Interactive Data Integration through Smart Copy & Paste

نویسندگان

  • Zachary G. Ives
  • Craig A. Knoblock
  • Steven Minton
  • Marie Jacob
  • Partha Pratim Talukdar
  • Rattapoom Tuchinda
  • José Luis Ambite
  • Maria Muslea
  • Cenk Gazen
چکیده

In many scenarios, such as emergency response or ad hoc collaboration, it is critical to reduce the overhead in integrating data. Here, the goal is often to rapidly integrate “enough” data to answer a specific question. Ideally, one could perform the entire process interactively under one unified interface: defining extractors and wrappers for sources, creating a mediated schema, and adding schema mappings — while seeing how these impact the integrated view of the data, and refining the design accordingly. We propose a novel smart copy and paste (SCP) model and architecture for seamlessly combining the design-time and run-time aspects of data integration, and we describe an initial prototype, the CopyCat system. In CopyCat, the user does not need special tools for the different stages of integration: instead, the system watches as the user copies data from applications (including the Web browser) and pastes them into CopyCat’s spreadsheet-like workspace. CopyCat generalizes these actions and presents proposed auto-completions, each with an explanation in the form of provenance. The user provides feedback on these suggestions — through either direct interactions or further copy-and-paste operations — and the system learns from this feedback. This paper provides an overview of our prototype system, and identifies key research challenges in achieving SCP in its full generality.

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عنوان ژورنال:
  • CoRR

دوره abs/0909.1769  شماره 

صفحات  -

تاریخ انتشار 2009