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Sem-ODB: Semantic Object DBMS

Sem-ODB: Semantic Object DBMS. SEMANTIC DATABASE. FIU High Performance Database Research Center Dr. Naphtali Rishe, Director. SEMANTIC DATABASE PRESENTATION OUTLINE. Introduction DEFINITION Features Benefits Market Demonstration Summary. SEMANTIC DATABASE DEFINITION.

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Sem-ODB: Semantic Object DBMS

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  1. Sem-ODB: Semantic Object DBMS SEMANTIC DATABASE FIU High Performance Database Research Center Dr. Naphtali Rishe, Director

  2. SEMANTIC DATABASEPRESENTATION OUTLINE • Introduction • DEFINITION • Features • Benefits • Market • Demonstration • Summary

  3. SEMANTIC DATABASEDEFINITION THE FLEXIBLE DATABASE MANAGEMENT SYSTEM THAT STORES THE MEANING OF INFORMATION AS FACTS ABOUT OBJECTS.

  4. SEMANTIC DATABASEDEFINITION • Semantic Binary Model • Object-Oriented Features • Semantically-Enhanced Object-Relational • A Collection of Facts • Arbitrary Relationships • Storing the Inherent Meaning of Information • Information in its Natural Form • Information Handling System 

  5. SEM-ODB Meaning of Information is Stored Relationship Between Classes No Restriction on Data Type/Size Any Query Can be Run Ad Hoc Any Relation Can be Viewed No Keys are Required RDBMS Meaning of Information is Lost Relationships not Supported Restricted Data Type and Sizes Most Queries Have to be Predicted Expensive “Joins” are Needed Keys are Required and are Static SEMANTIC DATABASEDEFINITION

  6. SEMANTIC DATABASEPRESENTATION OUTLINE • Introduction • Definition • FEATURES • Benefits • Market • Demonstration • Summary

  7. SEMANTIC DATABASEFEATURES • Semantic Database Design • Optimal Processing Algorithms • Efficient Storage Techniques • Application Schema Design Methodology • ODBC/SQL Compliance • Semantic SQL • Internet/WEB Enabled 

  8. SEMANTIC DATABASEFEATURES • Exceptional usability and flexibility • Shorter application design and programming cycle • Provides user control via an intuitive structure of information • Empowers end-users to pose complex ad hoc decision support queries • Superior efficiency-Highest level of optimization • Massive reduction in storage size for large applications, such as Data Warehouses • Directly supports conceptual data model of the enterprise • Internet-integrated

  9. Semantic view mirrors real world Complex relations made simple Queries made simple, very short Shorter application programs No restrictions on data Very efficient full indexing Full indexing -- indexing on every attribute and relationship Flexible classification of objects Lazy queries Compaction of sparse data No keys are needed Automatic consistency of database Better concurrency control Multi-processor parallelism Interoperability (ODBC, SQL) No tuning required Benchmarks SEMANTIC DATABASEFEATURES

  10. SEMANTIC DATABASEPRESENTATION OUTLINE • Introduction • Definition • Features • BENEFITS • Market • Demonstration • Summary

  11. SEMANTIC DATABASEBENEFITS • Strategic/Enterprise • Performance • Architecture • Development • Users

  12. SEMANTIC DATABASEBENEFITS-Strategic 1 Source: IDC, 4/98

  13. SEMANTIC DATABASEBENEFITS-Strategic 1 Source: IDC, 4/98

  14. SEMANTIC DATABASEBENEFITS-Strategic 1 Source: IDC, 4/98

  15. 2 Source: Arbor Sotware (Essbase), 4/98 SEMANTIC DATABASEBENEFITS-Strategic

  16. SEMANTIC DATABASEBENEFITS-Strategic 2 Source: Arbor Software (Essbase), 4/98

  17. SEMANTIC DATABASEBENEFITS-Performance • SB2 Benchmark • Cold Times • Times are in Seconds • 100,000 Customers

  18. SEMANTIC DATABASEBENEFITS-Performance • SB2 Benchmark • Cold Times • Times are in Seconds • 500,000 Customers

  19. SEMANTIC DATABASEBENEFITS-Performance • SB2 Benchmark • Hot Times • Times are in Seconds • 100,000 Customers

  20. SEMANTIC DATABASEBENEFITS-Performance • SB2 Benchmark • Hot Times • Times are in Seconds • 500,000 Customers

  21. SEMANTIC DATABASEBENEFITS-Performance • TPC-D Benchmark • 1GB • Times are in Seconds • Identical Hardware • Published Results for DB2

  22. COMPANYname: String m:maddress: String m:m PRODUCTspecification: String m:mweight_kg: Number m:m manufactures (m:m) SEMANTIC DATABASEBENEFITS-Architecture Semantic Database Facts Subschema: Facts: Fact types: aC aRy aRv 1. object1 COMPANY2. object1 NAME ‘IBM’3. object1 MANUFACTURES object24. object1 MANUFACTURES object35. object2 PRODUCT6. object2 SPECIFICATION ‘Thinkpad’7. object3 PRODUCT8. object3 SPECIFICATION ‘TrackPoint’

  23. Basic Queries: aC Verify the fact aC.aRy Verify the fact aRy.a? Find all the categories to which a belongs.?C Find all objects of category C.aR? Find all y such that aRy.?Ra Find all abstract objects x such that xRa.a?+a??+??a Retrieve all the immediate information about an abstract object.?Rv Find all x such that xRv.?R[v1,v2] Find all objects x and v such that xRv and v1 <v < v2 SEMANTIC DATABASEBENEFITS-Architecture Access Level 1 disk access per basic query 

  24. SEMANTIC DATABASEBENEFITS-Architecture Update Transactions Accumulated Transaction: (V,D,I) New_database=old_database - the-set-of-facts-to-be-Deleted + + the-set-of-facts-to-be-Inserted V= queries to be verified

  25. SEMANTIC DATABASEBENEFITS-Architecture Direct and Inverted Facts Direct: Inverted: object1 COMPANYobject1 NAME ‘IBM’object1 MANUFACTURES object2object1 MANUFACTURES object3object2 PRODUCTobject2 SPECIFICATION ‘Thinkpad’object3 PRODUCTobject3 SPECIFICATION ‘TrackPoint’ COMPANY invobject1NAME inv ‘IBM’ object1 object2 MANUFACTURES inv object1object3 MANUFACTURES inv object1PRODUCT invobject2SPECIFICATION inv ‘Thinkpad’ object2PRODUCT invobject3SPECIFICATIONinv ‘TrackPoint’ object3

  26. SEMANTIC DATABASEBENEFITS-Architecture Sorted Facts Sorted: COMPANY invobject1NAME inv ‘IBM’ object1 PRODUCT invobject2PRODUCT invobject3SPECIFICATION inv ‘Thinkpad’ object2SPECIFICATIONinv ‘TrackPoint’ object3object1 COMPANYobject1 MANUFACTURES object2object1 MANUFACTURES object3object1 NAME ‘IBM’object2 PRODUCTobject2 MANUFACTURES inv object1object2 SPECIFICATION ‘Thinkpad’object3 PRODUCTobject3 SPECIFICATION ‘TrackPoint’object3 MANUFACTURES inv object1

  27. SEMANTIC DATABASEBENEFITS-Development • Much Shorter Application Development • Inherent Data Modeling in the Sem-ODB • Minimal Database “Design” - Sem-ODB is as Users View Their Needs • Relations Between Classes/Objects Don’t Have to be Programmed • Considerably Smaller & Simpler SQL Statements 

  28. LOCATIONnorth-UTM: Number key/2east-UTM: Number key/2elevation-ft: Numberdescription: String PROJECTname: String keydescription: Stringcomments: Stringstarting-date: Dateending-date:Date SEMANTIC DATABASEBENEFITS-Development SCHEMA located at(m:1) serves(m:m) runs(m:m) FIXED STATIONplatform-height-ft: 0..50.000 PHYSICAL OBSERVATIONSTATIONis-part-of m:1:structure: Stringcomments: Stringhousing: String ORGANIZATIONis-part-of m:m:name: String keydescription: String belongs to(m:m) MEASUREMEMENTTYPEname: String keymeasurement-unit: Stringupper-limit: Numberlower-limit: Number IMAGEimage: Rawsubject: Stringdirection-of-view: 0..360comments: Stringtype: Char(3) by(m:1) OBSERVATIONtime: Date-timecomment: String of(m:1) MEASUREMENTvalue: Number

  29. { select description, LOCATION.north-UTM-in-key, LOCATION.east-UTM-in-key from ORGANIZATION, LOCATION where exists ( select * from FIXED-STATION where exists ( select * from PHYSICAL-OBSERVATION-STATION- BELONGS-TO-ORGANIZATION where name-key = organization-name-in-key and PHYSICAL-OBSERVATION-STATION- BELONGS-TO-ORGANIZATION. physical_observation-station-id-in-key = FIXED-STATION.physical-observation- station-id-key and located-at--north-UTM = north-UTM-in-key and located-at--east-UTM = east-UTM-in-key ) ) SQL for RDBMS SQL for SDB Select description, LOCATION from ORGANIZATION SEMANTIC DATABASEBENEFITS-Development “GIVE ME A DESCRIPTION OF ALL ORGANIZATIONS AND THE LOCATION OF THEIR FIXED STATIONS” 

  30. { ( select MEASUREMENT-TYPE.*, LOCATION.north-UTM-in-key, LOCATION.east-UTM-in-key, MEASUREMENT.*, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL from MEASUREMENT-TYPE, LOCATION, MEASUREMENT where time > '1993/01' and exists ( select * from FIXED-STATION where by-physical-observation-station-id = physical-observation-station-id-key and located-at--north-UTM = north-UTM-in-key and located-at-east-UTM = east-UTM-in-key and of--name = name-key)) union ( select MEASUREMENT-TYPE.*, NULL, NULL, MEASUREMENT.*, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL from MEASUREMENT-TYPE, MEASUREMENT where time > '1993/01' and not exists ( select * from FIXED-STATION where by-physical-observation-station-id = physical-observation-station-id-key and of-name = name-key)) union ( select NULL, NULL, NULL, NULL, LOCATION.north-UTM-in-key, LOCATION.east-UTM-in-key, NULL, NULL, NULL, NULL, NULL, NULL, IMAGE.* from LOCATION, IMAGE where time > '1993/01' and exists ( select * from FIXED-STATION where by-physical-observation-station-id = physical-observation-station-id-key and located-at-north-UTM = north-UTM-in-key and located-at—east-UTM = east-UTM-in-key)) union ( select NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, IMAGE.* from IMAGE where time > '1993/01' and not exists ( select * from FIXED‑STATION where by--physical-observation-station-id = physical-observation-station-id-key)) SQL for RDBMS SQL for SDB Select OBSERVATION__, of__, LOCATION from OBSERVATION where time > '1993/01' SEMANTIC DATABASEBENEFITS-Development “GIVE ME ALL OF THE OBSERVATIONS, WITH ALL OF THEIR ATTRIBUTES, SINCE JANUARY 1, 1993, AND THE LOCATION OF THE OBSERVING STATIONS” 

  31. SEMANTIC DATABASEPRESENTATION OUTLINE • Introduction • Definition • Features • Benefits • MARKET • Demonstration • Summary

  32. SEMANTIC DATABASEMARKET • DBMS Market • $12Billion - 2001 (RDBMS) • $2 Billion - 2001 (ODBMS) • OO-Tools $4Billion • DW/DSS $8Billion • Internet Market • $21-$32Billion • Tools, DBMS & Applications • Sem-ODB • DBMS, Tool, DSS & Internet READY SOURCES Corporate Financial Statements IDC Survey

  33. SEMANTIC DATABASEMARKET • Sem-ODB Applications: • Internet/WEB Data Access • Data Warehouse/DSS • Video/Audio/Spatial Data Storage • Vertical Applications • Geographic Information Systems • Visualization/Data Modeling • Knowledge Base

  34. SEMANTIC DATABASEPRESENTATION OUTLINE • Introduction • Definition • Features • Benefits • Market • DEMONSTRATION • Summary

  35. SEMANTIC DATABASEDEMONSTRATION • PROVEN APPLICATIONS: • Satellite Observations Databases • NASA’s EOS • 1TB+ per day • Everglades National Park Database • 300 Classes, 2,500 Attributes • 40 Years of Environmental Observations • TerraFly Edutainment • Control Systems • GIS

  36. SEMANTIC DATABASEDEMONSTRATION Visualization: GIS Database: Sem-ODB Size: 1 TB Contents: Landsat Multispectral, USGS Ortho Photography, Ozone Spatial Data, Factual data 

  37. SEMANTIC DATABASEPRESENTATION OUTLINE • Introduction • Definition • Features • Benefits • Market • Demonstration • SUMMARY

  38. SEMANTIC DATABASESUMMARY • Information • Knowledge Base • Real World • User Accessible • High Performance • Any Type of Data • Cost & Processing Reduction 

  39. SEMANTIC DATABASESUMMARY SEMANTIC DATABASE 

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