385 results about "Data products" patented technology

A system for converting a source data feed schema into a canonical data product including a memory for storing computer-executable instructions and a processor for executing the instructions stored on the memory. Execution of the instructions programs the processor to perform operations that include receiving a source data feed having a source schema, identifying a plurality of data fields of the source schema, assigning a data category from a plurality of predefined data categories to each data field of the plurality of data fields, modifying the source schema based on predefined parameters, wherein the source schema is modified to match a target schema, comparing the modified source schema to the target schema, and in response to a determination that the modified source schema matches the target schema, converting the source data feed to a canonical data product having the target schema based on the assigned data categories.

The invention discloses an intelligent logistics supply chain management system, and the system comprises a block chain information sharing platform which is responsible for building an information sharing platform based on a block chain, inviting all participants on the supply chain to join, and storing and transmitting the data of each link of the supply chain through the distributed account book technology of the block chain; the product information tracing system is responsible for distributing a unique block chain ID for each fresh food and recording the circulation process of the fresh food in a supply chain; and the collaborative management platform is responsible for integrating and uniformly managing data of purchasing, warehousing, transportation and sales, predicting future sales trend and inventory demand change by using a random forest according to historical sales data and market trend information, and optimizing an inventory level, a reorder strategy, a sales strategy and a promotion activity plan in combination with a genetic algorithm, so as to achieve the purpose of sales promotion. The inventory cost is minimized, the sales demand is met, and the block chain information sharing platform and the collaborative management platform carry out data synchronization.

The invention discloses an artificial intelligence auxiliary authentication method and system for data element right confirmation, and relates to the technical field of data element management and credible circulation. Comprising the following steps: data acquisition: acquiring a data product, an ownership statement and contract terms, and calculating an initial digital fingerprint of the data product; and ownership identification: extracting core value elements and features of the data product based on a multi-modal intelligent analysis model, quantifying value contribution weights formed by all links to the data product, and automatically generating a data element circulation graph. According to the method, the multi-modal intelligent analysis model is constructed, and the data product is deeply scanned and analyzed automatically, so that the dependence on predefined rules is reduced, and the intellectualization and automation of ownership identification are realized; by constructing an intelligent compliance verification model, data operation behaviors are monitored and compared in real time, substantive compliance control over the whole data use process is achieved, and a credible use closed loop is established.

The invention discloses a method for aggregating ocean buoy data, which comprises the following steps of: establishing a space-time correlation model according to the spatial distribution density of buoy clusters and the dynamic characteristics of an ocean environment, and adaptively dividing buoy groups with a data compression cooperative relationship; performing a data-related compression operation within the buoy group; constructing a transmission priority dynamic sorting engine, and calculating a dynamic weight coefficient; performing hierarchical packaging processing on the differential coding data, distributing enhanced forward error correction coding resources for high-priority data, and reserving redundant transmission time slots; the method comprises the following steps: receiving a hierarchical data packet through a low-orbit satellite and executing on-satellite preprocessing, reconstructing an original data stream by using a distributed decoder, and meanwhile, fusing multi-dimensional space-time related data to generate an aggregated data product; and finally, the aggregated data product is transmitted to a ground data center through a satellite downlink. According to the invention, uplink data volume is reduced, disaster monitoring timeliness is improved, ground station processing load is reduced, and system environment adaptability is enhanced.

The invention belongs to the technical field of hydrology and water resources, and discloses a cold and dry mountainous area drainage basin runoff simulation method based on an MIKE SHE / MIKE 11 coupling model in combination with GIS / RS data. According to the multi-source data fusion technology, a cold and dry mountainous area distributed input data set is constructed through TRMM satellite rainfall data, an MODIS LAI product and an ASTER DEM, and the rainfall space representation precision is improved by 40%. According to the model coupling mechanism, an MIKE SHE / MIKE 11 collaborative simulation framework is provided, earth surface-groundwater flow data interaction is achieved through river channel linkage, and the complex river network flood routing simulation error is reduced to 10% or below. According to the parameter partition calibration method, a drainage basin is divided into five hydrogeological regions, sensitive parameters such as a Manning coefficient and a hydraulic conduction coefficient are optimized in combination with a genetic algorithm, and the basic flow simulation precision is improved by 25%.

A computer-implemented method and apparatus for managing physical and digital products' customization using container format are disclosed. In some embodiments, the method comprises receiving a container file with serialized objects, deserializing these objects to form a hierarchical object structure, and interacting with a database to obtain real-time configuration data. Custom attributes of the products are defined by binding attribute / value pairs to the hierarchical structure. A visualization of the customized product is generated based on these pairs, and manufacturing instructions are determined considering the attribute / value pairs and manufacturing constraints. The apparatus comprises a memory and a processor to execute instructions for deserializing the container file, retrieving configuration data, organizing objects into a hierarchical tree, negotiating product customizations, and outputting manufacturing data. This system enables efficient and accurate production of customized products by managing data, rendering graphics, and incorporating manufacturing constraints.

The invention discloses a traffic data security encryption and circulation system and method based on a block chain, belongs to the technical field of traffic control, and aims to solve the problems of security, privacy and trust in traffic data sharing. The system comprises an edge computing node which is deployed near a data source and is used for performing encryption or privacy enhancement processing on original traffic data; a block chain network with a smart contract is deployed, node identities are managed, verification information is recorded, an access strategy is stored, and data circulation is controlled; and the data processing unit is used for aggregating the processed data to generate a circulatory data product. The method comprises the steps of edge security processing, block chain management verification, product generation by the data processing unit and management and control circulation of the block chain according to a strategy. Through edge security processing and a block chain trust mechanism, data security privacy is guaranteed, safe, transparent and credible circulation and utilization of traffic data are realized, and reliable data support is provided for intelligent upgrading and digital transformation of the traffic industry.

The invention provides an electric power data product quality evaluation system. The system comprises a data acquisition module; the rule generation module is used for extracting data features from the power data and inputting the data features into a rule generation model obtained through training to output a candidate rule set, and rules in a candidate rule base are reordered based on service weights to obtain a recommendation rule set; the dynamic threshold value optimization module is used for dynamically updating an abnormal threshold value based on the data distribution condition of the power data in the historical time period and the business demand adjustment coefficient; the quality evaluation module is used for performing quality evaluation on the power data based on rules in the recommendation rule set and corresponding abnormal thresholds to obtain a quality evaluation result; and the feedback optimization module is used for feeding back and adjusting the rule generation module and the dynamic threshold optimization module based on the quality evaluation result, and realizing intelligent recommendation and dynamic threshold optimization of the power data quality evaluation rule and self-adaptive updating of the rule base.

The embodiment of the invention provides a method and a system for processing ocean multi-parameter wide-width imaging data of a Beidou interference altimeter, and relates to the technical field of GNSS-R. The method comprises the following steps: constructing a set of complete and strict data processing chain; through precise calculation of a GNSS-R direct signal and reflection signal delay inequality interference geometric model and correction of actual measurement delay inequality errors, systematic errors in the process of converting original signals into geophysical parameters are remarkably reduced, and the precision and reliability of parameters obtained through final inversion are improved. And on the basis of a self-adaptive data collection strategy of parameter space-time transformation characteristics and a spatial interpolation reconstruction process, discrete strip data is intelligently'woven 'into a continuously-covered wide-swath imaging type data product, so that the data format better meets the analysis requirements in the fields of oceanography, climatics and the like, and the intuition and usability of the product are improved.

The invention relates to a part generation method based on atomization disassembly and encapsulation data. The part generation method comprises the following steps: step 1, analyzing a demand scene; step 2, carrying out atomization disassembly; step 3, performing standardization verification; step 4, packaging the function logic layer; step 5, packaging the element part layer; 6, packaging an interface layer; according to the method, the problems of function solidification and difficult splitting of a traditional data product are solved, and efficient circulation and value release of data elements are promoted; and reusability and circulation efficiency of data parts are improved through the element part layer.

The invention provides a step optimization method, medium and system for a complex industrial process, and belongs to the technical field of big data modeling, and the method comprises the steps: building a multi-dimensional data collection system, installing a sensor and a monitoring device at a key node of a target industrial process, collecting process parameter data, equipment state data and product quality data in a parallel multi-thread mode to form an original data set, and collecting process flow connection relation data; performing time domain decomposition operation on the original data set, decomposing each data into a long-term stable numerical component and a short-term fluctuation numerical component, and respectively obtaining a process parameter stable component, a process parameter fluctuation component, an equipment state stable component and an equipment state fluctuation component; according to the technical scheme of the invention, the problem that the product cannot stably operate in the optimal state can be solved.

A system for event-driven distributed data network analysis, the system includes: a multitude of domain data nodes, each comprising a stream storage, a multitude of transformation pods, and a product API, with each domain data node ingesting heterogeneous event streams, validating schema compliance, performing enrichments, and making data products available under versioned schema contracts; each domain data node further comprises a hardware-based edge intelligence appliance comprising an enclosure, a compute module with heterogeneous processing units selected from CPUs, GPUs, and TPUs, a secure enclave module for confidential execution of transformation code on encrypted data, a protocol-structured stream storage medium supporting multi-level retention, and industrial I / O interfaces configured for direct interaction with sensors, programmable logic controllers, and cloud-native services; an event mesh backbone processor configured to connect the multitude of domain data nodes via a publish-subscribe architecture, with the backbone guaranteeing exactly one-time delivery, partition-level sorting, and geo-replicated durability; a Contextual Intelligence Engine coupled with the Event Mesh Backbone processor, the engine comprising a semantic graph memory and a Streaming Graph Reasoner configured to map raw events into an ontology, perform graph joins in real time, and recognize composite causal patterns across multiple domain data nodes; a governance and policy control unit integrated into both the data and control layers. This layer enforces zero-trust security, role-based access control, real-time provenance tracking, and regulatory compliance; and An actuation interface coupled with the contextual intelligence engine and the governance layer. The actuation interface is configured to generate control commands for operational technology devices and digital workflows, thus closing the loop from data acquisition to autonomous decision-making.

The invention relates to the technical field of big data management, in particular to a big model metadata authority management method and system based on an RBAC-ABAC fusion model, and the method comprises metadata annotation, data product release, big model and user access, semantic perception, dynamic authority adjustment, row-level authority control and authority life cycle management. The method has the beneficial effects that by fusing the advantages of the RBAC model and the ABAC model, the defects of a single authority management model are overcome, the efficient, dynamic and fine-grained authority management of the large model metadata is realized, the security of the large model metadata is improved, and the authority management requirement of the large model for accessing the dynamic business data is met.

The embodiment of the invention provides a structured data field use control method and device, a medium and a product, and relates to the technical field of data use. The method comprises the steps of obtaining a data product published by a data provider; the data product is formed by accessing structured data into a data space in a data source form by a data provider; binding a target strategy generated based on the structured data to the data product, and determining a bound target data product; the target strategy comprises a post strategy and a calculation strategy executed at a first trusted connector of the data user, and a pre strategy executed at a second trusted connector of the data provider; and performing data contract signing with the data provider according to the target data product. The method is based on a structured data form, and is more accurate than traditional privacy calculation control; the target strategy and the data product are directly bound, and a traditional strategy configuration mode based on a central server is replaced.

The invention provides a data consanguinity establishing method, which comprises the following steps of: reading metadata of a technical index configured for a data product, and acquiring an identifier of the technical index from the metadata of the technical index; reading metadata of a business index configured for the data product, and obtaining an identifier of the business index and an identifier of a technical index associated with the business index from the metadata of the business index; reading configuration information of an application program of the data product, and obtaining an identifier of an application index related to the application program of the data product and an identifier of a technical index associated with the application index from the configuration information; and determining an association relationship among the technical index, the business index and the application index based on the identifier of the technical index, the identifier of the business index, the identifier of the technical index associated with the business index, the identifier of the application index and the identifier of the technical index associated with the application index. The invention further provides a data blood relationship establishing device, electronic equipment, a storage medium and a program product.

The invention relates to the technical field of data product pricing, and discloses a data pricing method based on multi-dimensional value evaluation, a terminal and a storage medium. The method comprises the steps of performing desensitization processing on data needing to be priced based on a differential privacy mechanism, generating a privacy budget value and a privacy risk value of the data, and obtaining a privacy score according to the privacy budget value and the privacy risk value; generating a quality score of the data according to the evaluation index of the desensitized data on the specified task; calculating a dynamic weight coefficient meeting the optimal privacy budget value by using a dual-objective optimization algorithm, wherein the dynamic weight coefficient is used for balancing a privacy protection objective and a data quality objective; and based on the privacy score, the quality score, the dynamic weight coefficient and the cost information of the data provider, generating a data pricing formula by using a meta-learning model, and outputting a pricing result. According to the invention, fair and reasonable data pricing is realized, the expectation of the data purchaser for the data and the leakage risk of the data provider are balanced, and the healthy development of the data transaction market is promoted.

The invention relates to an urban fine-scale day-by-day atmospheric pollutant concentration estimation method, which comprises the following steps: acquiring urban region multi-source data, and performing multi-scale space-time matching processing; constructing a global estimation model of the atmospheric pollutants and training the global estimation model; obtaining the annual global atmospheric pollutant concentration under the fine scale of the urban area, and converting the annual global atmospheric pollutant concentration into a global atmospheric pollutant concentration weight; calculating a day-by-day local atmospheric pollutant concentration estimation residual error; and estimating to obtain the urban fine-scale day-by-day atmospheric pollutant concentration. The method has the beneficial effects that global features and local changes are comprehensively considered, the spatial resolution of an existing data product in a city is effectively improved, a high-precision hectometer-level day-by-day atmospheric pollutant data product is obtained, a polluted area can be positioned more accurately, and the method has a wide application prospect. Therefore, formulation and implementation of accurate prevention and control measures of urban atmospheric pollution are more scientifically guided, and the method has important application value.

The techniques described herein relate to systems and methods for generating data products personalized to users. An example system includes at least one hardware processor and at least one computer-readable storage medium storing processor-executable instructions that, when executed, cause the hardware processor(s) to perform a method comprising receiving, from a service provider, a request for a data product personalized to a user and comprising (i) first information identifying or that can be used to identify data source(s) storing user data for the user that the user has authorized for access and (ii) second information indicating how to transform at least some of the user data to generate the data product, obtaining, using the second information, the at least some of the user data from, or previously retrieved from, the data source(s), generating, using the second information, the data product, and providing, to the service provider, the generated data product.

The invention provides a cascade universal synchronous data acquisition method and system, and the method comprises the steps: enabling a master collector to transmit a received synchronous data acquisition instruction to each slave collector in communication connection with an expansion unit through the expansion unit of the master collector; the master control module of each slave collector sends the synchronous data collection instruction to each function module of the slave collector so as to collect data frames, and feeds back the collected data frames to the master control module of the slave collector; and then the data frames collected by the slave collectors are summarized through the master control modules of the slave collectors to form slave collection data, and the slave collection data are synchronously transmitted to the master collector based on the expansion units, so that the plurality of collectors complete synchronous data collection. The universal, serialized and standardized design of a module of a data acquisition product is realized, and the consistency of hardware design and the consistency of embedded software design are achieved, so that the cost is reduced, and the production and test efficiency of the product is improved.

The invention provides a data element value measurement and pricing control method, system and device, and belongs to the technical field of data asset value evaluation and management. Pricing information similar to data product fields is collected; analyzing the data element supermarket, and recording data quality, data volume, data timeliness and data application scene information at the same time; constructing a preliminary pricing model, and performing a simulated pricing test on the fields of the known prices by using the preliminary pricing model; determining a final price of the data product; formulating and executing a data directory putting mode; a putting monitoring mechanism is established, and the page view, the click rate and the inquiry amount of the data catalog are tracked in real time to know market response; setting an order quantity monitoring index and a market comparison analysis dimension; and collecting order quantity data, sorting and analyzing to generate a monitoring report. Through a value measurement and pricing management and control method, data products are priced by comprehensively considering various factors, and reasonable flow and configuration of data elements are promoted.

The invention discloses a related device of a data space connector, which belongs to the technical field of data processing, breaks through the technical barriers in the traditional data circulation through the functions of identity authentication, heterogeneous data source access, data product packaging and the like, enables data spaces of different organizations and industries to be seamlessly jointed based on a dual-channel interactive interface, and improves the data communication efficiency. A cross-domain data resource pool is formed, and the data circulation efficiency is improved; then, an access rule is customized for a shared data resource pool and a data product, so that the data management efficiency can be effectively improved, and the cross-domain cooperation trust cost can be effectively reduced; and finally, the data interaction is encrypted, so that the security of the data in the cross-domain interaction process is comprehensively ensured.

The invention provides a full-life-cycle digital asset management system. According to the technical scheme, the full-life-cycle digital asset management system is characterized by comprising a meta-model management module, a data source management module, a metadata management module, a data architecture design module, a data management module, a data product management module and a data asset management module; wherein the data management module comprises a data standard management module and a data quality management module; wherein the meta-model management module is connected with the metadata management module; the data source management module is interactively connected with the metadata management module, and the data source management module is also interactively connected with an external data source; the data management module is in interactive connection with the metadata management module, the data architecture design module, the data product management module and the data asset management module. According to the application, a layered modular architecture is adopted, and an automatic process from data modeling to capitalized operation is realized through a full-life-cycle management mechanism driven by a meta-model.

Telecommunications systems, computer devices and systems, and methods are provided. One example method, performed by a data abstraction layer of a telecommunications system for a network, includes accessing data elements associated with a network function of the network, performing abstraction on the data elements to generate one or more data products, receiving a customer request for a service on the network, identifying the data product related the service, and provisioning the identified data product to the customer. The method may further include identifying proprietary data and private data of the data elements based on a predefined policy and removing proprietary data and private data before performing abstraction.

This disclosure relates to methods, devices, and computer-readable media for use in developing data products. One such method comprises receiving an existing build of the data product, identifying a data product version associated with the existing build, receiving a user-specified modification for the data product, in response to a user input, automatically determining a compatibility result for the modification with the identified data product version, based on the existing build of the data product, and in response to the determined compatibility result being a negative compatibility result, triggering a failure event in relation to the identified data product version.

The invention relates to a data commodity recommendation method and system based on deep learning, and the method comprises the steps: carrying out the word embedding coding of a user text and a commodity text of a data commodity through a first deep learning model, and obtaining a user text matrix representation and a commodity text matrix representation; respectively carrying out feature extraction and feature compression on the user text matrix representation and the commodity text matrix representation by utilizing a second deep learning model to obtain a user text vector representation and a commodity text vector representation; fusing the user text vector representation and the commodity text vector representation to obtain a fusion vector; and calculating a prediction score of the data commodity according to the fusion vector. According to the method, the data commodity recommendation effect can be improved, the recommended data commodity can meet the purchase demand of the user, and the user experience and the transaction efficiency are improved.

The invention discloses a marine geological environment-oriented multi-source heterogeneous data acquisition quality control method and system, and belongs to the technical field of marine exploration. According to the method, a unified data description model is constructed, and the data structure and the space-time reference of the sensor are standardized; executing an adaptive collaborative acquisition strategy based on a preset task, and dynamically adjusting sensor parameters according to data characteristics to realize multi-source collaboration; and through multi-dimensional verification of integrity, range, time sequence stability, association consistency and the like, real-time evaluation and quality marking are carried out on the acquired data, and the data quality is guaranteed from the source. And the processed data and metadata are packaged into a standardized data product, so that the data usability and the reliability of system operation are ensured. By means of the method, pre-processing of quality control is achieved, the follow-up cleaning workload is reduced, support is provided for efficient data fusion analysis and scientific interpretation, and the automation level and the intelligent level of marine geological survey are improved.

The invention provides an ice and snow product inversion method and device based on a geological resource hyperspectral satellite, and relates to the technical field of remote sensing data processing.The inversion method comprises the steps that remote sensing image data and auxiliary data of a research area are obtained through the geological resource hyperspectral satellite, the remote sensing image data are preprocessed, and the preprocessed remote sensing image data are obtained; obtaining real reflectivity and spectral data of the earth surface; using a multilevel decision tree accumulated snow recognition algorithm to generate an accumulated snow range data product; obtaining a normalized snow index according to the spectral data; inputting the real earth surface reflectivity and the auxiliary data into a preset snow water equivalent inversion model to obtain snow water equivalent data; and inputting the auxiliary data, the normalized snow index and the remote sensing image data into a preset deep belief network to obtain accumulated snow area proportion data. According to the invention, based on the high-frequency observation capability of a geological resource hyperspectral satellite, high-precision ice and snow product inversion is realized under a complex terrain condition through the combination of a satellite remote sensing technology and a machine learning algorithm.

Described are methods, systems, and techniques to implement an improved map interface that displays updatable geographic information and that enables users to request one or more data products for a geospatial asset corresponding to a region of a geographic area. In some embodiments, a GIS application can be configured to interface with third party geospatial data suppliers that provide different types of data products displayable in the map interface. One or more of these data products can be requested by the user and may be associated with a recurring time interval to provide the user with expanded display views that are up to date and complete.

The invention relates to the technical field of data management, and particularly discloses an efficient management method and system for a data directory in a data space, and the method comprises the steps: carrying out the incremental updating of metadata information, data product registration information and cross-node data directory information related to the data directory to a distributed data storage system; constructing a full-text index and a vector index of metadata in the distributed data storage system, and matching a vector generated based on the request content with the full-text index or the vector index to obtain a retrieval response result; marking a semantic equivalence data set based on the semantic vectors of all the data sets, constructing a data set node graph based on all the semantic entity lists, and outputting a semantic equivalence field list based on the semantic equivalence data set and the data set node graph; determining an associated recommendation result of the retrieval response result based on the semantic equivalence field list, and synchronously returning the retrieval response result and the associated recommendation result; data directory management and efficient utilization in a distributed heterogeneous cross-domain data space are supported.

The invention belongs to the technical field of data processing, and discloses an enterprise-oriented AI cross-data integration service architecture design method and system, and the method comprises the steps: building a semantic connection layer of a cross-enterprise data source, penetrating bottom layer heterogeneous metadata in a layering and non-isolation manner to carry out logic unification, combining hotspot perception and a self-evolution mechanism, and carrying out the self-evolution of the semantic connection layer. Forming a cross-source semantic ontology of data weaving; based on the cross-source semantic ontology, generating a virtualized data view by adopting a zero-migration architecture; an optimization mechanism with query delay and a data filtering rate as reward signals is introduced to dynamically adjust a mapping strategy, and a virtual data product is output in combination with semantic mapping; low cost, high efficiency and sustainable evolution of enterprise cross-data integration are realized, and a solid support is provided for deep application of AI in a multi-enterprise cooperation scene.