Sensor metadata processing device with an open standards-based ontology

Abstract

We provide a sensor metadata processing device with an open standards-based ontology. [Solution] The sensor metadata processing device 10 includes an ontology unit 100 that stores the measured values ​​and metadata for the sensor, which includes a result class 107 having measured values ​​input from the sensor, an observation attribute class 109 relating to the measured values ​​of the sensor, a measurement unit class 111, and a data type class 113; a relationship setting unit 200 that sets predicates that represent the relationship between the values ​​of each class in the ontology unit according to user input; a query input unit 400 that receives query input from the user in the form of a subject, object, and predicate combination of the set predicates and the values ​​of each class in the ontology unit; and a result value calculation unit 500 that retrieves the values ​​of the result class and metadata class in the ontology unit via an index point and calculates result values ​​based on the query.

Description

Technical Field

[0001] The present invention relates to a sensor metadata processing device having an open standard-based ontology, and more particularly, to a sensor metadata processing device having an ontology based on the Sensorthings API open standard of the International Industry Consortium OGC (Open Geospatial Consortium).

[0002] The present invention has been completed as a research result of a research and development project (project specific number: 2710008419, project management number: II220622, project name: construction of a digital twin-based smart city LAB demonstration site, construction of a digital twin test bed) carried out with the support of the Ministry of Science and ICT and the Korea Institute for Information and Communications Technology Planning and Evaluation.

Background Art

[0003] Ontology serves to give meaning to data and help it be understood and processed by machines. Structuring the connection between sensors with ontology is a system that clearly defines the concepts and their relationships in a specific domain, contributing to a clear representation of the concepts and structure of sensors. Furthermore, such ontology facilitates cooperation with other domain knowledge and enhances data interoperability.

[0004] Resources within ontology are represented in RDF (Resource Description Framework), and rules are defined using RDF-based OWL (Web Ontology Language). RDF has a graph structure, with each vertex represented as a triple in the form of subject-predicate-object, where the object is linked to another subject or a literal that has meaning as its value. Also, all subjects are represented by URLs (Universal Resource Identifiers) indicating individual objects, and predicates are divided into object properties where another subject comes as the object and data properties where the object is represented by a literal.

[0005] L. Chamari et al. designed a smart building structure with a reusable and scalable heterogeneous domain knowledge linkage structure using PROPS, BOT, and MEP ontologities for the building's IFC (Industry Foundation Classes) model and Brick and SSN ontologities for the Internet of Things. This is related to the fact that sensor structures are suitable for ontology, as argued in the research of C. Peng et al., and the RESTful services mainly used in sensor structures are viewed from a Web of Things (WoT) perspective, so resources can be considered as graphs and nodes, converted into RDF linked data, and then information can be provided via SPARQL (SPARQL Protocol and RDF Query Language).

[0006] Creating domain knowledge representations for ontologs requires clear criteria and definitions. According to KI Kotis et al., inadequate conceptual explanations or synonym conflicts negatively impact the reusability, which is a key benefit of ontology implementation. Furthermore, E. Karabulut et al. point out that while digital twin-related ontology research has tripled since 2017 and demonstrated effectiveness in defining the concept of linking physical objects and environments, more than half of the research focuses on creating new ontologs rather than reusing existing structures, thus failing to demonstrate the reusability that is a key benefit of ontologs. [Prior art documents] [Patent Documents]

[0007] [Patent Document 1] Korean Registered Patent No. 10-0868331 [Patent Document 2] U.S. Patent Publication No. 2021-0209144 [Overview of the project] [Problems that the invention aims to solve]

[0008] The present invention was made to solve the problems of the prior art described above, and its objective is to provide a sensor metadata processing device having an ontology suitable for smart cities that is compatible with the Sensorthings API open standard of the international industrial consortium OGC (Open Geospatial Consortium). [Means for solving the problem]

[0009] To achieve the above objective, a sensor metadata processing device having an open standard-based ontology according to one aspect of the present invention includes a result class having measured values ​​input from a sensor, a metadata class for each metadata relating to the measured values ​​of the sensor, the metadata class including an observation attribute class having observation attribute information of the sensor as a literal, a measurement unit class having measurement unit information for the measured values ​​of the sensor as a literal, a data type class having data format information of the sensor as a literal, and an index point linked to have a one-to-one correspondence with any of the observation attribute class, measurement unit class, and data type class, and linked to at least one result class, for the sensor The system includes an ontology section for storing measured values ​​and metadata; a relationship setting section for setting predicates that represent the relationships between classes or values ​​of each class in the ontology section according to user input; a query input section for receiving query input from the user, consisting of subject-object-predicate combinations that include the predicates set in the relationship setting section and the classes or values ​​of each class in the ontology section as the subject or object; and a result value calculation section that, when a query is entered, retrieves the values ​​of the result class and metadata class in the ontology section via the index points of the ontology section, and calculates result values ​​based on the query, along with operators according to predefined rules. [Effects of the Invention]

[0010] According to the present invention, a sensor metadata processing device having an open standard-based ontology according to an embodiment of the present invention has the advantage of being compatible with STA standard models currently used in the sensor field, resolving the silo phenomenon where data is isolated between organizations or services, and ensuring reusability and semantic consistency of data by embodying it in an ontology. [Brief explanation of the drawing]

[0011] [Figure 1] This figure shows a sensor metadata processing device having an open standards-based ontology according to an embodiment of the present invention. [Figure 2] This figure illustrates the ontology structure of a sensor metadata processing device having an open standard-based ontology according to an embodiment of the present invention. [Figure 3] This is a conceptual diagram of a virtual smart city environment for performance testing of a sensor metadata processing device 10 having an open standard-based ontology according to an embodiment of the present invention. [Modes for carrying out the invention]

[0012] With respect to embodiments of the present invention disclosed herein, any specific structural or functional descriptions are provided as examples for the purpose of illustrating embodiments of the present invention, and embodiments of the present invention can be carried out in various forms and should not be construed as being limited to embodiments described herein.

[0013] The present invention can be modified in various ways and may take on various forms; therefore, specific embodiments are illustrated in the drawings and described in detail in the text. However, this should not be understood as limiting the invention to any particular disclosure, but rather as including all modifications, equivalents, or substitutions that fall within the scope of the spirit and art of the invention.

[0014] Terms such as "first," "second," etc., can be used to describe various components, but these components should not be limited by these terms. These terms are used solely for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, the first component may be named the second component, and similarly, the second component may be named the first component.

[0015] When it is mentioned that one component is “linked” or “connected” to another component, it should be understood that this may mean that it is directly linked or connected to the other component, or that another component may be intervening between them. Conversely, when it is mentioned that one component is “directly linked” or “directly connected” to another component, it should be understood that there is no other component intervening between them. Other expressions describing the relationship between components, such as “between…” and “immediately between…”, or “adjacent to…” and “directly adjacent to…”, should be interpreted similarly.

[0016] The terms used in this application are used solely to describe specific embodiments and do not limit the invention. Singular expressions include plural expressions unless they have a clearly different meaning in context. In this application, terms such as “includes” or “has” are intended to specify the existence of disclosed features, figures, steps, actions, components, parts, or combinations thereof, and should be understood not to preclude the existence or possibility of adding one or more other features, figures, steps, actions, components, parts, or combinations thereof.

[0017] Unless otherwise defined, all terms used herein, including technical or scientific terms, shall have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. Terms defined in commonly used dictionaries shall be interpreted to have a meaning consistent with the context of the relevant art and shall not be interpreted in an idealized or overly formal sense unless clearly defined in this application.

[0018] On the other hand, in some embodiments where other realizations are possible, the functions or operations specified within a particular block may be performed in an order different from the order specified in the flowchart. For example, two consecutive blocks may actually be performed substantially simultaneously, or depending on the related functions or operations, the blocks may be performed in reverse.

[0019] Hereinafter, a sensor metadata processing device having an open standard-based ontology according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings.

[0020] FIG. 1 is a diagram showing a sensor metadata processing device having an open standard-based ontology according to an embodiment of the present invention.

[0021] The international industry consortium OGC (Open Geospatial Consortium) defines open standards to ensure the integration and compatibility of various spatial data and services. The OGC standards play an important role in fields such as geographic information systems (GIS), location-based services (LBS), and environmental monitoring.

[0022] The OGC's Sensorthings API (hereinafter referred to as STA) is an open standard that represents sensors including measurement values and metadata in OGC. Using the officially certified API service FROST, information created with this open standard can be handled.

[0023] The STA model is a hierarchical JSON structure represented by a UML diagram, and because it offered users a degree of non-regular flexibility, the process of restructuring it to represent it in an ontology involves declaring structural rules, such as using the STA model based on "MultiDatastream," designing how to define ontology classes and property literals, and finally defining detailed OWL (Web Ontology Language) rules such as Restriction.

[0024] One embodiment of the present invention provides a sensor metadata processing device 10 having an open standard-based ontology, characterized by its compatibility with an ontology structure based on STA, the Sensorthings API open standard of the international industrial consortium OGC (Open Geospatial Consortium). Specifically, it includes an ontology unit 100, a relationship setting unit 200, an assignment unit 300, a query input unit 400, and a result value calculation unit 500.

[0025] The ontology unit 100 stores the measured values ​​and metadata for the sensor, including a Thing class 101 having information about the name, description, and attributes of the sensor; a multi-datastream class 103 linked to the Thing class 101 and having information about a JSON array; an observation class 105 linked to the multi-datastream class 103 and having a value that records the time when the sensor's measured value is input; a result class 107 linked to the observation class 105 and having the measured value input from the sensor; a metadata class for each metadata related to the sensor's measured value, including an observation attribute class 109 having the sensor's observation attribute information as a literal; a measurement unit class 111 having the measurement unit information for the sensor's measured value as a literal; a data type class 113 having the sensor's data format information as a literal; and an index point 120 linked to have a one-to-one correspondence with any of the observation attribute class 109, measurement unit class 111, and data type class 113, and linked to at least one result class 107.

[0026] Here, index point 120 plays the role of combining metadata for each sensor and forming a connection relationship with the sensor. Using index point 120, it is possible to process directly using the connection relationship with metadata queries from the multi-data stream class 103 of the Thing class 101, demonstrating that the features of the STA standard model can be used identically in ontology. This provides ontology users with the ability to select the relationship that ensures optimal performance for each query, whether combining specific metadata for a physical sensor set (i.e., all "Things") or combining specific metadata for a specific "Thing".

[0027] Here, the observation attribute information may be temperature, atmospheric pressure, humidity, etc., and the literal may be a string corresponding to the observation attribute information.

[0028] The ontology structure, based on the class-to-class linkage relationships of the ontology section 100 according to the embodiment of the present invention, is compatible with the ontology structure based on the STA standard model described above.

[0029] In the ontology section 100 according to an embodiment of the present invention, the result class 107 may correspond to the result attribute, which is directly related to the sensor measurement value, among the UML attributes defined in the STA standard model; the observation attribute class 109 may correspond to the ObservationProperty attribute, which is related to observation attribute metadata for the sensor measurement value, among the UML classes defined in the STA model; the measurement unit class 111 may correspond to the unitOfMeasurements attribute, which is related to measurement unit metadata for the sensor measurement value, among the UML attributes defined in the STA model; and the data type class 113 may correspond to the multiObservationDatatype attribute, which is related to data format metadata for the sensor measurement value, among the UML attributes defined in the STA model.

[0030] On the other hand, in embodiments of the present invention, since the ontology in a sensor program where weight reduction and speed are paramount must be defined by consistent rules, an extended STA model structure is adopted that has a multi-datastream, which is a modified version of the datastream defined in the official STA UML diagram.

[0031] This is because, in the STA standard model, data streams and multidatas JPEG2026090221000002.jpg16169

[0032] (Equation 1) JPEG2026090221000003.jpg785

[0033] As a result, in embodiments of the present invention, measurement data relating to various observation attributes can be managed and analyzed efficiently and consistently.

[0034] The relationship setting unit 200 sets predicates that represent the relationships between classes or values ​​of each class in the ontology unit 100, according to the user's input. In embodiments of the present invention, attributes corresponding to UML classes or JSON arrays in the STA standard model are defined as OWL classes, and object properties and data properties including the inverse relationships thereunder are set.

[0035] In other words, in an embodiment of the present invention, a predicate (e.g., has) can be set via the relationship setting unit 200 in response to user input to set a relationship between classes, or a relationship between classes and the values ​​they possess. Formula 2 is an example of establishing interrelationships between classes.

[0036] (Equation 2) JPEG2026090221000004.jpg7138

[0037] hasObservation is an expression formed by combining the English expression "has," which is an active predicate corresponding to the predicate, and the English expression "Observation," which corresponds to the subject or object, because equation 2 means that the multi-data stream has the observation attribute.

[0038] When a relationship is established as in the case of equation 2, the multi-data stream class 103 and the observation class 105 are set to have a relationship as indicated by the predicate "has". In this case, the multi-data stream class 103 can be interpreted as having the observation class 105.

[0039] The relationship setting unit 200 may set an active predicate according to user input when a superclass and a subclass of the ontology unit 100 are linked, or when a class is linked to a value that the class possesses, and set a passive predicate according to user input when a subclass and a superclass are linked, or when classes or values ​​of the same level are linked.

[0040] The distinction between superclasses, subclasses, and same-level classes can be a classification in ontology structure that takes into account the linking relationships and linking attributes between classes. Furthermore, in embodiments of the present invention, the class names or attribute names within the STA standard model are used identically as the names of the classes, values ​​belonging to the classes, and relationships in the ontology section 100.

[0041] This prevents ambiguity in data processing for elements with the same name but differing only in case, such as the "Location" class and its internal "location" attribute in the STA standard model, thereby enabling consistent data processing and integration with services that use the STA standard model.

[0042] The ontology structure formed by the relationship set in the ontology section 100 and the relationship setting section 200 according to the embodiment of the present invention has an ontology structure that corresponds to the definition expressed in the STA standard model. Therefore, the subject and object that come through a specific predicate can also be defined in the same or similar way as in the STA standard model.

[0043] In the ontology structure based on the relationship set by the ontology unit 100 and the relationship setting unit 200 according to the embodiment of the present invention, there are subjectable rule domains and objectable rule ranges of object properties or data properties, similar to the STA standard model, and additional restrictions can be included.

[0044] For example, in the ontology structure according to an embodiment of the present invention, as shown in Equation 3, any value (x) belonging to the set of values ​​belonging to the Observation class 105, which indicates a viewpoint, is defined to be linked to any one (y) belonging to the set of values ​​of one or more Result class 107, as shown in Equation 3, using "hasresult" which expresses the relationship with the Result class. As a restriction, it can be defined that any value belonging to the set of values ​​belonging to the Observation class is always linked to a value in the set of values ​​of one or more Result classes.

[0045] (Equation 3) JPEG2026090221000005.jpg7143

[0046] In the ontology structure according to the embodiment of the present invention, the properties may have the aforementioned Domain, Range, and Restriction as Characteristics. This is to ensure data consistency and clarity by consistently defining the ontology from both a class and property perspective, thereby integrating data to solve the heterogeneous data processing problem that is essential for sensor structures for digital twins and preventing silo phenomena.

[0047] Table 1 shows examples of how object properties f(x,y) are used in the OWL ontology when it means that objects x and y are used as the subject and object of the predicate f.

[0048] [Table 1]

[0049] The JSON concatenation structure of the STA standard model, as represented by UML, can be divided into two conditions: it can have zero or one element or relationship, or it can have zero or an unlimited number of elements or relationships. Relationships between attributes or classes represented by arrays with an unlimited number of connections, as in the latter case, use an index as an identifier.

[0050] The STA standard model classes "MultiDatastream" and "Observation" have classes and attributes that are directly related to sensor measurements. The "ObservationProperty" class is linked to the "MultiDatastream" class, and within the "MultiDatastream" class, there are attributes such as "unitOfMeasurements" and "multiObservationType". The "Observation" class has numerous result attributes. In fact, when creating an STA standard model in JSON format for use in services such as FROST, these values ​​are linked via array indices. However, since these index structures cannot be directly represented in OWL predicates, they must be represented with additional predicates.

[0051] Representing an index directly as a predicate means converting an infinitely long index into an attribute with its own inherent meaning. This limits the flexibility and semantic expressiveness of RDF (Resource Description Framework), a framework for describing resources within an ontology, making it unsuitable to directly convert the STA standard model into an ontology.

[0052] Therefore, in the embodiments of the present invention, the classes and inter-class relationships of the ontology section 100 are characterized by being compatible with the STA standard model, but modified to match the ontology structure that takes RDF into consideration.

[0053] In the STA standard model, the three classes of metadata for the measured value "result"—"ObservationProperty," "unitOfMeasurements," and "multiObservationType"—and their class values ​​are related to "result," which proliferates as the number of "Observations" increases. Because they contain potentially duplicate values, they are not suitable for representing separate, simple values ​​as literals.

[0054] Therefore, the ontology section 100 in the embodiment of the present invention includes a result class 107, an observation attribute class 109, a measurement unit class 111, and a data type class 113. This minimizes redundancy and allows for the reuse of attributes, preparing the system for complex inference and analysis.

[0055] Furthermore, since the subject or object within the triple structure must always be a class or literal defined in OWL, the class in the ontology section 100 is set to be a class or literal defined in OWL, and the predicate in the relationship setting section 200 is set to be a predicate for a class or literal defined in OWL.

[0056] The assignment unit 300 assigns the sensor's measured values ​​and metadata related to the sensor to the corresponding class values ​​in accordance with predetermined rules or user input, matching the classes in the ontology unit 100 and the relationships set in the relationship setting unit 200. In other words, values ​​from the sensor and metadata for the sensor are input via the allocation unit 300 in accordance with the ontology structure based on the relationships set in the ontology unit 100 and the relationship setting unit 200, and the sensor data can be used in accordance with the ontology structure.

[0057] Figure 2 is an illustrative diagram showing how values ​​from a sensor and metadata for a sensor are input in accordance with the ontology structure of a sensor metadata processing device 10 having an open standard-based ontology according to an embodiment of the present invention.

[0058] In Figure 2, classes that perform the same function as the ontology unit 100 of the sensor metadata processing device 10 having an open standard-based ontology according to the embodiment of the present invention shown in Figure 1 are given the same reference numerals, and detailed descriptions are omitted.

[0059] The query input unit 400 receives query input from the user, which consists of a combination of subject, object, and predicate that includes a predicate set in the relationship setting unit 200 and a class or a value that each of the classes in the ontology unit 100 as the subject or object.

[0060] Here, a query can be a combination of instructions to retrieve sensor data according to the user's needs. The query can be constructed to include index point 120.

[0061] When a query is input via the query input unit 400, the result value calculation unit 500 retrieves the values ​​of the result class 107 and metadata classes 109, 111, and 113 of the ontology unit 100 via the index points of the ontology unit 100, calculates a result value based on the values ​​of the result class 107 and metadata classes 109, 111, and 113 of the ontology unit 100, operators according to predefined rules, and the query.

[0062] The result value calculation unit 500 may call an index point 120 associated with the subject or object included in the query and a class having a predicate corresponding to the subject or object, or a value held by such a class, and calculate the result value by applying arithmetic or logical operations to the values ​​held by the result class 107 linked to the index point 120 and the multiple classes linked to it.

[0063] The sensor metadata processing device having an open standard-based ontology according to an embodiment of the present invention is compatible with the STA standard model used in the sensor field, resolves the silo phenomenon where data is isolated between organizations or services, and ensures reusability and semantic consistency of the data by embodying it in an ontology.

[0064] <Experimental Data> To understand the sensor data processing performance when using index points of the sensor metadata processing device 10 having an open standard-based ontology according to an embodiment of the present invention, a virtual smart city was constructed and experiments were conducted assuming a virtual scenario.

[0065] Figure 3 is a conceptual diagram of a virtual smart city environment for performance testing of a sensor metadata processing device 10 having an open standard-based ontology according to an embodiment of the present invention.

[0066] The virtual smart city environment for the experiment assumed that multiple smart poles, each equipped with a composite sensor and smart scanner, were installed in multiple areas, with a spacing of 50M between the smart poles, and measurements were assumed to be taken for a unit area of ​​50M x 100M.

[0067] Tables 2 and 3 contain metadata of measurements for two "Things" (representing a composite sensor and a smart scanner) installed on a single smart pole. Table 2 shows metadata for measurements from the combined sensor, and Table 3 shows metadata for measurements from the smart scanner.

[0068] [Table 2]

[0069] [Table 3] The query scenarios used in the experiment are shown in Table 4.

[0070] [Table 4]

[0071] In query scenarios Q1 to Q3, queries created without using index points were designated as Q1-1, Q2-1, and Q3-1, while queries created with index points were designated as Q1-2, Q2-2, and Q3-2. The average CV (Coefficient of Variation) of query processing time and the average query processing time were calculated.

[0072] Table 5 shows the average Coefficient of Variation (CV) of query processing time for Q1-1 to Q3-2, and Table 6 shows the average query processing time for Q1-1 to Q3-2. In Tables 5 and 6, N is the number of areas and M is the number of observed attributes.

[0073] [Table 5]

[0074] [Table 6]

[0075] As shown in Table 5, we were able to confirm an average conversion rate of less than 10% per instance used for queries and experiments, and we were able to confirm that the average value was lower when query processing was performed using index points compared to when it was not used.

[0076] Furthermore, as shown in Table 6, it can be seen that when query processing takes index points into consideration, the processing speed can decrease by up to 99.93% and down to 41.31%.

[0077] The STA ontology demonstrates the ability to efficiently process queries related to smart cities, and in particular, the index points of the ontology section 100 according to the embodiment of the present invention demonstrate optimization even in the case of metadata-perspective queries in a digital twin background.

[0078] Complex metadata queries functioned correctly in the digital twin environment without experiencing heterogeneity issues. The ontology structure of the sensor metadata processing device 10, which has an open standards-based ontology according to an embodiment of the present invention, is suitable for smart cities where data connectivity and rapid inference are critical considerations.

[0079] Although the present invention has been described in detail above through preferred embodiments, the present invention is not limited thereto and can be implemented in various ways within the scope of the claims. In particular, the foregoing has described the features and technical strengths of the present invention in a somewhat broad manner so that the claims of the invention described later may be better understood. Therefore, it should be recognized by those skilled in the art that the above-described concepts and specific embodiments of the present invention are the basis for the design or modification of other forms to accomplish similar purposes and can be immediately used.

[0080] Furthermore, the embodiments described above are merely one embodiment of the present invention and can be understood by those with ordinary skill in the art to realize various modified and altered forms within the scope of the technical idea of ​​the present invention. Therefore, the disclosed embodiments should be considered in an explanatory rather than restrictive view, and as indicated in the claims of the present invention above, all differences within an equivalent scope should be interpreted as being included in the present invention. [Explanation of Symbols]

[0081] 10 Sensor metadata processing device with open standards-based ontology 100 Ontology Section 101 Things Class 103 Multi-Data Stream Class 105 Observation Class 107 Result Class 109 Observation Attribute Class 111 Measurement Unit Classes 113 Data Type Classes 120 Index Points 200 Relationship Setting Section 300 allocation section 400 Query Input Section 500 Result Value Calculation Unit

Claims

1. An ontology unit for storing measurement values ​​and metadata for a sensor, including: a result class having measurement values ​​input from a sensor; metadata classes for each metadata relating to the measurement values ​​of the sensor, each including an observation attribute class having observation attribute information of the sensor as a literal, a measurement unit class having measurement unit information for the measurement values ​​of the sensor as a literal, a data type class having data format information of the sensor as a literal, and an index point linked to any one of the observation attribute class, the measurement unit class, and the data type class, and linked to at least one result class; A relationship setting unit sets predicates that represent the relationships between classes or values ​​of the aforementioned ontology section, according to user input. A query input unit receives input from the user for queries that include a predicate set in the relationship setting unit and a combination of subject, object, and predicate, which includes the class or the value that each of the classes in the ontology unit has as the subject or object. A sensor metadata processing device having an open standard-based ontology, which, when the aforementioned query is input, retrieves the values ​​of the result class and metadata class of the ontology section via the index point of the ontology section, and includes the values ​​of the result class and metadata class of the ontology section, operators according to predefined rules, and a result value calculation unit that calculates a result value based on the query.

2. The aforementioned result value calculation unit, A sensor metadata processing device having an open standard-based ontology according to claim 1, characterized in that it calls an index point associated with a class having a subject or object included in the query and a predicate corresponding to the subject or object, or a value held by the class.

3. A sensor metadata processing device having an open standard-based ontology, as described in claim 2, characterized in that it calculates a result value by applying arithmetic or logical operations to the values ​​of a result class linked to an index point and to a plurality of classes linked to it.

4. The aforementioned relationship setting unit is: A sensor metadata processing device having an open standard-based ontology according to claim 1, characterized in that when a superclass and a subclass, or a class and a value possessed by a class are linked, an active predicate is set according to the user's input, and when a subclass and a superclass, or classes or values ​​of the same level are linked, a passive predicate is set according to the user's input.

5. A sensor metadata processing device having an open standard-based ontology, according to claim 1, further comprising an assignment unit that assigns the measured values ​​of the sensor and metadata related to the sensor to class-specific values ​​according to predetermined rules or user input, in accordance with the class of the ontology unit and the association relationship set by the association relationship setting unit.

Images