Abstract: A computing device receives a user input to add a data visualization to a first visualization card in a first scene of an interactive presentation. In response to the user input, when the first scene is an initial scene to be added, the device computes, for each metric of a plurality of metrics, a respective parameter that measures the variability of values of the respective metric, and identifies a first subset of metrics based on the computed parameters. The device generates a respective data visualization for each metric. The device displays a plurality of the generated data visualizations. The device receives user selection of a first data visualization of the plurality of data visualizations, corresponding to a first metric of the subset of metrics. In response to the user selection, the device populates the first visualization card with the first data visualization.

Abstract: A computing device performs an automated analysis of a data source and generates one or more first natural language outputs in accordance with the automated analysis. The device displays the first natural language outputs in a graphical user interface and receives user selection of a natural language output of the first natural language outputs. In response to receiving the user selection, the device generates a first data visualization according to the automated analysis, one or more data fields of the data source specified in the natural language output, and/or analytical operations specified in the natural language output. The device displays the first data visualization in the graphical user interface. The device generates one or more second natural language outputs and displays the second natural language outputs in the graphical user interface.

Abstract: Embodiments are directed to intent driven dashboard recommendations. A plurality of collection specifications that declare visualization declarations may be provided such that each collection specification is associated with an author intent. And attributes-of-interest selected from a data source may be provided. A plurality of collections may be generated based on the plurality of collection specifications, the attributes-of-interest, or data from the data source such that each collection may include visualizations that may be based on the visualization declarations. A preference score may be generated for each collection based on the author intent, visualizations in each collection, or the attributes-of-interest. The plurality of collections may be classified based on the preference scores associated with the classified collections such that the classified collections may be displayed based on the preference scores.

Abstract: A computing device displays, in a graphical user interface, a canvas region that includes a first scene. The first scene includes a first visualization card having a first data visualization and a first text card, adjacent to the first visualization card. The device receives, via the first text card, (i) text input from a user and (ii) user selection of a first user interface element for linking the first text card to the first visualization card. In accordance with the receiving, the device determines whether the text input includes a first expression having a first time span that intersects with a temporal domain of the first data visualization. In accordance with a determination that the text input includes the first expression, and in response to a first user interaction with a first region of the first text card that includes the first expression, the device visually emphasizes a first portion of the first data visualization, corresponding to the first time span.

Abstract: A computing device receives user selection of a data source. In accordance with the user selection, the device generates one or more initial natural language utterances according to metrics of data fields in the data source and/or previous user interaction with the data source. Each of the initial natural language utterances corresponds to a respective suggestion to guide visual analysis of the data source. The device displays the initial utterances in a graphical user interface. The device receives user selection of a first initial utterance of the initial utterances. In response to the user selection, the device generates and displays a first data visualization in accordance with data fields and/or analytical operations specified in the first initial utterance. The device also generates updated natural language utterances in accordance with the first initial utterance and the first data visualization, and displays the updated utterances with the first data visualization.

Abstract: A computing device receives user interaction with a portion of a data visualization that is displayed on the computing device. In response to receiving the user interaction, the computing device generates a first prompt that includes (i) a first parameter specifying a visualization type of the data visualization, (ii) a second parameter specifying a data array corresponding to data marks of the data visualization, and (iii) a third parameter specifying a title of the data visualization. The computing device inputs the first prompt into a large language model (LLM) and obtains, from the LLM, a text narrative for the portion of the data visualization. The device generates a second prompt in accordance with the text narrative, inputs the second prompt into the LLM, and obtains from the LLM a title for the text narrative. The device generates a self-contained story based on the text narrative and the title.

Abstract: A method provides visual analysis of datasets. A system receives a natural language search query that is directed to data repositories including data sources and data visualizations. The system parses search tokens to determine if the natural language search query contains analytic intents. The system also determines if the search tokens match fields in one or more data sources, using a semantic search. When (i) the search tokens match fields in the one or more data sources and (ii) the natural language search query contains analytic intents, the system generates and displays visualization responses. When (i) the search tokens do not match fields in the data sources or (ii) the natural language search query does not contain the analytic intents, the system displays pre-authored content from the data visualizations.

Abstract: A framework for generating and presenting verbal command suggestions to facilitate discoverability of commands capable of being understood and support users exploring available commands. A target associated with a direct-manipulation input is received from a user via a multimodal user interface. A set of operations relevant to the target is selected and verbal command suggestions relevant to the selected set of operations and the determined target are generated. At least a portion of the generated verbal command suggestions is provided for presentation in association with the multimodal user interface in one of three interface variants: one that presents command suggestions as a list, one that presents command suggestions using contextual overlay windows, and one that presents command suggestions embedded within the interface. Each of the proposed interface variants facilitates user awareness of verbal commands that are capable of being executed and teaches users how available verbal commands can be invoked.

Abstract: A computing device receives a user input to add a data visualization to a first visualization card in a first scene of an interactive presentation. In response to the user input, when the first scene is an initial scene to be added, the device computes, for each metric of a plurality of metrics, a respective parameter that measures the variability of values of the respective metric, and identifies a first subset of metrics based on the computed parameters. The device generates a respective data visualization for each metric. The device displays a plurality of the generated data visualizations. The device receives user selection of a first data visualization of the plurality of data visualizations, corresponding to a first metric of the subset of metrics. In response to the user selection, the device populates the first visualization card with the first data visualization.

Abstract: A computing device identifies a plurality of metrics corresponding to one or more data sources. The device receives a first user input to add a first data visualization to a first visualization card in a first scene of the interactive presentation. In response to the first user input, and in accordance with a determination that the graphical user interface includes a prior scene having a second visualization card with a second data visualization, the device computes, for each metric, a respective parameter that measures a variability of values of the respective metric. The device identifies a subset of metrics based on the computed parameters and identifies a first metric to which the second data visualization corresponds. The device determines whether the first subset of metrics includes the first metric and displays a plurality of the generated data visualizations in accordance with the determination.

Abstract: A computing device displays, in a graphical user interface, a canvas region that includes a first scene. The first scene includes a first visualization card having a first data visualization and a second visualization card, adjacent to the first visualization card, the second visualization card having a second data visualization. The device receives user input to specify merging the first data visualization with the second data visualization. Responsive to the user input, and in accordance with a determination that (i) the first data visualization and the second data visualization share a common time period and (ii) there is a substantial overlap between a first range of values in a vertical axis of the first data visualization and a second range of values in a vertical axis of the second data visualization, the device merges the first data visualization and the second data visualization into a single data visualization.

Abstract: A computing device displays, in a graphical user interface, a canvas region that includes a first scene. The first scene includes a first visualization card having a first data visualization and a first text card, adjacent to the first visualization card. The device receives, via the first text card, (i) text input from a user and (ii) user selection of a first user interface element for linking the first text card to the first visualization card. In accordance with the receiving, the device determines whether the text input includes a first expression having a first time span that intersects with a temporal domain of the first data visualization. In accordance with a determination that the text input includes the first expression, and in response to a first user interaction with a first region of the first text card that includes the first expression, the device visually emphasizes a first portion of the first data visualization, corresponding to the first time span.

Abstract: A computing device displays, in a graphical user interface, a canvas region that includes a first scene. The first scene includes a first visualization card. The device also displays, in the graphical user interface, a recommendation region that includes one or more data visualizations. Each data visualization corresponds to a respective metric of one or more metrics of a data source. The respective metric has a respective temporal attribute. The device receives user selection to add a first data visualization, corresponding to a first metric of the one or more metrics, to the first visualization card. In response to the user selection, the device updates display of the first visualization card to include the first data visualization.

Abstract: Embodiments are directed to intent driven dashboard recommendations. A plurality of collection specifications that declare visualization declarations may be provided such that each collection specification is associated with an author intent. And attributes-of-interest selected from a data source may be provided. A plurality of collections may be generated based on the plurality of collection specifications, the attributes-of-interest, or data from the data source such that each collection may include visualizations that may be based on the visualization declarations. A preference score may be generated for each collection based on the author intent, visualizations in each collection, or the attributes-of-interest. The plurality of collections may be classified based on the preference scores associated with the classified collections such that the classified collections may be displayed based on the preference scores.

Abstract: A framework for generating and presenting verbal command suggestions to facilitate discoverability of commands capable of being understood and support users exploring available commands. A target associated with a direct-manipulation input is received from a user via a multimodal user interface. A set of operations relevant to the target is selected and verbal command suggestions relevant to the selected set of operations and the determined target are generated. At least a portion of the generated verbal command suggestions is provided for presentation in association with the multimodal user interface in one of three interface variants: one that presents command suggestions as a list, one that presents command suggestions using contextual overlay windows, and one that presents command suggestions embedded within the interface. Each of the proposed interface variants facilitates user awareness of verbal commands that are capable of being executed and teaches users how available verbal commands can be invoked.

Abstract: A framework for generating and presenting verbal command suggestions to facilitate discoverability of commands capable of being understood and support users exploring available commands. A target associated with a direct-manipulation input is received from a user via a multimodal user interface. A set of operations relevant to the target is selected and verbal command suggestions relevant to the selected set of operations and the determined target are generated. At least a portion of the generated verbal command suggestions is provided for presentation in association with the multimodal user interface in one of three interface variants: one that presents command suggestions as a list, one that presents command suggestions using contextual overlay windows, and one that presents command suggestions embedded within the interface. Each of the proposed interface variants facilitates user awareness of verbal commands that are capable of being executed and teaches users how available verbal commands can be invoked.

Abstract: A framework for generating and presenting verbal command suggestions to facilitate discoverability of commands capable of being understood and support users exploring available commands. A target associated with a direct-manipulation input is received from a user via a multimodal user interface. A set of operations relevant to the target is selected and verbal command suggestions relevant to the selected set of operations and the determined target are generated. At least a portion of the generated verbal command suggestions is provided for presentation in association with the multimodal user interface in one of three interface variants: one that presents command suggestions as a list, one that presents command suggestions using contextual overlay windows, and one that presents command suggestions embedded within the interface. Each of the proposed interface variants facilitates user awareness of verbal commands that are capable of being executed and teaches users how available verbal commands can be invoked.

Abstract: An infrastructure monitor receives an indication of a fault on a first host computer of a plurality of host computers, wherein each of the plurality of host computers is associated with a different subset of a plurality of queues, and wherein each of the plurality of queues are serviced by a different subset of the plurality of host computers. The monitor identifies a first subset of the plurality of queues associated with the first host computer and determines a workload present on the first subset of the plurality of queues. The monitor further generates a single visualization to provide the indication of the fault on the first host computer, the first subset of the plurality of queues impacted by the fault, and the workload present on the first subset of the plurality of queues and causes presentation of the single visualization.

Abstract: A framework for generating and presenting verbal command suggestions to facilitate discoverability of commands capable of being understood and support users exploring available commands. A target associated with a direct-manipulation input is received from a user via a multimodal user interface. A set of operations relevant to the target is selected and verbal command suggestions relevant to the selected set of operations and the determined target are generated. At least a portion of the generated verbal command suggestions is provided for presentation in association with the multimodal user interface in one of three interface variants: one that presents command suggestions as a list, one that presents command suggestions using contextual overlay windows, and one that presents command suggestions embedded within the interface. Each of the proposed interface variants facilitates user awareness of verbal commands that are capable of being executed and teaches users how available verbal commands can be invoked.

Abstract: A computer implemented method for denoising a set of seismic datasets, specifically belonging to different 3D subsets of a 4D survey the method including: (a) receiving a baseline and a monitor seismic dataset which were acquired by surveying over the same subsurface formation over different periods of time; (b) cross-equalizing the monitor seismic dataset to match to the baseline seismic dataset in terms of amplitude, frequency, phase and timing of events; (c) computing an initial 4D difference between the monitor and baseline seismic datasets; (d) formulating a common noise template from the initial 4D difference; (e) de-noising the baseline and monitor seismic datasets, independently, using the common noise template in a curvelet domain; (f) updating the initial 4D difference to form an updated 4D difference, which reflects de-noised baseline and monitor datasets from step (e); and iterating the steps (d) through (F) until the updated 4D difference satisfies a predetermined criteria.