Analysis of time-based geospatial mashups using AD HOC visual queries

• US 20090172511A1
• Filed: 12/26/2007
• Published: 07/02/2009
• Est. Priority Date: 12/26/2007
• Status: Active Grant

• Current Assignee: Omnitracs LLC (Solera Holdings Incorporated)
• Original Assignee: VisTracks Incorporated (Solera Holdings Incorporated)
• Inventors: Kowalski, James, Rivard, Kurt David, Alworth, Colin, Horst, Brian, Eick, Stephen Gregory, Wolosewicz, Andrzej, Eick, M. Andrew, Decherd, Alexander, Fugitt, Jesse Adam
• Granted Patent: US 8,230,333 B2
• Time in Patent Office: Days
• US Class Current: 715/207
• CPC Class Codes: G06F 16/9537 Spatial or temporal dependent retrieval, e.g. spatiotemporal queries

Abstract

An apparatus in one example has an analytical environment for mashup data having visual analysis metaphors, and linking and correlation functionality among the visual analysis metaphors. A system may have: at least one store having a predetermined floor plan layout; at least one predetermined location on the predetermined floor plan layout for displaying at least one product; analytical environment for mashup data having visual analysis metaphors, the mashup data formed from data indiciative of the predetermined floor plan layout, and data indicated of sales of the at least one product; and linking and correlation functionality among the visual analysis metaphors through a web browser. In one example, a plurality of products may be positioned on a plurality of shelves, and may be depicted in a geographical display. Sales of each product may be depicted in a in time line display that is linked to the geographical display.

Claims

1. An apparatus comprising:

analytical environment for mashup data having visual analysis metaphors; and

linking and correlation functionality among the visual analysis metaphors.

2. The apparatus according to claim 1, wherein the apparatus further comprises lightweight web protocols, and reception of at least one of RSS and GeoRSS and KML data streams.

3. The apparatus according to claim 1, wherein in the analytical environment a unified model handles live and static data.

4. The apparatus according to claim 1, wherein the analytical environment allows multi-dimensional spatial analysis.

5. The apparatus according to claim 1, wherein the mashup data is presented spatially on a map, temporally on a timeline and cyclically on a time wheel.

6. The apparatus according to claim 1, wherein the mashup data is presented spatially on a map, temporally on a timeline and on at least one of:

a bar chart, line chart, pie chart, node and link graph.

7. The apparatus according to claim 1, wherein the analytical environment has components that are linked so that interactive operations are automatically propagate from one component displayed on a page to other components displayed on the page.

8. The apparatus according to claim 1, wherein the interactive operations are at least one of selection, tool tips, and highlighting.

9. The apparatus according to claim 1, wherein the analytical environment has a plurality of visual components, and wherein each of the visual components is live, dynamic and interactive.

10. The apparatus according to claim 9, wherein the visual components form building blocks that enable web authors to publish time-oriented geospatial content.

11. The apparatus according to claim 9, wherein the visual components automatically ingest new information as it is published by information providers.

12. The apparatus according to claim 1, wherein the apparatus further comprises a linked view visualization system that is completely implemented in a browser using JavaScript built around RSS functionality.

13. An apparatus comprising:

linked-view visualization system that is completely browser-based having light-weight maps and a set of thin client visualization components;

wherein data sources are combined to create a mashup web site and visualization components are linked in real time.

14. The apparatus according to claim 13, wherein at least one of live and static data is received from several different sources and is presented for rich analysis.

15. The apparatus according to claim 13, wherein the apparatus forms an interactive environment for analyzing time-based geospatial feature data, and wherein the apparatus receives at least one of RSS and GeoRSS, KML streams and creates an interactive mashup.

16. The apparatus according to claim 15, wherein each GeoRSS item is displayed on a map and in a timeline, and wherein RSS item without a geospatial element are only displayed in the timeline.

17. The apparatus according to claim 13, wherein the timeline has at least one of the following:

interactive panning and interactive zooming, detailed timeline that is synchronized with an overview timeline, panning to most recent events in a watch mode, multiple time scales, built in RSS support, linking to other visualizations, multiple data display modes, ability to select specific data items, ability to highlight specific data items, rich API to program against, built in toolbar, visual scalability over plotting indicator, best fit algorithms to position labels to avoid over plotting, algorithms to fit all points on a display, and height plotting to encode information using a y-position.

27. The system according to claim 17, wherein the system further comprises at least one planogram, and wherein product performance data is dynamically linked to each planogram, and wherein the linked planogram and product performance data is at least one of store specific, and shelf level specific.

28. The system according to claim 27, wherein the planogram and the product performance data is integrated with at least one of perpetual inventory systems, POS data, and RFID data and scanner data.

29. The system according to claim 17, wherein the analytical environment is integratable with existing systems and is accessible via a web browser.

30. The system according to claim 17, wherein retailers and suppliers are allowed access to the mashup data, and wherein the retailers and suppliers gauge compliance with programs by at least one of product type, location, and geography.

31. The system according to claim 17, wherein the retailer and supplier collaborate on key performance metrics and view results in real-time using common diagrams and visuals that are the same as in a planning process.

18. A system comprising:

at least one store;

at least one customer segment, each customer segment having a respective shopping pattern, wherein at least one of the shopping patterns occurs in at least one of the stores;

at least one customer transaction, the customer transaction occurring in a respective store of the plurality of stores by a customer in a respective customer segment of the plurality of customer segments;

analytical environment for mashup data having visual analysis metaphors, the mashup data formed form data indicative of the at least one store, the at least one customer segment, at least one shopping pattern, and at least one customer transaction; and

linking and correlation functionality among the visual analysis metaphors that enables interaction and interrogation of data through a web browser.

19. The system according to claim 18, wherein the system further comprises at least one display of geospatial and temporal shopping patterns of the customer segments.

20. The system according to claim 18, wherein customers are grouped into at least three customer segments:

“

brand aspirationals”

, “

value-price shoppers”

, and “

price-sensitive affluents”

that are related spatially and geo-spatially.

21. The system according to claim 18, wherein the linking and correlation functionality enables review of what specific customers are buying and when they are shopping.

22. The system according to claim 18, wherein at least the customer transactions form business data, and wherein at least the store locations form map data.

23. The system according to claim 22, wherein the analytical environment fuses the business data with the map data.

24. The system according to claim 18, wherein retailers identify buying patterns within or among key customer segments which drive more targeted promotions, better merchandising, improved product mix, and modified store hours for greater sales per square foot.

25. The system according to claim 18, wherein the system further comprises, for a display of store locations, a display of additional map layers.

26. The system according to claim 25, wherein an additional map layer is a representative store floor plan having at least one aisle and at least one shelf, and wherein the system further comprises a zoom function to zoom in to view sales and inventory data for a specific floor, a specific aisle, and a specific shelf of the store floor plan.

32. A system comprising:

at least one store;

at least one customer segment, each customer segment having a respective shopping pattern, wherein at least one of the shopping patterns occurs in at least one of the stores;

at least one customer transaction, the customer transaction occurring in a respective store of the plurality of stores by a customer in a respective customer segment of the plurality of customer segments;

analytical environment for mashup data having visual analysis metaphors, the mashup data formed form data indicative of the at least one store, data indicative of the at least one customer segment, data indicative of at least one shopping pattern, and data indicative of at least one customer transaction; and

linking and correlation functionality among the visual analysis metaphors that enables interaction and interrogation of data through a common web browser.

33. The system according to claim 32, wherein the system further comprises at least one display of geospatial and temporal shopping patterns of the customer segments.

34. The system according to claim 32, wherein customers are grouped into at least three customer segments:

“

brand aspirationals”

, “

value-price shoppers”

, and “

price-sensitive affluents”

that are related spatially and geo-spatially.

35. The system according to claim 32, wherein the linking and correlation functionality enables review of what specific customers are buying and when they are shopping.

36. The system according to claim 32, wherein the analytical environment fuses business data with map data.

37. The system according to claim 32, wherein sales of products forms product performance data, and wherein the system further comprises at least one planogram, and wherein product performance data is dynamically linked to each planogram.

38. The system according to claim 37, wherein the planogram and the product performance data is integrated with at least one of perpetual inventory systems, POS data, and RFID or scanner data.

39. A system comprising:

at least one store having a predetermined floor plan layout;

the at least one store having at least one predetermined location on the predetermined floor plan layout for displaying at least one product;

analytical environment for mashup data having visual analysis metaphors, the mashup data formed from data indiciative of the predetermined floor plan layout of the at least one store, and data indicated of sales of the at least one product; and

linking and correlation functionality among the visual analysis metaphors that enables interaction and interrogation of the mashup data through a web browser.

40. The system according to claim 39, wherein data indicative of the predetermined floor plan layout is depicted in a geographical display, and wherein data indicated of sales of the at least one product is depicted in a timeline display.

41. The system according to claim 39, wherein the geographical display and the timeline are depicted in a common browser, and wherein the analytical environment has a functionality that allows a zooming in on the geographical display in the common browser for analysis of sales of the product, in relation to the floor plan layout, as depicted in the timeline in the common browser.

42. The system according to claim 39, wherein the predetermined floor plan layout of the store comprises a plurality of shelves, and wherein a plurality of products are positioned on the plurality of shelves, and wherein each product on a particular shelf is depicted in a geographical display, and wherein sales of each product is depicted in a in time line display that is linked to the geographical display.

43. The system according to claim 39, wherein the analytical environment shows how much of at least one class of product sells over a period of time in light of a geographical location(s) of the at least one class of product in the store.

44. The system according to claim 39, wherein the analytical environment shows how much of at least a first class of product sells over a period of time in light of a geographical location(s) of the first class of product in the store as opposed to how much of at least a second class of product sells over a period of time in light of a geographical location(s) of the second class of product in the store.