Developing Digital Libraries

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II PGL DB CONFERENCE ORLANDO, June/2004
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Developing Digital Libraries Using Data
Warehousing And Data Mining Techniques
Cássia Blondet Baruque Rubens Nascimento Melo
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1) INTRODUCTION 2) DATA WAREHOUSE DL ??
DW 3) DWING AND DATA LIBRARYING DL
DWing ?? DLing 4) DATA MINING IN THE ETL/OLAP
PROCESSES DLing Dming ?? IDLing 5)
CONCLUSION
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1. INTRODUCTION

• IS THE INTERNET A DL?
• DL?
• DL DEVELOPMENT
• RELATED WORK

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1. INTRODUCTION

• IS THE INTERNET A DL?
• DL?
• DESENVOLVIMENTO DE DL
• TRABALHOS RELACIONADOS

• one of the biggest information repositories
  CHA95
• heterogeneous database
• structured, semistructured and nonstructured
  data
• difficult search and information retrieval
• is not a DL but may be its source

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1. INTRODUCTION

• IS THE INTERNET A DL?
• DL?
• DESENVOLVIMENTO DE DL
• TRABALHOS RELACIONADOS

• new research area (focus on organizing and
  promoting an easier access to documents on the
  Web) - polemic term SCHARTZ2001
• a large object collection, in diverse digital
  formats, persistent, managed and well organized
  in a Catalog accessed through the Web (this
  work focus on the textual format)

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1. INTRODUCTION

• A INTERNET É UMA DL?
• DL?
• DL DEVELOPMENT
• RELATED WORK

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1. INTRODUCTION

• Integrate the distributed Web-based multimedia
  content
• CORBA, mediators, agents
• Facilitate the information access
• semantic aids (ontology and data mining)

• A INTERNET É UMA DL?
• DL?
• DL DEVELOPMENT
• RELATED WORK

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1. INTRODUCTION

• Standford Digital Libraries Technology
• Illinois Digital Library Initiative Project
• Alexandria Digital Library Project
• University of Michigan Digital Library Project
• THERE IS NOT A COMPREHENSIVE SOLUTION TO
  ADDRESS THE MAIN ISSUES OF DIGITAL LIBRARY
  DEVELOPMENT

• A INTERNET É UMA DL?
• DL?
• DESENVOLVIMENTO DE DL
• RELATED WORK

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2. DATA WAREHOUSE

• DL ?? DW
• DL DWing ?? DLing
• DLing DMing ?? IDLing

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2. DATA WAREHOUSE

• DL ?? DW

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2. DATA WAREHOUSE

• DL ?? DW (Immon)
• DL DWing ?? DLing
• DLing Dming ?? IDLing

• DW is a database
• subject-oriented
• integrated
• non volatile
• variant in time
• to support management decisions

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2. DATA WAREHOUSE

• DL ?? DW (Immon)
• DL DWing ?? DLing
• DLing Dming ?? IDLing

• DL is a DW!
• subject-oriented
• integrated
• non volatile
• variant in time
• to support management decisions

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3. DWING AND DATA LIBRARYING

• DL ?? DW
• DL DWing ?? DLing
• DLing DMing ?? IDLing

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3. DWING AND DATA LIBRARYING

• DL DWing ?? DLing

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3. DWING AND DATA LIBRARYING

• DL DWing ?? DLing

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3. DWING AND DATA LIBRARYING
How to integrate complex data?
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3. DWING AND DATA LIBRARYING
How to facilitate access to information?
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4. DATA MINING IN THE ETL OLAP PROCESSES

• DL ?? DW
• DL DWing ?? DLing
• DLing Dming ?? IDLing

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4. DATA MINING IN THE ETL PROCESS

• DLing Dming ?? IDLing

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4. DATA MINING IN THE ETL PROCESS

• DLing DMing ?? IDLing

The documents are searched on the Web, filtered
and then selected. The Ontology is the entry
for this search and filtering processes.
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4. DATA MINING IN THE ETL PROCESS

• DLing DMing ?? IDLing

After being selected, the documents must be
catalogued. A data mining algorithm is applied
to the documents selected and then the Dublin
Core Metadata (bib and auth records) is
generated.
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4. DATA MINING IN THE ETL PROCESS

• DLing DMing ?? IDLing

Both library catalogue and library records are
loaded in the DW. Documents not authorized for
copying are not stored.
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4. DATA MINING IN THE OLAP PROCESS

• DLing DMing ?? IDLing

The users acesses patterns are analysed. This
analysis may cause the DL refreshing.
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5. CONCLUSION (Web ? LOs repositories)
Data Librirying
Learning Objects Data Libryring
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THE END