Automatic cross-version schema adaptation for data requests in distributed data holding systems

Abstract

The invention relates to a computer-implemented method, a computer-implemented device, a system, and a computer program product for automatically converting a data representation into data requests for a distributed data holding system, comprising: providing an initial data holding model as part of the distributed data holding system, which contains information about a data representation associated with the initial data holding model, providing a different sub-model derived from the initial data holding model as part of the data holding system, which contains information about a data representation associated with the derived sub-model, receiving a data request, comprising a request to provide data from the distributed data holding system and at least one parameter indicative of a data holding model of the requested data, loading the requested data from the distributed data holding system, converting the loaded data from a data representation associated with a data holding model of the loaded data into a data representation according to the data holding model requested by the data request if the requested data holding model does not match the stored data holding model, the initial data holding model and each of the sub-models being associated with a versioned object type and at least one attribute of the versioned object type, and the versioned object type of two consecutive data holding models differing at least in an added attribute, a deleted attribute, an unnamed attribute, a formally changed attribute, a content-changed attribute with rule-based transition of values and / or a content-related change of attributes which are not subject to a rule-based transition, and the conversion being carried out as a forward conversion, from an older version to a newer version, or as a backward conversion, from a newer version to an older version, and providing the converted data.

Description

[0001] 202410955 Foreign version

[0002] 1

[0003] Description

[0004] Automatic cross-version schema adaptation for data queries in distributed data storage systems

[0005] The present invention relates to a computer-implemented method, a computer-implemented device, a system, and a computer program product for automatically converting a data representation into data queries to a distributed data storage system.

[0006] A modern (automated) industrial plant often consists of a multitude of different entities (e.g., sub-plants), each equipped with its own control software. The totality of these diverse entities and their associated control software can result in a complex industrial plant architecture.

[0007] The complexity can be further increased, particularly in situations where individual software parameters of an entity within the industrial plant are adjusted, as this adjustment may also need to be compatible with the respective control software solutions of other entities in order to maintain a holistic control functionality for the industrial plant.

[0008] To address the diverse requirements of industrial plants, various industrial automation software solutions exist throughout their lifecycle, and these solutions must be compatible and able to work together. These software solutions are often used independently for planning, automation, operation, monitoring, optimization, maintenance, etc. However, data overlaps or commonalities can occur in certain aspects of their project-specific use.

[0009] If changes are required in a project-specific data set of an industrial automation software solution, these changes must also be manually adjusted in the overlapping data sets of other industrial automation software solutions used to maintain consistency. Such manual reconciliation is not only time-consuming but also error-prone, thus posing a challenge in the lifecycle of a (process engineering) industrial plant. In addition to a purely content-based reconciliation, the specific format of each industrial automation software solution must usually also be taken into account during the reconciliation process. 202410955 Foreign version

[0010] 2

[0011] An example of this is a pump that is dimensioned and integrated during process engineering planning, controlled and regulated in automation, optimized in simulation, subjected to proactive maintenance during operation, and automated, operated, and monitored in actual plant operation. Planning, automation, simulation, operation, and monitoring are often implemented using different industrial automation software solutions with their respective data sets.

[0012] The object "pump," for example, can be present in every industrial automation software solution with some of its properties. If, for example, one of these properties, such as pump output, is changed, this must be taken into account in the respective industrial automation software solution, as a change to this parameter does not necessarily propagate to other solutions. This requirement ultimately corresponds to the previously mentioned content alignment into the respective (desired) form, which cannot yet be achieved reliably and efficiently for common use cases.

[0013] CN114379608A discloses a method for integrating heterogeneous data from multiple sources for the design of a railway transport system.

[0014] Therefore, there is a need to ensure improved data matching across multiple entities of an industrial plant, which at least partially overcomes currently prevailing disadvantages and limitations.

[0015] The present invention therefore aims to provide an improved method for the (automatic) comparison of heterogeneous data sets across multiple software solutions of an industrial plant.

[0016] According to a first aspect, a computer-implemented method for automatically converting a data representation into data queries to a distributed data storage system is proposed. The computer-implemented method comprises providing an initial data storage model as part of the distributed data storage system, which contains information about a data representation associated with the initial data storage model, and providing a different submodel derived from the initial data storage model as part of the data storage system, which contains information about a data representation associated with the derived submodel.Furthermore, the computer-implemented procedure includes receiving a data request, comprising a request to provide data from the distributed data storage system and at least one parameter indicative of a data storage model of the requested data, as well as loading the requested data. 202410955 Foreign version.

[0017] 3 from the distributed data storage system. The computer-implemented procedure further comprises converting the loaded data from a data representation associated with a data storage model of the loaded data into a data representation according to the data storage model requested by the data query, if the requested data storage model does not match the stored data storage model, wherein the initial data storage model and each of the submodels are associated with a versioned object type and at least one attribute of the versioned object type, and wherein the versioned object type of two successive data storage models is represented at least in an added attribute, a deleted attribute, an unnamed attribute, a formally modified attribute, a content-modified attribute with rule-based value transfer, and / or a content-based modification of attributes.which are not subject to a rule-based transition, and wherein the conversion is performed as a forward conversion, from an older version to a newer version, or as a backward conversion, from a newer version to an older version, as well as providing the converted data.

[0018] In this context, a distributed data storage system can be understood as a system for storing data (such as a database). In some cases, the database can be provided not only as a central database, but as a distributed database (i.e., a database (e.g., consisting of several entities) that can be distributed across multiple computers and / or servers (geographically separated)).

[0019] In this context, a data storage model can be understood as an abstract description of how data is stored according to the respective data storage model. This can include, for example, information about how numbers should be formatted according to the relevant data storage model (e.g., in an integer representation, a floating-point number representation, a string representation, etc.). In some cases, the data storage model can additionally or alternatively specify in which unit data should be stored (e.g., whether temperature readings should be stored in °C, K, and / or °F).

[0020] A data request can be understood as a request, e.g., from a user of the distributed data storage system, relating to the provision of selected data stored in the distributed data storage system to the user. 202410955 Foreign version

[0021] 4

[0022] At least one parameter can be a parameter that relates, for example, to a specific data storage model and thus to a desired formatting of the requested data (e.g., whether temperature readings should be provided in °C, K and / or °F).

[0023] Loading the requested data can be understood as compiling the requested data from multiple entities of the data storage system.

[0024] Providing the converted data can include, for example, providing the converted data via a user interface (e.g., on a screen).

[0025] In some cases, the data query and the provision of the data to / from the same user can occur. In other cases, the data query can be initiated by a person different from the person to whom the converted data is provided.

[0026] If it is determined that the requested data storage model matches the stored data storage model, the stored data storage model can be provided without further data conversion.

[0027] In this way, data requested from a distributed data storage system can be automatically converted from a stored data representation to a desired data representation associated with the data request. This allows data to be read from heterogeneous distributed data storage systems that hold data in different data representations (e.g., in different units, such as different temperature units) and processed or converted according to a data request so that the data provided has the requested, desired data representation, thus homogenizing and standardizing it. In this way, the heterogeneity of the data storage system's entities can be hidden from the user, and the usability of the data storage system can be efficiently improved.

[0028] According to one embodiment, the conversion can include conversion based on a predetermined set of rules, wherein the predetermined set of rules specifies how a data representation associated with a stored data storage model is to be mapped to a data representation associated with a data storage model requested by the data query. 202410955 Foreign version

[0029] 5

[0030] The rule set may include, for example, a formula for converting different units used in the data storage models (e.g., from °C to °F (or vice versa), from cm to m (or vice versa), factors for converting different currencies into each other (e.g., EUR to US$ (or vice versa)).

[0031] Based on the rule set, an efficient (automatic) deterministic conversion of a (stored) data representation (according to a data storage model) into a requested data representation (according to a requested data storage model) can thus be achieved.

[0032] According to another embodiment, each data storage model can be assigned a continuous version code.

[0033] Each data storage model is associated with a unique (and unmistakable) version number (e.g. v1 , v2, v3, v4, etc.), which is expressed by the version coding.

[0034] Version coding can be considered continuous if newer data storage models are associated with a higher (version) number than older data storage models.

[0035] In this way, a clear distinction between different data storage models can be achieved. Furthermore, it is possible to infer the development stage of data storage models based on the version coding. In this latter case, for example, a version code associated with a higher number can be associated with a newer data storage model than a lower number, which can be associated with an older data storage model.

[0036] According to another embodiment, the distributed data storage system can contain at least N, with N > 1, further sub-models which can be derived from the initial data storage model and / or from the derived sub-model.

[0037] In this context, derivability can be understood as meaning that the derived data storage model differs from the initial data storage model with respect to at least one modified parameter. For example, the derived data storage model may have a different temperature unit and / or reference a different currency and / or be based on a metric system compared to the initial data storage model, while the 202410955 foreign version

[0038] 6. Initial data storage model can refer to an Anglo-American, imperial system of measurement, for example.

[0039] In some cases, it may be possible to derive more than one data storage model (e.g., at least two, at least three, at least four, or more than four) from the initial data storage model.

[0040] The derived data storage models can be in a hierarchical relationship (e.g. an inheritance hierarchy) to each other and / or to the initial data storage model.

[0041] This allows for the efficient further development of data storage models over time.

[0042] According to another embodiment, the distributed data storage system can contain at least N, with N > 2, further sub-models, wherein at least one of the N further sub-models is derivable from a sub-model of the N further sub-models.

[0043] In some cases, this can enable the further development of data storage models over time and across multiple sub-models. This allows for the branching out of data storage model development into individual development branches, thus providing multiple options for how data can be stored according to the data storage models.

[0044] According to the invention, the initial data storage model and each of the sub-models is associated with a versioned object type and at least one attribute of the versioned object type.

[0045] In this context, an object can be understood as a coherent set of data, whereby the object can be described by the entirety of the attributes associated with the object.

[0046] An attribute can be understood as a parameter that defines a functionality of the object more precisely. In some cases, for example, the object itself might refer to the description of a component of an industrial plant. In such a case, attributes could include, for example, the manufacturing date of the component, the elapsed operating time (e.g., in months and / or years), etc. 202410955 Foreign version

[0047] 7

[0048] Over time, object types (e.g., regarding possible attribute values) can change. To track and clearly represent these changes over time, versioning of the object types is planned.

[0049] The versions associated with the object can be described using a schema, such as a data storage model. These versions can be tagged with comments, which can be made available in such a way as to allow for the tracking of changes and resulting conversions.

[0050] Based on this, a digital model of an industrial plant can be efficiently created.

[0051] According to another embodiment, the versioned object type of two successive data storage models differs at least in one added attribute, one deleted attribute, one unnamed attribute, one formally changed attribute, one content-changed attribute with rule-based transfer of values ​​and / or one content-change of attributes that are not subject to a rule-based transfer.

[0052] The added attribute refers, for example, to a name and / or an identification number (ID) of the added attribute. An unnamed attribute can refer to an attribute with a new name but the same ID. A formally modified attribute can refer to a new ID with the same semantics and name, but possibly only a changed data type (e.g., integer, string, floating-point number, etc.), or to a formal change. A content-modified attribute can also refer to an attribute where all attribute values ​​must be multiplied by a factor when a unit of measurement changes. In the case of a content-modified attribute, it may be necessary to adopt the new value of an attribute as the default value after converting an object.

[0053] This can contribute to a fine-grained gradation of data storage models relative to each other.

[0054] According to another embodiment, the provision may also include the provision of a quality parameter which is indicative of the quality of the conversion.

[0055] The quality parameter can, for example, indicate that information loss has occurred during conversion, such as a truncation error. This can occur, for example, if a data storage model of the distributed data storage system uses a numerical format that is not compatible with the data.

[0056] 8 would be stored as a floating-point number (float), but a user initiates a data request that aims to provide the requested data as an integer. In such a case, the decimal places of the floating-point number would be truncated (and / or rounded to an integer), which results in a corresponding loss of information regarding the decimal places. This loss can be addressed, for example, by an appropriate quality parameter.

[0057] In some cases, a converted value can also be replaced by a default value if, for example, the latter does not have the required precision.

[0058] In some cases, the quality parameter may, for example, have one of the following values: "valid", "reduced accuracy", "to be checked" or "default value".

[0059] The quality parameter can be provided as a Boolean value indicating whether or not information loss occurred during the conversion. Alternatively, the quality parameter can also specify a (predefined) degree of information loss that may accompany the conversion.

[0060] This ensures that any information loss resulting from the conversion process is recorded and, if necessary, made available to the user who initiated the data request.

[0061] According to another embodiment, the conversion can be performed as a forward conversion, from an older version to a newer version.

[0062] The conversion can refer to converting an object type.

[0063] This can enable efficient conversion from an older data storage model (and associated data representation) to a newer data storage model (and associated data representation).

[0064] According to another embodiment, the conversion can be performed as a reverse conversion, from a newer version to an older version.

[0065] The conversion can refer to converting an object type. 202410955 Foreign version

[0066] 9

[0067] This can enable efficient conversion from one newer data storage model (and associated data representation) to another newer data storage model (and associated data representation). In this way, backward compatibility can be achieved between newer stored data storage models and older, requested data storage models.

[0068] According to another embodiment, the conversion can be performed by the initial data storage model.

[0069] The conversion through the initial data storage model can be rule-based.

[0070] This can contribute to a reduction in the complexity of the conversion process.

[0071] According to a second aspect, a computer program product is proposed, comprising instructions which, when the program is executed by a computer, cause it to perform the procedure as described herein.

[0072] A computer program product, such as a computer program tool, can be provided or delivered from a server on a network, for example, as a storage medium such as a memory card, USB stick, CD-ROM, DVD, or as a downloadable file. This can be done, for example, in a wireless communication network by transmitting the corresponding file containing the computer program product or tool.

[0073] According to a third aspect, a computer-implemented device for automatically converting a data representation into data queries to a distributed data storage system is proposed. The computer-implemented device can comprise a first provisioning unit for providing an initial data storage model as part of the distributed data storage system, containing information about a data representation associated with the initial data storage model, and a second provisioning unit for providing a different submodel derived from the initial data storage model as part of the data storage system, containing information about a data representation associated with the derived submodel.The computer-implemented device may include a receiving unit for receiving a data request, comprising a request to provide data from the distributed data storage system and at least one parameter indicative of a data storage model of the requested data, as well as a loading unit for loading the requested data from the distributed data storage system. (See also 202410955 Foreign Version.)

[0074] 10. The computer-implemented device may include a conversion unit for converting the loaded data from a data representation associated with a data storage model of the loaded data into a data representation according to the data storage model requested by the data request, if the requested data storage model does not match the stored data storage model, and a third provisioning unit for providing the converted data, wherein the initial data storage model and each of the submodels are associated with a versioned object type and at least one attribute of the versioned object type, and wherein the versioned object type of two successive data storage models is represented at least by an added attribute, a deleted attribute, an unnamed attribute, or a formally modified attribute.distinguishes between a content-modified attribute with rule-based value transitions and / or a content-modified attribute that is not subject to rule-based transitions, and where the conversion is performed as a forward conversion, from an older version to a newer version, or as a backward conversion, from a newer version to an older version.

[0075] The respective unit, for example, one of the provisioning units, charging unit, receiving unit, and / or conversion unit, can be implemented in hardware and / or software. In a hardware implementation, the respective unit can be a device or part of a device, for example, a computer, a microprocessor, or a vehicle control unit. In a software implementation, the respective unit can be a computer program product, a function, a routine, part of program code, or an executable object.

[0076] According to one embodiment, the computer-implemented device may comprise an execution unit for executing the computer program product as described herein, and / or a further execution unit for executing the method as described herein.

[0077] The execution unit can be, for example, a computer, processor, Field Programmable Gate Array (FPGA) or a combination thereof.

[0078] According to a fourth aspect, a system for automatically converting a data representation into data queries of a distributed data storage system is proposed. The system may include the computer program product as described herein, as well as the computer-implemented device as described herein. 202410955 Foreign version

[0079] 11

[0080] The computer program product can be contained within the computer-implemented device. Alternatively, the computer program can also be contained in a unit located remotely from the computer-implemented device. In the latter example, the computer-implemented device can access the computer program product via a network (e.g., a local network or the internet) or a USB connection.

[0081] The embodiments and features described for the proposed device apply accordingly to the proposed method.

[0082] Other possible implementations of the invention also include combinations of features or embodiments described previously or subsequently with regard to the exemplary embodiments, even if not explicitly mentioned. In such cases, the person skilled in the art will also add individual aspects as improvements or additions to the respective basic form of the invention.

[0083] Further advantageous embodiments and aspects of the invention are the subject of the dependent claims and the exemplary embodiments of the invention described below. The invention will be explained in more detail below with reference to preferred embodiments and the accompanying figures.

[0084] Further advantageous embodiments and aspects of the invention are the subject of the dependent claims and the exemplary embodiments of the invention described below. The invention will be explained in more detail below with reference to preferred embodiments and the accompanying figures.

[0085] Fig. 1 shows a schematic system diagram;

[0086] Fig. 2 shows an embodiment of an automatic conversion of a data representation into data queries to a distributed data storage system;

[0087] Fig. 3 shows a flowchart of an exemplary computer-implemented procedure;

[0088] Fig. 4 shows an exemplary computer-implemented device; and

[0089] Fig. 5 shows an exemplary system. 202410955 Foreign version

[0090] 12

[0091] In the figures, identical or functionally equivalent elements have been given the same reference symbols, unless otherwise indicated.

[0092] Fig. 1 shows a schematic system diagram 100 which represents an automatic conversion of a data representation into data queries to a distributed data storage system.

[0093] The DB data storage system includes a first data provider DP1 (engl.: data provider") and a second data provider DP2.

[0094] In the embodiment shown here, the first data provider DP1 and the second data provider DP2 provide a data storage model 110 of type X in version A.

[0095] A data provider can generally define which version of the data supplied and stored by the data provider refers to.

[0096] Data storage model 110 is composed of data storage models 120 and 130.

[0097] Data storage model 120 of type X in version A' was derived from data storage model 110 and is provided by data provider DP1.

[0098] Data storage model 130 of type X in version A" was derived from data storage model 110, which is provided by data provider DP2.

[0099] The derivation of data storage models (or versions) from an initial data storage model (or version) can be documented over time using tracking information. The derived data storage models can be stored within a consolidated schema registry (which can be maintained centrally or decentrally). This ensures a linear progression of the data storage models (or versions).

[0100] System diagram 100 shows three example data queries A1-A3 to the distributed data storage system DB, which are made by a user APP (English: serves). In some cases, the data query may refer to an (automatic) data query from an application (English: app). 202410955 Foreign version

[0101] 13

[0102] According to request A1, for example, the data storage model of type X in version A can be requested, or a representation of data that can be derived from this data storage model. This would correspond to data storage model 110, which is provided by the first data provider DP1 and the second data provider DP2.

[0103] To provide data storage model 110 as requested in request A1, it is first necessary to convert data storage model 120 of type X in version A' to data storage model 110 of type X in version A. Furthermore, it is necessary to convert data storage model 130 of type X in version A" to data storage model 110 of type X in version A. After the conversion is complete, data storage model 110 of type X in version A can be provided to the user as requested in request A1.

[0104] Request A2 requests a data storage model of type X in version A'. Such a data storage model is provided, for example, by data provider DP1 as data storage model 120. According to request A2, providing data storage model 120 does not require conversion, as it is already provided by data provider DP1 in a suitable model format. Data storage model 120 can therefore be transmitted directly to the user as per request A2.

[0105] In order to provide data according to the requested data storage model, starting from data storage model 130, it is first necessary to convert data storage model 130 of type X in version A" to data storage model 110 (type X, version A). From there, a second conversion takes place from data storage model 110 (type X, version A) to data storage model 120 (type X, version A'), which can then be provided to the user according to request A2.

[0106] Finally, system diagram 100 shows another data request A3, which aims to provide a data storage model of type X in version A. The data provider DP2 maintains the data storage model 130 (type X, version A), so no data conversion is required from this point.

[0107] Data provider DP1, on the other hand, uses data storage model 120 (Type X, Version A'). This requires first converting the data to data storage model 110 (Type X, Version A) and then to data storage model 130 (Type X, Version A") before the data can be provided to the initiator of the data request A3 according to data storage model 130. 202410955 Foreign version

[0108] 14

[0109] Fig. 2 shows an embodiment of an automatic conversion of a data representation into data queries to a distributed data storage system.

[0110] The embodiment is based on a data request 210, which is made to a distributed data provisioning system.

[0111] Data request 210 involves requesting data associated with a mixer. The requested data should provide information about the mixer's name, its capacity (in liters), its rotational speed (in rpm), and a target temperature in °C.

[0112] The distributed data storage system consists of a first data storage model which references a first object 230, a second data storage model which references a second object 240, and a third data storage model which references a third object 250.

[0113] Each of the objects 230, 240 and 250 is described by respective attributes (e.g. name, fill level, stirring stage), data types assigned to the attributes (based on which the respective attribute values ​​are stored) and concrete instance data (i.e. attribute values).

[0114] The data storage systems associated with objects 230, 240 and 250 can be considered as sub-models derived from a higher-level initial data storage model.

[0115] The first object 230, for example, holds information about the name of the mixer associated with the first object 230, in this case "MixerT" and of data type "String".

[0116] The first object, 230, contains information about the "filling capacity" of the mixer in question, in the unit (liters) and with the attribute value "100". According to data request 210, however, an attribute "capacity" should be stored in the unit It will be provided. Since the attribute "capacity" is not present in object 230, a conversion must first be performed.

[0117] A rule set 220 is provided here, which offers information on how individual data storage models can be converted into one another. For example, this stipulates that for object 230, the attribute "Füllinhalf" in the unit according to object 230 must be converted into the attribute "Kapitität" in can be converted according to data request 210. Since the attribute 'fill content' is already in the unit Since the reference is made as requested in data request 210, no conversion is required. 202410955 Foreign version

[0118] 15

[0119] The first object 230 also contains information about the attribute "stirring level", which can take a value from 1 to 10 of the data type "integer". In this case, the attribute value assigned to "stirring level" is "3".

[0120] According to data request 210, the attribute "rotational speed" should be provided in the unit "rpm". Since the requested data representation is not yet available in object 230, a conversion of the stored data storage model to the requested data storage model is necessary. Rule set 220 stipulates that the attribute value of the attribute "stirring level (1-10)" can be multiplied by a factor of 100 to obtain the attribute "rotational speed" in the unit "rpm".

[0121] Object 240 already contains all attributes "capacity", "speed" and "temp. setpoint", as requested by data request 210, so no conversion is necessary in this case.

[0122] Regarding object 250, the attribute "capacity" is stored in the unit "hl", while data request 210 requested the attribute value for the attribute "capacity" in the unit "hl". Rule 220 stipulates that multiplying the attribute value of the attribute "capacity" by a factor of 100 will yield the attribute "capacity" with an attribute value in the unit. The remaining attributes of object 250 are already available in the data representation requested by data request 210, so no further conversion is necessary.

[0123] Object 250 also stores information about the attribute "Max. Mixing Time" in the unit "min". Since this attribute is not part of data request 210, it is not provided to the user who initiated data request 210.

[0124] The rules of rule set 220 can be generated automatically for simple conversions (e.g., renaming fields / properties or changing data types (e.g., between integers and floating-point numbers and vice versa)). For complex conversions (e.g., changing a unit of measurement with the necessary data conversion), it may be necessary for a user to perform or define the corresponding conversion manually.

[0125] In the case of a forward conversion (or backward conversion), it is possible that the necessary rules of rule set 220 will be generated automatically. Should this occur, see 202410955 Foreign Version

[0126] If 16 is not possible, it may be necessary for a user to define and set them manually.

[0127] A conversion process (e.g., at least partially based on rule set 220) can be carried out in a version tree, which maps existing model versions, creating a path from the current version to the desired version. Subsequently, it may be possible to evaluate the necessary mapping rules along this path and use them to convert the data.

[0128] Fig. 3 shows a flowchart of an exemplary computer-implemented procedure 300 for automatically converting a data representation into data queries to a distributed data storage system.

[0129] In step 310, an initial data storage model is provided as part of the distributed data storage system, which contains information about a data representation associated with the initial data storage model.

[0130] In step 320, a different submodel derived from the initial data storage model is provided as part of the data storage system, which contains information about a data representation associated with the derived submodel.

[0131] Step 330 involves receiving a data request, comprising a request to provide data from the distributed data storage system and at least one parameter that is indicative of a data storage model for the requested data.

[0132] In step 340, the requested data is loaded from the distributed data storage system.

[0133] In step 350, the loaded data is converted from a data representation associated with a data storage model of the loaded data into a data representation according to the data storage model requested by the data request, if the requested data storage model does not match the stored data storage model.

[0134] Step 360 involves making the converted data available.

[0135] Fig. 4 shows an exemplary computer-implemented device 400 for automatically converting a data representation into data queries of a distributed data storage system. 202410955 Foreign version

[0136] 17

[0137] The device 400 includes a first provisioning unit 410, a second provisioning unit 420, a receiving unit 430, a charging unit 440, a conversion unit 450 and a third provisioning unit 460.

[0138] The first provisioning unit 410 is configured to provide an initial data storage model as part of the distributed data storage system, which contains information about a data representation associated with the initial data storage model.

[0139] The second provisioning unit 420 is configured to provide a different submodel derived from the initial data storage model as part of the data storage system, which contains information about a data representation associated with the derived submodel.

[0140] The receiving unit 430 is configured to receive a data request, comprising a request to provide data to the distributed data storage system and at least one parameter indicative of a data storage model of the requested data.

[0141] The loading unit 440 is configured to load the requested data from the distributed data storage system.

[0142] The conversion unit 450 is configured to convert the loaded data from a data representation associated with a data storage model of the loaded data into a data representation according to the data storage model requested by the data request, if the requested data storage model does not match the stored data storage model.

[0143] The deployment unit 460 is configured to deploy the converted data.

[0144] Fig. 5 shows an exemplary system 500 for automatically converting a data representation into data queries to a distributed data storage system. The system 500 includes a computer-implemented device 510 and a computer program product 520.

[0145] The computer-implemented device 510 can be configured as described herein.

[0146] The computer program product 520 can be configured as described herein. 202410955 Foreign version

[0147] 18

[0148] Although the present invention has been described using exemplary embodiments, it can be modified in many ways.

[0149] Regardless of the grammatical gender of a particular term, persons with male, female or other gender identities are included.

[0150] 202410955 Foreign version

[0151] 19

[0152] Reference symbol list

[0153] 100 System diagram

[0154] 110 Data storage model

[0155] 120 Data storage model

[0156] 130 Data storage model

[0157] 210 Data request

[0158] 220 Rulebook

[0159] 230 objects

[0160] 240 objects

[0161] 250 objects

[0162] 300 computer-implemented procedures

[0163] 310 steps

[0164] 320 steps

[0165] 330 steps

[0166] 340 steps

[0167] 350 steps

[0168] 360 steps

[0169] 400 computer-implemented devices

[0170] 410 first deployment unit

[0171] 420 second deployment unit

[0172] 430 receiver unit

[0173] 440 charging unit

[0174] 450 conversion units

[0175] 460 third deployment unit

[0176] 500 System

[0177] 510 computer-implemented device

[0178] 520 Computer program product

[0179] APP users

[0180] DP1 Data Provider

[0181] DP2 Data Provider

[0182] DB data storage system

[0183] A1 Inquiry

[0184] A2 Inquiry

[0185] A3 Inquiry

Claims

202410955 Foreign version 20 Patent claims 1. Computer-implemented method (300) for automatically converting a data representation into data queries to a distributed data storage system (DB), comprising: Providing (310) an initial data storage model as part of the distributed data storage system (DB), which contains information about a data representation associated with the initial data storage model; Providing (320) a different submodel derived from the initial data storage model as part of the data storage system (DB), which contains information about a data representation associated with the derived submodel; Receiving (330) a data request, comprising a request to provide data to the distributed data storage system (DB) and at least one parameter indicative of a data storage model of the requested data; Loading (340) the requested data from the distributed data storage system (DB); Converting (350) the loaded data from a data representation associated with a data storage model (DB) of the loaded data into a data representation according to the data storage model requested by the data query, if the requested data storage model does not match the stored data storage model, wherein the initial data storage model and each of the submodels are associated with a versioned object type and at least one attribute of the versioned object type, and wherein the versioned object type of two successive data storage models differs in at least one added attribute, one deleted attribute, one unnamed attribute, one formally changed attribute, one substantively changed attribute with rule-based transfer of values ​​and / or a substantive change of attributes that are not subject to a rule-based transfer, and wherein the conversion is a forward conversion,from an older version to a newer version, or as a reverse conversion, from a newer version to an older version; and, Providing (360) the converted data.

2. Computer-implemented method according to claim 1, wherein the conversion comprises conversion based on a predetermined set of rules (220), and wherein the predetermined set of rules (220) determines how a data representation associated with a stored data storage model is mapped to a data representation 202410955 Foreign version 21, which is associated with a data storage model requested by the data request.

3. Computer-implemented method according to one of claims 1 or 2, wherein each data storage model is assigned a continuous version coding.

4. Computer-implemented method according to one of claims 1-3, wherein the distributed data storage system (DB) contains at least N, with N > 1, further sub-models which are derivable from the initial data storage model and / or from the derived sub-model.

5. Computer-implemented method according to one of claims 1-4, wherein the distributed data storage system contains at least N, with N > 2, further submodels and wherein at least one of the N further submodels is derivable from a submodel of the N further submodels.

6. Computer-implemented method according to any one of claims 1-5, wherein the provision further comprises: Providing a quality parameter that is indicative of the quality of the conversion.

7. Computer-implemented method according to any one of claims 1-6, wherein the conversion is performed by the initial data storage model.

8. Computer program product comprising instructions which, when the program is executed by a computer, cause it to execute the method according to any one of claims 1-7.

9. Computer-implemented device (400) for automatically converting a data representation into data queries to a distributed data storage system (DB), comprising: a first provisioning unit (410) for providing an initial data storage model as part of the distributed data storage system (DB), which contains information about a data representation associated with the initial data storage model; 202410955 Foreign version 22 a second provisioning unit (420) for providing a different submodel derived from the initial data storage model as part of the data storage system (DB), which contains information about a data representation associated with the derived submodel; a receiving unit (430) for receiving a data request, comprising a request to provide data from the distributed data storage system (DB) and at least one parameter indicative of a data storage model of the requested data; a loading unit (440) for loading the requested data from the distributed data storage system; a conversion unit (450) for converting the loaded data from a data representation associated with a data storage model of the loaded data into a data representation according to the data storage model requested by the data request, if the requested data storage model does not match the stored data storage model,wherein the initial data storage model and each of the submodels are associated with a versioned object type and at least one attribute of the versioned object type, and wherein the versioned object type of two successive data storage models differs at least in one added attribute, one deleted attribute, one unnamed attribute, one formally changed attribute, one substantively changed attribute with rule-based value transition and / or one substantive change of attributes that are not subject to rule-based transition, and wherein the conversion is performed as a forward conversion, from an older version to a newer version, or as a backward conversion, from a newer version to an older version; and a third provisioning unit (460) for providing the converted data.

10. Computer-implemented device according to claim 9, further comprising: an execution unit for executing the computer program product according to claim 8; and / or a further execution unit for executing the method according to any one of claims 1-7.

11. System (500) for automatically converting a data representation into data queries to a distributed data storage system, comprising: a computer program product (520) according to claim 8; and 202410955 Foreign version 23 a computer-implemented device (510) according to one of claims 9 or 10.

Images