Laura M. Haas

Laura Myers Haas
NationalityAmerican
Alma materUniversity of Texas at Austin (Ph.D, 1981)
Harvard University (B.S., Computer Science, 1978)
Known forDatabase systems and Information integration
AwardsE. F. Codd Award (2015)
ACM Fellow (2006)
National Academy of Engineering (2010)
IBM Fellow (2009)
Scientific career
FieldsComputer Science
InstitutionsUniversity of Massachusetts Amherst
IBM Research, Almaden Laboratory (1981-2017)
Doctoral advisorK. Mani Chandy and Jayadev Misra

Laura M. Haas is an American computer scientist noted for her research in database systems and information integration. She is best known for creating systems and tools for the integration of heterogeneous data from diverse sources, including federated technology that virtualizes access to data, and mapping technology that enables non-programmers to specify how data should be integrated.

She led the Starburst project on extensible database systems, showing how diverse information could be integrated into a relational database.[1] Her research was the foundation for IBM's DB2 LUW query processor.[citation needed] She was the overall architect for Garlic,[2] a novel data federation system that provides integrated access to many data sources from a high-level nonprocedural language, and personally invented and implemented query optimization techniques that allowed Garlic to process queries efficiently, exploiting the capabilities of the underlying data sources.[3] Haas led the development of IBM InfoSphere Federation Server based on this technology, and was the technical lead of the IBM team which helped establish the enterprise information integration market. Laura also led the Clio project, inventing the concept and basic algorithms for schema mapping, and embodying them in the first tool to compute necessary transformations to bring data from diverse sources into a common format automatically.[4] She provided thought leadership[5] and pursued research around information integration, most recently in the context of big data, through her role as the Director of IBM Research's Accelerated Discovery Lab.[6]

  1. ^ Haas, L. M.; Freytag, J. C.; Lohman, G. M.; Pirahesh, H. (1989). "Extensible Query Processing in Starburst". ACM SIGMOD Record. 18 (2): 377–388. doi:10.1145/66926.66962.
  2. ^ Haas, L. M.; Lin, E. T.; Roth, M. A. (2002). "Data Integration through Database Federation". IBM Systems Journal. 41 (4): 578–596. doi:10.1147/sj.414.0578.
  3. ^ Haas, Laura M.; Kossmann, Donald; Wimmers, Edward L.; Yang, Jun (1997). "Optimizing Queries Across Diverse Data Sources". VLDB '97: Proceedings of the 23rd International Conference on Very Large Data Bases. pp. 276–285. ISBN 978-1-55860-470-4.
  4. ^ Miller, Renée J.; Haas, Laura M.; Hernández, Mauricio A. (2000). "Schema Mapping as Query Discovery". VLDB '00: Proceedings of the 26th International Conference on Very Large Data Bases. pp. 77–88. ISBN 978-1-55860-715-6.
  5. ^ Haas, Laura (2007). "Beauty and the Beast: The Theory and Practice of Information Integration". Database Theory – ICDT 2007. Lecture Notes in Computer Science. Vol. 4353. pp. 28–43. doi:10.1007/11965893_3. ISBN 978-3-540-69269-0.
  6. ^ Haas, Laura; Cefkin, Melissa; Kieliszewski, Cheryl; Plouffe, Wil; Roth, Mary (2014). "The IBM Research Accelerated Discovery Lab". ACM SIGMOD Record. 43 (2): 41–48. doi:10.1145/2694413.2694423. S2CID 1809253.