UMBC ebiquity
PhD Proposal : A Generic Data Model Pivot Query for Flexible, Adaptive, and Agile Systems
Tuesday, September 29, 2009, 10:15am - Tuesday, September 29, 2009, 11:30am
ITE 325 B
Fuesane Cheng's Ph.D. Preliminary Exam:
Abstract:
Generically modeled data structure has been widely used in the development of vertical application software systems and in the usage of XML and RDF for its flexibility, adaptability, and agility to support corporate business’ competition on speed to market for product and service development. However, generic data models require multiple self-joins on a single table with large volume of data, causing slow performance for Business intelligence (BI) applications On the other hand, traditional specific data models have faster performance but are not flexible, adaptive, or agile for speed to market. This research is to develop a novel generic data model with pivot query schemes which can maintain the flexibility, agility, and adaptability of generic data model and achieve the desired performance of a specific data model.
The goals for this research are to:
Develop a novel generic data model with pivot query schemes to maintain the flexibility, agility, and adaptability of generic data model and achieve the desired performance of a specific data model. Develop algorithms for generating static views and dynamic pivot SQL queries to improve the performance of generic data model approach. Develop parsing and dynamic pivot query generating algorithms to support XQuery and XPath data graph queries using the novel generic data model in any RDBMS. Develop approaches for implementing the COVER data structures and pivoting algorithms in native file management system with multi-core parallel processing.
Possible Contributions upon completion of this research:
A novel generic data model for Flexible, Adaptive, and Agile Systems. An Implementation of model and algorithms for Generic XML data store. A generic archival data store for any relational, hierarchical, or network DBMS database. A replacement of the core data storage management system of existing DBMS systems to provide Flexibility, Adaptability, and Agility for schema changes.
Committee:
Dr.Yelena Yesha (Chair)
Dr. Milton Halem
Dr. Tim Finin
Dr. Anupam Joshi
Abstract:
Generically modeled data structure has been widely used in the development of vertical application software systems and in the usage of XML and RDF for its flexibility, adaptability, and agility to support corporate business’ competition on speed to market for product and service development. However, generic data models require multiple self-joins on a single table with large volume of data, causing slow performance for Business intelligence (BI) applications On the other hand, traditional specific data models have faster performance but are not flexible, adaptive, or agile for speed to market. This research is to develop a novel generic data model with pivot query schemes which can maintain the flexibility, agility, and adaptability of generic data model and achieve the desired performance of a specific data model.
The goals for this research are to:
Develop a novel generic data model with pivot query schemes to maintain the flexibility, agility, and adaptability of generic data model and achieve the desired performance of a specific data model. Develop algorithms for generating static views and dynamic pivot SQL queries to improve the performance of generic data model approach. Develop parsing and dynamic pivot query generating algorithms to support XQuery and XPath data graph queries using the novel generic data model in any RDBMS. Develop approaches for implementing the COVER data structures and pivoting algorithms in native file management system with multi-core parallel processing.
Possible Contributions upon completion of this research:
A novel generic data model for Flexible, Adaptive, and Agile Systems. An Implementation of model and algorithms for Generic XML data store. A generic archival data store for any relational, hierarchical, or network DBMS database. A replacement of the core data storage management system of existing DBMS systems to provide Flexibility, Adaptability, and Agility for schema changes.
Committee:
Dr.Yelena Yesha (Chair)
Dr. Milton Halem
Dr. Tim Finin
Dr. Anupam Joshi