CN112699282A - Industrial internet data processing method and device, electronic equipment and storage medium - Google Patents
Industrial internet data processing method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The embodiment of the application provides an industrial internet data processing method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring dynamic data in industrial internet data and static data corresponding to the dynamic data, wherein the dynamic data are data generated by state change of an industrial product in a life cycle, and the static data are data describing the dynamic data; acquiring the relation between each static data and the dynamic data; and for each static data, constructing triple structure data comprising the static data, the relation and the dynamic data according to the relation between the static data and the dynamic data, and forming knowledge graph data corresponding to the industrial internet data. By adopting the scheme in the application, the industrial internet data can be unified in format and convenient to manage.
Description
Technical Field
The present application relates to data processing technologies, and in particular, to an industrial internet data processing method, apparatus, electronic device, and storage medium.
Background
In the whole life cycle of industrial internet production and supply chain, each link of the industrial product is recorded with information, and industrial internet data corresponding to the industrial product is generated. The data formats of the industrial internet data recorded by different recording nodes in different links, different industries, different enterprises and the like are different, so that the data management is difficult.
Disclosure of Invention
The embodiment of the application provides an industrial internet data processing method and device, electronic equipment and a storage medium, and formats of industrial internet data are unified into knowledge graph data, so that management is facilitated, and the problems are solved.
According to a first aspect of embodiments of the present application, there is provided an industrial internet data processing method, including: acquiring dynamic data in industrial internet data and static data corresponding to the dynamic data, wherein the dynamic data are data generated by state change of an industrial product in a life cycle, and the static data are data describing the dynamic data; acquiring the relation between each static data and the dynamic data; and for each static data, constructing triple structure data comprising the static data, the relation and the dynamic data according to the relation between the static data and the dynamic data, and forming knowledge graph data corresponding to the industrial internet data.
According to a second aspect of embodiments of the present application, there is provided an industrial internet data processing apparatus, including: the data acquisition module is used for acquiring dynamic data in industrial internet data and static data corresponding to the dynamic data, wherein the dynamic data are data generated by state change of an industrial product in a life cycle, and the static data are data describing the dynamic data; the relation acquisition module is used for acquiring the relation between each static data and the dynamic data; and the map generation module is used for constructing triple structure data comprising the static data, the relation and the dynamic data according to the relation between the static data and the dynamic data for each piece of static data to form knowledge map data corresponding to the industrial internet data.
According to a third aspect of embodiments of the present application, there is provided an electronic apparatus, including: one or more processors; a memory; one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs configured to perform the methods described above.
According to a fourth aspect of embodiments of the present application, there is provided a computer usable storage medium having program code stored therein, the program code being invoked by a processor to perform the method described above.
By adopting the industrial internet data processing method and device, the electronic equipment and the storage medium provided in the embodiment of the application, format conversion is performed on dynamic data in industrial internet data and static data describing the dynamic data, triple structure data including the static data, the relation and the dynamic data is constructed, the formats of the industrial internet data are unified, and therefore the management difficulty of the data is reduced.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a flowchart of an industrial internet data processing method according to an embodiment of the present disclosure;
FIG. 2 is a schematic view of knowledge-graph data provided in an embodiment of the present application;
FIG. 3 is a schematic illustration of another knowledge-graph data provided by an embodiment of the present application;
FIG. 4 is a flowchart of a method for processing industrial Internet data according to another embodiment of the present application;
FIG. 5 is a schematic representation of further knowledge-graph data provided in an embodiment of the present application;
fig. 6 is a schematic diagram of a static node according to an embodiment of the present application;
FIG. 7 is a schematic view of knowledge-graph data for a particular scenario provided by an embodiment of the present application;
FIG. 8 is another illustrative view of knowledge-graph data for a particular scenario provided by an embodiment of the present application;
FIG. 9 is a diagram of additional knowledge-graph data for a particular scenario provided by an embodiment of the present application;
fig. 10 is a functional block diagram of an industrial internet data processing apparatus according to an embodiment of the present application;
fig. 11 is a block diagram of an electronic device for executing an industrial internet data processing method according to an embodiment of the present application;
fig. 12 is a storage unit for storing or carrying program codes for implementing the industrial internet data processing method according to the embodiment of the present application.
Detailed Description
In the whole life cycle of raw material supply, production, circulation and use of industrial products, each link records data related to the products to form industrial internet data of the industrial products, for example, the raw material supply link records the name of a supplier of raw materials, the supply time, the supply mode, the batch number, the batch and the like, the production link records the name of a manufacturer, the production time, the production address and the like, the circulation link records the name of a transporter, the warehousing time, the ex-warehouse time, the warehousing place, the ex-warehouse place and the like, and the use link records the identity, the position, the name and the like of a user. And the whole industry chain data of each industrial product in the whole life cycle can be obtained by analyzing the industrial internet identification corresponding to the industrial product.
In the process of implementing the application, the inventor finds that in the technical field of industrial internet, because of differences of industries, types, scales, products and the like of enterprises, industrial internet data are different, and the processing difficulty of the industrial data is higher due to higher complexity of data formats and data models of the industrial internet data. The data format or data model of the data is different due to different recorders, so that the processing difficulty of the data is higher, for example, the difficulty of searching the data is increased, and the difficulty of presenting the data is increased.
In addition, because the industrial product has different life cycle links in the whole life cycle process, the state of the industrial product changes along with the change of the links in the life cycle, and the state of the industrial product may also change in the same link, such as the change of position, ownership, management right, form and the like in the production, circulation and use processes. Data resulting from dynamic changes in state are typically recorded by different recorders, possibly in different formats, and during dynamic changes in state of the industrial product, dynamic data representing the state changes and static data describing the state are generated.
In the embodiment of the application, the dynamic data may represent the state of the industrial product, and is used to describe data, such as production data, circulation data, and usage data, of the industrial product, which are recorded during production, circulation, and usage and are generated by state changes of location, ownership, management right, form, and the like, and a user may expand the data as needed. Wherein the production data is used to describe the process of the industrial product from raw materials to products through processing; the circulation data is used for describing warehousing, transportation and sales information of industrial products generated in a supply chain; the usage data is used to describe data generated by the industrial product in use. That is, the dynamic data may record information such as event identifiers, state generation time, and state descriptions of the states, so as to implement recording of different states, and specifically record which data of each state is not limited in this embodiment, and may be set as needed.
The static data corresponding to the dynamic data describes various attribute features of the state, for example, data which is unique to an object related to the state and is different from attribute features of other entities can be described, and which attribute features are specifically described. Wherein, it is understood that a dynamic data may be a single data or a data set; each dynamic data may correspond to one or more static data, each static data may be a single data or a data set, and may be set as required, so as to implement clear description of features that need to be described.
Therefore, in view of the above problems, embodiments of the present application provide an industrial internet data processing method, an apparatus, an electronic device, and a storage medium, which can obtain dynamic data and static data corresponding to the dynamic data from industrial internet data, where the static data is data describing the dynamic data, or the static data is data describing a state corresponding to the dynamic data. And acquiring the relation between the static data and the dynamic data, and constructing triple structure data comprising the static data, the relation and the dynamic data, so that the uniform format of the industrial internet data is realized, the data relation is clear, and the management of the industrial internet data is facilitated.
The scheme in the embodiment of the application can be implemented by adopting various computer languages, such as object-oriented programming language Java and transliterated scripting language JavaScript.
In order to make the technical solutions and advantages of the embodiments of the present application more apparent, the following further detailed description of the exemplary embodiments of the present application with reference to the accompanying drawings makes it clear that the described embodiments are only a part of the embodiments of the present application, and are not exhaustive of all embodiments. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
Fig. 1 shows an industrial internet data processing method provided by an embodiment of the present application, which can be applied to a server, a computer, or other electronic devices. Referring to fig. 1, the method includes:
step S110: the method comprises the steps of obtaining dynamic data and static data corresponding to the dynamic data in industrial internet data, wherein the dynamic data are data generated by state change of industrial products in a life cycle, and the static data are data describing the dynamic data.
The method comprises the steps of obtaining dynamic data and static data describing the dynamic data from industrial internet data needing to be processed. The industrial internet data to be processed may include one or more dynamic data, and if the industrial internet data is one dynamic data, the dynamic data and static data describing the dynamic data are acquired; if the number of the dynamic data is multiple, the multiple dynamic data and the static data corresponding to each dynamic data may be obtained.
In the embodiment of the application, if the industrial internet data comprises a plurality of dynamic data, each dynamic data and the static data corresponding to the dynamic data are subjected to data processing and converted into knowledge graph data. The method comprises the steps of acquiring dynamic data and static data corresponding to the dynamic data, processing and converting the dynamic data and the static data into knowledge graph data, acquiring next dynamic data and corresponding static data, processing and converting the next dynamic data and corresponding static data into knowledge graph data; and the knowledge graph data corresponding to each dynamic data can be generated according to each dynamic data and the corresponding static data.
In the embodiment of the application, when the knowledge graph data is correspondingly constructed for each piece of dynamic data, the construction mode is the same, for example, the dynamic data a and the dynamic data B are obtained from industrial internet data to be processed, the knowledge graph data can be constructed by the dynamic data a and the static data corresponding to the dynamic data a, and the knowledge graph data can be constructed by the dynamic data B and the static data corresponding to the dynamic data B. Therefore, in the embodiment of the present application, the description of the construction of the knowledge graph data is mainly performed by taking one dynamic data and a static data corresponding to the dynamic data as examples.
Step S120: and acquiring the relation between each static data and the dynamic data.
Since static data describes dynamic data, or static data describes the state represented by dynamic data, there is a relationship between each static data and dynamic data. In the embodiment of the present application, the specific relationship between each static data and each dynamic data is not limited, and may be defined according to the features described by the static data, and if the static data describes the occurrence place of the state represented by the dynamic data, the relationship may be defined to represent the occurrence place; static data describes the attribution of the state represented by the dynamic data, then a relationship may be defined to represent the attribution.
Optionally, in the embodiment of the present application, if the industrial internet data includes a relationship between static data and dynamic data, the relationship may be obtained, and the same relationship is unified into the same representation manner; if the industrial internet data does not include the relationship between the static data and the dynamic data, the relationship can be defined according to the characteristics described by the static data, for example, the relationship corresponding to different characteristics described by the static data can be preset.
Step S130: and for each static data, constructing triple structure data comprising the static data, the relation and the dynamic data according to the relation between the static data and the dynamic data, and forming knowledge graph data corresponding to the industrial internet data.
Each static data and the dynamic data described by the static data are associated through the relationship between the static data and the dynamic data, and the triple data format can be constructed, namely the triple data format is constructed into the data structure of the dynamic data, the relationship and the static data, so that the triple structure data is constructed by each static data corresponding to the dynamic data and the dynamic data, and the knowledge graph data constructed corresponding to the dynamic data is obtained. As shown in fig. 2, the knowledge graph data constructed corresponding to the dynamic data a, the static data describing the dynamic data a includes static data a1, static data a2, static data a3, and static data a4, the relationship between the static data a1 and the dynamic data a is relationship a1, the relationship between the static data a2 and the dynamic data a is relationship a2, the relationship between the static data a3 and the dynamic data a is relationship a3, and the relationship between the static data a4 and the dynamic data a is relationship a 4.
Optionally, for different types of dynamic data, the established relationship may not be completely the same, and is determined according to the actual relationship between the static data and the dynamic data.
In the embodiment of the application, if the industrial internet data to be processed comprises dynamic data, the knowledge graph data constructed corresponding to the dynamic data is the knowledge graph data corresponding to the industrial internet data; if the industrial internet data needing to be processed comprises a plurality of dynamic data, the knowledge graph data constructed corresponding to all the dynamic data can be used as the knowledge graph data corresponding to the industrial internet data.
In addition, optionally, if there is a relationship between static data, static data having a relationship may also be associated by a relationship to form triple structure data of the static data, the relationship and the static data, as shown in fig. 3, a relationship a12 exists between static data a1 and static data a 2.
In the embodiment of the application, dynamic data and corresponding static data in industrial internet data are obtained, for each dynamic data, triple structure data is constructed by the corresponding static data and the dynamic data, knowledge graph data corresponding to the dynamic data is formed, and therefore knowledge graph data corresponding to the industrial internet data needing to be processed can be obtained.
Another embodiment of the present application provides an industrial internet data processing method, which can encapsulate each static data in a corresponding format to serve as a static node; and packaging each dynamic data in a corresponding format to serve as a dynamic node. When the knowledge graph data is constructed, the static nodes obtained by packaging the static data are associated with the dynamic nodes obtained by packaging the dynamic data through a relationship, and the triple construction is carried out to form the knowledge graph data. Specifically, as shown in fig. 4, the method provided in this embodiment includes:
step S210: the method comprises the steps of obtaining dynamic data and static data corresponding to the dynamic data in industrial internet data, wherein the dynamic data are data generated by state change of industrial products in a life cycle, and the static data are data describing the dynamic data.
In the embodiment of the present application, what industrial internet data needs to be processed specifically includes, but is not limited to.
In one embodiment, a user may set a query condition, perform a query from a database in which industrial internet data is available, and use the queried industrial internet data as the industrial internet data processed in the embodiment of the present application. For example, through a related query interface docking module or a subscription interface docking module, according to a set query condition, an access entry of a related identification data information service is acquired through a secondary node, and a poll function of related different identification data information services is called to query industrial internet data meeting the query condition. If poll inquiry is set, a timer can be set, and inquiry is automatically carried out when the timer is up. In this embodiment, the query may be an automatic query based on the query condition when the timer time is reached, or may be a query performed when the query instruction is received.
In this embodiment, the query condition may be selected or set by the querying party, for example, the query may refer to the industrial internet data stored in the specified database, the query may refer to the industrial internet data in the specified state, the query may refer to the industrial internet data of the specified type of product, the query may refer to the industrial internet data of a specified product, or a combination of the foregoing examples.
Optionally, in this embodiment, the user may also query the industrial internet data corresponding to the specified industrial internet identifier under the set query condition. The electronic equipment executing the industrial internet data processing method can receive a query request, wherein the query request carries an industrial internet identifier and a query condition; and inquiring industrial internet data corresponding to the industrial internet identification from a database indicated by the inquiry condition. If the query condition clearly indicates which databases to query from, then the query can be performed from the indicated databases; if the query conditions do not explicitly indicate which databases to continue with the query, the default queryable database may be used as the database indicated by the query conditions. The database can be a related identification data information service, and before acquiring industrial internet data, information service access parameters can be registered to determine the format of a data source; the database can also be other databases storing industrial internet data.
In another embodiment, a user may subscribe to industrial internet data, and an electronic device executing the method according to the embodiment of the present application may subscribe to the industrial internet data from an information service or a database, etc. which can acquire the industrial internet data, and use the subscribed industrial internet data as the processed industrial internet data. For example, the related query interface docking module or the subscription interface docking module calls the subscribe function of the related different identification data information services to subscribe the identification data, and in addition, the unsubscribe function can also be used for unsubscribing the identification data.
In the embodiment of the application, when the dynamic data and the static data corresponding to the dynamic data are acquired from the industrial internet data, the dynamic data of each state can be acquired according to the definition of the dynamic data, namely according to which data are specifically included in the defined dynamic data; and acquiring corresponding static data describing the dynamic data according to the definition of the static data, namely according to which data are specifically included in the defined static data. The definition mode of the dynamic data is not limited in the embodiment of the present application, for example, a dynamic data list may be set, where various types of data included in the dynamic data list are used as the dynamic data; as another example, specifying that data having certain fields is defined as dynamic data. The definition mode of the static data is not limited in the embodiment of the present application, for example, a static data list may be set, where various types of data included in the static data list are used as the static data; as another example, data having certain fields is specified to be defined as static data.
Step S220: and acquiring the relation between each static data and the dynamic data.
This step can be referred to the corresponding step of the foregoing embodiment, and is not described herein again.
Step S230: converting the dynamic data into dynamic nodes according to a preset dynamic node model; and converting each static data into a static node according to a preset static node model.
In the embodiment of the present application, when triple structure data including static data, relationship, and dynamic data is constructed, the dynamic data and the static data may be encapsulated, and the encapsulated data is used as a corresponding node in a triple.
Specifically, a dynamic node model may be preset, and the dynamic node model defines an arrangement rule between data of target types in the dynamic data. Through the dynamic node model, which types of data are needed for generating the dynamic node can be determined, and for convenience of description, the type of the data in the dynamic node model is defined as a target type, and the target type can be one or more types of data; in addition, according to the dynamic node model, an arrangement rule or a presentation format between data of each target type can be determined.
In the present application, what type the target type is not limited, and may be set as needed. In addition, which data each type of data includes may also be set as needed. Optionally, the target type data may include data that can be directly obtained from the dynamic data, or may include data that is converted or defined according to the dynamic data. The target type data converted or defined according to the dynamic data is data that is not directly included in the dynamic data, and what kind of data the target type data is can be determined according to the definition of the target type and the dynamic data. If the target type data includes a data tag of the dynamic data, what kind of tag the tag of the dynamic data is may be determined according to the definition of the tag or a corresponding relationship between different tags and data, so as to obtain the target type data of the tag, and the tag may also be used as the obtained tag of the dynamic node.
When the dynamic data is converted into the dynamic nodes, the data of the target type can be obtained from the dynamic data, and the obtained data of the target type is arranged according to the arrangement rule defined by the dynamic node model to be used as the dynamic nodes. For example, each state is changed into an event, each state is an event, an arrangement rule among event identifiers, event occurrence times and event recording times of the states is defined in the dynamic node model, the event identifiers, the event occurrence times and the event recording times are arranged according to the specified arrangement rule, and the event identifiers, the event occurrence times and the event recording times are stored as dynamic nodes.
In addition, a static node model may be set in advance, and the static node model defines an arrangement rule between data of a specified type in static data. Through the static node model, which types of data are needed for generating the static node can be determined, and for convenience of description, the types of the data in the static node model are defined as specified types, and the specified types can be one or more types of data; in addition, according to the static node model, an arrangement rule or a presentation format between data of each specified type can be determined.
In the present application, what specific types are is not limited, and may be set as needed. In addition, which data each specified type of data includes can also be set as desired. Optionally, the data of the specified type may include data that can be directly obtained from static data, or may include data that is converted or defined according to the static data. The data of the designated type converted or defined according to the static data is data which is not directly included in the static data, and which data of the designated type is determined according to the definition of the designated type and the static data. For example, the data of the designated type includes a data tag of static data, which tag of the static data is determined according to the definition of the tag or the corresponding relationship between different tags and data, so as to obtain the data of the designated type, which tag is also used as the obtained tag of the static node.
When the static data are converted into the dynamic nodes, the data of the specified type can be obtained for each static data; and arranging the acquired data of the specified type according to an arrangement rule defined by the static node model to serve as the static node. If the static node model defines the arrangement rule among the equipment for executing the manufacturer name, the product address and processing the product, for each static data, the equipment for executing the manufacturer name, the product address and processing the product is arranged according to the specified arrangement rule and stored as a static node.
Optionally, in this embodiment of the application, the dynamic node model may further set a visualization rule, which is used to set a type of data that is directly visible to the user and a type of data that needs to be viewed and then presented by the user. The data display method comprises the steps that when the dynamic node is visually presented, which types of data are directly visible to a user, and which types of data are presented when the user performs further viewing operation on the dynamic node. The data of the target type can also be set as directly visualized data, the data is displayed according to a display format defined by the dynamic node model and is used as a visualized dynamic node, other dynamic data is non-visualized and is triggered and displayed by a user, and the display format or mode can also be set by the dynamic node model. For example, when the event name and the identifier are used as directly visualized data, and the dynamic node is displayed, the corresponding event name and identifier are displayed, so that a user can easily identify which state of the displayed graph data is, and when the user selects the dynamic node or further clicks, other dynamic data corresponding to the dynamic node is displayed.
Optionally, the static node model may also set a corresponding visualization rule, which is used to set a type of data directly visible to the user and a type of data that needs to be viewed and then presented by the user, which may be specifically referred to the description of the dynamic node. The data of the designated type can also be set as directly visual data, the data is displayed according to a display format defined by the static node model and is used as a visual static node, other static data is non-visual and is displayed by being triggered by a user, and the display format or the display mode can also be set by the static node model and is not repeated herein.
Step S240: and associating each static node with the dynamic node, and setting the relationship between the corresponding static node and the dynamic node according to the relationship between the static data and the dynamic data to form the knowledge graph data corresponding to the industrial internet data.
And the relation between the static data and the dynamic data corresponding to the static node is used as the relation between the static node and the dynamic node, the static node and the dynamic node are associated, and the relation between the static node and the dynamic node is set to form a triple structure of the static node, the relation and the dynamic node. And respectively associating the dynamic nodes and the static nodes related to the dynamic nodes to form the knowledge graph data corresponding to the dynamic nodes.
In the embodiment of the present application, there may also be a relationship between some static data, and static nodes corresponding to the static data may also be associated with each other in a corresponding relationship to form a triple structure. Namely, the relationship between corresponding static nodes is established according to the relationship between static data. Optionally, if there is static data that does not describe the dynamic data but has a relationship with the static data describing the dynamic data, the related static data may also be converted into a static node, and the static node is associated with the static node describing the dynamic data through the relationship to form a triple structure.
In the embodiment of the application, the formed knowledge graph data can be stored in a graph database. When the knowledge graph data is stored, the knowledge graph data can be stored according to the storage rule of the graph database and realized through the storage command sentence of the graph database. Optionally, in this embodiment of the present application, output conditions such as the output graph database connection parameter, the graph database type, and the push time may be set. For example, setting the output graph data connection parameters may include that different libraries have different storage command statements and different statements for storing different databases may be set because the storage gallery does not have a standard language; in addition, relevant parameters required for setting the external device to access the graph database, such as user name (username), password (password) and other parameters, can also be included.
In the embodiment of the present application, the specific database is not limited, and may be, for example, a Neo4j database, an OrientDB database, a JanusGraph database, and the like. Optionally, if different graph databases can be used for storing data in different formats, the knowledge map data may be stored according to the storage format of the graph database, and the storage is realized by the graph database pair docking module.
In addition, in the embodiment of the application, the formed knowledge-graph data can be presented to the user.
In one embodiment, after acquiring industrial internet data according to a query condition or subscription submitted by a user side and converting the industrial internet data into knowledge graph data, the knowledge graph data can be pushed to the user side, or a visual interface is displayed on a human-computer interaction interface of the user side, and the user acquires the knowledge graph data from a graph database through the visual interface and displays the knowledge graph data. Optionally, if the converted data is a user side, the user side may display the push; if the server performs the data conversion of the knowledge graph, the server can push the data to the user side.
In another embodiment, a map query instruction sent by a user side may be received, where the map query instruction carries a query condition and is used to query the knowledge graph data meeting the query condition, and then the knowledge graph data meeting the query condition may be obtained from a graph database and returned to the user side for visual presentation; or acquiring industrial internet data meeting the query instruction, converting the industrial internet data into knowledge graph data, and returning the knowledge graph data to the client for visual presentation.
In the embodiment of the application, if one dynamic data is described by a plurality of static data, a plurality of static nodes are associated with the dynamic node by a relationship in a stored graph database, and each node is uniquely displayed when visualized to form a node network. For example, fig. 5 shows the knowledge graph data constructed corresponding to the dynamic node a, the static data describing the dynamic node a includes static data a1, static data a2, static data a3, and static data a4, the static data a1, the static data a2, the static data a3, and the static data a4 correspond to the static node a1, the static node a2, the static node a3, and the static node a4, respectively, the relationship between the static node a1 and the dynamic node a is relationship a1, the relationship between the static node a2 and the dynamic node a is relationship a2, the relationship between the static node a3 and the dynamic node a is relationship a3, and the relationship between the static node a4 and the dynamic node a is relationship a4, so as to form the knowledge graph relationship network shown in fig. 5.
In the embodiment of the application, the dynamic data can be packaged into dynamic nodes, the static data can be packaged into static nodes, the dynamic nodes and the static nodes describing the dynamic nodes are associated through the relationship to form knowledge graph data, so that the formats of the industrial internet data are unified, and the management is convenient. Moreover, the relation among various data in the industrial Internet data is described simply and clearly by the knowledge graph data, and the readability is improved.
In another embodiment of the present application, specific dynamic data and static data are taken as examples, which illustrate that the construction of the knowledge graph is performed by encapsulating the dynamic data into dynamic nodes and encapsulating the static data into static nodes.
In the embodiment of the application, the dynamic data and the static data are obtained from the industrial internet data corresponding to a production state. Wherein the dynamic data may include one or more of: an event name indicating the name of the state; an event unique identifier (eventID) for indicating the identity of the state; production data generation time (eventTime); production data recording time (recordTime); time zone (eventtimezoneooffset); a business step (BizStepID) to which the production business belongs; state of the object after production of the service (displacement). The static data may include one or more of: location identification of production enterprise (evtLocation), unique identifier of production business generation enterprise (bizLocation), business starting point (sourceList), business ending point (destinationList), industrial internet identification of industrial internet product participating in production as input (inputIIIDList), industrial internet identification of industrial internet product participating in production as output (outputIIIDList).
In the static model node, a node label, a node attribute and a node identifier are defined, and an arrangement rule of the node label, the node attribute and the node identifier may include an arrangement rule when storage is performed and an arrangement rule when visualization is performed.
The node label represents the category of static data of the node, and each category corresponds to which data can be defined according to the requirement. For example, the node tag may include a location tag (location), a body tag (entity), an object tag (object), and an industrial internet identity tag (eID), where the tag representing the location-related data is defined as a location data tag for describing a physical or logical location, such as an address, a ownership of a property, specifically, a location identity of a manufacturing enterprise, a location name of the manufacturing enterprise, and so on; the label of the relevant data representing the execution subject is defined as a subject data label and is used for describing enterprises, organizations and natural persons, such as a unique identifier of a production business generation enterprise, the name of the production business generation enterprise and the like; the label of the related data representing the acting object or the acted object is defined as an object data type and is used for describing a physical object, such as the unique identification of a production machine, the name of the production machine and the like; each industrial internet identification tag associated with the dynamic data is an industrial internet identification tag, and the nodes of the tags contain an industrial internet identification (mID) attribute that is unique among such tag nodes.
The node attribute and the node identifier form a node main body (master), the node identifier is used for identifying the node identity, and each node generates a unique identifier for the node, for example, the unique identifier may be represented by a Uniform Resource Name (URN), or may be represented by a node name or other data convenient to identify, which is not limited in the embodiment of the present application. Optionally, in the node identifier, nodes with the same label may have the same part, so that the categories of the nodes may also be distinguished by the node identifier.
The node attribute may describe an attribute of static data corresponding to the node, and may be a set of unordered name/value pairs associated with a single vocabulary element, and describe one or more of an identity attribute (mID), a category attribute (mType), and a description attribute (mDesc) of the static data, and what the values of the identity attribute, the category attribute, and the description attribute are respectively is not limited in the embodiment of the present application, and may be determined according to definitions of the identity attribute, the category attribute, and the description attribute, or according to contents corresponding to the identity attribute, the category attribute, and the description attribute, respectively. Of course, in the embodiment of the present application, what the node attributes include, the definition of each attribute, and the like may be extended and set as needed.
When the static nodes are generated, the node labels, the node attributes and the node identifiers are arranged according to the arrangement rule defined by the static node model when stored, and are displayed according to the defined visual arrangement rule when visually displayed.
In addition, optionally, in the generated static node, backup data may also be displayed, that is, the static data corresponding to the static node is backup displayed, as shown in the static node shown in fig. 6. The backup data may be directly displayed when the map data is displayed, or may be displayed when a user issues a display request.
In the dynamic node model, a node label, a node identifier, and an arrangement rule of the node label and the node identifier are defined, and the arrangement rule may include an arrangement rule when storing and an arrangement rule when visually presenting.
The node label represents the category of the dynamic data of the node, and each category corresponds to which data can be defined according to the requirement. For example, the node label may include a production label, a circulation label, and a use label, the generation label indicates that the dynamic data is data of a production link, the circulation label indicates that the dynamic data is data of a production link, and the use label indicates that the dynamic data is data of a use link. The node identification is used for identifying the node identity, and each node generates a unique identification for the node identity.
When the dynamic nodes are generated, the node labels and the node identifiers are arranged according to the arrangement rule defined by the dynamic node model when stored, and are displayed according to the defined visual arrangement rule when visually displayed. In the knowledge-graph data shown in fig. 7, the middle nodes show the display of the dynamic nodes.
In the embodiment of the present application, a relationship between each static data and each dynamic data may also be obtained as a relationship between a corresponding static node and a corresponding dynamic node. And when the knowledge graph data is generated, associating each static node with each dynamic node through the relation between the static nodes and the dynamic nodes.
For example, FIG. 7 illustrates an example of specific knowledge-graph data generated from industrial Internet data of production status. In fig. 7, the node corresponding to the middle dynamic node identifier represents a dynamic node, and the label of the dynamic node is a production label; each node around the dynamic node is a static node. In the static node, the static node includes a node body and a node label, and the text shown in parentheses below the node body of the static node in fig. 7 is used to indicate which static data corresponding node the node belongs to. As shown in fig. 7, the static node corresponding to the industrial internet identity of the input product represents the static node corresponding to the static data inputIIIDList, and the node label is an industrial internet identity (eID); the static node corresponding to the industrial internet identifier of the output product represents the static node corresponding to the static data outputIIIDList, and the node label of the static node is an industrial internet identifier (eID); a static node corresponding to the service starting point, wherein a node label of the static node is a main body; the node labels of the static nodes corresponding to the service end points are main bodies, and so on, which are not described in detail herein.
In addition, optionally, in the knowledge graph data, pointing directions may also be set corresponding to different relationships between the static nodes and the dynamic nodes, that is, whether the static nodes point to the dynamic nodes or the dynamic nodes point to the static nodes, and the same pointing direction represents the same relationship logic. As in fig. 7, a dynamic node points to a static node, which may represent that the static node of the dynamic node in the relationship is the static node to which it points; the static node points to the dynamic node, which means that the dynamic node of the static node under the relationship is the dynamic node in fig. 7. As in fig. 7, the text between the nodes represents the relationship between the nodes, and the dynamic node of the production state points to the static node represented by the unique identifier of the production enterprise, which may represent that the production state occurs in the enterprise represented by the unique identifier of the production enterprise; the static node corresponding to the industrial internet identifier of the output product points to the dynamic node, which indicates that the industrial internet identifier is a certain role in the production state, and the specific role can be determined according to the actual situation, and the role relationship can be set to be a corresponding specific role, such as an input role (input), an output role (output), a connection role (link), an identity role (id), and a parent role (parent).
In the embodiment of the present application, if a relationship exists between static nodes, the relationship may also be used for association. Fig. 8 shows that two static nodes have an association relationship.
In addition, optionally, a backup data node may be further included in the knowledge-graph data, and is associated with the dynamic node. The node where the backup data is located as shown in fig. 9 represents a backup data node, connected to the dynamic node. All dynamic data may be included in the backup data node. Or the backup data node may also include all dynamic data and static data, so as to implement the whole data backup in the state, and by displaying the backup node, a user can view the dynamic data and each static data describing the dynamic data.
In an embodiment of the present application, the obtained knowledge-graph data may be used for a visual display, representing a relationship between a dynamic node and a static node, such as the knowledge-graph data shown in fig. 7 or fig. 9.
Additionally, the generated knowledge-graph data may be input to a corresponding graph database. Optionally, the number of the graph databases may be multiple, at least some of the graph databases have different formats, and the data of the knowledge graph after the graph transformation is input to the graph database corresponding to the format of the data.
The map-converted data of the knowledge map is input to a map database corresponding to the format thereof. Alternatively, the format of the knowledge-graph data may be determined by the format of its source data, i.e., the industrial internet identification obtained from the information service. Optionally, in this embodiment of the application, source data in different formats may be provided with corresponding static node models and dynamic node models, so that the converted data of the knowledge graph can be stored in the graph database for storage.
The embodiment of the application provides a specific conversion mode of knowledge graph data in a specific scene, and it can be understood that in the embodiment of the application, which data are included in nodes, the arrangement mode and the presentation mode among the data are not limited, dynamic data and static data can be converted into corresponding nodes in a knowledge graph in various reasonable modes, and the nodes are connected through relationships, so that the industrial internet data are converted into the knowledge graph data.
Another embodiment of the present application further provides an industrial internet data processing apparatus 300. As shown in fig. 10, the apparatus 300 may include: the data acquisition module 310 is configured to acquire dynamic data in industrial internet data and static data corresponding to the dynamic data, where the dynamic data is data generated by state change of an industrial product in a life cycle, and the static data is data describing the dynamic data; a relationship obtaining module 320, configured to obtain a relationship between each static data and the dynamic data; the map generation module 330 is configured to, for each static data, construct triple structure data including the static data, the relationship, and the dynamic data according to the relationship between the static data and the dynamic data, and form knowledge map data corresponding to the industrial internet data.
Optionally, the map generation module 330 may include a dynamic node sub-module, configured to convert the dynamic data into dynamic nodes according to a preset dynamic node model; the static node submodule is used for converting each static data into a static node according to a preset static node model; and the relation setting submodule is used for associating each static node with the dynamic node and setting the relation between the corresponding static node and the corresponding dynamic node according to the relation between the static data and the dynamic data.
Optionally, the static node model defines an arrangement rule between data of specified types in the static data, and the static node submodule may be configured to, for each static data, obtain the data of the specified type from the static data; and arranging the acquired data of the specified type according to an arrangement rule defined by the static node model to serve as the static node.
Optionally, the dynamic node model defines an arrangement rule between target type data in the dynamic data, and the dynamic node submodule may be configured to obtain the target type data from the dynamic data; and arranging the acquired data of the target type according to an arrangement rule defined by the dynamic node model to serve as the dynamic node.
Optionally, the relationship setting sub-module may be further configured to establish a relationship between corresponding static nodes according to a relationship between static data.
Optionally, the apparatus may further include a query module, configured to receive a query request, where the query request carries an industrial internet identifier and a query condition; and inquiring industrial internet data corresponding to the industrial internet identification from a database indicated by the inquiry condition.
Optionally, the apparatus may further include a storage module for storing the knowledge-graph data to a graph database.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described apparatuses and modules may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, the coupling or direct coupling or communication connection between the modules shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or modules may be in an electrical, mechanical or other form.
In addition, functional modules in the embodiments of the present application may be integrated into one processing module, or each of the modules may exist alone physically, or two or more modules are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode.
Referring to fig. 11, a block diagram of an electronic device according to an embodiment of the present application is shown. The electronic device 400 may be a computable smart device capable of running an application, such as a smart phone, a tablet computer, a desktop computer, a server, and the like, and an operating system may be installed in the electronic device for managing hardware and software resources of the electronic device. The electronic device 400 in the present application may include one or more of the following components: a processor 410, a memory 420, and one or more programs, wherein the one or more programs may be stored in the memory 420 and configured to be executed by the one or more processors 410, the one or more programs configured to perform a method as described in the aforementioned method embodiments.
Optionally, the electronic device may include a visualization interface for providing a visualization operation portal and a viewing interface for a user or other related users.
Optionally, in this embodiment of the application, the electronic device may set various parameters required by the industrial internet data processing method, and may set parameters of the industrial internet data processing apparatus, such as settings for data input query rules, data collection subscriptions, output map database settings, and industrial internet data processing apparatus operating state and resource queries.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein. For example, FIG. 12 illustrates a computer usable storage medium 500 having program code 510 stored therein that can be invoked by a processor to perform the methods described above.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While the preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all alterations and modifications as fall within the scope of the application.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.
Claims (10)
1. An industrial internet data processing method is characterized by comprising the following steps:
acquiring dynamic data in industrial internet data and static data corresponding to the dynamic data, wherein the dynamic data are data generated by state change of an industrial product in a life cycle, and the static data are data describing the dynamic data;
acquiring the relation between each static data and the dynamic data;
and for each static data, constructing triple structure data comprising the static data, the relation and the dynamic data according to the relation between the static data and the dynamic data, and forming knowledge graph data corresponding to the industrial internet data.
2. The method of claim 1, wherein for each static data, constructing triple structure data comprising static data, relationships, and dynamic data according to relationships between the static data and the dynamic data comprises:
converting the dynamic data into dynamic nodes according to a preset dynamic node model;
converting each static data into a static node according to a preset static node model;
and associating each static node with the dynamic node, and setting the relationship between the corresponding static node and the dynamic node according to the relationship between the static data and the dynamic data.
3. The method of claim 2, wherein the static node model defines an arrangement rule between data of a specified type in the static data, and the converting each static data into a static node according to a preset static node model comprises:
for each static data, obtaining data of a specified type from the static data;
and arranging the acquired data of the specified type according to an arrangement rule defined by the static node model to serve as the static node.
4. The method of claim 2, wherein the dynamic node model defines an arrangement rule between data of a target type in dynamic data, and the converting the dynamic data into dynamic nodes according to a preset dynamic node model comprises:
acquiring data of a target type from the dynamic data;
and arranging the acquired data of the target type according to an arrangement rule defined by the dynamic node model to serve as the dynamic node.
5. The method of claim 2, further comprising:
and establishing the relation between corresponding static nodes according to the relation between the static data.
6. The method of claim 1, wherein before obtaining the dynamic data in the industrial internet data and the static data corresponding to the dynamic data, further comprising:
receiving a query request, wherein the query request carries an industrial internet identifier and a query condition;
and inquiring industrial internet data corresponding to the industrial internet identification from a database indicated by the inquiry condition.
7. The method of claim 1, further comprising: storing the knowledge-graph data to a graph database.
8. An industrial internet data processing apparatus, comprising:
the data acquisition module is used for acquiring dynamic data in industrial internet data and static data corresponding to the dynamic data, wherein the dynamic data are data generated by state change of an industrial product in a life cycle, and the static data are data describing the dynamic data;
the relation acquisition module is used for acquiring the relation between each static data and the dynamic data;
and the map generation module is used for constructing triple structure data comprising the static data, the relation and the dynamic data according to the relation between the static data and the dynamic data for each piece of static data to form knowledge map data corresponding to the industrial internet data.
9. An electronic device, comprising:
one or more processors;
a memory;
one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs configured to perform the method of any of claims 1-7.
10. A computer usable storage medium having program code stored therein, the program code being invoked by a processor to perform the method of any one of claims 1 to 7.
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Application publication date: 20210423 |