IBM Research
IBM Research
Data Management
Database Systems Projects
We are investigating fundamental research issues for the next generation of highly scalable, high performance database and decision support systems. Our research stretches from low-level data access layers of relational database systems to high-level semantic reasoning.
  Efficient Data Access Methods for RDBMS
  Information Integration and Business Intelligence
  Semi-structured and Un-structured Data Access
  XML Storage Manager
Intelligent Information Analysis and Unstructured Information Mining Projects

We are investigating fundamental research issues involved in the automatic extraction of intelligent information from unstructured information such as images, audio, video, rich text, as well as heterogeneous distributed sensor networks. The common goal across all projects in this area is to apply machine learning, signal processing and database techniques to extract information that can be used for accessing the unstructured data at a semantic level. This analysis will help build solutions for semantic enrichment and repurposing of the unstructured data.  

  Content Adaptation and MPEG 21
  CueVideo
  MARVEL (MPEG-7 Video Search Engine)
  SLAM - Semantic Learning and Analysis of Multimedia
Self Managing and Resource Tuning (SMART) Projects

SMART is part of IBM's autonomic computing initiative to help reduce complexity and improve quality of service through the advancement of self-managing capabilities within a database environment.

  Learning Optimizer (LEO)
  Partitioning Advisor
Past Projects Projects
We have initiated several projects in the area of XML data management with the aim of providing comprehensive support for processing structured and semistructured data using native storage abstractions and Xquery and SQL/XML query languages.
  Active Technologies
  DBCache
  DBProxy
  EpiSPIRE (Progressive Mining)
  Hippocratic Databases
  Simple Object Access Protocol (SOAP)
  SPIRE
  XML Mediation
  XML Query Processing
  Xperanto
 
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