Abstract: A UI for presenting and reviewing a document is optimized based upon the type of computing device being utilized to present the document. One such UI includes a first pane showing a view of the document under review that is sized and formatted for display on a large-format display device. The first pane can also be utilized to emphasize a portion of the document. The UI also includes a second pane that includes indicators for each of the reviewers of the document. The selection of an indicator will cause a portion of the document being reviewed by the corresponding reviewer to be displayed in the first pane. The UI also includes a third pane that includes a scaled image of the document shown in the first pane. Selection of a portion of the scaled image causes the selected portion of the document to be displayed in the first pane.

Abstract: Input data may define an approach, model or theme for presenting text in a two-dimensional or a three-dimensional display environment. The input data may be analyzed to determine a legibility score of the text. The legibility score may be based on a number of factors including the characteristics of the text, characteristics of the environment, an aggregate contrast ratio derived from aggregate luminance values, a relative importance of legibility, other contextual information and/or combinations thereof. If the legibility score does not meet at least one threshold, one or more treatments may be applied to the input data. For example, a treatment may involve a modification of the text size, font, text position, text color and/or modifications to the display environment, to improve the legibility of the text and/or the overall aesthetics of the display environment and the text.

Abstract: Technologies are described herein for obtaining and processing intent-based feedback. Authored content may be generated by the use of one or more layouts. The generated layouts may then be utilized to present the content to the author or other user. The author may further provide feedback to request the generated layout be adjusted or re-generated. The feedback may include overriding feedback that overrides the intent interpretation used in the layout, and/or intent feedback that changes or adds more intent data for the content data.

Abstract: One or more signals are used to identify regions of interest of an image. The signals are applied to the image to generate one or more models that are based on the regions of interest. The models may present different perspectives of the image by emphasizing various features and focal points. The models may be ranked and displayed according to a scoring paradigm that is based on one or more signals. Multi-tiered feedback mechanisms allow for the collection of user intent and/or other forms of explicit input. Feedback associated to the models may be obtained and used to generate additional models that are based on one or more signals and the feedback. The feedback may also be stored and utilized for machine learning purposes.

Abstract: Technologies are described herein for content authoring based on user intent. During content authoring, intent data can be obtained along with content data. The intent data may be obtained directly from the author or inferred from documents related to the content data. The intent data indicates the author's intent as to how to present the content data without utilizing explicit formatting instructions. A layout may be generated for the content data based on the intent data. Additional data may be utilized to generate the layout, such as the capabilities of a display device and the preferences of the content consumer.

Abstract: Technologies are described herein for inferring the layout intent associated with explicitly formatted document elements in a document. The layout type of a document having explicitly formatted document elements is determined. Once the layout type for the document has been determined, the layout intent of explicitly formatted document elements in the document may be determined based, at least in part, on the determined layout type of the document. Heuristic algorithms and/or machine learning classifiers may determine the layout intent of the explicitly formatted document elements in the document. An intent-based document is then created using the inferred layout intent for some or all of the explicitly formatted document elements in the document. The intent-based document may then be provided to an intent-based rendering or authoring application for rendering based upon the inferred layout intent.

Abstract: Concepts and technologies are described herein for transforming data into consumable content. In accordance with the concepts and technologies disclosed herein, a computing device can execute a transformation engine for transforming data into the consumable content. The computing device can be configured to analyze the data to identify relationships within data elements or other portions of the data. The computing device also can determine a visualization model to apply to the data and to choose a world based upon the determined visualization model. The computing device can obtain rules associated with the selected or chosen world, and can apply the rules to the data to generate the output. In some embodiments, the computing device can be configured to obtain and apply feedback to the output.

Abstract: Concepts and technologies are described herein for transforming data into consumable content. In accordance with the concepts and technologies disclosed herein, a computing device can execute a transformation engine for transforming data into the consumable content. The computing device can be configured to analyze the data to identify relationships within data elements or other portions of the data. The computing device also can determine a visualization model to apply to the data and to choose a world based upon the determined visualization model. The computing device can obtain rules associated with the selected or chosen world, and can apply the rules to the data to generate the output. In some embodiments, the computing device can be configured to obtain and apply feedback to the output.

Abstract: Concepts and technologies are described herein for creating variations when transforming data into consumable content. In accordance with the concepts and technologies disclosed herein, a computing device can execute a transformation engine for transforming data into the consumable content. The computing device can be configured to analyze the data to identify relationships among data elements or other portions of the data, and to identify any possible approaches to transforming the data (“worlds”) based upon the relationships and the data. The worlds can be ranked and selected based upon rank. The computing device can obtain rules associated with the selected and apply the rules to the data to generate the output. In some embodiments, the computing device can be configured to obtain and apply feedback regarding the world selection.

Abstract: Concepts and technologies are described herein for transforming data into consumable content. In accordance with the concepts and technologies disclosed herein, a computing device can execute a transformation engine for transforming data into the consumable content. The computing device can be configured to analyze the data to identify relationships within data elements or other portions of the data. The computing device also can determine a visualization model to apply to the data and to choose a world based upon the determined visualization model. The computing device can obtain rules associated with the selected or chosen world, and can apply the rules to the data to generate the output. In some embodiments, the computing device can be configured to obtain and apply feedback to the output.

Abstract: Concepts and technologies are described herein for creating variations when transforming data into consumable content. In accordance with the concepts and technologies disclosed herein, a computing device can execute a transformation engine for transforming data into the consumable content. The computing device can be configured to analyze the data to identify relationships among data elements or other portions of the data, and to identify any possible approaches to transforming the data (“worlds”) based upon the relationships and the data. The worlds can be ranked and selected based upon rank. The computing device can obtain rules associated with the selected and apply the rules to the data to generate the output. In some embodiments, the computing device can be configured to obtain and apply feedback regarding the world selection.

Abstract: Concepts and technologies are described herein for transforming data into consumable content. In accordance with the concepts and technologies disclosed herein, a computing device can execute a transformation engine for transforming data into the consumable content. The computing device can be configured to analyze the data to identify relationships within data elements or other portions of the data. The computing device also can determine a visualization model to apply to the data and to choose a world based upon the determined visualization model. The computing device can obtain rules associated with the selected or chosen world, and can apply the rules to the data to generate the output. In some embodiments, the computing device can be configured to obtain and apply feedback to the output.

Abstract: Technologies are described herein for ranking visualization types. In order to rank the visualization types, visualization metadata is generated for each of the visualization types and data set metadata is generated for the data set. A suitability score is then computed based upon the visualization metadata and the data set metadata through the use of data mapping rules and chart selection rules. The visualization types are then ranked according to the computed scores. A user interface may then be displayed that includes visual representations corresponding to the visualization types that are ordered according to the ranking. One of the visual representations may then be selected to apply the corresponding visualization type to the data set.

Abstract: Concepts and technologies are described herein for transforming data to create layouts. In accordance with the concepts and technologies disclosed herein, a computing device can execute a layout generator. The computing device can be configured to receive or retrieve data that includes visual content such as an image and other content such as text. The computing device can analyze the visual content to identify a salient region and/or an invariant region within the visual content. The computing device can access designs for laying out visual content and other content based upon an identified salient region and/or invariant region. The computing device can evaluate the designs to determine if a design matches the data. The computing device can load the data into the selected design to generate the layout.

Abstract: Concepts and technologies are described herein for creating variations when transforming data into consumable content. In accordance with the concepts and technologies disclosed herein, a computing device can execute a transformation engine for transforming data into the consumable content. The computing device can be configured to analyze the data to identify relationships among data elements or other portions of the data, and to identify any possible approaches to transforming the data (“worlds”) based upon the relationships and the data. The worlds can be ranked and selected based upon rank. The computing device can obtain rules associated with the selected and apply the rules to the data to generate the output. In some embodiments, the computing device can be configured to obtain and apply feedback regarding the world selection.

Abstract: Concepts and technologies are described herein for an abstract relational model for transforming data into consumable content. In accordance with the concepts and technologies disclosed herein, a computing device can execute a transformation engine for transforming data into the consumable content. The computing device can be configured to generate an abstract relational model from data to analyze the data and to identify relationships within data elements or other portions of the data. The computing device also can determine a visualization model to apply to the data and to choose a world based upon the determined visualization model. The computing device can obtain rules associated with the selected or chosen world, and can apply the rules to the data to generate the output. In some embodiments, the computing device can be configured to obtain and apply feedback to the output.

Abstract: Concepts and technologies are described herein for transforming data into consumable content. In accordance with the concepts and technologies disclosed herein, a computing device can execute a transformation engine for transforming data into the consumable content. The computing device can be configured to analyze the data to identify relationships within data elements or other portions of the data. The computing device also can determine a visualization model to apply to the data and to choose a world based upon the determined visualization model. The computing device can obtain rules associated with the selected or chosen world, and can apply the rules to the data to generate the output. In some embodiments, the computing device can be configured to obtain and apply feedback to the output.

Abstract: Concepts and technologies are described herein for processing touch sensor signals from sensors located on a portable touch screen device along with accelerometer data, to determine if, and how, the device is currently being used. Data from touch sensors along with accelerometer data are analyzed to identify a manner in which the device is being held, including how the user is holding the device. The touch sensor signals can be used to better control the device, including placing the device into a sleep state, and waking up the device. The touch sensor signals can also be used to configure the display contents, including where to locate various virtual keys or function keys on the screen or how to present a virtual keyboard based on how the user is holding and using the device.

Abstract: A UI for presenting and reviewing a document is optimized based upon the type of computing device being utilized to present the document. One such UI includes a first pane showing a view of the document under review that is sized and formatted for display on a large-format display device. The first pane can also be utilized to emphasize a portion of the document. The UI also includes a second pane that includes indicators for each of the reviewers of the document. The selection of an indicator will cause a portion of the document being reviewed by the corresponding reviewer to be displayed in the first pane. The UI also includes a third pane that includes a scaled image of the document shown in the first pane. Selection of a portion of the scaled image causes the selected portion of the document to be displayed in the first pane.

Abstract: Technologies are described herein for ranking visualization types. In order to rank the visualization types, visualization metadata is generated for each of the visualization types and data set metadata is generated for the data set. A suitability score is then computed based upon the visualization metadata and the data set metadata through the use of data mapping rules and chart selection rules. The visualization types are then ranked according to the computed scores. A user interface may then be displayed that includes visual representations corresponding to the visualization types that are ordered according to the ranking.