International Business Machines Corporation

Frank N Lee

Joseph W Dain

Nilesh Prabhakar Bhosale

Christopher J Vollmar

Sarvesh S Patel

Chin Ngai Sze

Yu-Cheng Hsu

Wayne A Sawdon

Abhishek Jain

Deepavali M Bhagwat

James Hewitt

Daniel De Souza Casali

Linda C Cham

Adriana Pellegrini Furnielis

Qingda Wang

Yi-Ling J Wong

A computer-implemented method, according to one approach, includes: receiving, at an edge computing environment, internet of things (IoT) data generated by IoT devices in communication with the edge computing environment. One or more inference models are used at the edge computing environment to: classify the IoT data, and generate labeled metadata for the classified IoT data. The labeled metadata is further used at the edge computing environment to identify portions of the IoT data to transmit to a cloud computing environment. Copies of the identified portions of the IoT data are also sent to the cloud computing environment.

Metadata based data distribution

Computer-implemented methods for management of data collection devices. Aspects include creating a cluster of data collection devices and a distributed meta-key manager for the cluster and providing an authentication key for each data collection device to access the distributed meta-key manager. Aspects also include collecting and storing data by one or more of the data collection devices and periodically perform a quorum check for each data collection device of the cluster. Aspects further include updating an operational mode of each data collection device based on the quorum check and offloading the stored data from a data collection device based on successful verification of the stored data and the operational mode of the data collection device.

Zero trust management for data collection devices

Provided are techniques for data search with automated selection of one or more AI inference models and inference label indexing. Metadata for a data object that is stored in a data source is retrieved. The metadata is matched to filtering criteria. The filtering criteria is used to identify an Artificial Intelligence (AI) inference model. The data object is sent to an inference engine for the AI inference model. An inference result is received from the inference engine. The inference result is stored in a database to associate the inference result with the data object. Then, in response to receiving a search request with one or more terms, the one or more terms are matched to the inference result in the database. and the data object and the inference result are returned.

Data search with automated selection of artificial intelligence inference models and inference label indexing

A set of metafiles that stores at least metadata information and provenance information of an artificial intelligence (AI) process is generated, where the AI process is trained with a source data. The set of metafiles is accessed via an application programming interface (API) to the set of metafiles. In response to accessing the set of metafiles, the source data in the set of metafiles is transferred to a cache for processing by the AI process.

Generation of a metadata-driven artificial intelligence platform

Embodiments for storage resource utilization analytics using metadata tags by a processor. Storage capacity utilization in the plurality of heterogeneous storage systems may be determined using one or more events indexed into a centralized search index.

Storage resource utilization analytics in a heterogeneous storage system environment using metadata tags

A method, computer program product, and system for providing provenance tracking in a workflow system. The computer-implemented process provides for one or more processors to receive a workflow definition input. One or more processors perform workflow job commands, in response to receiving a workflow definition, and a workflow instance request. One or more processors access an input file associated with the workflow instance. One or more processors generate, at run-time, provenance metadata. One or more processors generate, at run-time, a global file identification (ID) associated with an output file. One or more processors link the global file ID and the provenance metadata to the output file of the workflow instance, and one or more processors store the output file, which includes the global file ID and the provenance metadata, both linked to the output file.

Reliable workflow system provenance tracking at runtime

Systems, methods and computer program products configured to provide and perform metadata-based workflow management are disclosed. The inventive subject matter includes a computer readable storage medium having computer readable program instructions embodied therewith. The computer readable program instructions are configured to: initiate a workflow configured to process data; associate the data with metadata; and drive at least a portion of the workflow based on at least some of the metadata. The metadata include anchoring metadata; common metadata; and custom metadata. Inventive subject matter also encompasses a method for managing genomic data processing workflows using metadata includes: initiating a workflow; receiving a request to manage the workflow using metadata comprising: anchoring metadata, common metadata, and custom metadata, associating the metadata with the data; and driving at least a portion of the workflow based on the metadata. The workflow involves genomic analyses.

Metadata-driven workflows and integration with genomic data processing systems and techniques

Systems, methods and computer program products configured to provide and perform metadata-based workflow management are disclosed. The inventive subject matter includes a computer readable storage medium having computer readable program instructions embodied therewith. The computer readable program instructions are configured to: initiate a workflow configured to process data; associate the data with metadata; and drive at least a portion of the workflow based on at least some of the metadata. The metadata include anchoring metadata; common metadata; and custom metadata. Inventive subject matter also encompasses a method for managing genomic data processing workflows using metadata includes: initiating a workflow; receiving a request to manage the workflow using metadata comprising: anchoring metadata, common metadata, and custom metadata, associating the metadata with the data; and driving at least a portion of the workflow based on the metadata. The workflow involves genomic analyzes.

Growing community of inventors

Sunset Hills, MO, United States of America

Frank N Lee