specification of W3C, a language for verifying RDF graphs according to a set of conditions, and verifies whether the data graphs satisfy the conditions according to defined RDF shape graphs;

RDFS (rdf schema) is a definition language for defining metadata attribute elements to describe resources, RDFS does not provide actual application-specific classes and attributes, but rather provides a framework that describes application-specific classes and attributes; RDFS can be thought of as an ontology language that describes class and attribute (binary relations), value domain and definition domain constraints on attributes, and sub-class and sub-attribute implication relations;

OWL is a semantic Web language designed to represent rich and complex knowledge about entities, relationships between entities; OWL is a language based on computational logic, and knowledge represented by OWL can be reasoned (deductive reasoning) through a computer program so as to verify the consistency of knowledge or make implicit knowledge explicit;

step S908, form and content check;

performing formal inspection based on the structure and data constraints, and then performing content inspection according to technical content specified in the reference source to modify the violations;

the form check includes: data completeness check, semantic consistency verification and constraint conformity check;

the content inspection includes: the method comprises the following steps of required consistency verification, consistency verification of a verification rule, and consistency verification of a judgment rule, wherein the consistency verification is checked in a comparison mode;

after the form and the content are checked to be qualified, generating the target DSS into an independent DSS file and submitting the independent DSS file to a DSS management organization for examination and release;

the file format of the DSS file can be a file format generated by RDF Turtle, RDF-Star, Notation 3, JSON-LD or other Serialization (Serialization) modes;

step S909, the DSS administration checks and numbers to issue;

the DSS management organization reviews the compliance of the submitted DSS file with other related DSS and decides whether to accept the registration of the body element submitted as a general class or a general attribute;

the approved DSS file is published by a DSS management organization in a serial number manner, and the universal body is updated according to the requirement;

the number issuing means that: the management organization brings the common ontology registered by the independent DSS file into the common ontology database, and assigns a unique IRI to each object, so as to realize the reuse of the DSS ontology object, and the issued DSS model or instance can realize the reference through the network and push the prompt information to the reference party after the change.

On the basis of the above semantic-based digital standard meta-model, as shown in fig. 10, the present invention further provides an application method of the semantic-based digital standard meta-model, wherein the application method is used for providing a compliance report or a comparison report based on the comparison between a reference object and a target object;

when the reference object is a DSS model, the target object may be a DSS model or a DSS instance;

when the reference object is a DSS instance, the target object may be a DSS instance;

which comprises the following steps:

step S1001, comparing the core subjects of the target object and the reference object;

the specific comparison contents comprise:

comparing whether the core subjects belong to the same super class or not;

comparing whether the core subject belongs to the same subclass or whether the core subject belongs to a subclass with membership association;

when the core theme has the physical components, comparing whether the physical components in the target object belong to the same class of the physical components in the reference object or belong to the subclass of the physical components in the reference object;

when the core theme has the abstract components, comparing whether the abstract components in the target object belong to the same class of the abstract components in the reference object or belong to the subclasses of the abstract components in the reference object;

when at least one comparison result does not belong to the comparison result, recording the difference and generating a first comparison result identifier and a second comparison result identifier, and then jumping to the step S1005, or else jumping to the step S1002; the first class comparison result identification is used for generating a conclusion in a compliance report, and the second class comparison result identification is used for generating difference item description information;

if there is a "not belonging" comparison result in the comparison content of the core subject, it indicates that the comparison basis between the target object and the reference object is not established, so that the subsequent comparison does not need to be continued, and the step S1005 is skipped;

step S1002, comparing the core attributes of the target object and the reference object;

the specific comparison contents comprise:

whether the core attribute quantities are consistent;

whether the core attributes belong to the same DSS object attribute;

whether the measurement units of the core attribute are consistent;

whether the test methods associated with the core attributes are consistent or not;

recording the difference and generating a second comparison result identifier, and continuing the subsequent comparison step;

step S1003, comparing the requirements of the target object and the reference object;

the specific comparison contents comprise:

determining whether the target object includes all mandatory requirements in the reference object according to the necessity attributes;

when at least one "not included" exists in the comparison results, recording the difference and generating a first comparison result identifier and a second comparison result identifier, and then jumping to step S1005;

if there is a "not included" comparison result in the comparison contents for the mandatory requirement, since the mandatory requirement is not included, it indicates that the comparison basis between the target object and the reference object is not established, and therefore the subsequent comparison does not need to be continued, and the process goes to step S1005;

when the comparison result aiming at the mandatory requirement is 'all including', further comparing whether the preconditions in the requirement are consistent one by one, and comparing whether each verification rule in the requirements with all consistent preconditions is consistent; if necessary, it is also necessary to compare whether the required important attributes such as the weight coefficients are consistent;

recording the difference and generating a second comparison result identifier, and continuing the subsequent comparison step;

the specific steps of comparing the preconditions in the requirements one by one to determine whether the preconditions are consistent are as follows:

acquiring corresponding premises in the target object and the reference object one by one, and determining whether the premises are consistent through consistency verification;

the consistency verification specifically comprises:

verifying whether the components in the condition group are consistent;

verifying whether the nesting relation of the condition groups is consistent;

verifying whether the value ranges of the relevant attributes related to the conditions in the condition group are consistent or not;

when the verification results are consistent, the preconditions are consistent;

when the value range of the relevant attribute in the target object is wider than the value range of the corresponding relevant attribute in the reference object, the same condition is represented, and the condition is called that the adaptability of the target object to the reference object is enhanced;

for example:

the requirement in the reference object is that the product can normally work within the range of-30 ℃ to +60 ℃ under the ambient temperature, and the premise of the requirement is that the ambient temperature is not less than-30 ℃ and the ambient temperature is not more than +60 ℃;

when the requirement in the target object is that the product can normally work within the range of-40 ℃ to +65 ℃, the requirement is premised on that the environmental temperature is not less than-40 ℃ and the environmental temperature is not more than +65 ℃;

this is the situation that the value range of the relevant attribute in the target object is wider than the value range of the corresponding relevant attribute in the reference object, which reflects that the environmental adaptability of the product targeted by the target object is better, so that the method is a precondition for enhancing the adaptability; in addition, the conditions are all inconsistent;

the specific steps for comparing whether the verification rules in all the requirements on the premise of consistency are consistent are as follows:

acquiring a certain verification rule of the target object, comparing the certain verification rule with the corresponding verification rule of the reference object, and if the condition group, the result statement and the execution item statement are completely consistent or the value range, the result statement and the execution item statement are completely consistent, indicating that the verification rules are consistent;

if the result statement and the execution item statement are completely consistent, and the value range of the target object is completely contained in the range of the value range corresponding to the reference object, namely the target pair range covers the range of the reference object and is not completely coincident, the verification rule is consistent, and the verification rule of the target object is technically enhanced for the reference object in the case that the verification rule is consistent; in addition, the verification rules are inconsistent;

step S1004, comparing decision items of the target object and the reference object;

the specific comparison contents comprise:

comparing whether the decision items are consistent;

comparing one by one to judge whether the rules are consistent;

recording the difference and generating a second comparison result identifier, and continuing the subsequent comparison step;

the comparison of the decision rules is implemented with reference to the validation rules and is not detailed;

step S1005, summarizing the comparison result to generate a compliance report or a comparison report;

summarizing comparison results of the steps S1001 to S1004;

when the first type of comparison result identification exists, the conclusion in the compliance report is a non-compliance conclusion, otherwise, the conclusion in the compliance report is a compliance conclusion;

when the second comparison result identifier exists, corresponding difference item description information is given in the comparison report.

On the basis of the above semantic-based digital standard meta-model, as shown in fig. 11, the present invention further provides an application method of the semantic-based digital standard meta-model, where the application method is used to compare the difference between a target object and a reference object and determine whether the target object meets the requirements of the reference object;

the reference object is a DSS instance, the target object is instance data (referred to as instance data for short) of a core theme of the reference object, and the instance data refers to a specification value of the instance or data obtained after the instance is tested; for example: as described above, the specification of a specific model of a specific manufacturer is a DSS instance, and data obtained after testing a specific model of a specific mechanical watch or a batch of specific models is data obtained after testing the instance;

which comprises the following steps:

step S1101, determining core subjects of the target object and the reference object;

acquiring a target object and a reference object, wherein the target object is a DSS format data file, and the file comprises instance data;

generally, the format of the instance data is consistent with that of a DSS model or a DSS instance, the data description mode is expressed by adopting a principal and predicate object SPO triple format, and the difference from the DSS model or the DSS instance is as follows: the core attribute in the example data is a determined point value, the requirement in the example data is premised on the actual condition when the core attribute is determined, and the example data does not contain decision items;

judging whether the core theme of the target object belongs to the example of the core theme of the reference object;

when the core theme has the physical components, whether the physical components of the target object belong to the instances of the physical components of the reference object is also judged;

when the abstract component exists in the core theme, whether the abstract component of the target object belongs to the instance of the abstract component of the reference object is judged;

when at least one judgment result is not included, recording the difference and generating a first type comparison result identifier, and then jumping to the step S1105, otherwise jumping to the step S1102; the first type comparison result identification is used for marking whether the target object meets the requirement of the reference object;

if there is a "not belonging" judgment result in the comparison content of the core subject, it indicates that the comparison basis between the target object and the reference object is not established, so that the subsequent judgment does not need to be continued, and the step S1105 is skipped to;

step S1102, performing formal check on the target object;

the form check specifically includes:

the compliance of DSS format data files is checked based on structural and data constraints, such as: the DSS format data file adopting RDF Turtle text grammar is subjected to form check based on structure and data constraint, and can be specifically implemented according to the prior art;

checking whether the data items exist and whether the quantity of the data items accords with the cardinal number constraint;

checking whether the data type and the range constraint of each data item are met;

acquiring a necessity attribute required in the reference object, and when it is determined that there is an optional requirement according to the necessity attribute, the formal check further includes:

comparing the conditional branches with optional requirements in the reference object one by one, determining whether the target object meets the condition of a certain conditional branch, and correspondingly setting the required necessity attribute in the target object to the attribute value specified in the conditional branch when the conditional branch is met;

recording the difference and generating a second comparison result identifier, and continuing the subsequent comparison step; the second analog comparison result identifying a change in a required attribute of necessity for use in marking the target object;

for example, the core theme of the reference subject is health assessment, where the essential attribute of "requirement for assessment of cancer risk" is "optional", which requirement comprises the following conditional branches: at an age greater than 50 years, the assessment of cancer risk is mandatory; if the age of the target object is more than 50 years, comparing the conditional branch of the requirement in the reference object, determining that the target object meets the conditional branch, and setting the necessity attribute of the requirement in the target object as the mandatory requirement specified in the conditional branch;

step S1103, judging the conformity of each core attribute in the target object to the requirement in the reference object one by one;

the specific judgment content comprises:

judging whether the test method of the target object is consistent with the test method related to the core attribute in the reference object;

judging whether the testing conditions of the core attribute data of the target object are consistent with the corresponding requirements in the reference object, and judging the conformity of each core attribute in the target object to the requirements in the reference object according to the verification rule that the core attribute data of the target object is matched with the corresponding requirements in the reference object when the testing conditions of the core attribute data of the target object are consistent with the corresponding requirements in the reference object;

or when the verification rule of the reference object adopts a value domain expression mode, calculating and judging the conformity of each core attribute in the target object to the requirement in the reference object through the following formula;

in the formula:

f(x_i) -the compliance value (compliance) of the ith requirement;

x_i-core property value (coreProperty) of the ith requirement corresponding to the target object;

e_i-the i-th request value range expectation (expectation);

l_i-the lower boundary value (lowerLimit) of the ith request value field;

u_i-upper boundary value (upperLimit) of the ith requirement value range;

w_i-the weight coefficient (weight) as claimed in item i;

int — is a rounding function;

recording the difference, generating a first type comparison result identifier, and continuing the subsequent comparison step;

step S1104, judging the whole conformity of the target object and the decision execution;

judging the overall conformity result of the target instance to all the requirements of the reference object or judging the ranking of the target instance to the reference object based on the result obtained in the step S1103 according to the judgment rule of the decision item in the reference object;

if there is an execution item in the decision rule in the reference object, automatic handling of the disqualification is realized by the action contained in the statement about the action being executed;

recording the difference, generating a first type comparison result identifier, and continuing the subsequent comparison step;

as an alternative embodiment, the determination rule of the reference object adopts any one of the following:

the total score accumulation type judgment rule is used for calculating the sum of the conformity values of all requirements, judging whether the product is qualified or determining the product grade according to the value range, wherein the type needs to stipulate the product grade and a corresponding total score value domain in the judgment rule;

the short plate decision type judgment rule is used for determining the grade of a product or judging whether the product is qualified or not according to the judgment rule defined by referring to DSS (direct sequence digital subscriber identity) by taking the minimum value of the conformity result of each requirement as the final conformity of the product;

according to the maximum allowable difference type judgment rule, counting the unsatisfied requirement items according to the lowest acceptable conformity level defined by the judgment rule in the reference DSS, judging the unqualified requirement items or the unqualified requirement items if the maximum unqualified requirement items exceed the total number defined by the rule, otherwise judging the qualified requirement items, wherein the method is generally used as a judgment method of batch products;

step S1105, summarizing the judgment result to give a judgment conclusion;

summarizing the judgment results of the steps S1101-S1104;

when the first type of comparison result identification exists, judging whether the target object meets the requirement of the reference object or not, wherein the judgment result is that the target object does not meet the requirement, and otherwise, judging that the target object meets the requirement;

when the second analog comparison result identification exists, a change prompt of the required necessity attribute in the target object is given.

According to another aspect of the embodiments of the present invention, there is also provided an apparatus for applying a semantic-based digital standard meta model, including:

the target DSS generation module is configured to generate a target DSS based on the reference source, and specifically includes:

the reference source setting unit is used for selecting a reference source according to a target DSS to be generated and citing a DSS general ontology in the reference source;

the theme and attribute establishing unit is used for establishing a core theme and core attribute and establishing a related theme and a related attribute;

a requirement establishing unit for establishing requirements item by item;

the decision item establishing unit is used for establishing a decision item;

the submitting and publishing management module is used for determining the attribute data of the target DSS, determining the general ontology element and carrying out identification, defining structure and data constraint, checking form and content, generating the target DSS into an independent DSS file and submitting the independent DSS file to a DSS management organization for auditing and publishing;

a first comparison module for comparing the reference object with the target object;

the report generation module is used for generating a compliance report or a comparison report according to the comparison result of the first comparison module;

the second comparison module is used for comparing the difference between the target object and the reference object;

and the judgment prompt module is used for giving a judgment conclusion according to the judgment result of the second comparison module.

According to another aspect of the embodiments of the present invention, there is also provided a non-volatile storage medium, which includes a stored program, where the program is executed to control a device in which the non-volatile storage medium is located to execute any one of the foregoing methods for applying the semantic-based digital standard meta model.

According to another aspect of the embodiments of the present invention, there is also provided an electronic device, including a processor and a memory; the memory is stored with computer readable instructions, and the processor is used for executing the computer readable instructions, wherein the computer readable instructions execute the method for applying any one of the above digital standard meta-models based on semantics.

The digital standard meta-model based on the semantics and the application method thereof have the following beneficial effects:

establishing a DSS meta-model based on a unified semantic framework, generating the DSS model through the DSS meta-model, and further establishing a DSS instance, thereby establishing a complete and unified standard element semantic relationship, and realizing the sharing and reusing of standard elements through semantic-based content expression;

the DSS model or DSS instance has clear and uniform validation rules and decision rules, the structural information contained in the requirement of the DSS is complete, so that the DSS model or DSS instance can be automatically read, understood and processed by a computer, the automatic comparison between the DSS models, between the DSS models and the DSS instances or between the DSS instances can be realized, and then the conformity result of an object (product or process or other) which is normalized through the DSS is obtained (decided), so that the computer realizes the support of reasoning and decision and automatic control.

The semantic-based digital standard meta-model and the application method thereof can realize the automatic retrieval of parts and materials related to a standardized object and the requirements of safety, environmental protection, test methods and other aspects of standards in the product design or standard system revision process, carry out accurate reference or optimization, ensure the design compliance, avoid repeated design and improve the design efficiency and the standard implementation benefit;

the automatic verification and judgment of the conformity of other standards or products/processes and batch products can be realized according to the specified reference standard;

the automatic comparison of different standards can be realized, the difference or technical level sequencing of the standards is determined, and a detailed comparison result is given;

reasoning can be realized according to the semantic relation of the standardized objects, and the applicability of the attributes and requirements of the standardized objects to subclasses or instances can be automatically judged; realizing automatic classification and unqualified disposal of product grades according to decision rules; and executing corresponding execution items in the rule to realize the support for automatic control.

Drawings

The invention has the following drawings:

the drawings are included to provide a better understanding of the invention and are not to be construed as unduly limiting the invention. Wherein:

FIG. 1 is a schematic diagram of the construction of the semantic-based digital standard meta-model according to the present invention.

FIG. 2 is a schematic diagram of the structure of the DSS component class according to the present invention.

FIG. 3 is a schematic diagram of the core theme and related theme according to the present invention.

FIG. 4 is a schematic diagram of the construction of the present invention.

FIG. 5 is a schematic diagram of the set of conditions according to the present invention.

FIG. 6 is a schematic diagram of the construction of the statement of the invention.

FIG. 7 is a schematic diagram showing the construction of the present invention.

FIG. 8 is a schematic diagram of the decision term of the present invention.

Fig. 9 is a schematic diagram of an embodiment 1 of a method for applying a semantic-based digital standard meta model according to the present invention.

FIG. 10 is a schematic diagram of an embodiment 2 of the method for applying the semantic-based digital standard meta-model according to the present invention.

Fig. 11 is a schematic diagram of an embodiment 3 of the method for applying the semantic-based digital standard meta-model according to the present invention.

FIG. 12 is a drawing illustrating a DSS establishment implementation of the watch product specification of the present invention.

Detailed Description

The present invention will be described in further detail with reference to the accompanying drawings. The detailed description, while indicating exemplary embodiments of the invention, is given by way of illustration only, in which various details of embodiments of the invention are included to assist understanding. Accordingly, it will be appreciated by those skilled in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

The terms used in the present invention have the following meanings:

ontology (Ontology), which refers to a formal specification of a shared conceptual model, specifically embodies the meaning of four aspects: conceptualization (Conceptualization), Explicit (Explicit), formalization (format), and sharing (Share). Wherein:

it is clear that the definitions of the various concepts and their constraints used in the ontology are accurate and non-conflicting;

formalization means that resources in an ontology can be recognized, read and processed by a computer;

sharing is an important feature of an ontology, meaning that the concept of the use of the ontology is recognized and forms a consensus in the field.

At present, according to the hierarchy and domain dependency of an ontology, Guarino et al classify it into four categories: the system comprises a top layer body, a field body, a task body and an application body. An ontology may be composed of five elements, class (class), relationship (relations), axioms (axioms), function (function), and instances (entities). Wherein a class is also referred to as a concept.

The meta-model is a model related to a model, defines concepts and relationships thereof in a specific field, provides construction elements for creating the model in the specific field, and realizes the consistency of semantics or the unification of structures in the field through layer-by-layer recursive constraint of the semantics or the structures.

Several specific examples of implementation follow.

As shown in fig. 12, the relationship between the wristwatch, the mechanical watch, the X-card table, and the DSS component class, DSS object relationship, DSS object attribute, and DSS object instance involved is displayed. The following examples all adopt RDF Turtle language as the description language of DSS, and may also adopt other serialization modes such as RDF-Star, Notation 3(N3), OWL, JSON-LD, N-triple, etc., or adopt graph database to express.

The following example 1 is a DSS model whose core theme is a mechanical watch, and is stored in a DSS format data file "example 1". Example 1 a core attribute "time-of-day error" of a core theme is chosen for illustration.

The above example 1 shows that the daily error requirement of the mechanical watch is a mandatory requirement, the requirement for the daily error tester and the requirement for the test environment temperature are included in the premise, the allowable value range of the verification rule of the daily error conformity of the mechanical watch is-80 to +100(s/d, second/day), and the verification rule of the non-conformity of the daily error is omitted in the present example. Example 1 also specifies the conformity determination rule of its subordinate specification, and the mechanical-watch product qualification determination rule.

The following example 2 is an example of a DSS whose core subject is an X-card table, which belongs to a mechanical table and whose daily error requirement is-70 to +90(s/d), stored in a DSS format data file "example 2".

The above example 1 may be used as a reference object, and the example 2 may be used as a target object, and by comparing two DSS files according to the application method shown in fig. 10 of the present invention, it may be determined that the core subject X-brand table of the example 2 belongs to the subclass of the mechanical table, and the parts thereof also belong to the subclasses of the parts corresponding to the mechanical table, respectively; the precondition of the X-card daily error requirement is consistent with the precondition of the mechanical daily error requirement, and the value range of the X-card daily error is contained in the value range of the mechanical daily error, so that the comparison conclusion is as follows: the daily error requirement of example 2 meets the requirement of example 1. The X-card table also adds a mandatory requirement for the appearance of the watch case glass, which can be considered a technical enhancement requirement and is therefore in line with example 1. According to the comparison result, all comparison items are in accordance, so that the condition that the example 2 is in accordance with the example 1 can be judged according to the judgment rule.

Example 3 below is example data for a core subject X-card table, such as product inspection data for X-card tables numbered X001 and X002:

example 3 dss product example test data on X-brand List-

@prefix:<http://dssu.org/#>.

X001, type X brand table;

the core attribute is X001 day error.

X001 day error, type X brand table day error;

x001 day error test value 60.

X002 type is X brand table;

the core attribute is X002 day error.

X002 day error is X brand table day error;

x002 day error test value is-90.

# omit other core attribute values and test instrument precision, ambient temperature, etc. prerequisite data # end/BL

By comparing example 2 with example 3 by the application method shown in fig. 11 of the present invention, example 3 is used as a target object, example 2 is used as a reference object, and whether the target object meets the requirements of the reference object or not can be determined;

assuming that the data such as the parameters of the test instrument, the environmental temperature and the like are consistent with those of the example 2, and the travel time day error of the X-card table with the number X001 is within the value range specified by the specification of the X-card table, so that the day error of the X-card table with the number X001 meets the requirement specified by the specification of the X-card table, and at the moment, if other core attribute values of the X-card table with the number X001 meet the requirement of the example 2, the X-card table with the number X001 belongs to the qualified product specified in the example 2;

similarly, it can be found that the X-card table of number X002 does not meet the requirement of example 2, and is a defective product.

Example 4 below defines the day error data constraint of the X-brand table as an integer type with SHACL and the number of occurrences can only be 1. Therefore, if the daily error test data of the X002 table is 120.5, or the data is missing or appears more than 1 time, an error is reported.

Example 5 computer-selected apple DSS model application example

The following is an application example of a DSS model for automatically sorting apples by using a production line, wherein the production line automatically measures the diameter and weight of a single apple, then the system respectively calculates a conformity value C1 and a weight conformity value C3 of the diameter of the apple according to a verification rule in example 5.DSS, then calculates a total conformity value C1+ C2, finally sorts the apples according to a total score accumulation type judgment rule, and the production line sorts each apple according to different classifications.

The corresponding relation between the total conformity value C of the apples and the apple grade L is as follows:

value range of total conformity value C of mechanically selected apples	Machine-selected apple grade L
		70≤C≤100	Superior product
30≤C＜70	First-class product
		0≤C＜30	Second grade product
C＜0	Unqualified product

For example: 1[ fruit diameter: 102mm, weight: 204g ] of apple;

first, the diameter x is calculated according to the formula (1)₁C1, when x_i＝102，e_i＝100，u_i120, due to x_i>e_iSo corresponding to the third part of equation (1),

in the formula u_iFor the upper boundary value of the median range required for the diameter of the fruit, e_iSetting the weight coefficient of the fruit diameter requirement as 70 (percentage system, if 1 division system is adopted, the weight coefficient is 0.7) as the expected value of the value range in the fruit diameter requirement, and calculating to obtain the fruit diameter requirement conformance value of the apple 1 as 63;

next, the weight x is calculated according to the formula (1)₂C2, when x_i＝204，e_i＝200，u_i240, due to x_i>e_iSo corresponding to the third part of equation (1),

in the formula u_iIs a requirement for weightUpper boundary value of the median region, e_iThe weight requirement is an expected value of a value range in the weight requirement, the weight coefficient of the weight requirement is 30 (adopting a percentage system), and the weight requirement conformance value of the apple 1 is 27 through calculation;

thirdly, calculating the total conformity value C of the apple 1, namely C1+ C2, 63+27 and 90; and judging the apple 1 as a superior product according to the corresponding relation between the total conformity value C of the mechanically-selected apples and the grade L of the mechanically-selected apples by the judgment rule.

Setting 2[ 94mm diameter and 184g weight ] of apple according to the procedure of apple 1;

at this time x_i＝94，e_i100, x_i<e_iTherefore, corresponding to the first part of the formula (1), the final calculated apple 2 total conformity value C is 49+ 18-67; the judging rule judges the apple 2 to be a first-class product according to the corresponding relation between the total conformity value C of the apple and the apple grade L.

Setting apple 3 (fruit diameter: 86mm, weight: 168 g) according to the process of apple 1, and finally calculating the total conformity value C of apple 3 to 21+6 to 27; and judging that the apple 3 is the second-class apple according to the corresponding relation between the total conformity value C of the mechanically selected apples and the mechanically selected apple grade L by the judgment rule.

Setting apple 4 (diameter: 78mm, weight: 152 g) according to the process of apple 1, and finally calculating the total conformity value C of apple 4 to 21+6 to 27; the judging rule judges the apple 4 as a defective product according to the corresponding relation between the total conformity value C of the mechanically-selected apple and the mechanically-selected apple grade L, and the system executes the action of removing the defective product in the production line according to the content of the execution item because the execution item exists in the judging rule.

Example 6 application example of DSS model in software automatic test

A certain data analysis software (X software for short) includes a statistical analysis module and a result output module, and the software specification of the data analysis software is stored in a DSS format data file "example 6. DSS", and includes the following software requirements:

1) using a designated computer hardware configuration (configuration 1), and when the actual service data volume is not more than 5 million, the total time consumption of a single statistical analysis task is not more than 20 seconds; the requirement is tested using test case 1;

2) the file format output by the analysis result supports the CSV format; the requirement is tested by using a test case 2;

example code for an instance of the X software Specification DSS is as follows:

in the above DSS example, the core topic is software X, which associates two modules in a sub-element relationship, and the DSS example includes two mandatory requirements: the analysis task time consumption requirement (quantitative requirement) and the output file CSV format support requirement (qualitative requirement) comprise corresponding preconditions. The task time consumption rule is expressed in a value domain mode, and the CSV format support rule is expressed in a condition group mode. According to the method similar to that in examples 2 and 3, the result of the test data can be judged to determine whether the tested software meets the requirements of the example.

Example 7 application example of DSS model in knowledge graph

Defining products, processes and related ontologies thereof in a DSS model, accurately describing classification, class attributes, interrelations and constraints of the products and the processes, defining technical requirements of the products and the processes, and verifying, accepting and evaluating rules, wherein the DSS model and the DSS instance data are stored in a file or a database in a semantic data or graph data mode, are queried by various semantic query tools, and can be displayed in a graph data mode; the DSS is convenient to implement conformance analysis and comparison analysis on standards or products for reference and inheritance management mechanisms of technical requirements, particularly expression and storage of value ranges, so that the DSS is very suitable for assisting in building product class and technical class knowledge maps, and supporting auxiliary design, manufacturing and knowledge management.

Those not described in detail in this specification are within the skill of the art.

The above description is only a preferred embodiment of the present invention, and the scope of the present invention is not limited to the above embodiment, but equivalent modifications or changes made by those skilled in the art according to the present disclosure should be included in the scope of the present invention as set forth in the appended claims.

Claims (10)

1. The semantic-based digital standard meta-model is used for assisting in building a DSS model or a DSS instance, and is characterized in that the meta-model comprises three parts of DSS general ontology built based on a unified semantic framework, technical description data and structure and data constraint, wherein:

the unified semantic framework is expressed by adopting a main guest and predicate guest SPO triple format, and semantic elements of the unified semantic framework comprise a DSS composition class, a DSS object relationship, a DSS object attribute and a DSS object instance;

the DSS composition classes are used for generalizing concepts, and specifically include: a primary class and a secondary class;

the main classes include: core subject, core attribute, related subject, related attribute, requirement and decision item; the secondary classes include: rules, conditions, condition sets, statements, preconditions, results, execution terms.

2. The semantic-based digital standard meta-model of claim 1, characterized in that the core topics, which correspond to standardized objects in the standard literature, are unique in one DSS model or DSS instance, the core topics being classified by type into product-like core topics, process-like core topics and other core-like topics;

the core attributes correspond to the DSS object attributes owned by core topics, and one core topic has at least one core attribute;

the related topics correspond to related factors which can influence core attributes, and one core attribute has at least one related topic;

the relevant attributes correspond to the DSS object attributes owned by the relevant subjects and are used for forming the premise of requirements, and one relevant subject has at least one relevant attribute;

the core attribute and the related attribute are uniformly attributed to a subject attribute in a meta-model, the subject attribute is managed as a class object in a DSS model or a DSS instance, the subject attribute is associated with a test method, and the type of the subject attribute is divided into a quantitative attribute, a qualitative attribute and an identification attribute;

the statement is used for describing things and is constructed in a triple format;

the condition, consisting of a statement, being true, the logical result of the condition is 1, being false, the logical result of the condition is 0;

the condition group comprises m components related through the element relationship, m is greater than or equal to 1, the components are conditions or condition groups, the element logic of the condition group is AND or OR, and the logic result of the condition group is obtained by the operation of each component in the condition group according to the element logic;

the requirement comprises a precondition and at least one verification rule, and when the logic result of the precondition is true, the conformity result of the requirement is obtained according to the verification rule; the request has a necessity attribute for setting the request as any one of a mandatory request, a recommended request and an optional request according to the attribute; one requirement is associated with only one core attribute through a targeting relationship, and one core attribute is associated with at least one requirement through a targeting relationship;

the precondition is a condition group that the logic of the elements is defaulted to AND, and the logic result of the precondition is obtained by the operation of each component in the condition group according to the logic of the elements;

the verification rule is composed of a condition group, a result and an execution item, the result is a set of statements about compliance, the execution item is a set of statements about action, the statements about compliance are effective when the condition group is true, and the action contained in the statements about action is executed; or, the validation rule is composed of a value range, a result and an execution item, when the value range is satisfied, the statement about the compliance is valid, and the action contained in the statement about the action is executed;

the decision item comprises at least one judgment rule, and the decision item is associated with the decision item according to the relationship and obtains an overall conformance result of the decision item according to the judgment rule;

the judgment rule has the same structure as the verification rule, and the difference between the judgment rule and the verification rule lies in that the specific values of the condition group and the target-specific results are different;

the validation rules and the decision rules are collectively attributed to rules in the secondary class in the meta-model.

3. Application method of a semantic-based digital standard meta-model for generating a target DSS based on a reference source, comprising the following steps:

step S901, selecting a reference source, and referring to a DSS general ontology in the reference source;

when the target DSS to be generated is a DSS model, the reference source selects a DSS meta model;

when the target DSS to be generated is a DSS instance, selecting a DSS model according to the reference source;

step S902, establishing a core theme and a core attribute;

determining a main class related to a core theme of the target DSS through a theme and attribute establishing unit, and establishing the core theme of the target DSS as a new subclass under a super class by taking the main class related to the core theme of the target DSS as the super class in the cited DSS general ontology;

after the core theme is established, acquiring the core attribute owned by the core theme through the theme and attribute establishing unit, wherein the core attribute is from inheritance of the super-class owned DSS object attribute on one hand, and from a newly added DSS object attribute on the other hand, and the core attribute is associated with the core theme and inherits the metering unit from the metering unit body in the DSS general body;

step S903, establishing a related theme and related attributes;

acquiring core attributes of the target DSS through a theme and attribute establishing unit, acquiring relevant factors influencing the core attributes, and establishing relevant themes one by one according to the relevant factors;

after the related subject is established, acquiring related attributes owned by the related subject through a subject and attribute establishing unit, wherein the related attributes are from inheritance of the super-class owned DSS object attributes on one hand and from newly added DSS object attributes on the other hand, and the related attributes are associated with the related subject and inherit the metering units from the metering unit bodies in the DSS general bodies;

step S904, establishing requirements item by item;

acquiring core attributes of the target DSS through a requirement establishing unit, establishing requirements for the core attributes one by one, establishing a precondition first, establishing a verification rule item by item and setting a necessity attribute finally when establishing the requirements;

step S905, establishing a decision item;

when the decision item is established, the target DSS is obtained through the decision item establishing unit, the decision item is determined according to the purpose of the target DSS, all requirements associated with the decision item are determined, and the judgment rule is established according to all the requirements.

4. The method for applying the semantic-based digital standard meta-model according to claim 3, wherein in step S902, when the core topic of the target DSS is a product-class core topic or a process-class core topic, the method further comprises establishing a physical component of the core topic, wherein the physical component is associated with the core topic through a sub-element relationship, and the physical component comprises a part or a sub-process;

in step S902, when the core theme of the target DSS is a product class core theme or a process class core theme, further including establishing an abstract component of the core theme, where the abstract component is associated with the core theme through a component relationship, and the abstract component includes a function, an interface, a structure, and a feature;

in step S904, the concrete steps of establishing the premise are as follows:

establishing a condition group of which the component logic defaults to be AND, and determining components included in the condition group, wherein when the components are conditions, the subject parts of the conditions are all from related attributes, and when the components are the condition group, repeating the step until the nesting structure of the condition group is completed;

in step S904, the specific steps of establishing the validation rule are as follows:

determining condition groups, results and execution items in the verification rules in sequence, and then completing the establishment of the verification rules;

or, sequentially determining a value range, a result and an execution item in the verification rule, and then completing the establishment of the verification rule;

in step S905, specific steps of determining all the requirements associated with the decision item are as follows:

determining all involved core attributes according to decision items;

determining all requirements involved according to all core attributes;

in step S905, the specific steps of establishing the determination rule according to all the requirements are as follows:

determining condition groups, results and execution items in the judgment rules in sequence, and then finishing the establishment of the judgment rules;

or, sequentially determining the value range, the result and the execution item in the judgment rule, and then completing the establishment of the judgment rule.

5. The method for applying a semantic-based digital standard meta-model as claimed in claim 3, further comprising the steps of:

step S906, determining the self attribute data of the target DSS, determining a general ontology element and identifying;

step S907, defining structure and data constraints;

step S908, form and content check;

performing formal inspection based on the structure and data constraints, and then performing content inspection according to technical content specified in the reference source to modify the violations;

after the form and the content are checked to be qualified, generating the target DSS into an independent DSS file and submitting the independent DSS file to a DSS management organization for examination and release;

in step S909, the DSS authority checks and numbers the publication.

6. The application method of the digital standard meta-model based on the semanteme is characterized in that the application method is used for giving a compliance report or a comparison report based on the comparison between a reference object and a target object;

when the reference object is a DSS model, the target object may be a DSS model or a DSS instance;

when the reference object is a DSS instance, the target object may be a DSS instance;

which comprises the following steps:

step S1001, comparing the core subjects of the target object and the reference object;

the specific comparison contents comprise:

comparing whether the core subjects belong to the same super class or not;

comparing whether the core subject belongs to the same subclass or whether the core subject belongs to a subclass with subordinate association;

when the core theme has the physical components, comparing whether the physical components in the target object belong to the same class of the physical components in the reference object or belong to the subclass of the physical components in the reference object;

when the core theme has the abstract components, comparing whether the abstract components in the target object belong to the same class of the abstract components in the reference object or belong to the subclasses of the abstract components in the reference object;

when at least one comparison result does not belong to the comparison result, recording the difference and generating a first comparison result identifier and a second comparison result identifier, and then jumping to the step S1005, or else jumping to the step S1002;

step S1002, comparing the core attributes of the target object and the reference object;

the specific comparison contents comprise:

whether the core attribute quantities are consistent;

whether the core attributes belong to the same DSS object attribute;

whether the measurement units of the core attribute are consistent;

whether the test methods associated with the core attributes are consistent or not;

recording the difference and generating a second comparison result identifier, and continuing the subsequent comparison step;

step S1003, comparing the requirements of the target object and the reference object;

the specific comparison contents comprise:

determining whether the target object includes all mandatory requirements in the reference object according to the necessity attributes;

when at least one "not included" exists in the comparison results, recording the difference and generating a first comparison result identifier and a second comparison result identifier, and then jumping to step S1005;

when the comparison result aiming at the mandatory requirement is 'all including', further comparing whether the preconditions in the requirement are consistent one by one, and comparing whether each verification rule in the requirements with all consistent preconditions is consistent;

recording the difference and generating a second comparison result identifier, and continuing the subsequent comparison step;

step S1004, comparing decision items of the target object and the reference object;

the specific comparison contents comprise:

comparing whether the decision items are consistent;

comparing one by one to judge whether the rules are consistent;

recording the difference and generating a second comparison result identifier, and continuing the subsequent comparison step;

step S1005, summarizing the comparison result to generate a compliance report or a comparison report;

summarizing comparison results of the steps S1001 to S1004;

when the first type of comparison result identification exists, the conclusion in the compliance report is a non-compliance conclusion, otherwise, the conclusion in the compliance report is a compliance conclusion;

when the second comparison result identifier exists, corresponding difference item description information is given in the comparison report.

7. The application method of the digital standard meta-model based on the semantics is characterized in that the application method is used for comparing the difference between a target object and a reference object and judging whether the target object meets the requirement of the reference object;

the reference object is a DSS instance, the target object is instance data of a core theme of the reference object, and the instance data refers to a specification value of the instance or data obtained after the instance is tested;

which comprises the following steps:

step S1101, determining core subjects of the target object and the reference object;

acquiring a target object and a reference object, wherein the target object is a DSS format data file, and the file comprises instance data;

judging whether the core theme of the target object belongs to the example of the core theme of the reference object;

when the core theme has the physical components, whether the physical components of the target object belong to the instances of the physical components of the reference object is also judged;

when the abstract component exists in the core theme, whether the abstract component of the target object belongs to the instance of the abstract component of the reference object is judged;

when at least one judgment result is not included, recording the difference and generating a first type comparison result identifier, and then jumping to the step S1105, otherwise jumping to the step S1102;

step S1102, performing formal check on the target object;

performing formal checking based on structure and data constraints;

acquiring a necessity attribute required in the reference object, and when it is determined that there is an optional requirement according to the necessity attribute, the formal check further includes:

comparing the conditional branches with optional requirements in the reference object one by one, determining whether the target object meets the condition of a certain conditional branch, and correspondingly setting the required necessity attribute in the target object to the attribute value specified in the conditional branch when the conditional branch is met;

recording the difference and generating a second comparison result identifier, and continuing the subsequent comparison step;

step S1103, judging the conformity of each core attribute in the target object to the requirement in the reference object one by one;

the specific judgment content comprises:

judging whether the test method of the target object is consistent with the test method related to the core attribute in the reference object;

judging whether the testing conditions of the core attribute data of the target object are consistent with the corresponding requirements in the reference object, and judging the conformity of each core attribute in the target object to the requirements in the reference object according to the verification rule that the core attribute data of the target object is matched with the corresponding requirements in the reference object when the testing conditions of the core attribute data of the target object are consistent with the corresponding requirements in the reference object;

or when the verification rule of the reference object adopts a value domain expression mode, calculating and judging the conformity of each core attribute in the target object to the requirement in the reference object through the following formula;

in the formula:

f(x_i) -the compliance value of the ith requirement;

x_i-core attribute value of the ith requirement corresponding to the target object;

e_i-the expected value of the ith request value range;

l_i-the lower boundary value of the ith request value field;

u_i-the upper boundary value of the ith request value range;

w_i-the weight coefficients as claimed in item i;

int — is a rounding function;

recording the difference, generating a first type comparison result identifier, and continuing the subsequent comparison step;

step S1104, judging the whole conformity of the target object and the decision execution;

judging the overall conformity result of the target instance to all the requirements of the reference object or judging the ranking of the target instance to the reference object based on the result obtained in the step S1103 according to the judgment rule of the decision item in the reference object;

if there is an execution item in the decision rule in the reference object, automatic handling of the disqualification is realized by the action contained in the statement about the action being executed;

recording the difference, generating a first type comparison result identifier, and continuing the subsequent comparison step;

step S1105, summarizing the judgment result to give a judgment conclusion;

summarizing the judgment results of the steps S1101-S1104;

when the first type of comparison result identification exists, judging whether the target object meets the requirement of the reference object or not, wherein the judgment result is that the target object does not meet the requirement, and otherwise, judging that the target object meets the requirement;

when the second analog comparison result identification exists, a change prompt of the required necessity attribute in the target object is given.

8. The application device of the digital standard meta-model based on the semanteme is characterized by comprising the following steps:

the target DSS generation module is configured to generate a target DSS based on the reference source, and specifically includes:

the reference source setting unit is used for selecting a reference source according to a target DSS to be generated and citing a DSS general ontology in the reference source;

the theme and attribute establishing unit is used for establishing a core theme and core attribute and establishing a related theme and a related attribute;

a requirement establishing unit for establishing requirements item by item;

the decision item establishing unit is used for establishing a decision item;

the submitting and publishing management module is used for determining the attribute data of the target DSS, determining the general ontology element and carrying out identification, defining structure and data constraint, checking form and content, generating the target DSS into an independent DSS file and submitting the independent DSS file to a DSS management organization for auditing and publishing;

a first comparison module for comparing the reference object with the target object;

the report generation module is used for generating a compliance report or a comparison report according to the comparison result of the first comparison module;

the second comparison module is used for comparing the difference between the target object and the reference object;

and the judgment prompting module is used for giving a judgment conclusion according to the judgment result of the second comparison module.

9. A non-volatile storage medium, comprising a stored program, wherein the program when executed controls a device in which the non-volatile storage medium is located to perform a method of applying the semantic-based digital standard meta-model according to any one of claims 3 to 7.

10. An electronic device comprising a processor and a memory; the memory is stored with computer readable instructions, and the processor is used for executing the computer readable instructions, wherein the computer readable instructions execute the application method of the digital standard meta model based on the semantic meaning according to any one of claims 3 to 7.

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