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Orion 2.0: native support for uncertain data
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International Conference on Management of Data archive
Proceedings of the 2008 ACM SIGMOD international conference on Management of data table of contents
Vancouver, Canada
DEMONSTRATION SESSION: Group 1 table of contents
Pages 1239-1242  
Year of Publication: 2008
ISBN:978-1-60558-102-6
Authors
Sarvjeet Singh  Purdue University, West Lafayette, IN, USA
Chris Mayfield  Purdue University, West Lafayette, IN, USA
Sagar Mittal  Purdue University, West Lafayette, IN, USA
Sunil Prabhakar  Purdue University, West Lafayette, IN, USA
Susanne Hambrusch  Purdue University, West Lafayette, IN, USA
Rahul Shah  Purdue University, West Lafayette, IN, USA
Sponsors
ACM: Association for Computing Machinery
SIGMOD: ACM Special Interest Group on Management of Data
Publisher
ACM  New York, NY, USA
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ABSTRACT

Orion is a state-of-the-art uncertain database management system with built-in support for probabilistic data as first class data types. In contrast to other uncertain databases, Orion supports both attribute and tuple uncertainty with arbitrary correlations. This enables the database engine to handle both discrete and continuous pdfs in a natural and accurate manner. The underlying model is closed under the basic relational operators and is consistent with Possible Worlds Semantics. We demonstrate how Orion simplifies the design and enhances the capabilities of two example applications: managing sensor data (continuous uncertainty) and inferring missing values (discrete uncertainty).


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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J. E. Conway. PL/R - R Procedural Language for PostgreSQL. http://www.joeconway.com/plr/, 2008.
 
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S. Singh, C. Mayfield, S. Prabhakar, R. Shah, and S. Hambrusch. Indexing Uncertain Categorical Data. In IEEE 23rd Intl. Conference on Data Engineering, 2006.
 
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S. Singh, C. Mayfield, R. Shah, S. Prabhakar, and S. Hambrusch. Query Selectivity Estimation for Uncertain Data. In 20th Intl. Conf. on Scientific and Statistical Database Management, 2008.
 
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S. Singh, C. Mayfield, R. Shah, S. Prabhakar, S. Hambrusch, J. Neville, and R. Cheng. Database Support for Probabilistic Attributes and Tuples. In IEEE 24th Intl. Conference on Data Engineering, 2008.


Collaborative Colleagues:
Sarvjeet Singh: colleagues
Chris Mayfield: colleagues
Sagar Mittal: colleagues
Sunil Prabhakar: colleagues
Susanne Hambrusch: colleagues
Rahul Shah: colleagues