Abstract: One example method includes data orchestration. Data sets are available to users in an online marketplace. Based on requests for data sets, other data sets may be recommended. The recommended data sets are moved or copied to recommended locations. This ensures that the data sets are available to the user more quickly if subsequently requested.

Abstract: One example method includes extracting content metadata from data, storing the content metadata in a data catalogue, receiving at the data catalogue, from a user, a request to access the data, transmitting, by the data catalogue to a security service provider, an access request that includes the extracted content metadata and metadata relating to the access request, accessing, by the security service provider, identity metadata concerning an identity of the user, and a data access policy, and transmitting, by the security service provider to the data catalogue, a decision as to whether or not access can be granted to the data, and the decision is based on the data access policy, the identity metadata, and the metadata in the access request.

Abstract: Methods, apparatus, and processor-readable storage media for automatically generating context-based alternative text using artificial intelligence techniques are provided herein. An example computer-implemented method includes generating text captions for an image derived from a web page by processing the image using an artificial intelligence-based image captioning model; determining context information pertaining to the image by processing the image using an artificial intelligence-based context and emotion recognition library; generating context-based alternative text for at least a portion of the image by processing, using at least one artificial intelligence-based alternative text generation model, at least a portion of one or more of the generated text caption(s) for the image and the determined context information pertaining to at least a portion of the image; and performing one or more automated actions based on the generated context-based alternative text.

Abstract: One example method includes determining representation bias in a data set. A bias detection engine is trained using a data set that is sufficiently diversified and/or unbiased. Once trained, test data sets can be evaluated by the bias detection engine to determine an amount of representation bias in the test data sets. The representation bias can be visually conveyed to a user and suggestions on how to reduce the representation bias may be provided and/or implemented to reduce the representation bias in the test data set. Suggestions can be implemented by adding or removing data from the test data that will reduce the representation bias.

Abstract: One example method includes data orchestration. Data sets are available to users in an online marketplace. Based on requests for data sets, other data sets may be recommended. The recommended data sets are moved or copied to recommended locations. This ensures that the data sets are available to the user more quickly if subsequently requested.

Abstract: One example method includes monitoring a data access pattern, registering a data access request directed to data, comparing metadata associated with the data access request to a rule, based on a result of the comparing, sending a trigger to a graph service, and using information in the trigger to generate a visual representation of the data access request, wherein the visual representation indicates an extent to which the data access request is considered to constitute a potential threat to the data.

Abstract: One example method includes extracting an expected communication specification of a service that is in development in a build pipeline, stimulating the service to exercise communication variations of the service, capturing communication traffic involving the service and one or more endpoints, comparing the captured communication traffic to the expected communication specification, and based on the comparing, detecting, in the captured communication traffic, and flagging, any anomalous communication behavior of the service.

Abstract: One example method includes extracting content metadata from data, storing the content metadata in a data catalogue, receiving at the data catalogue, from a user, a request to access the data, transmitting, by the data catalogue to a security service provider, an access request that includes the extracted content metadata and metadata relating to the access request, accessing, by the security service provider, identity metadata concerning an identity of the user, and a data access policy, and transmitting, by the security service provider to the data catalogue, a decision as to whether or not access can be granted to the data, and the decision is based on the data access policy, the identity metadata, and the metadata in the access request.