US20160104308A1 - Performance optimization for data visualization - Google Patents

Performance optimization for data visualization Download PDF

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Publication number
US20160104308A1
US20160104308A1 US14/683,091 US201514683091A US2016104308A1 US 20160104308 A1 US20160104308 A1 US 20160104308A1 US 201514683091 A US201514683091 A US 201514683091A US 2016104308 A1 US2016104308 A1 US 2016104308A1
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data
geometry
visualization
abstract
primitives
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US14/683,091
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Barry Christopher Allyn
Michael Woolf
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Microsoft Technology Licensing LLC
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Microsoft Technology Licensing LLC
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Priority to US14/683,091 priority Critical patent/US20160104308A1/en
Assigned to MICROSOFT TECHNOLOGY LICENSING, LLC. reassignment MICROSOFT TECHNOLOGY LICENSING, LLC. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: ALLYN, BARRY CHRISTOPHER, WOOLF, MICHAEL
Priority to CN201580055854.2A priority patent/CN106796734A/zh
Priority to PCT/US2015/055415 priority patent/WO2016061157A1/en
Priority to EP15788505.4A priority patent/EP3207528A1/de
Publication of US20160104308A1 publication Critical patent/US20160104308A1/en
Abandoned legal-status Critical Current

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Definitions

  • Data visualization is a process for graphically representing data in a visualization, for example, a chart, an infographic, a map, a gauge, etc.
  • Visualizations of large data sets require signification system resources, including processor time and memory, to prepare or store the visualization, which can cause the system to lock up or slow down. It is with respect to these and other considerations that examples will be made.
  • aspects of the present disclosure provide performance optimization by culling data from a data visualization to reduce memory requirements.
  • data is culled during layout time to intelligently skip data that does not materially impact the presentation of the visualization; preserving the presentation while reducing complexity.
  • geometry produced during layout is culled such that the geometry vectors are reduced or simplified/trimmed to reduce post-layout processing (e.g., rendering).
  • each series layout uses private optimized data structures to store geometry in abstract form for reduced memory usage.
  • aspects of the present disclosure also provide for deferring the cost of layout to a background thread by cloning a visualization and performing layout on the background thread, then transferring the computed layout to the foreground thread in near constant time.
  • Examples may be implemented as a computer process, a computing system, or as an article of manufacture such as a computer program product or computer readable media.
  • the computer program product may be a computer storage media readable by a computer system and encoding a computer program of instructions for executing a computer process.
  • FIG. 1 illustrates a pipelined architecture in which data flows in a single direction
  • FIG. 2 illustrates a block diagram of a system for optimizing the performance of creating and laying out a visualization
  • FIG. 3 is a flow chart showing general stages involved in a method for providing data visualization platform performance optimization
  • FIG. 4 is a block diagram illustrating example physical components of a computing device
  • FIGS. 5A and 5B are block diagrams of a mobile computing device.
  • FIG. 6 is a block diagram of a distributed computing system.
  • memory is often a bottleneck for application performance.
  • Aspects allow for application performance to be optimized by bounding the amount of memory used and by storing data in a single, contiguous allocation.
  • geometry when geometry is computed by a layout engine, it may be cached within a bounded series object.
  • Aspects provide for data culling and the privatization, on a per-layout basis, for storing abstracting geometry to optimize performance.
  • Examples of the present disclosure are directed to providing performance optimization within a data visualization platform architecture via culling data from a data visualization.
  • the architecture enables building of a data visualization (e.g., a chart, an infographic, a map, a gauge, etc.) via a one-directional chain of separate stages, each stage having a simple input interface and output interface.
  • FIG. 1 illustrates a pipelined architecture 100 in which data flows in a single direction.
  • data flows from raw data 105 , to abstract geometry 115 , to series object 125 , to visualization 135 .
  • Data can be privatized or culled at each stage in the pipeline, which reduces the memory used for laying out and creating a visualization 135 . Accordingly, visualization generation is performed more efficiently.
  • Raw data 105 comprises the collection of data points to be plotted in a visualization 135 .
  • Raw data 105 in various aspects is organized by rows, vectors, arrays, tables, matrices, etc.
  • raw data 105 is taken from a group of cells in the EXCEL® spreadsheet software, offered by MICROSOFT CORPORATION of Redmond, Wash.
  • Visualizations 135 include, for example, charts, infographics, maps, gauges, etc., which are used to graphically display the raw data 105 .
  • Abstract geometry 115 comprises a limited set of primitives (e.g., lines, Beziers curves, Bezier surfaces, etc.) which can be passed directly to an appropriate rendering Application Programming Interface (API) or to an additional module or engine for further processing. From these primitives, any geometry can be approximated.
  • API Application Programming Interface
  • the abstract geometries 115 are stored as a series object 125 in a compact form that is tailored to each type of layout.
  • the abstract geometries 115 are assembled into a series object 125 that is stored in a single allocation as a continuous block in memory, which improves the speed of retrieval.
  • a series object 125 is a form of privatized storage, which is operable to provide all the abstract geometries 115 comprising it without being interrogated for individual abstract geometries 115 ; the entire series object 125 is provided in one synchronous operation to produce the visualization 135 .
  • the amount of abstract geometry 115 cached within a series object 125 is bounded by the display size of the visualization 135 and is computed to have a fixed cost in memory.
  • some aspects use multiple series objects 125 to create portions of the visualization 135 .
  • One example of a series objects 125 is a circle comprised of abstract geometry 115 (e.g., four cubic Beziers, each comprising a quadrant of the circle), which may represent the raw data 105 in the visualization 135 as a function of the circle's radius.
  • Abstract geometries 115 are stored in various forms according to various aspects. According to one aspect, abstract geometries 115 are stored as a master and instances compact form (e.g., lists of rectangles, circles, diamonds, lines, pie slices, etc.). A master and instances compact form enables a visualization type that uses geometry with repeating forms (e.g., a scatter series where each data point is a diamond shape) to improve performance by compacting the volume of series objects 125 to be provided.
  • a master and instances compact form e.g., lists of rectangles, circles, diamonds, lines, pie slices, etc.
  • a master and instances compact form enables a visualization type that uses geometry with repeating forms (e.g., a scatter series where each data point is a diamond shape) to improve performance by compacting the volume of series objects 125 to be provided.
  • abstract geometries 115 can be stored as path geometry (e.g., area charts, surface charts, radar charts, trend lines, etc.).
  • abstract geometries 115 can be stored as a formula. For example, in a business chart plotting supply and demand curves, functions describing the curves are stored. Accordingly, the abstract geometry 115 can be synthesized during rendering. For example, in cases of simple layout (e.g., line charts, column charts, etc.) that are computationally inexpensive and where the data is local, abstract geometry 115 may be synthesized directly from the raw data 105 .
  • FIG. 2 illustrates a block diagram of a system 200 for optimizing the performance of creating and laying out a visualization 135 .
  • data is passed to a layout engine 210 from client 240 during the layout phase of creating a visualization 135 , processed, and abstract geometry 115 is passed back to the client 240 to provide the visualization 135 .
  • the data received from the client 240 includes raw data 105 and a surface description 235 , which provides context on the client 240 and a coordinate space in which the raw data 105 will be visualized.
  • data is passed to a series layout module 250 to create abstract geometry 115 according to the surface description 235 to graphically represent the raw data 105 in a visualization 135 , which in turn is passed back to the layout engine 210 to cull the abstract geometry 115 before it is transmitted to the client 240 .
  • the system 200 is operable to privatize or cull data or geometry at any point.
  • raw data 105 received from the client 240 is converted into abstract geometry 115 .
  • the data culler 220 performs a layout-specific culling of the raw data 105 using custom culling logic.
  • Raw data 105 that, if removed, does not materially impact the visualization 135 , as determined by the custom culling logic, is culled; it is ignored or skipped when geometry is calculated.
  • data that is culled is retained by the layout engine 210 or the client 240 , but is not transmitted to the series layout module 250 or used in subsequent operations.
  • the data culler 220 enables the layout engine 210 to construct a visualization 135 that will still convey the same interpretation of the raw data 105 , but using less data.
  • raw data 105 is culled when its graphical representation in the visualization 135 is materially affected by the presentation of other raw data 105 .
  • a visualization 135 of a column series where data series comprising the raw data 105 are visualized as vertical columns
  • data series are culled from the raw data 105 when the vertical columns of other data series would overlap them in the visualization 135 .
  • raw data 105 (represented as circles) are culled from areas of high density within the bubble chart.
  • each visualization type comprises custom culling logic appropriate for its layout.
  • a particular culling logic is chosen based on the visualization type (e.g., column, scatter, pie, etc.) that selectively skips/ignores raw data 105 that would produce abstract geometry 115 or series objects 125 that materially affect the display of other abstract geometry 115 or series objects 125 .
  • the raw data 105 is not deleted in a cull; it is merely ignored for purposes of creating a visualization 135 .
  • raw data 105 that is not culled is converted to the appropriate primitives that can be used to synthesize geometry for downstream processes in the pipelined architecture 100 (e.g., rendered or interacted with via the visualization 135 ). By culling the raw data 105 , processes occurring later in the pipelined architecture 100 are provided with a reduced amount of data to manipulate while providing an equivalent interpretation of the data.
  • a geometry culler 230 culls abstract geometry 115 further to reduce rendering and rasterization costs of abstract geometry 115 and series objects 125 that are too complex for the current output resolution of the client 240 (or the device on which the client 240 is executed).
  • the geometry culler 230 executes geometry culling logic to drop abstract geometry 115 or convert it to a simpler form when the visualized abstract geometry 115 will fall below a size threshold within the visualization 135 .
  • the geometry culler 230 is operable to drop abstract geometry 115 when the culling will not materially impact the displayed visualization 135 .
  • the geometry culler 230 drops the abstract geometry 115 for empty series objects 125 and line segments that will be rendered in the visualization 135 with zero-length, trims/converts rectangles with zero height/width and short Bezier curves (e.g., less than 4 pixels) into lines, combines collinear segments, etc.
  • the geometry culler 230 reduces the number of primitives needed to display a set of abstract geometry 115 without materially affecting the visualization 135 according to the surface description 235 .
  • abstract geometry 115 comprised of fewer or simpler primitives (e.g., lines instead of Beziers)
  • geometry culling reduces the amount of processing required by subsequent stages in the pipelined architecture 100 .
  • a surface description 235 (e.g., visualization type, visualization size, client resolution/dpi, etc.) to be generated for the visualization 135 to provide client context on which the culling thresholds are based.
  • a client 240 with a display resolution of 1920 ⁇ 1080 pixels has greater resolution than a client 240 with a display resolution of 800 ⁇ 600 pixels, which is not able to display the same visualization 135 with as great of detail as the client 240 with the larger resolution.
  • a geometry for a rectangle displayed on the client 240 with the larger resolution may be culled to be displayed as a line (or not displayed at all) on the client 240 with the smaller resolution.
  • the surface description 235 is used by the data culler 220 to determine when abstract geometries 115 will materially impact one another (and thereby cull the associated raw data 105 ) and by the geometry culler 230 to determine when an abstract geometry 115 can be dropped or simplified/trimmed without materially affecting the display of the visualization 135 .
  • the entire data set is processed during the layout phase in order to produce the correct and reduced set of abstract geometries 115 , can take a long time and can introduce brief hangs and moments of unresponsiveness in the User Interface (UI) of a client 240 .
  • UI User Interface
  • a million rows of raw data 105 are “walked through” (i.e., processed row-by-row) to perform the data culling process and the resulting abstract geometries 115 are similarly processed to perform the geometry culling.
  • aspects provide for deferring the cost of the layout phase to a background thread to improve responsiveness by allowing the client 240 to clone the visualization 135 and push the layout phase to a background thread.
  • cloning can be achieved in near-constant time (e.g., less than 0.5 ms).
  • the background layout process allows the client 240 to still be responsive to user input while the layout of the visualization 135 is calculated in the background.
  • aspects allow for the foreground visualization 135 to remain blank, display a previous layout, display a progress bar (or similar indication of the ongoing layout process) for the background thread or combinations thereof.
  • aspects also allow for the background thread to be aborted by the client 240 , such as, for example, when a user manually aborts or when a second request is made.
  • the computed layout can be transferred back to a foreground thread at near constant time via an API that involves a pointer swap to replace or update the visualization 135 in the foreground.
  • FIG. 3 is a flow chart showing general stages involved in a method 300 for providing data visualization platform performance optimization.
  • Method 300 begins at START 301 and proceeds to OPERATION 310 , where the data to be used in a visualization 135 is received.
  • the received data includes raw data 105 and the surface description 235 for the visualization 135 .
  • Method 300 then proceeds to OPERATION 320 , where the layout is pushed to a background thread.
  • the layout is pushed to a background thread to prevent hangs or moments of unresponsiveness that may be introduced in the UI of a client 240 during processing.
  • Method 300 then proceeds to DECISION OPERATION 330 .
  • coordinate system requirements e.g., Cartesian, value/value (e.g. scatter chart); Cartesian, category/value (e.g., column chart); radial, category/value (e.g., pie chart, radar chart); etc.
  • method 300 proceeds to OPERATION 335 , where, according to aspects, the raw data 105 is culled according to layout-specific, custom culling logic (e.g., for a scatter series, overlapping markers are dropped) and method 300 then proceeds to OPERATION 340 .
  • layout-specific, custom culling logic e.g., for a scatter series, overlapping markers are dropped
  • raw data 105 may be culled according to several culling schemes, which may be user-defined or set by the system based on the visualization type, according to various aspects, including: by sequential truncation (e.g., ignoring data series after a threshold is reached), interleaved truncation (e.g., every other data series is culled), merging (e.g., combining small data series in appropriate visualization, such as a pie chart, into a “miscellaneous” data series), outlier culling, etc.
  • sequential truncation e.g., ignoring data series after a threshold is reached
  • interleaved truncation e.g., every other data series is culled
  • merging e.g., combining small data series in appropriate visualization, such as a pie chart, into a “miscellaneous” data series
  • outlier culling e.g., combining small data series in appropriate visualization, such as a pie chart, into a “
  • method 300 proceeds to OPERATION 340 .
  • Abstract geometries 115 are calculated and generated at OPERATION 340 to represent the raw data 105 in the visualization 135 . According to an aspect, abstract geometries 115 are calculated and generated individually for each data series comprising the raw data 105 . According to an aspect, abstract geometries are comprised of primitives (e.g., lines, Bezier curves, Bezier surfaces, etc.).
  • Method 300 then proceeds to DECISION OPERATION 350 , where is it determined whether to cull the abstract geometry 115 based on the display characteristics of the client 240 and the visualization 135 retrieved via the surface description 235 .
  • DECISION OPERATION 330 if 500 columns were to be rendered as rectangles having a width of one pixel, the decision to cull (via trimming) their geometry from rectangles to lines can be made without materially affecting the visualization 135 ; the visualization 135 will look substantially the same to a user.
  • culling the primitives comprising the abstract geometry 115 includes, but is not limited to: setting a master and instance format, so that a geometry is only passed once to the client 240 ; trimming the primitives of abstract geometries (e.g., a rectangle of width/height of one pixel can be represented as a line, a short curve can be represented as a line, etc.), to reduce the amount of processing needed by the client 240 ; dropping negligible geometry, such as the abstract geometry 115 corresponding to data series that are empty, zero-value, or too small to be accurately displayed in the visualization 135 (e.g., slices of a pie chart that would be too thin to be accurately displayed as a line on the chart) to reduce rendering time needed by the client 240 ; combining the primitives of collinear segments to group processes for the client; etc.
  • setting a master and instance format so that a geometry is only passed once to the client 240 ; trimming the primitives of abstract geometries (e.g., a rectangle of width/
  • method 300 proceeds to OPERATION 360 , where the abstract geometries 115 are privately stored on a per-series layout basis, such as, for example, via a series object 125 .
  • series objects 125 are stored in a single allocation as a contiguous block in memory, which improves the speed of retrieval.
  • a series object 125 is bounded by the display constraints of the visualization 135 , as indicated by the surface description 235 , and is computed to have a fixed cost in memory, such that it can be retrieved from memory in near-constant time (e.g., less than 0.5 ms).
  • each series object 125 corresponds to a data series (or, in other aspects, a combined data series) and can be stored individually, which allows method 300 to begin storing before all abstract geometry 115 has been culled according to OPERATION 355 .
  • several series objects 125 are stored in adjacent continuous blocks in memory, which further improves the speed of retrieval in OPERATION 380 .
  • Method 300 then proceeds to OPERATION 370 .
  • the computed layout is transferred back to a foreground thread from the background thread.
  • Method 300 then proceeds to OPERATION 380 , where the abstract geometry 115 is provided to the client 240 .
  • the abstract geometry 115 is streamed as series objects 125 to the client 240 .
  • the visualization 135 can be provided, and method 300 concludes at END 399 .
  • FIGS. 4-6 and the associated descriptions provide a discussion of a variety of operating environments in which examples of the disclosure may be practiced.
  • the devices and systems illustrated and discussed with respect to FIGS. 4-6 are for purposes of example and illustration and are not limiting of a vast number of computing device configurations that may be used for practicing aspects of the disclosure, described herein.
  • FIG. 4 is a block diagram illustrating physical components (i.e., hardware) of a computing device 400 with which examples of the present disclosure may be practiced.
  • the computing device components described below may be suitable for the client device described above.
  • the computing device 400 may include at least one processing unit 402 and a system memory 404 .
  • the system memory 404 may comprise, but is not limited to, volatile storage (e.g., random access memory), non-volatile storage (e.g., read-only memory), flash memory, or any combination of such memories.
  • the system memory 404 may include an operating system 405 and one or more programming modules 406 suitable for running software applications 450 , such as layout engine 210 .
  • the system memory 404 may include the client 240 .
  • the operating system 405 may be suitable for controlling the operation of the computing device 400 .
  • aspects of the invention may be practiced in conjunction with a graphics library, other operating systems, or any other application program and is not limited to any particular application or system.
  • This basic configuration is illustrated in FIG. 4 by those components within a dashed line 408 .
  • the computing device 400 may have additional features or functionality.
  • the computing device 400 may also include additional data storage devices (removable or non-removable) such as, for example, magnetic disks, optical disks, or tape. Such additional storage is illustrated in FIG. 4 by a removable storage device 409 and a non-removable storage device 410 .
  • program modules 406 may perform processes including, but not limited to, one or more of the stages of the method 300 illustrated in FIG. 3 .
  • Other program modules that may be used in accordance with examples of the present disclosure and may include other applications 450 such as, for example, electronic mail and contacts applications, word processing applications, spreadsheet applications, database applications, slide presentation applications, drawing or computer-aided application programs, etc.
  • examples of the disclosure may be practiced in an electrical circuit comprising discrete electronic elements, packaged or integrated electronic chips containing logic gates, a circuit using a microprocessor, or on a single chip containing electronic elements or microprocessors.
  • examples of the disclosure may be practiced via a system-on-a-chip (SOC) where each or many of the components illustrated in FIG. 4 may be integrated onto a single integrated circuit.
  • SOC system-on-a-chip
  • Such an SOC device may include one or more processing units, graphics units, communications units, system virtualization units and various application functionality all of which are integrated (or “burned”) onto the chip substrate as a single integrated circuit.
  • the functionality, described herein may be operated via application-specific logic integrated with other components of the computing device 400 on the single integrated circuit (chip).
  • Examples of the present disclosure may also be practiced using other technologies capable of performing logical operations such as, for example, AND, OR, and NOT, including but not limited to mechanical, optical, fluidic, and quantum technologies.
  • aspects of the disclosure may be practiced within a general purpose computer or in any other circuits or systems.
  • the computing device 400 may also have one or more input device(s) 412 such as a keyboard, a mouse, a pen, a sound input device, a touch input device, etc.
  • the output device(s) 414 such as a display, speakers, a printer, etc. may also be included.
  • the aforementioned devices are examples and others may be used.
  • the computing device 400 may include one or more communication connections 416 allowing communications with other computing devices 418 . Examples of suitable communication connections 416 include, but are not limited to, RF transmitter, receiver, or transceiver circuitry; universal serial bus (USB), parallel, or serial ports.
  • Computer readable media may include computer storage media.
  • Computer storage media may include volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information, such as computer readable instructions, data structures, or program modules.
  • the system memory 404 , the removable storage device 409 , and the non-removable storage device 410 are all computer storage media examples (i.e., memory storage.)
  • Computer storage media may include RAM, ROM, electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other article of manufacture which can be used to store information and which can be accessed by the computing device 400 . Any such computer storage media may be part of the computing device 400 .
  • Computer storage media does not include a carrier wave or other propagated data signal.
  • Communication media may be embodied by computer readable instructions, data structures, program modules, or other data in a modulated data signal, such as a carrier wave or other transport mechanism, and includes any information delivery media.
  • modulated data signal may describe a signal that has one or more characteristics set or changed in such a manner as to encode information in the signal.
  • communication media may include wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, radio frequency (RF), infrared, and other wireless media.
  • RF radio frequency
  • FIGS. 5A and 5B illustrate a mobile computing device 500 , for example, a mobile telephone, a smart phone, a tablet personal computer, a laptop computer, and the like, with which aspects of the disclosure may be practiced.
  • a mobile computing device 500 for example, a mobile telephone, a smart phone, a tablet personal computer, a laptop computer, and the like, with which aspects of the disclosure may be practiced.
  • FIG. 5A an example of a mobile computing device 500 for implementing the aspects is illustrated.
  • the mobile computing device 500 is a handheld computer having both input elements and output elements.
  • the mobile computing device 500 typically includes a display 505 and one or more input buttons 510 that allow the user to enter information into the mobile computing device 500 .
  • the display 505 of the mobile computing device 500 may also function as an input device (e.g., a touch screen display). If included, an optional side input element 515 allows further user input.
  • the side input element 515 may be a rotary switch, a button, or any other type of manual input element.
  • mobile computing device 500 may incorporate more or less input elements.
  • the display 505 may not be a touch screen in some examples.
  • the mobile computing device 500 is a portable phone system, such as a cellular phone.
  • the mobile computing device 500 may also include an optional keypad 535 .
  • Optional keypad 535 may be a physical keypad or a “soft” keypad generated on the touch screen display.
  • the output elements include the display 505 for showing a graphical user interface (GUI), a visual indicator 520 (e.g., a light emitting diode), or an audio transducer 525 (e.g., a speaker).
  • GUI graphical user interface
  • a visual indicator 520 e.g., a light emitting diode
  • an audio transducer 525 e.g., a speaker
  • the mobile computing device 500 incorporates a vibration transducer for providing the user with tactile feedback.
  • the mobile computing device 500 incorporates peripheral device ports 540 , such as an audio input (e.g., a microphone jack), an audio output (e.g., a headphone jack), and a video output (e.g., a HDMI port) for sending signals to or receiving signals from an external device.
  • an audio input e.g., a microphone jack
  • an audio output e.g., a headphone jack
  • a video output e.g., a HDMI port
  • FIG. 5B is a block diagram illustrating the architecture of one example of a mobile computing device. That is, the mobile computing device 500 can incorporate a system (i.e., an architecture) 502 to implement some examples.
  • the system 502 is implemented as a “smart phone” capable of running one or more applications (e.g., browser, e-mail, calendaring, contact managers, messaging clients, games, and media clients/players).
  • the system 502 is integrated as a computing device, such as an integrated personal digital assistant (PDA) and wireless phone.
  • PDA personal digital assistant
  • One or more application programs 450 may be loaded into the memory 562 and run on or in association with the operating system 564 .
  • Examples of the applications 450 include phone dialer programs, e-mail programs, personal information management (PIM) programs, word processing programs, spreadsheet programs, Internet browser programs, messaging programs, and so forth.
  • the layout engine 210 may be loaded into memory 562 .
  • the system 502 also includes a non-volatile storage area 568 within the memory 562 . The non-volatile storage area 568 may be used to store persistent information that should not be lost if the system 502 is powered down.
  • the applications 450 may use and store information in the non-volatile storage area 568 , such as e-mail or other messages used by an e-mail application, and the like.
  • a synchronization application (not shown) also resides on the system 502 and is programmed to interact with a corresponding synchronization application resident on a host computer to keep the information stored in the non-volatile storage area 568 synchronized with corresponding information stored at the host computer.
  • other applications may be loaded into the memory 562 and run on the mobile computing device 500 .
  • the system 502 has a power supply 570 , which may be implemented as one or more batteries.
  • the power supply 570 might further include an external power source, such as an AC adapter or a powered docking cradle that supplements or recharges the batteries.
  • the system 502 may also include a radio 572 that performs the function of transmitting and receiving radio frequency communications.
  • the radio 572 facilitates wireless connectivity between the system 502 and the “outside world,” via a communications carrier or service provider. Transmissions to and from the radio 572 are conducted under control of the operating system 564 . In other words, communications received by the radio 572 may be disseminated to the application programs 450 via the operating system 564 , and vice versa.
  • the visual indicator 520 may be used to provide visual notifications or an audio interface 574 may be used for producing audible notifications via the audio transducer 525 .
  • the visual indicator 520 is a light emitting diode (LED) and the audio transducer 525 is a speaker.
  • LED light emitting diode
  • the LED may be programmed to remain on indefinitely until the user takes action to indicate the powered-on status of the device.
  • the audio interface 574 is used to provide audible signals to and receive audible signals from the user.
  • the audio interface 574 may also be coupled to a microphone to receive audible input, such as to facilitate a telephone conversation.
  • the system 502 may further include a video interface 576 that enables an operation of an on-board camera 530 to record still images, video stream, and the like.
  • a mobile computing device 500 implementing the system 502 may have additional features or functionality.
  • the mobile computing device 500 may also include additional data storage devices (removable or non-removable) such as, magnetic disks, optical disks, or tape.
  • additional storage is illustrated in FIG. 5B by the non-volatile storage area 568 .
  • Data/information generated or captured by the mobile computing device 500 and stored via the system 502 may be stored locally on the mobile computing device 500 , as described above, or the data may be stored on any number of storage media that may be accessed by the device via the radio 572 or via a wired connection between the mobile computing device 500 and a separate computing device associated with the mobile computing device 500 , for example, a server computer in a distributed computing network, such as the Internet.
  • a server computer in a distributed computing network such as the Internet.
  • data/information may be accessed via the mobile computing device 500 via the radio 572 or via a distributed computing network.
  • data/information may be readily transferred between computing devices for storage and use according to well-known data/information transfer and storage means, including electronic mail and collaborative data/information sharing systems.
  • FIG. 6 illustrates one example of the architecture of a system for providing data visualization as described above.
  • Content developed, interacted with, or edited in association with the client 240 or the layout engine 210 may be stored in different communication channels or other storage types.
  • various documents may be stored using a directory service 622 , a web portal 624 , a mailbox service 626 , an instant messaging store 628 , or a social networking site 630 .
  • the client 240 or layout engine 210 may use any of these types of systems or the like for providing data visualization, as described herein.
  • a server 615 may provide the client 240 or layout engine 210 to clients 605 A-C.
  • the server 615 may be a web server providing the client 240 or layout engine 210 over the web.
  • the server 615 may provide the client 240 or layout engine 210 over the web to clients 605 through a network 610 .
  • the client computing device may be implemented and embodied in a personal computer 605 A, a tablet computing device 605 B or a mobile computing device 605 C (e.g., a smart phone), or other computing device. Any of these examples of the client computing device may obtain content from the store 616 .
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Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20170323028A1 (en) * 2016-05-04 2017-11-09 Uncharted Software Inc. System and method for large scale information processing using data visualization for multi-scale communities
US10216750B2 (en) 2014-10-14 2019-02-26 Microsoft Technology Licensing, Llc Annotated geometry
US10552445B1 (en) * 2018-07-17 2020-02-04 Merck Sharp & Dohme Corp. Progressive data distribution visualization
US11348293B2 (en) * 2020-02-13 2022-05-31 Eric Schneider Dynamic price range symbol update and display system, method, and device

Families Citing this family (63)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11017569B2 (en) 2014-09-08 2021-05-25 Tableau Software, Inc. Methods and devices for displaying data mark information
US10380770B2 (en) 2014-09-08 2019-08-13 Tableau Software, Inc. Interactive data visualization user interface with multiple interaction profiles
US10347018B2 (en) 2014-09-08 2019-07-09 Tableau Software, Inc. Interactive data visualization user interface with hierarchical filtering based on gesture location on a chart
US10635262B2 (en) 2014-09-08 2020-04-28 Tableau Software, Inc. Interactive data visualization user interface with gesture-based data field selection
US10347027B2 (en) 2014-09-08 2019-07-09 Tableau Software, Inc. Animated transition between data visualization versions at different levels of detail
US10353793B2 (en) 2014-11-05 2019-07-16 Oracle International Corporation Identifying improvements to memory usage of software programs
US20160162165A1 (en) * 2014-12-03 2016-06-09 Harish Kumar Lingappa Visualization adaptation for filtered data
WO2016141373A1 (en) 2015-03-05 2016-09-09 Magic Leap, Inc. Systems and methods for augmented reality
US10838207B2 (en) 2015-03-05 2020-11-17 Magic Leap, Inc. Systems and methods for augmented reality
FR3033919B1 (fr) * 2015-03-20 2018-09-07 Niel Vassort Thomas Procede de generation d'une sequence video cyclique
US9786081B1 (en) * 2015-05-14 2017-10-10 Domo, Inc. Transitioning between visual representations
US11068647B2 (en) * 2015-05-28 2021-07-20 International Business Machines Corporation Measuring transitions between visualizations
US10896532B2 (en) 2015-09-08 2021-01-19 Tableau Software, Inc. Interactive data visualization user interface with multiple interaction profiles
US9905034B2 (en) * 2015-09-14 2018-02-27 Salesforce.Com, Inc. Secure isolation of scripting from native graphic rendering of animated data visualizations
US10115213B2 (en) * 2015-09-15 2018-10-30 Salesforce, Inc. Recursive cell-based hierarchy for data visualizations
US10089368B2 (en) 2015-09-18 2018-10-02 Salesforce, Inc. Systems and methods for making visual data representations actionable
US10607139B2 (en) 2015-09-23 2020-03-31 International Business Machines Corporation Candidate visualization techniques for use with genetic algorithms
US10217254B2 (en) * 2015-09-24 2019-02-26 Oracle International Corporation Graphical editing of memory layout rules for software programs
US10127136B2 (en) 2015-09-24 2018-11-13 Oracle International Corporation Identifying and visualizing suboptimal memory layouts in software programs
US10489130B2 (en) 2015-09-24 2019-11-26 Oracle International Corporation Configurable memory layouts for software programs
US10909711B2 (en) 2015-12-04 2021-02-02 Magic Leap, Inc. Relocalization systems and methods
US10685035B2 (en) 2016-06-30 2020-06-16 International Business Machines Corporation Determining a collection of data visualizations
US10459938B1 (en) 2016-07-31 2019-10-29 Splunk Inc. Punchcard chart visualization for machine data search and analysis system
US10853380B1 (en) 2016-07-31 2020-12-01 Splunk Inc. Framework for displaying interactive visualizations of event data
US11037342B1 (en) * 2016-07-31 2021-06-15 Splunk Inc. Visualization modules for use within a framework for displaying interactive visualizations of event data
US10861202B1 (en) 2016-07-31 2020-12-08 Splunk Inc. Sankey graph visualization for machine data search and analysis system
US10459939B1 (en) 2016-07-31 2019-10-29 Splunk Inc. Parallel coordinates chart visualization for machine data search and analysis system
US10649211B2 (en) 2016-08-02 2020-05-12 Magic Leap, Inc. Fixed-distance virtual and augmented reality systems and methods
US10290130B2 (en) * 2016-08-31 2019-05-14 International Business Machines Corporation Visualization of connected data
US11430195B2 (en) * 2016-08-31 2022-08-30 Sony Corporation Information processing apparatus, information processing method, and program for improving user-friendliness of an animated tutorial depicting assembling parts for creating a robot
US10936559B1 (en) * 2016-09-28 2021-03-02 Amazon Technologies, Inc. Strongly-consistent secondary index for a distributed data set
PT109807A (pt) * 2016-12-23 2018-06-25 Inst Superior Tecnico Método para interação remota em tempo-real entre um telespetador e um programa de televisão em direto, e sistema que o implementa
US10304225B2 (en) 2016-12-30 2019-05-28 Microsoft Technology Licensing, Llc Chart-type agnostic scene graph for defining a chart
US11086498B2 (en) 2016-12-30 2021-08-10 Microsoft Technology Licensing, Llc. Server-side chart layout for interactive web application charts
US10395412B2 (en) 2016-12-30 2019-08-27 Microsoft Technology Licensing, Llc Morphing chart animations in a browser
US10812936B2 (en) 2017-01-23 2020-10-20 Magic Leap, Inc. Localization determination for mixed reality systems
US10580167B1 (en) * 2017-01-24 2020-03-03 Amazon Technologies, Inc. Excluding masked regions of virtual reality (VR) frames from encoder processing
US10593122B1 (en) 2017-01-24 2020-03-17 Amazon Technologies, Inc. Mirroring edge pixels
US10769752B2 (en) 2017-03-17 2020-09-08 Magic Leap, Inc. Mixed reality system with virtual content warping and method of generating virtual content using same
IL303275B1 (en) 2017-03-17 2024-04-01 Magic Leap Inc A mixed reality system with the assembly of multi-source virtual content and a method for creating virtual content using it
IL298822A (en) 2017-03-17 2023-02-01 Magic Leap Inc A mixed reality system with color virtual content distortion and a method for creating virtual content using it
US10572970B2 (en) * 2017-04-28 2020-02-25 Google Llc Extracting 2D floor plan from 3D GRID representation of interior space
US11940990B1 (en) 2017-06-16 2024-03-26 Amazon Technologies, Inc. Global clock values for consistent queries to replicated data
US10572108B2 (en) * 2017-07-20 2020-02-25 Vmware, Inc. Hierarchical inventory tree operation
US10534587B1 (en) * 2017-12-21 2020-01-14 Intuit Inc. Cross-platform, cross-application styling and theming infrastructure
CN112136101A (zh) 2018-06-03 2020-12-25 苹果公司 为用户界面和动画提供应用程序编程接口的框架
WO2020023383A1 (en) 2018-07-23 2020-01-30 Magic Leap, Inc. Mixed reality system with virtual content warping and method of generating virtual content using same
WO2020040749A1 (en) * 2018-08-21 2020-02-27 Google Llc Dynamically generated interface transitions
CN109388306B (zh) * 2018-09-29 2022-04-29 创新先进技术有限公司 信息显示方法及装置
CN110162763A (zh) * 2019-07-18 2019-08-23 成都希盟泰克科技发展有限公司 海量质量验评表单数据进行智能配置的优化方法及其系统
US10896480B1 (en) 2019-09-23 2021-01-19 International Business Machines Corporation Visualization rendering using an extensible rendering sequence
US11316951B2 (en) * 2019-09-30 2022-04-26 Citrix Systems, Inc. Polytree queue for synchronizing data with a shared resource
US11341703B2 (en) 2020-07-24 2022-05-24 Unity Technologies Sf Methods and systems for generating an animation control rig
US11562522B2 (en) 2020-07-24 2023-01-24 Unity Technologies Sf Method and system for identifying incompatibility between versions of compiled software code
US11698776B2 (en) 2020-07-24 2023-07-11 Unity Technologies Sf Method and system for processing computer code
US11410368B2 (en) 2020-07-24 2022-08-09 Unity Technologies Sf Animation control rig generation
US11645803B2 (en) * 2020-08-07 2023-05-09 International Business Machines Corporation Animation effect reproduction
US11880385B1 (en) 2020-09-29 2024-01-23 Amazon Technologies, Inc. Ordering updates to secondary indexes using conditional operations
US11250022B1 (en) 2020-09-29 2022-02-15 Amazon Technologies, Inc. Offline index builds for database tables
CN112419458A (zh) * 2020-11-20 2021-02-26 青岛以萨数据技术有限公司 基于安卓动画的用户交互方法、服务器、介质及系统
US20220218438A1 (en) * 2021-01-14 2022-07-14 Orthosnap Corp. Creating three-dimensional (3d) animation
CN113052942B (zh) * 2021-03-31 2023-06-30 抖音视界有限公司 图表生成方法、装置、存储介质及电子设备
CN113633970B (zh) * 2021-08-18 2024-03-08 腾讯科技(成都)有限公司 动作效果的显示方法、装置、设备及介质

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6359629B1 (en) * 1998-07-06 2002-03-19 Silicon Graphics, Inc. Backface primitives culling
US6480205B1 (en) * 1998-07-22 2002-11-12 Nvidia Corporation Method and apparatus for occlusion culling in graphics systems
US6636215B1 (en) * 1998-07-22 2003-10-21 Nvidia Corporation Hardware-assisted z-pyramid creation for host-based occlusion culling
US20100277507A1 (en) * 2009-04-30 2010-11-04 Microsoft Corporation Data Visualization Platform Performance Optimization
US20120218254A1 (en) * 2011-02-28 2012-08-30 Microsoft Corporation Data visualization design and view systems and methods
US20120229445A1 (en) * 2010-06-30 2012-09-13 Jenkins Barry L System and method of reducing transmission bandwidth required for visibility-event streaming of interactive and non-interactive content

Family Cites Families (50)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US543469A (en) * 1895-07-30 deuet
GB2270243B (en) 1992-08-26 1996-02-28 Namco Ltd Image synthesizing system
US7023440B1 (en) * 1998-09-14 2006-04-04 Fisher Rosemount Systems, Inc. Methods and apparatus for integrated display of process events and trend data
US6213944B1 (en) * 1999-03-05 2001-04-10 Atl Ultrasound, Inc. Ultrasonic diagnostic imaging system with a digital video recorder with visual controls
US7500188B1 (en) * 2000-04-26 2009-03-03 Novarra, Inc. System and method for adapting information content for an electronic device
US6853375B2 (en) 2000-05-10 2005-02-08 Cognos Incorporated Method for preemptive screen rendering
US6859217B2 (en) 2000-07-19 2005-02-22 Microsoft Corporation System and method to display and manage data within hierarchies and polyarchies of information
US7765255B2 (en) 2002-07-30 2010-07-27 Sap Ag Extended web infrastructure for business applications
US7171412B2 (en) 2002-10-07 2007-01-30 Sun Microsystems, Inc. Restricted access model for hierarchical data structures
US7949953B2 (en) 2003-06-13 2011-05-24 Sap Aktiengesellschaft Designing and generating charts to graphically represent data in a data source
JP4121125B2 (ja) 2003-09-10 2008-07-23 インターナショナル・ビジネス・マシーンズ・コーポレーション グラフィックス・イメージ生成装置及びその方法、データ解析装置及びその方法並びにプログラム
US7511718B2 (en) 2003-10-23 2009-03-31 Microsoft Corporation Media integration layer
US8090776B2 (en) 2004-11-01 2012-01-03 Microsoft Corporation Dynamic content change notification
US7911467B2 (en) 2005-12-30 2011-03-22 Hooked Wireless, Inc. Method and system for displaying animation with an embedded system graphics API
US8487937B2 (en) * 2006-01-04 2013-07-16 Microsoft Corporation Representing animation as a static image on a graphical user interface
US9019300B2 (en) 2006-08-04 2015-04-28 Apple Inc. Framework for graphics animation and compositing operations
US8990258B2 (en) * 2006-12-29 2015-03-24 Izenda, Inc. Self-service database reporting systems and methods
US7737979B2 (en) 2007-02-12 2010-06-15 Microsoft Corporation Animated transitions for data visualization
CN101111049B (zh) 2007-08-14 2010-07-28 华为技术有限公司 实现一个小区覆盖多区域的系统、方法和网络设备
US8184096B2 (en) 2007-12-04 2012-05-22 Apple Inc. Cursor transitions
US20090184977A1 (en) 2008-01-18 2009-07-23 Qualcomm Incorporated Multi-format support for surface creation in a graphics processing system
US8346897B2 (en) 2008-02-25 2013-01-01 Jon Jaroker System and method for deploying and maintaining software applications
US20090327921A1 (en) 2008-06-27 2009-12-31 Microsoft Corporation Animation to visualize changes and interrelationships
US8176096B2 (en) * 2008-12-18 2012-05-08 Microsoft Corporation Data visualization interactivity architecture
US9250926B2 (en) 2009-04-30 2016-02-02 Microsoft Technology Licensing, Llc Platform extensibility framework
US8725775B2 (en) 2009-06-03 2014-05-13 Business Objects Software Limited Identifying and abstracting a visualization point from an arbitrary two-dimensional dataset into a unified metadata for further consumption
WO2011010688A1 (ja) 2009-07-22 2011-01-27 日本電気株式会社 コンテンツ配信システム、コンテンツ配信方法、コンテンツ配信プログラム
US8527458B2 (en) 2009-08-03 2013-09-03 Oracle International Corporation Logging framework for a data stream processing server
US8694906B2 (en) 2010-04-15 2014-04-08 Adobe Systems Incorporated Dynamic visualization of physical and geographical multitenant cloud computing
US20110285727A1 (en) * 2010-05-24 2011-11-24 Microsoft Corporation Animation transition engine
US8244743B2 (en) 2010-06-08 2012-08-14 Google Inc. Scalable rendering of large spatial databases
CN102473319A (zh) 2010-06-16 2012-05-23 松下电器产业株式会社 动画控制装置、动画控制方法及动画控制程序
US9292587B2 (en) 2010-07-21 2016-03-22 Citrix System, Inc. Systems and methods for database notification interface to efficiently identify events and changed data
US9069557B2 (en) 2010-12-17 2015-06-30 Microsoft Technology Licensing, LLP Business intelligence document
US20120313957A1 (en) 2011-06-09 2012-12-13 Microsoft Corporation Staged Animated Transitions for Aggregation Charts
US9262849B2 (en) 2011-11-14 2016-02-16 Microsoft Technology Licensing, Llc Chart animation
US20130179791A1 (en) 2011-12-16 2013-07-11 Webotics Inc. System and method for real-time data in a graphical user interface
US9286162B2 (en) 2012-02-02 2016-03-15 Netapp, Inc. System and method for guaranteeing consistent data synchronization from a volatile data source
US9530272B2 (en) 2012-02-22 2016-12-27 Zotobi Management Ltd. System and method for displaying multiple activities
US20130271472A1 (en) 2012-04-12 2013-10-17 Motorola Mobility, Inc. Display of Value Changes in Between Keyframes in an Animation Using a Timeline
US20140046923A1 (en) 2012-08-10 2014-02-13 Microsoft Corporation Generating queries based upon data points in a spreadsheet application
US8631034B1 (en) 2012-08-13 2014-01-14 Aria Solutions Inc. High performance real-time relational database system and methods for using same
US9075618B2 (en) 2012-11-02 2015-07-07 Microsoft Technology Licensing, Llc Cross-platform data visualizations using common descriptions
KR20140066392A (ko) 2012-11-23 2014-06-02 삼성전자주식회사 캐시 메모리 및 캐시 메모리를 포함하는 어플리케이션 프로세서의 데이터 관리 방법
US9910574B2 (en) * 2012-12-21 2018-03-06 What-Ifolution Technology Bv Method and system for visualizing and manipulating graphic charts
US11256524B2 (en) 2013-02-19 2022-02-22 Quick Eye Technologies Inc. Data structures for visualization of hierarchical data
US10691309B2 (en) 2013-03-27 2020-06-23 Broadsign Serv, Llc Media element transition electronic device, method and application
CN103678578B (zh) * 2013-12-10 2017-07-18 广东威创视讯科技股份有限公司 一种数据可视化处理方法、服务器及数据可视化处理系统
US9767145B2 (en) * 2014-10-10 2017-09-19 Salesforce.Com, Inc. Visual data analysis with animated informational morphing replay
US20160104308A1 (en) 2014-10-14 2016-04-14 Microsoft Technology Licensing, Llc. Performance optimization for data visualization

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6359629B1 (en) * 1998-07-06 2002-03-19 Silicon Graphics, Inc. Backface primitives culling
US6480205B1 (en) * 1998-07-22 2002-11-12 Nvidia Corporation Method and apparatus for occlusion culling in graphics systems
US6636215B1 (en) * 1998-07-22 2003-10-21 Nvidia Corporation Hardware-assisted z-pyramid creation for host-based occlusion culling
US20100277507A1 (en) * 2009-04-30 2010-11-04 Microsoft Corporation Data Visualization Platform Performance Optimization
US20120229445A1 (en) * 2010-06-30 2012-09-13 Jenkins Barry L System and method of reducing transmission bandwidth required for visibility-event streaming of interactive and non-interactive content
US20120218254A1 (en) * 2011-02-28 2012-08-30 Microsoft Corporation Data visualization design and view systems and methods

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
Fabian Nuñez. “An extended spreadsheet paradigm for data visualization systems, and its implementation”, Master’s thesis, University of Cape Town, November 2000. At http://citeseer.ist.psu.edu/543469.html. *

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10216750B2 (en) 2014-10-14 2019-02-26 Microsoft Technology Licensing, Llc Annotated geometry
US10430382B2 (en) 2014-10-14 2019-10-01 Microsoft Technology Licensing, Llc Data visualization architecture
US10810159B2 (en) 2014-10-14 2020-10-20 Microsoft Technology Licensing, Llc. Modular updating of visualizations
US20170323028A1 (en) * 2016-05-04 2017-11-09 Uncharted Software Inc. System and method for large scale information processing using data visualization for multi-scale communities
US10552445B1 (en) * 2018-07-17 2020-02-04 Merck Sharp & Dohme Corp. Progressive data distribution visualization
US11163790B2 (en) * 2018-07-17 2021-11-02 Merck Sharp & Dohme Corp. Progressive data distribution visualization
US11348293B2 (en) * 2020-02-13 2022-05-31 Eric Schneider Dynamic price range symbol update and display system, method, and device

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EP3633630A1 (de) 2020-04-08
EP3207529A1 (de) 2017-08-23
US20160103828A1 (en) 2016-04-14
US20160104306A1 (en) 2016-04-14
WO2016061158A1 (en) 2016-04-21
US20160104307A1 (en) 2016-04-14
EP3207528A1 (de) 2017-08-23
US20160104318A1 (en) 2016-04-14
WO2016061157A1 (en) 2016-04-21
WO2016061159A1 (en) 2016-04-21
EP3207527A1 (de) 2017-08-23
US20160104311A1 (en) 2016-04-14
CN106796734A (zh) 2017-05-31
CN106852178A (zh) 2017-06-13
US10216750B2 (en) 2019-02-26
KR20170067853A (ko) 2017-06-16
EP3207527B1 (de) 2019-11-20
US10810159B2 (en) 2020-10-20
US10430382B2 (en) 2019-10-01
CN107077752A (zh) 2017-08-18

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