Abstract: Example embodiments relate to providing pixel-based visualizations of time series data using nested helices. In example embodiments, helix portions in the time series data may be identified according to a measured time interval, where each of the helix portions represents the measured time interval in the time series data. A helical time period may then be determined and used as a helical revolution in a helical pixel representation. At this stage, the helical pixel representation may be generated using the helix portions, where proximate helix portions along a common line parallel to an axis of the helical pixel representation are chronologically separated by the helical time period.

Abstract: Data records contain corresponding values of an attribute and are associated with location information. Hierarchical levels of transparency images are generated, where each of the transparency images includes corresponding pixels that represent the respective data records, and where the transparency images at different ones of the hierarchical levels correspond to different zoom levels of a geographic map. At least one of the transparency images at a dynamically-selected one of the hierarchical levels is overlaid over the geographic map according to which of the zoom levels is selected by a user in zooming of the geographic map, where the at least one transparency image is automatically selected without user input.

Abstract: A calendar graphical visualization is generated that includes an arrangement of blocks including pixels representing data records containing user feedback, wherein plural groups of the blocks represent different attributes of the data records, and wherein the blocks correspond to respective time intervals. A size of the blocks is determined based on identifying a union of time positions corresponding to data records received for the different attributes in a particular time interval of the time intervals. Pixels in a first of the blocks corresponding to a first of the attributes are aligned with pixels in a second of the blocks corresponding to a second of the attributes by placing gaps in the first and second blocks at respective time positions that are missing values for corresponding ones of the attributes.

Abstract: Actions associated with visualizing an input data set using plural graphs are monitored. At least one of the graphs is produced based on selection from another of the graphs. A relationship tree that represents relationships of the graphs is created based on monitoring the actions. Output information including description data and image data is provided, where the description data contains at least a portion of the relationship tree. The output information enables interactive navigation through the plural graphs without accessing the input data set.

Abstract: A multi-attribute visualization is generated that includes non-overlapped cells that represent respective items. The cells are placed in the visualization according to geographic locations associated with the items, and the cells being assigned visual indicators to represent a first attribute of the items. The cells are arranged in clusters in the visualization, where a size of a particular one of the clusters indicates a second attribute representing a number of cases associated with a corresponding one of the items. Multiple coordinated views of the cells are presented in the visualization, the multiple views corresponding to respective different time intervals.

Abstract: A system may include an extraction engine to extract candidate phrases from a content stream, and an analysis engine to assign the candidate phrases visual cues and display the visual cues to an operator.

Abstract: Multivariate time-series prediction is combined with motif discovery. Multivariate time-series prediction is performed on measured (past) data points to generate or determine predicted data points. One or more motifs are discovered or determined within the combined measured data points and the predicted data points. The motifs within the measured data points are associated with the motifs within the predicted data points to permit inferences of the motifs within the measured data points to be applied to the motifs within the predicted data points. The measured data points, the predicted data points, and the motifs are displayed. User interaction with this display of the measured data points, the predicted data points, and the motifs is permitted.

Abstract: A collection of data values is divided into plural bins, wherein a number of the bins is dependent upon a change feature of the data values. Parameter values associated with respective bins are determined. Based on the parameter values, visualization of the plural bins is provided in corresponding plural display screen partitions of a display screen, wherein at least one of the display screen partitions has a resolution that is different from another of the display screen partitions.

Abstract: Example embodiments relate to providing visual analytics of temporal-spatial relationships. In example embodiments, power meters may be located at regions within a building for collecting power consumption data at regular intervals. The power consumption data can be recursively processed to generate a pixel calendar tree by using a power meter hierarchy to subdivide the pixel calendar tree into tree portions according to a proportion of the power consumption data attributed to each of power meter nodes, where the tree portions are arranged in the pixel calendar tree according to an importance of the proportion; generating pixel cells in the pixel calendar tree that each represent a day in the power consumption data; and generating cell borders that each surround one of the pixel cells. At this stage, a pixel calendar display of a physical infrastructure of the building that includes the pixel cells and the cell borders can be generated.

Abstract: Attributes in data records are identified. Episodes corresponding to the respective attributes include respective data records. The episodes are scored, where scoring of a particular one of the episodes is based on relative time densities between successive data records of the particular episode. A visualization of at least some of the episodes to provide an alert of time-dense episodes.

Abstract: A plurality of time series having corresponding sets of data over time are received. Visual indicators for display in a display region are presented for values of at least a first attribute of the plurality of time series in corresponding cell-based lines, where the cell-based lines have cells to display the corresponding visual indicators for the values of the at least first attribute over time. The plurality of time series in the display region are ordered according to an aggregate of at least one attribute of the plurality of time series.

Abstract: Example embodiments relate to providing visual analytics of spatial time series data. In example embodiments, sensors may be located at regions within a building for collecting sensor data at regular time intervals. A sensor hierarchy can be generated including sensor nodes that are hierarchically arranged according to a physical infrastructure of the building, where each of the sensor nodes corresponds to a sensor. Sensor data can be obtained from the sensors, and a pixel calendar tree can be generated based on the sensor data and the sensor hierarchy, where the pixel calendar tree is recursively subdivided into tree portions according to a proportion of the sensor data attributable to each of the sensors. The pixel calendar tree can be displayed, where each of the tree portions includes time series sensor data of a corresponding region that is generated based on the sensor data.

Abstract: Data records are grouped into clusters according to attributes of the data records to be correlated. At least two of the clusters that satisfy a proximity criterion are merged. At least one ellipsoid is created for presentation in a scatter plot visualization based on the grouping and merging, the ellipsoid including pixels representing multiple corresponding data records. The ellipsoid has a characteristic based on a corresponding local correlation of the attributes of the data records represented by the ellipsoid. The characteristic of the ellipsoid is adjusted based on a direction of the local correlation.

Abstract: An event occurring in a particular geographic region is identified based on disseminated information containing public commentary in the particular geographic region. Attributes that are related to the event are identified, and sentiment words relating to the identified event are extracted from the disseminated information, where the extracted sentiment words are in a local language of the particular geographic region. A sentiment trend visualization is generated that depicts a trend of sentiments of at least a particular one of the identified attributes, wherein the sentiments are based on the sentiment words for at least the particular attribute.

Abstract: A scatter plot that represents plural periodic time intervals is animated as new data points are received, where the animating includes performing real-time backward rewriting. The real-time backward rewriting includes overlaying a subset of previously written data points with the new data points, and painting a remainder of previously written data points outside the subset in the scatter plot, where painting the remainder of previously written data points is performed without shifting pixels corresponding to the remainder. A divider structure is drawn in the scatter plot to indicate a position in the scatter plot between a current time point and a previous time point.

Abstract: A region is selected in a visualization that displays cells representing respective events, the cells being depicted in the visualization according to a first group of attributes of the events, where the region corresponds to a subset of the events. In response to detecting a first type of input provided with respect to the region, a semantic zoom-in visualization of the region is generated, the semantic zoom-in visualization depicting the cells representing the events of the subset at an enlarged scale and according to the first group of attributes and at a higher resolution to show further information relating to the events of the subset. In response to detecting a second type of input provided with respect to the region, a semantic drill-down visualization of the region is generated, the semantic drill-down visualization visualizing the events of the subset at an enlarged scale and according to a second group of attributes having at least one attribute that differs from the attributes of the first group.

Abstract: Sentiment analysis of user feedback is performed, using uncertainty rules. Different levels of uncertainty associated with sentiment results of the sentiment analysis are determined, where the sentiment results identify user sentiments contained in the user feedback. At least one visualization of the sentiment result is provided, where the visualization has first visual indicators to represent respective user sentiments, and second visual indicators associated with the first visual indicators to represent respective levels of uncertainty associated with the respective user sentiments.

Abstract: A method, apparatus, and system are disclosed for pixel charts with data dependent display spaces. One embodiment is a method for software execution. The method includes building a pixel bar chart having plural bars with different heights and different widths; and simultaneously displaying the plural bars of the pixel bar chart.

Abstract: For plural categorical values of a first attribute, more relevant categorical values of a second attribute are selected from among candidate categorical values of the second attribute, where the selecting uses a relevance determination process that considers frequencies of occurrence of respective pairs of the categorical values of the first and second attributes. A visualization that includes groups of cells corresponding to the respective pairs of categorical values of the first and second attributes is generated. At least one of the groups includes cells assigned visual indicators based on values of a third attribute.

Abstract: To perform time slice-based visual prediction, a weighted moving aggregate of data values in a data set is calculated over previous time slices to predict data values based on interactive user input. A visual accuracy indicator is generated for display to indicate a quality of prediction of data values at different times. A visualization presents data values from the data set and the predicted data values, where the data values from the data set and the predicted data values are represented as corresponding cells.