Automatically incorporating new sources in keyword search-based data integration

Scientific data offers some of the most interesting challenges in data integration today. Scientific fields evolve rapidly and accumulate masses of observational and experimental data that needs to be annotated, revised, interlinked, and made available to other scientists. From the perspective of the user, this can be a major headache as the data they seek may initially be spread across many databases in need of integration. Worse, even if users are given a solution that integrates the current state of the source databases, new data sources appear with new data items of interest to the user. Here we build upon recent ideas for creating integrated views over data sources using keyword search techniques, ranked answers, and user feedback [32] to investigate how to automatically discover when a new data source has content relevant to a user’s view — in essence, performing automatic data integration for incoming data sets. The new architecture accommodates a variety of methods to d...

• Type: Conference
• Year: 2010
• Where: SIGMOD
• Authors: Partha Pratim Talukdar, Zachary G. Ives, Fernando Pereira
• Keywords: Data Integration, Data Source, Database, Schema Matchers, SIGMOD 2010