Invention Grant
- Patent Title: On-demand generation of correlated collections of mashable data from distributed, non-homogeneous data sources
- Patent Title (中): 按需生成来自分布式非均匀数据源的可混合数据的相关集合
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Application No.: US13086952Application Date: 2011-04-14
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Publication No.: US09053184B2Publication Date: 2015-06-09
- Inventor: Scott N. Gerard , John K. Gerken, III
- Applicant: Scott N. Gerard , John K. Gerken, III
- Applicant Address: US NY Armonk
- Assignee: International Business Machines Corporation
- Current Assignee: International Business Machines Corporation
- Current Assignee Address: US NY Armonk
- Agency: CRGO Law
- Agent Steven M. Greenberg, Esq.
- Main IPC: G06F7/00
- IPC: G06F7/00 ; G06F17/30

Abstract:
Embodiments of the present invention provide a method, system and computer program product for the on-demand generation of correlated collections of mashable data from distributed, heterogeneous data sources. In an embodiment of the invention, a method for on-demand generation of correlated collections of mashable data from distributed, heterogeneous data sources is provided. The method includes receiving a request for a data feed from a widget in a mashup rendered in a content browser executing in memory of a computer. The method further includes inspecting a virtual database of data aggregated from different data sources over a computer communications network to locate data requisite to returning the data feed to the widget in the mashup. The method yet further includes querying the data of the virtual database to produce the data feed. Finally, the method includes returning the data feed in the format specified to the widget in the mashup.
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