1 XML Based Networking Method for Connecting Distributed Anthropometric Databases 24 October 2006...

1

XML Based Networking Method for Connecting Distributed Anthropometric

Databases 24 October 2006

Huaining Cheng

Dr. Kathleen M. RobinetteHuman Effectiveness Directorate

Air Force Research Laboratory

Approved for public release; distribution is unlimited. AFRL-WS 06-2387 (Oct 13 2006)

2

Overview

• Integration issues

• Solution options with pros and cons

• WEAR short-term solutions

• WEAR long-term solution

• Summary

3

WEAR Group

• WEAR stands for World Engineering Anthropometry Resources

– A nonprofit organization based in France to promote sharing and using of its members’ anthropometry resources

– A dozen members located around world

– Members have huge collection of anthropometry survey data over large span of time

4

Integration Issues

• Data extraction and search

• Network accessibility

• Data representation

• Data quality

• Security

• Data analysis

• Data autonomy

• Financial and manpower constraints

5

Integration Solution Options

• Examine three possible integration solutions for the WEAR group integration

– Linked servers

– Data warehouse

– Service-oriented architecture (XML Web services)

• Examine how the solutions can address the above integration issues

• Envision potential anthropometry applications for the integrated WEAR

6

Linked Server Structure

• Use four-part name syntax in a query instead of only table name

– LinkedServerName

– DatabaseName

– Owner

– TableName

REF 1: “Configuring Linked Servers,” Microsoft MSDN Library, http://msdn.microsoft.com/library/default.asp?url=/library/en-us/adminsql/ad_1_server_4uuq.asp

7

Linked Server Pros & Cons

• Advantages – conceptually easy

– The ability to issue distributed queries and transactions on heterogeneous data sources across the enterprise

• Disadvantages – tight integration and direct access

– Maintenance and update nightmare

– No data autonomy

– Require direct access and reliable connection

8

Data Warehouse

• Main objective of data warehouse is business intelligence analysis of integrated data over time

– Business trend and variance analysis through OLAP (On-Line Analytical Processing)

– Data mining – automated discovery of implicit patterns and interesting knowledge hidden in the large amounts of data

9

Data Warehouses

• Characteristics of data warehouse

– Specialized database built on top of operational databases.

– Integration process through ETL (Extract, Transform, and Load)

– Optimized for over time data analysis

– Highly normalized structure

10

Anthropometry Star Schema

• Anthropometry database application of star schema

– Find groups of anthropometry measurements as biometrics identifier

Birth_Place_Key

Ethnicity_Key

Gender_Key

Age_Key

Measurement_1

Measurement_2

…

Landmark_1

Landmark_2

…

Measurement Fact

Birth_Place_Key

City

Province_or_State

Country

Geographical_Region

Birth Place Dimension

Ethnicity_Key

Ethnicity_Name

Ethnicity_Description

Ethnicity Dimension

Gender_Key

Gender

Gender Dimension

Age_Key

Starting_Age

Ending_Age

Age Dimension

Birth_Place_Key

Ethnicity_Key

Gender_Key

Age_Key

Measurement_1

Measurement_2

…

Landmark_1

Landmark_2

…

Measurement Fact

Birth_Place_Key

Ethnicity_Key

Gender_Key

Age_Key

Measurement_1

Measurement_2

…

Landmark_1

Landmark_2

…

Measurement Fact

Birth_Place_Key

City

Province_or_State

Country

Geographical_Region


Ethnicity_Key

Ethnicity_Name


Ethnicity Dimension

Ethnicity_Key

Ethnicity_Name


Ethnicity Dimension

Gender_Key

Gender

Gender Dimension

Gender_Key

Gender

Gender Dimension

Age_Key

Starting_Age

Ending_Age

Age Dimension

Age_Key

Starting_Age

Ending_Age

Age Dimension

11

Data Warehouse Pros & Cons

• Advantages – strong analytical capability

– A platform for many potential anthropometry applications of OLAP and data mining

• Disadvantages – tight integration and high cost

– Difficult to build ETL processes with various systems platforms and database structures as well as different locales

– Lack of data autonomy

12

Web Service Architecture

• Web service architecture adheres to the principles of service-orientation

– Services are loosely coupled, autonomous, stateless, and discoverable.

• Consists of three basic types of entities

– Service requestor, service provider, and service registry

– Communicate through TCP/IP

13

WEAR Application of Web Services

• Member 1 requests survey data & shape descriptors

Service Registry

Member 2

Italy Survey

Member 3

Netherland Survey

Member 4

Shape Descriptor Tool

Member 1

US Survey

Publish WSDL

Publish WSDL

Publish WSDL

Publish WSDL

Discover and Retrieve WSDL


SOAP Message

Request Survey

SOAP Message Return Survey Data

SO

AP

Mes

sage

-R

eque

st S

urve

y

SO

AP

Mes

sage

R

etur

n S

urve

y D

ata

SOAP Message - Request Calculation of Shape Descriptor and Data

SOAP Message - Return Shape Descriptor & Data

2

3

4

1

5

6

4

5Service RegistryService Registry

Member 2

Italy Survey

Member 3

Netherland Survey

Member 4


Member 1

US Survey

Publish WSDL

Publish WSDL

Publish WSDL

Publish WSDL



SOAP Message

Request Survey


SO

AP

Mes

sage

-R

eque

st S

urve

y

SO

AP

Mes

sage

R

etur

n S

urve

y D

ata



22

33

44

11

55

66

44

55

14

Loosely Coupled Integration

• XML Web service architecture is a loosely coupled integration

– Integration is done through the service contract (WSDL) instead of open connection

– Work is requested/delivered as payloads in the SOAP messages

– Messaging mechanism brings

• Autonomy

• Statelessness

15

Web Services Pros & Cons

• Advantages – autonomy and scalability

– Solve the problems that are difficult to handle by a tight integration

• Disadvantages – security and performance

– Challenge in performing and propagating user authentication and authorization

– XML documents are slow to create and process

– Evolving standards and specifications

16

WEAR Integration ObjectivesShort-Term

• Real world – two types of integrations

– Enterprise systems integration

– Business to business (B2B) integration

• Short-term WEAR integration objectives

– Integrate and share anthropometry survey data automatically

– WEAR members maintain and control independently their databases and existing web application

17

WEAR Integration Solution Short-Term

• WEAR has to be treated as a federation

• Web service architecture is inherently federated because of its loosely coupled nature

– Best solution to make the WEAR integration satisfy the short-term objectives

• Universal anthropometry data sets – XML

• Autonomous

18

WEAR Integration SolutionImplementation Issues

• Limit services to data sets only without RPC (remote procedure call)

• Real-time performance is not a concern

• Use restricted UDDI registry to increase security

• Implement user authentication using X509 digital client certificate

• Implement user authorization through SOAP header

19

WEAR Integration Objectives Long-Term

• WEAR integration long-term objectives

– Build analytical models to produce anthropometry solution toolkits

– Offer these toolkits as Web services accessible by the public and special industry groups

20

WEAR Hybrid Web Service / Data Mart Model

Service Registry

Member 2

Italy Survey

Member 3

Netherland Survey

Member 4


Member 1

US Survey

Publish WSDL

Publish WSDL

Publish WSDL

Publish WSDL



SOAP Message

Request Survey


SO

AP

Mes

sage

-R

eque

st S

urve

y

SO

AP

Mes

sage

R

etur

n S

urve

y D

ata



2

3

4

1

5

6

4


Member 2

Italy Survey

Member 3

Netherland Survey

Member 4


Member 1

US Survey

Publish WSDL

Publish WSDL

Publish WSDL

Publish WSDL



SOAP Message

Request Survey


SO

AP

Mes

sage

-R

eque

st S

urve

y

SO

AP

Mes

sage

R

etur

n S

urve

y D

ata



22

33

44

11

55

66

44

55

Birth_Place_Key

Ethnicity_Key

Gender_Key

Age_Key

Measurement_1

Measurement_2

…

Landmark_1

Landmark_2

…

Measurement Fact

Birth_Place_Key

City

Province_or_State

Country

Geographical_Region


Ethnicity_Key

Ethnicity_Name


Ethnicity Dimension

Gender_Key

Gender

Gender Dimension

Age_Key

Starting_Age

Ending_Age

Age Dimension

Birth_Place_Key

Ethnicity_Key

Gender_Key

Age_Key

Measurement_1

Measurement_2

…

Landmark_1

Landmark_2

…

Measurement Fact

Birth_Place_Key

Ethnicity_Key

Gender_Key

Age_Key

Measurement_1

Measurement_2

…

Landmark_1

Landmark_2

…

Measurement Fact

Birth_Place_Key

City

Province_or_State

Country

Geographical_Region


Ethnicity_Key

Ethnicity_Name


Ethnicity Dimension

Ethnicity_Key

Ethnicity_Name


Ethnicity Dimension

Gender_Key

Gender

Gender Dimension

Gender_Key

Gender

Gender Dimension

Age_Key

Starting_Age

Ending_Age

Age Dimension

Age_Key

Starting_Age

Ending_Age

Age Dimension

Member A (Data Marts)


Data Feeds

(SOAP Message)

External Web Service Client

Public UDDI Registry

Publish WSDL


SOAP Message Request Datasets/Toolkits

SOAP Message Return Solutions

Replicate public accessible web services registration

SO

AP

Mes

sage

R

eque

st D

atas

ets/

Too

lkits

SO

AP

Mes

sage

R

etur

n S

olut

ions

Service Registry

Member 2

Italy Survey

Member 3

Netherland Survey

Member 4


Member 1

US Survey

Publish WSDL

Publish WSDL

Publish WSDL

Publish WSDL



SOAP Message

Request Survey


SO

AP

Mes

sage

-R

eque

st S

urve

y

SO

AP

Mes

sage

R

etur

n S

urve

y D

ata



2

3

4

1

5

6

4


Member 2

Italy Survey

Member 3

Netherland Survey

Member 4


Member 1

US Survey

Publish WSDL

Publish WSDL

Publish WSDL

Publish WSDL



SOAP Message

Request Survey


SO

AP

Mes

sage

-R

eque

st S

urve

y

SO

AP

Mes

sage

R

etur

n S

urve

y D

ata



22

33

44

11

55

66

44

55

Birth_Place_Key

Ethnicity_Key

Gender_Key

Age_Key

Measurement_1

Measurement_2

…

Landmark_1

Landmark_2

…

Measurement Fact

Birth_Place_Key

City

Province_or_State

Country

Geographical_Region


Ethnicity_Key

Ethnicity_Name


Ethnicity Dimension

Gender_Key

Gender

Gender Dimension

Age_Key

Starting_Age

Ending_Age

Age Dimension

Birth_Place_Key

Ethnicity_Key

Gender_Key

Age_Key

Measurement_1

Measurement_2

…

Landmark_1

Landmark_2

…

Measurement Fact

Birth_Place_Key

Ethnicity_Key

Gender_Key

Age_Key

Measurement_1

Measurement_2

…

Landmark_1

Landmark_2

…

Measurement Fact

Birth_Place_Key

City

Province_or_State

Country

Geographical_Region


Ethnicity_Key

Ethnicity_Name


Ethnicity Dimension

Ethnicity_Key

Ethnicity_Name


Ethnicity Dimension

Gender_Key

Gender

Gender Dimension

Gender_Key

Gender

Gender Dimension

Age_Key

Starting_Age

Ending_Age

Age Dimension

Age_Key

Starting_Age

Ending_Age

Age Dimension


Birth_Place_Key

Ethnicity_Key

Gender_Key

Age_Key

Measurement_1

Measurement_2

…

Landmark_1

Landmark_2

…

Measurement Fact

Birth_Place_Key

City

Province_or_State

Country

Geographical_Region


Ethnicity_Key

Ethnicity_Name


Ethnicity Dimension

Gender_Key

Gender

Gender Dimension

Age_Key

Starting_Age

Ending_Age

Age Dimension

Birth_Place_Key

Ethnicity_Key

Gender_Key

Age_Key

Measurement_1

Measurement_2

…

Landmark_1

Landmark_2

…

Measurement Fact

Birth_Place_Key

Ethnicity_Key

Gender_Key

Age_Key

Measurement_1

Measurement_2

…

Landmark_1

Landmark_2

…

Measurement Fact

Birth_Place_Key

City

Province_or_State

Country

Geographical_Region


Ethnicity_Key

Ethnicity_Name


Ethnicity Dimension

Ethnicity_Key

Ethnicity_Name


Ethnicity Dimension

Gender_Key

Gender

Gender Dimension

Gender_Key

Gender

Gender Dimension

Age_Key

Starting_Age

Ending_Age

Age Dimension

Age_Key

Starting_Age

Ending_Age

Age Dimension



Data Feeds

(SOAP Message)

External Web Service Client



Publish WSDL


SOAP Message Request Datasets/Toolkits

SOAP Message Return Solutions

Replicate public accessible web services registration

SO

AP

Mes

sage

R

eque

st D

atas

ets/

Too

lkits

SO

AP

Mes

sage

R

etur

n S

olut

ions

21

Conclusions

• WEAR integration is a type of federated integration

• XML Web service is the best solution due to its loosely coupling nature and service orientation

• Data marts have great potential for discovery of anthropometry data

• Hybrid Web service/data mart model is a solution to combine analytical models and XML web services

• XML is the foundation of the entire integration solution

1 XML Based Networking Method for Connecting Distributed Anthropometric Databases 24 October 2006...

Documents

Transcript of 1 XML Based Networking Method for Connecting Distributed Anthropometric Databases 24 October 2006...