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Schema matching for Database Systems

Schema matching for Database Systems. Bhavik Doshi Chair: Prof. Rajendra K. Raj Reader: Dr. Carol Romanowski Department of Computer Science Rochester Institute of Technology. EMPID. Name. Salary. EMPID. Name. Salary. has. Employee. Position-type. Employee. SSN. Position. SSN.

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Schema matching for Database Systems

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  1. Schema matching for Database Systems Bhavik Doshi Chair: Prof. Rajendra K. Raj Reader: Dr. Carol Romanowski Department of Computer Science Rochester Institute of Technology

  2. EMPID Name Salary EMPID Name Salary has Employee Position-type Employee SSN Position SSN Position Schema Matching • Given: Source and Target schemas • Matching: Maps the source schema elements to target schema elements.

  3. Why Schema Matching? • First step of Data Integration • Upcoming field in Data management research because of its important role in Enterprise Information Integration. • Building data warehouses and marts • Manual approach is very laborious

  4. Motivation

  5. Syntactical Approach • Uses Syntax used for naming databases Elemental Level Approach ? Random Names

  6. Data value and Constraint based approach • Uses data values, data types, comparison of ranges. Instance based approach ? Data values not appropriate

  7. Hypothesis & Objective

  8. Hypothesis • Relying on a single technique for schema matching may not always succeed. • Each approach is implemented independently of the others and so the overall impact is not as effective. • Develop an integrated technique which is domain independent for oracle databases.

  9. Objective • Develop a generic integrated matching technique. • Implement two substantially different techniques • Kang et al. • Lingmei et al. • Transform steps of the above two algorithms and make use of additional techniques for better matching. • Testing the developed technique with (~30) relational datasets and then observing the results.

  10. Algorithms • Instance Based schema matching • Kang et al. • Element Level schema matching • Lingmei et al.

  11. Route to Success!! Probability Distribution Syntax Semantics Structure Kang’s Approach Lingmei’s Approach Instance Based Element Based Data Type and Range Integrated Approach

  12. Questions??

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