Uniform chart formatting based on semantics in data models

• US 10,282,360 B2
• Filed: 08/03/2017
• Issued: 05/07/2019
• Est. Priority Date: 08/03/2017
• Status: Active Grant

• Current Assignee: SAP SE
• Original Assignee: SAP SE
• Inventors: Krause, Gerald, Monnier, Vincent, Balzar, Andreas, Shao, Sihang, Fei, Jingting
• Primary Examiner(s): Chu, David H
• Application Number:
  US15/668,476
• Publication Number:
  US 20190042632A1
• Time in Patent Office: 642 Days
• Field of Search: None
• CPC Class Codes: G06F 12/0837 with software control, e.g. non-cacheable data
• CPC Class Codes: G06F 12/126 with special data handling, e.g. priority of data or instructions, handling errors or pinning
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 40/103 Formatting, i.e. changing of presentation of documents automatic justification G06F40/189; automatic line break hyphenation G06F40/191
• CPC Class Codes: G06F 40/169 Annotation, e.g. comment data or footnotes
• CPC Class Codes: G06Q 10/00 Administration; Management
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06T 11/206 Drawing of charts or graphs

Abstract

A system for visually enhancing a chart of one or more data sets with semantic information, the data points in the data sets being values of one or more measures. The system includes a data model that specifies the one or more measures and includes measure annotations for the one or more measures. The measure annotations include semantic information of the measures. The system further includes a processor that executes instructions stored in the memory to implement a chart component. The chart component renders data points of the one or more data sets in a chart, and visually enhances the chart with semantic information of the one or more measures retrieved from the data model.

Claims

1. A system for visually enhancing a chart of one or more data sets with semantic information, data points in the data sets being values of one or more measures, the system comprising:

a data model including specifications of the one or more measures and measure annotations for the one or more measures, the measure annotations including semantic information of the measures, wherein the data model includes information on one or more of criticality semantics, semantic roles, and semantic relations of the one or more measures;

at least one processor; and

a memory,

the at least one processor executing instructions stored in the memory to implement a chart component, the chart component rendering the data points of the one or more data sets in a chart and visually enhancing the chart with semantic information of the one or more measures retrieved from the data model, wherein, for calculated-by-reference criticality thresholds, the chart component determines a criticality for each data point or measure value with reference to a reference item specified in the measure annotation for each data point or measure value, and annotates the chart with the determined criticality information.

2. The system of claim 1, wherein the measure annotations in the data model are constructed using language constructs of a data modeling language of the data model.

3. The system of claim 1, wherein the criticality semantics provide definitions for categorizing measure values as being in one or more criticality categories, wherein the chart component determines criticality categories of the data points rendered in the chart, and wherein the chart component enhances the chart to visually depict the criticality categories of the data points rendered in the chart.

4. The system of claim 3, wherein the chart component visually depicts different criticality categories of the data points rendered in the chart in different graphical patterns and or colors.

5. The system of claim 3, wherein the chart component visually enhances the chart by using a dedicated graphical pattern and or color in the chart to depict a semantic role of a charted measure.

6. The system of claim 3, wherein the chart component visually enhances the chart by depicting a semantic relation between two charted measures using respective dedicated graphical patterns and or colors to depict the two charted measures.

7. The system of claim 1, wherein the criticality semantics provide thresholds or category boundary values for one or more criticality categories, wherein the chart component determines the criticality category of a data point rendered in the chart by comparing the data point value with thresholds or category boundary values provided by the criticality semantics.

8. The system of claim 1, wherein the criticality semantics provide fixed thresholds or category boundary values for the one or more criticality categories, and wherein the chart component determines the criticality category of a data point rendered in the chart by comparing the data point value with the fixed thresholds or category boundary values provided by the criticality semantics.

9. The system of claim 1, wherein the criticality semantics provide dynamic thresholds or category boundary values for the one or more criticality categories, and wherein the chart component determines the dynamic thresholds or category boundary values from values of one or more reference measures specified in the criticality semantics.

10. The system of claim 1, wherein, for static criticality categories, the chart component retrieves a criticality specified in the measure annotation for each data point or measure value, and annotates the chart with the retrieved criticality information.

11. A computer-implemented method for visually enhancing a chart of one or more data sets with semantic information, data points in the data sets being values of one or more measures, the method comprising:

providing, a data model that includes specifications of the one or more measures and measure annotations for the one or more measures, the measure annotations including semantic information of the measures, wherein the data model includes information on one or more of criticality semantics, semantic roles, and semantic relations of the one or more measures; and

accessing, with a chart component, the data model and a data source containing the one or more data sets; and

using the chart component to render data points of the one or more data sets in the chart and visually enhance the chart with semantic information of the one or more measures retrieved from the data model, and wherein, for calculated-by-reference criticality thresholds, the chart component determines a criticality for each data point or measure value with reference to a reference item specified in the measure annotation for each data point or measure value, and annotates the chart with the determined criticality information.

12. The computer-implemented method of claim 11, wherein the measure annotations in the data model are constructed using language constructs of a data modeling language of the data model.

13. The computer-implemented method of claim 11, wherein the criticality semantics provide definitions for categorizing measure values as being in one or more criticality categories, wherein the chart component determines criticality categories of the data points rendered in the chart, and wherein the chart component enhances the chart to visually depict the criticality categories of the data points rendered in the chart.

14. The computer-implemented method of claim 13, wherein the chart component visually depicts different criticality categories of the data points rendered in the chart in different graphical patterns and or colors.

15. The computer-implemented method of claim 13, wherein the chart component visually enhances the chart by using a dedicated graphical pattern and or color in the chart to depict a semantic role of a charted measure.

16. The computer-implemented method of claim 13, wherein the chart component visually enhances the chart by depicting a semantic relation between two charted measures using respective dedicated graphical patterns and or colors to depict the two charted measures.

17. The computer-implemented method of claim 11,

wherein when the criticality semantics provide thresholds or category boundary values for the one or more criticality categories the chart component determines the criticality category of a data point rendered in the chart by comparing the data point value with thresholds or category boundary values provided by the criticality semantics,

wherein when the criticality semantics provide fixed thresholds or category boundary values for the one or more criticality categories the chart component determines the criticality category of a data point rendered in the chart by comparing the data point value with the fixed thresholds or category boundary values provided by the criticality semantics,

wherein when the criticality semantics provide dynamic thresholds or category boundary values for the one or more criticality categories the chart component determines the dynamic thresholds or category boundary values from the values of one or more reference measures specified in the criticality semantics, and

wherein, for static criticality categories, the chart component retrieves a criticality specified in the measure annotation for each data point or measure value, and annotates the chart with the retrieved criticality information.