Final Words

Jian-hua Yeh ( 葉建華 )

真理大學資訊科學系助理教授au4290@email.au.edu.tw

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Outline

• What have we learned so far?

• What could a digital library really do?

• More selected extensions

• Final words

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What have we learned so far?

• Digital content industry overview

• Digital library case studies

• Digital repository system

• Digital library related technologies

• Knowledge management issues

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Digital Content Industry Overview

• Government project: e-Taiwan

• NSC-DMP

• NSC-NDAP

• CCA-NRCH

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NSC Projects

• NSC Digital Museum Project (DMP)– 1998 – 2002

– Pilot projects & digital museum projects

• NSC National Digital Archives Program (NDAP)– 2002 -- 2006

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NSC DMP

主題計畫• 語文藝術類 ﹕ 4 件• 人文社會類 ﹕ 12 件• 自然生態類 ﹕ 5 件• 生活醫療類： 4 件• 建築與地理類﹕ 3 件

技術支援計畫• 人文與自然資源地圖• 搜文解字─語文知識網路• 資源組織與檢索之規範• 系統評估• 數位典藏系統先導計畫• 數位博物館影像版權資訊植入技術與

軟體之開發

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NSC NDAP

• Combination of three major NSC projects– Digital museum project

– Digital archive project

– International digital library project with NSF (US)

• As a basis of e-Taiwan project

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NSC NDAP (cont.)

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CCA NRCH

• 文化藝術活動資訊網路

提昇政府文化服務 及國際行銷• 數位文化加值計畫• 故宮文物數位博物館建置 與加值應用計畫

創造文化產業經濟

加強文化藝術資源數位化 與應用• 國家文化資料庫建置計畫• 國家文化藝術人才庫建置計畫• 文化藝術主題知識庫• 文化藝術數位資源應用與呈現計畫

強化文化機構基礎建設‧ 文化藝術機構基礎建設

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Digital Archive Applications

原有典藏 數位化檔案群

文化產業加值產業內容產業軟體產業所有資訊相關之產業

教育與學習研究與發展資訊共享、公共資訊系統創造力、生產力、競爭力以及生活品質的提升

政府各部會民眾

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Digital Library Case Studies

• NTU digital library/museum project

– Content generation: centralized

– Information management: centralized

– Information access: centralized

• NSC NDAP project

– Content generation: distributed

– Information management: distributed

– Information access: distributed

• CCA NRCH project

– Content generation: distributed

– Information management: centralized & distributed

– Information access: centralized

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Usage Model

• Centralized information access– Centralized information-lookup only

• Catalog (meta-information) centralized

• NDAP union catalog project: OAI-based

– Centralized information-lookup & content access• Catalog & content centralized

• NRCH digital archive project

• Distributed information access– Distributed information lookup

• OpenURL, Z39.50

– Distributed content access• DOI

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Related Technologies

• XML/DTD

• Metadata description

• Multimedia processing

• You are already familiar with this from your term project!

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Knowledge Management Issue

• Turning data into information– Resource organization

• convert digital content into useful information

• Meta-information

• Turning information into knowledge– Information organization

• Semantics generation: ontology creation

• Meta-meta-information

• Classification problem

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The Problem

• With the increasing complexity of our systems and our IT needs, we need to go to human level interaction

• We need to maximize the amount of Semantics we can utilize

• From data and information level, we need to go to human semantic level interaction

DATA Information Knowledge

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Noise Human Meaning

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Vise maneuver

• And represented semantics means multiple represented semantics, requiring semantic integration

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Interpretation Continuum

Simple Metadata: XML

Human interpreted Computer interpreted

DATA KNOWLEDGE• Relatively unstructured• Random

• Very structured• Logical

Moving to the right depends on increasing automated semantic interpretation

• Info retrieval

• Web search

• Text summarization• Content extraction• Topic maps

• Reasoning services

• Ontology Induction

...Display raw documents;All interpretation done by humans

Find and correlate patterns in raw docs; display matches only

Store and connect patterns via conceptual model (i.e,. an ontology); link to docs to aid retrieval

Automatically acquire concepts; evolve ontologies into domain theories; link to institution repositories (e.g., MII)

Richer Metadata: RDF/S

Very Rich Metadata: DAML+OIL

Automatically span domain theories and institution repositories; inter-operate with fully interpreting computer

Interpretation Continuum

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Complexity of Ontology

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OWL: Web Ontology Language

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XTM: Topic Maps Language

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Semantic Analysis

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Categorization & Visualization

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Key Persons

• Information level– Content experts

– Computer technologists

– Library/Information experts

• Knowledge level– Content experts

– Computer technologists

– Cognitive scientists

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What could a digital library really do?

• Preservation

• Education

• Research

• Development– Application

– Innovation

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Selected Digital Library Extensions• Presentation

– RIA: rich internet application• Flash-based presentation• AJAX-based presentation• AFlax: combining Flash and AJAX technologies

– Visualization

• Service– Web service application

• UDDI

– Knowledge service• Standard transformation: XTM, OWL, SKOS, etc.

• Extension– Education: SCORM

• Archive/library content to learning content

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AJAX

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Conclusion