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For more than three decades, IBM Research has produced major contributions to the area of data management. This includes E. F. Codd's seminal work on relational algebra; the System R relational database management system prototype, which led to IBM's DB2®; ARIES transaction recovery and logging; Starburst extensible database technology, and DB2 parallel database technology.
The Information Management (IM) group is proud to carry on IBM's rich tradition of excellence with groundbreaking research in data management technology. We utilize our expertise in XML, machine learning, text analysis, artificial intelligence, and application-enabling middleware to tackle the challenges posed by the proliferation of unstructured and semi-structured data in business applications, the life sciences, and personal information management.
The areas we focus on include query optimization, OLAP cubes, information processing, enterprise mashups, multidimensional content, and integration of structured, semi-structured, and unstructured data, as well as the emerging areas of e-commerce, Internet, and mobile applications.
The research contributions of our projects result not only in patents and papers in leading conferences, but provide a steady stream of technology shipping within IBM products, such as IBM's Content Manager, Lotus Discovery Server, and DB2.
We work at the intersection of data management and distributed systems to
develop the next generation of distributed information systems. We design
algorithms, build prototype systems, and transfer technology to IBM's software
products.
In the past, our group did pioneering research on parallel database systems,
which has provided underlying technology for IBM DB2's widely deployed data
sharing product. We also developed DataLinks technology for DB2, and have more
recently collaborated on autonomic
computing for DBMSs.
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