KR102665209B1 - BIM data query system, apparatus and method - Google Patents

Abstract

The present invention relates to a BIM data query system, device, and method. More specifically, the present invention relates to an ontology-based conversion and storage of BIM data, which has the effect of increasing the connectivity, scalability, recyclability, and maintainability of BIM data. there is.

Description

BIM data query system, apparatus and method}

The present invention relates to a BIM data query system, device, and method. More specifically, the present invention relates to an ontology-based conversion and storage of BIM data, which has the effect of increasing the connectivity, scalability, recyclability, and maintainability of BIM data. there is.

Recently, with the start of full-scale BIM (Building Information Modeling) orders, interest in methods to extract knowledge information necessary for decision-making from the generated BIM is increasing.

Generally, information generated through BIM modeler programs is used in limited areas such as clash checking and process simulation. If you want to use data in conjunction with heterogeneous data, such as facility management, rather than data generated by a BIM modeler, save the BIM attribute information in RDBMS (Relational Database Management System), search, and retrieve the results in a separately developed program. Develop and use a separate system that shows.

This approach causes problems such as having to redefine the database schema and migrate existing stored data and business logic to fit the newly defined schema when a request for connection and expansion of datasets related to BIM objects occurs. I order it.

For example, if you want to utilize IoT sensor data applied in the smart construction field from a BIM perspective, a new schema must be designed in RDBMS using the existing method, and business logic such as information query will have to be redeveloped in a specific programming language. These problems have a negative impact on the connectivity, scalability, recyclability, and maintainability of model information, which are one of the purposes of using BIM. One of our expectations when using BIM is to easily connect various heterogeneous datasets from the construction field with BIM to easily explore the information needed for decision making. However, if the schema of the BIM database is fixed to a specific form, it is difficult to use BIM as a data hub. Therefore, a system to solve these problems is needed.

Registration number 10-2353827, registration date January 17, 2022, 'Rule-based Scan-to-BIM mapping pipeline structure design device and method' Registration number 10-2105589, registration date April 22, 2020, 'BEMS sensor-BIM linkage device and method for energy monitoring'

The present invention was created in response to this need, and the purpose of the present invention is a BIM data query system that can increase the connectivity, scalability, recyclability, and maintainability of BIM data by converting and storing BIM data based on ontology. , to provide devices and methods.

In order to achieve the above object, the BIM data query device according to the present invention includes a data collection unit that collects BIM data from a BIM DB server; an object definition unit defining IFC objects of the collected BIM data; a data conversion unit that generates RDF data in a tuple structure by converting the defined IFC object based on ontology; a data storage unit where the RDF data is stored; and a question and answer unit that generates query results according to the request of the user terminal. It is characterized by including.

In addition, the object definition unit is characterized in that it defines one or more IFC objects among IfcRoot, IfcObject, and IfcPropertyDefinition.

In addition, the tuple structure is characterized in that it is specified in OWL (Web Ontology Language) language as follows.

Building rdf:type owl:Thing.

Building rdf:type _:x.

_:x owl:onProperty contain.

_:x owl:minCardinality "1"^^xsd:nonNegativeInteger.

In addition, the question answering unit includes a query analysis unit that receives a query about object information in the SPARQL language and interprets the query; a query search unit that searches RDF data according to the interpretation of the query analysis unit and, if matching data is found, outputs it as a return value in a tuple format; and a query result unit that visualizes the return value using a predefined language to generate a query result and transmits it to the user terminal. It is characterized by including.

Meanwhile, in order to achieve the above object, the BIM data query method according to the present invention includes step A in which the BIM data query device receives BIM data from the BIM DB server and converts it into ontology-based BIM data; Step B, where the user terminal requests a query about object information; and step C in which the BIM data query device generates a query result according to the request of the user terminal and transmits it to the user terminal; It is characterized by including.

In addition, step A includes a data collection unit collecting BIM data from the BIM DB server; An object definition unit defining an IFC object of the collected BIM data; A data conversion unit converting the defined IFC object based on ontology to generate tuple-structured RDF data; and a data storage unit storing the RDF data; It is characterized by including.

In addition, the object definition unit is characterized in that it defines one or more IFC objects among IfcRoot, IfcObject, and IfcPropertyDefinition.

In addition, the tuple structure is characterized in that it is specified in OWL (Web Ontology Language) language as follows.

Building rdf:type owl:Thing .

Building rdf:type _:x .

_:x owl:onProperty contain .

_:x owl:minCardinality "1"^^xsd:nonNegativeInteger.

In addition, step C includes: a query interpretation unit receiving a query about object information in the SPARQL language from a user terminal and interpreting the query; A query search unit searches RDF data according to the interpretation of the query analysis unit, and if matching data is found, outputting it as a return value in a tuple format; and a query result unit visualizing the return value using a predefined language to generate a query result and transmitting the query result to the user terminal. It is characterized by including.

Meanwhile, in order to achieve the above object, the BIM data query system according to the present invention includes a BIM DB server in which BIM data is stored; A BIM data query device that collects BIM data from the BIM DB server, converts it to ontology, and stores it; And a user terminal that performs a query request for object information to the BIM data query device; It is characterized by including.

In addition, the BIM data query device includes a data collection unit that collects BIM data from a BIM DB server; an object definition unit defining IFC objects of the collected BIM data; a data conversion unit that generates RDF data in a tuple structure by converting the defined IFC object based on ontology; a data storage unit where the RDF data is stored; and a question-and-answer unit that generates query results according to the request of the user terminal and transmits them to the user terminal. It is characterized by including.

The BIM data query system, device, and method according to the present invention has the effect of increasing the connectivity, scalability, recyclability, and maintainability of BIM data by converting and storing BIM data based on ontology.

The problems to be solved by the present invention are not limited to those mentioned above, and other problems not mentioned will be clearly understood by those skilled in the art from the description below.

1 is a block diagram of a BIM data query system according to an embodiment of the present invention.
Figure 2 is a block diagram of a BIM data query device according to an embodiment of the present invention.
Figure 3 is a block diagram of a question and answer section according to an embodiment of the present invention.
Figure 4 is a flowchart of the BIM data query method according to an embodiment of the present invention.
Figure 5 is a flowchart of a data conversion method according to an embodiment of the present invention.
Figure 6 is a schematic diagram of an object definition unit according to an embodiment of the present invention.
Figure 7 is an exemplary diagram of a data conversion unit according to an embodiment of the present invention.
Figure 8 is a flowchart of a question answering method according to an embodiment of the present invention.
Figure 9 is an exemplary diagram of a question and answer section according to an embodiment of the present invention.

The above objects, other objects, features and advantages of the present invention will be easily understood through the following preferred embodiments related to the attached drawings. However, the present invention is not limited to the embodiments described herein and may be embodied in other forms. Rather, the embodiments introduced herein are provided so that the disclosed content will be thorough and complete and so that the spirit of the present invention can be sufficiently conveyed to those skilled in the art.

When an element, component, device, or system is referred to herein as including a component consisting of a program or software, even if explicitly stated, that element, component, device, or system is intended to include a component consisting of a program or software. It should be understood as including hardware necessary for execution or operation (e.g., memory, CPU, etc.) or other programs or software (e.g., operating system or drivers required to run hardware, etc.).

Additionally, when an element (or component) is implemented, unless otherwise specified, it should be understood that the element (or component) may be implemented in any form of software, hardware, or software and hardware.

Additionally, the terms used in this specification are for describing embodiments and are not intended to limit the present invention. As used herein, singular forms also include plural forms, unless specifically stated otherwise in the context. As used in the specification, 'comprises' and/or 'comprising' does not exclude the presence or addition of one or more other elements.

Additionally, in this specification, terms such as 'unit' and 'device' may be intended to refer to the functional and structural combination of hardware and software driven by or for driving the hardware. For example, the hardware here may be a data processing device including a CPU or other processor. Additionally, software driven by hardware may refer to a running process, object, executable, thread of execution, program, etc.

Hereinafter, specific technical details to be implemented in the present invention will be described in detail with reference to the accompanying drawings.

Each configuration shown in the drawing indicates that it can be separated functionally and logically, and does not necessarily mean that each configuration is divided into a separate physical device or written in a separate code. Experts will be able to make inferences easily.

Figure 1 is a block diagram of a BIM data query system according to an embodiment of the present invention, Figure 2 is a block diagram of a BIM data query device according to an embodiment of the present invention, and Figure 3 is an embodiment of the present invention. This is a block diagram of the question and answer section according to an example.

As shown in Figure 1, the BIM data query system according to the present invention may be configured to include a BIM DB server 100, a BIM data query device 200, and a user terminal 300.

As shown, the BIM DB server 100 is a data storage device in which BIM data is stored, and may be composed of a plurality of devices, and may also store data in formats other than BIM data.

Here, BIM data refers to the process of virtually modeling facilities in a multidimensional virtual space, including planning, design, engineering (structure, equipment, electricity, etc.), construction, and even maintenance and disposal. Building in BIM refers to the entire life cycle of the target building - design, construction, operation and management, information refers to all information included in the entire life cycle of the target building, and modeling refers to all information included in the entire life cycle of the target building. It refers to an integrated tool and platform that provides production, management, and publication of all information included in the entire life cycle.

The BIM method is a 3D-based design and modeling method that converts buildings into data to create numerical data and allows you to see 3D display effects. Rather than simple line and surface work, data on the length connecting the start and end points of the line are generated, and the area of the surface is converted into data based on a closed surface. And by combining length and area data, volume data can be obtained.

In addition, the BIM method includes information on the shape, attribute, relationship, and topology of objects, making it excellent for analysis, service connection, and usability. In other words, BIM recognizes the relationships between building objects such as walls, slabs, windows, doors, roofs, and stairs by expressing each attribute, and immediately reflects the changing elements of the building in the building design.

Therefore, by using BIM, regardless of whether the building to be designed is structured or unstructured, it is possible to integrate and utilize information at all stages through compatibility and sharing for each project and process for the data generated when constructing a building. .

The BIM data query device 200 is configured to convert and store BIM data from the BIM DB server 100 into an ontology method. As shown in FIG. 2, it includes a data receiving unit 210, an object defining unit 220, It may include a data conversion unit 230 and a data storage unit 240.

At this time, the BIM data query device 200 receives BIM data from the BIM DB server 100 and converts it into the Ifc ontology method to generate RDF data, or receives data in a format other than BIM format and maps it to the IFC schema. And this can be converted to a general ontology method to generate RDF data.

In addition, the BIM data query device 200 is configured to generate and transmit a query result when the user terminal 300 requests a query for object information, and may further include a question response unit 250, and may further include a question response unit 250. As shown in FIG. 3, the response unit 250 may include a query analysis unit 251, a query search unit 252, and a query result unit 253.

The user terminal 300 can display query results provided from the BIM data query device 200, and visual results can be generated and displayed through mapping between RDF data and the BIM model.

Each of the components 100, 200, or 300 may include at least one processor. At least one processor may be an application specific integrated circuit (ASIC), a digital signal processor (DSP), a programmable logic device (PLD), a field programmable gate array (FPGA), a central processing unit (CPU), a graphic processing unit (GPU), or a microprocessor. It may be implemented with a controller (microcontroller) and/or microprocessor, etc. Each component 100, 200, or 300 may further include memory. Memory includes flash memory, hard disk, SSD (Solid State Disk), RAM (Random Access Memory), SRAM (Static Random Access Memory), ROM (Read Only Memory), and PROM (Programmable Read Only). Memory), EEPROM (Electrically Erasable and Programmable ROM), EPROM (Erasable and Programmable ROM), and/or eMMC (embedded multimedia card).

Additionally, each component (100, 200, or 300) may be connected through a network, where the network refers to a connection structure that allows information exchange between each node, such as a plurality of terminals and servers. Examples of networks include local area networks (LANs), wide area networks (WANs), World Wide Webs (WWWs), wired and wireless data networks, telephone networks, and wired and wireless television networks. Examples of wireless data communication networks include 3G, 4G, 5G, 3rd Generation Partnership Project (3GPP), 5th Generation Partnership Project (5GPP), Long Term Evolution (LTE), World Interoperability for Microwave Access (WIMAX), and Wi-Fi. , Internet, LAN (Local Area Network), Wireless LAN (Wireless Local Area Network), WAN (Wide Area Network), PAN (Personal Area Network), RF (Radio Frequency), Bluetooth network, NFC ( Near-Field Communication) network, satellite broadcasting network, analog broadcasting network, DMB (Digital Multimedia Broadcasting) network, etc. are included, but are not limited to these.

Hereinafter, the BIM data query method according to the BIM data query system configured as above will be described in detail through FIGS. 4 to 9.

Figure 4 is a flowchart of a BIM data query method according to an embodiment of the present invention. As shown in Figure 4, the BIM data query method according to the present invention includes the steps of the BIM data query device 200 receiving BIM data from the BIM DB server 100 and converting it into ontology-based BIM data (S100). A step in which the user terminal 300 requests a query for object information (S200) and a step in which the BIM data query device 200 generates a query result according to the request of the user terminal 300 and transmits it to the user terminal 300. It consists of (S300).

Looking at the above step (S100) in more detail, it is as shown in FIG. 5. Figure 5 is a flowchart of a data conversion method according to an embodiment of the present invention. As shown in Figure 5, the step (S100) is a step (S110) in which the data collection unit 210 collects BIM data from the BIM DB server 100 and the object definition unit 220 collects the collected BIM data. A step of defining an IFC object (S120), a step of the data conversion unit 230 converting the defined IFC object based on ontology to generate tuple-structured RDF data (S130), and the data storage unit 240. It consists of a step (S140) in which RDF data is stored.

In step S110, the data collection unit 210 can receive not only BIM data but also data in other formats.

In the step S120, the object definition unit 220 may define an IFC object for the collected BIM data. At this time, one or more IFC objects among IfcRoot, IfcObject, and IfcPropertyDefinition can be defined. This is because all objects of IFC start from IfcRoot, so at least IfcRoot must be defined. This embodiment is shown in FIG. 6. Figure 6 is a schematic diagram of an object definition unit according to an embodiment of the present invention.

Additionally, the object definition unit 220 can map collected data of other formats to the IFC schema and define an IFC object as described above.

In the steps (S130, S140), the data conversion unit 230 converts the defined IFC object into an Ifc ontology-based Ifc perspective in the case of BIM data and a general ontology-based in the case of data in other formats, into a tuple structure. RDF data can be generated and stored in the data storage unit 240, as shown in FIG. 7. Figure 7 is an exemplary diagram of a data conversion unit according to an embodiment of the present invention.

Here, RDF (Resource Description Framework) is a framework for expressing web resources as structured data. The data structure of RDF has a tuple structure of subjects, objects, and predicates, where resources are expressed as nodes, and a set of RDFs is a labeled RDF. It is expressed in the form of a graph.

At this time, the resource is identified by URI (Universal Resource Identifier). RDF data formats include XML syntax-based RDF/XML, Turtle (TTL), N-Tripes, and JSON-based JSON-LD and N3.

Additionally, the tuple structure can be specified in OWL (Web Ontology Language) language as follows.

Building rdf:type owl:Thing.

Building rdf:type _:x.

_:x owl:onProperty contain.

_:x owl:minCardinality "1"^^xsd:nonNegativeInteger.

OWL (Ontology Web Language) is an ontology definition language for expressing shared general understanding, concepts, and relationships between concepts for a specific domain, and defines relationships between vocabularies to describe RDF.

Next, in the above step (S200), the user terminal 300 requests a query for object information. At this time, the query language of the user terminal 300 is SPARQL (Simple Protocol and RDF Query Language), and SPARQL is It is a standard query language over HTTP for searching and manipulating data stored in RDF format.

At this time, in order to effectively query object information, the user terminal 300 can perform a query using SPARQL to filter out graph nodes unnecessary for search as shown below.

Inst:IfcWindow_6518 rdf:type Ifc:IfcWindow.

Inst:IfcRelDefinesByProperties_6532

ifc:golballd_IfcRoot inst:IfcGloballyIniqueld_20226;

ifc:ownerHistory_IfcRoot inst:IfcOwnerHistory_41;

ifc:relatedObjects_IfcRelDefines inst:IfcWindow_6518;

ifc:relatingPropertyDefinition_IfcRelDefinesByproperties

inst:IfcPropertySet_6524

inst:IfcPropertySet_6524

ifc:name_IfcRoot inst:IfcLabel_20219;

ifc:hasProperties_IfcPropertySet inst:IfcPropertySingleValue_6523.

Additionally, the RDF format defines the concept domain with a prefix that defines the namespace of the tuple component, where the inst prefix refers to the object instance of the IFC. Since the subject and object of the tuple have a graph structure in which they are interconnected, a query can be performed as follows to retrieve object attribute information.

SELECT ?subject ?property ?name ?value

WHERE {

?subject rdf:type ifc:IfcWindowStyle.

?subject ifc:hasPropertySets_IfcTypeObject ?property_set.

?property_set ifc:globalId_IfcRoot ?guid ;

ifc:ownerHistory_IfcRoot ?own_history ;

ifc:name_IfcRoot ?label ;

ifc:hasProperties_IfcPropertySet ?property.

?property ifc:name_IfcProperty ?identifier.

?identifier express:hasString ?name.

?property ifc:nominalValue_IfcPropertySingleValue ?value.

}

In the above SPARQL query statement, `?` refers to a variable that will contain the query result, and the WHERE statement can define query conditions similarly to an SQL statement.

Lastly, looking at the above step (S300) in more detail, it is shown in FIG. 8. Figure 8 is a flowchart of a question answering method according to an embodiment of the present invention. As shown in FIG. 8, the step (S300) includes a step (S310) in which the query interpretation unit 251 receives a query about object information in the SPARQL language from the user terminal 300 and interprets it, and a query search unit (252) searches the RDF data according to the interpretation of the query analysis unit 251, and if there is matching data, outputs it as a return value in the form of a tuple (S320), and the query result unit 253 returns the return value. It consists of a step (S330) of visualizing the value through a predefined language to generate a query result and transmitting it to the user terminal 300.

The steps (S310 to S330) may be performed as shown in FIG. 9. Figure 9 is a diagram illustrating an example of a question and answer section according to an embodiment of the present invention. As shown in FIG. 9, the question answering unit 250 performs query analysis, searches RDF data according to the analysis, outputs a return value in a tuple format, and visualizes the return value through a predefined language. to generate query results.

Therefore, as described above, the BIM data query system, device, and method according to the present invention have the effect of increasing the connectivity, scalability, recyclability, and maintainability of BIM data by converting and storing BIM data based on ontology. There is.

In the above, even though all the components constituting the embodiment of the present invention have been described as being combined or operated in combination, the present invention is not necessarily limited to this embodiment. That is, as long as it is within the scope of the purpose of the present invention, all of the components may be operated by selectively combining one or more of them. In addition, although all of the components may be implemented as a single independent hardware, a program module in which some or all of the components are selectively combined to perform some or all of the combined functions in one or more pieces of hardware. It may also be implemented as a computer program having. The codes and code segments that make up the computer program can be easily deduced by a person skilled in the art of the present invention. Such a computer program can be stored in a computer-readable storage medium and read and executed by a computer, thereby implementing embodiments of the present invention.

Meanwhile, although the preferred embodiments have been described and illustrated to illustrate the technical idea of the present invention, the present invention is not limited to the configuration and operation as shown and described, and does not deviate from the scope of the technical idea. Without limitation, those skilled in the art will understand that many changes and modifications can be made to the present invention. Accordingly, all such appropriate changes, modifications and equivalents should be considered to fall within the scope of the present invention. Therefore, the true scope of technical protection of the present invention should be determined by the technical spirit of the attached registration claims.

100: BIM DB server
200: BIM data query device
210: data receiving unit
220: Object definition part
230: data conversion unit
240: data storage unit
250: Question and answer section
251: Query analysis unit
252: Query search unit
253: Query result section
300: User terminal

Claims (11)

A data collection unit that collects BIM data from the BIM DB server;
an object definition unit defining one or more IFC objects among IfcRoot, IfcObject, and IfcPropertyDefinition in the collected BIM data;
a data conversion unit that generates RDF data in a tuple structure by converting the defined IFC object based on ontology;
a data storage unit where the RDF data is stored; and
Includes a question and answer section that generates query results according to the request of the user terminal;
The tuple structure is,
A BIM data query device characterized by a BIM data query device specified in OWL (Web Ontology Language) language as follows.
Building rdf:type owl:Thing.
Building rdf:type _:x.
_:x owl:onProperty contain.
_:x owl:minCardinality "1"^^xsd:nonNegativeInteger.
delete delete According to paragraph 1,
In the question and answer section,
A query interpretation unit that receives queries about object information in the SPARQL language and interprets them;
A query search unit that searches RDF data according to the interpretation of the query analysis unit and, if matching data is found, outputs it as a return value in tuple format; and
a query result unit that visualizes the return value using a predefined language to generate a query result and transmits it to the user terminal;
BIM data query device comprising a.
A BIM data query device receiving BIM data from a BIM DB server, and a data collection unit collecting BIM data from the BIM DB server;
A step of defining an IFC object of the collected BIM data by an object definition unit defining one or more IFC objects among IfcRoot, IfcObject, and IfcPropertyDefinition;
A data conversion unit converting the defined IFC object based on ontology to generate RDF data in a tuple structure; and
A data storage unit storing the RDF data;
A user terminal requesting a query about object information; and
Including a step where the BIM data query device generates a query result according to the request of the user terminal and transmits it to the user terminal,
The tuple structure is,
A BIM data query method characterized in that it is specified in OWL (Web Ontology Language) language as follows.
Building rdf:type owl:Thing .
Building rdf:type _:x .
_:x owl:onProperty contain .
_:x owl:minCardinality "1"^^xsd:nonNegativeInteger.
delete delete delete According to clause 5,
The step of generating the query result and transmitting it to the user terminal,
A query interpretation unit receiving a query about object information in the SPARQL language from a user terminal and interpreting the query;
A query search unit searches RDF data according to the interpretation of the query analysis unit, and if matching data is found, outputting it as a return value in tuple format; and
A query result unit visualizing the return value using a predefined language to generate a query result and transmitting the query result to the user terminal;
BIM data query method comprising:

delete delete

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