Download Semantic Database Presentation - Florida International University

Semantic Access: Semantic Interface for
Querying Databases
Naphtali Rishe, Jun Yuan, Rukshan Athauda, Xiaoling Lu,
Xiaobin Ma, Alexander Vaschillo, Artyom Shaposhnikov,
Dmitry Vasilevsky, Shu-Ching Chen
High Performance Database Research Center
School of Computer Science
Florida International University
Demonstration Outline
• Semantic Binary Object-Oriented Database
System (Sem-ODB) and Semantic SQL.
– Sem-ODB Engine.
– Semantic SQL Interpreter.
– ODBC Driver for Sem-ODB.
• Semantic Wrapper over Relational Databases.
– Access Semantic Wrapper via native APIs
– Access Semantic Wrapper via ODBC.
• CORBA Compliant Components.
System Architecture
QUERY
COORDINATOR
catalog of
database
schemas
User’s Semantic
SQL queries
Query Dispatcher
queries / query results
CORBA
meta-data
RELATIONAL
SITE
Semantic SQL
Semantic Schema
Semantic SQL
SEMANTIC
SITE
Semantic Schema
Translator
KDBTool
SDB-SQL Engine
Knowledge
Base
ODBC
Native C++/Java API
Commercial
RDBMS
DBA
Semantic
Database
Engine
Part I: SemODB and Semantic SQL
• More expressive data model
• Directly supports conceptual data model of
the enterprise
• Shorter application design and
programming cycle
• Empowers end-users to pose complex ad
hoc decision support queries
Semantic Data Model(Sem-ODM)
Benefits
Semantic Views over Relational Schemas
– Higher level data model
– Semantic view mirrors real world
– Flexible classification of objects
– Complex relations made simple: arbitrary
relationships
– Semantically-Enhanced Object-Relational
– Information in its Natural Form
Semantic Data Model(Sem-ODM)
Benefits (Cont.)
Semantic-Views
RDBMS
•
•
•
•
•
•
•
•
Data is described at conceptual
level.
Meaning of Information is Stored
Relationships Between Categories
Easier to formulate query
 Any Relationship CAN be
queried.
 Joins are NOT required to be
defined explicitly.
Data is described at logical level.
Meaning of Information is Lost
Relationships not Supported
Complex queries have to be preprogrammed
 “Joins” are required to be
defined explicitly.
Semantic Data Model
Benefits (cond.): Example schemas
Semantic View:
COMPANY
name: String m:m
address: String m:m
manufactures
(m:m)
PRODUCT
specification: String m:m
weight_kg: Number m:m
Equivalent Relational Schema:
COMPANY
CID_key: string
COMPANY_NAME
CID_in_key: string
Name_in_key: string
MANUFACTURES
CID_in_key: string
PID_in_key: string
PRODUCT_SPEC
PID_in_key: string
Spec_in_key: string
PRODUCT
PID_key: string
COMPANY_ADDRESS
CID_in_key: string
Address_in_key: string
PRODUCT_WEIGHT
PID_in_key: string
WeightKG_in_key: number
Semantic SQL
Features
• Semantic SQL
– Querying data at conceptual level
– Easier query facility
– ODBC/SQL Compliance
Semantic SQL
Benefits
• Easier query facility (i.e. much shorter
queries)
• Do not require to specify joins with the
existence of relations in the semantic
schem
Semantic SQL
Benefits (cond.): Example query
PROJECT
name: String key
description: String
comments: String
starting-date: Date
ending-date:Date
Semantic View
located at
(m:1)
serves
(m:m)
runs
(m:m)
ORGANIZATION
is-part-of m:m:
name: String key
description: String
IMAGE
image: Raw
subject: String
direction-of-view: 0..360
comments: String
type: Char(3)
PHYSICAL
OBSERVATION
STATION
belongs to
(m:m)
LOCATION
north-UTM: Number key/2
east-UTM: Number key/2
elevation-ft: Number
description: String
is-part-of m:1:
structure: String
comments: String
housing: String
by
(m:1)
OBSERVATION
time: Date-time
comment: String
FIXED STATION
platform-height-ft: 0..50.000
MEASUREMEMENT
TYPE
name: String key
measurement-unit: String
upper-limit: Number
lower-limit: Number
of
(m:1)
MEASUREMENT
value: Number
Semantic SQL
Benefits (cond.): Example query
RELATIONAL SCHEMA
Semantic SQL
Benefits (cond.): Example query
“GIVE ME ALL OF THE
OBSERVATIONS, WITH
ALL OF THEIR
ATTRIBUTES, SINCE
JANUARY 1, 1993, AND
THE LOCATION OF THE
OBSERVING STATIONS”
SQL for RDBMS
Semantic SQL Query:
Select OBSERVATION__, of__,
LOCATION
from
OBSERVATION where time >
'1993/01'

( 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 MEASUREMENTTYPE, 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))
Sem-ODB Architecture
Database
Applications
USERS
Existing Tools
(MS QBE)
Semantic SQL
Interpreter
Semantic Schema
C++/Java API
Control
Server
ODBC
Driver
Semantic Database Engine
Part II: Semantic Wrapper over
Relational Databases
Definition
AN OPEN MIDDLEWARE SYSTEM THAT PROVIDES
SEMANTIC VIEWS AGAINST LEGACY RELATIONAL
DATABASES
Semantic Wrapper
High-level Architectural View
Semantic Schemas/
Semantic SQL
New Applications
Semantic Wrapper
ODBC
Native DBMS
interfaces
Commercial
Relational
DBMS
(e.g. Microsoft Access,
Microsoft SQL Server, Oracle, ... )
Legacy Applications
Features of Semantic Wrapper
• Provides Semantic Binary Object-oriented Data
Model for Relational Databases
• Provides a powerful query language: Semantic
SQL
• Database autonomy
• Can function as a stand-alone application and/or
be plugged into a heterogeneous multi-database
system
• Portability
Part III: CORBA Compliant Components
• CORBA compliant components
– Sem-ODB
– Semantic Wrapper.
• Platform and network level heterogeneity
is resolved by using CORBA architecture.
• Common CORBA IDL provides semantic
access to both relational and semantic
databases.
• Sem-ODM view against each data source.
Summary
• Sem-ODM: an expressive data model.
• Sem-ODB: a robust database engine.
• Semantic SQL: an intelligent and easier query
language.
• Semantic Wrapper: a portable, autonomous,
stand-alone/ multi-database component tool for
legacy databases.
• Semantic Access via ODBC.
• CORBA compliant components.