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題名：透過Google Scholar與Web of Science探究數位資產管理之智識結構
作者：林俊銘
作者(外文)：Chun-Min Lin
校院名稱：國立東華大學
系所名稱：企業管理學系
指導教授：許芳銘
學位類別：博士
出版日期：2015
主題關鍵詞：共詞分析；數位資產；智識結構；co-word analysis；digital stewardship；intellectual structure
原始連結：連回原系統網址new window
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數位資產管理(Digital Stewardship, DS)是近二十年來的重要議題。數位資產包括任何人造文物(artifact)的數位型式資料，不論是政府、公司機關、個人，都擁有數量愈來愈龐大的數位資產。這些資產必須有計劃地管理，才能確保可以長期使用。數位資產管理的困境，涉及資訊科技的快速變化，以及管理制度與資訊技術議題必須同時考量。以政府或機構之數位資產為例，需要保存的資料包括機關電子檔案(Electronic Record, ER)、各種主題的數位典藏(Digital Archive, DA)等，這些資料的類型包括文字以及各種多媒體格式，保存方式則使用不同的資料庫系統與作業系統，這些多樣的數位資產管理問題，演變為學術研究的重要議題。
若要了解特定學術領域的研究議題，探討該領域的智識結構(Intellectual Structure)是一個量化的研究方法。書目計量學提供了數種分析智識結構的工具，共詞分析(Co-Word Analysis)就是其中一種分析方法。特別是現在已有數位化的學術資料庫，可以提供共詞分析所需的大量資訊。現今最具代表性的學術資料庫以Web of Science (WoS)為主，後來發展的Google Scholar (GS)也提供了一個新的學術資料的收集方向，兩個資料庫扮演嚴謹與開放、專家判斷與演算法判斷兩種不同的學術資料收集策略。在不同的資料庫當中，如何收集共詞分析所需的文獻，作為分析的依據，歷年的書目計量學研究使用了幾種不同的方式，包括根據關鍵字查詢、或者根據主要期刊的收錄內容、或者兩者方式的混合等方式。本研究依此規劃四種不同的分析文獻之收集方式，分別為WoS的DS主要期刊、DS領域期刊搭配關鍵字、WoS搭配關鍵字、以及GS搭配關鍵字四種不同方式，分析結果之優劣可做為將來書目計量研究者之參考依據。
此外本研究探討數位資產管理相關領域的智識結構，以提供數位資產管理單位，以及數位資料或檔案管理之相關學術研究的參考。分析結果顯示數位資產管理的研究議題包括資訊系統與管理(Information system and management)、檔案與圖書館知識管理(Knowledge、Archive and Library)、病患與健康照護(Patient care and hearthcare)、政府與社區歷史(Government and community’s history)、標準化與基礎設施(Standard and framework)、資訊演算法(Algorithm)，以及醫藥記錄管理(Hospital and medical record)等。藉由這些主題分類，可協助研究者找出數位資產管理的研究議題類別。
Digital Stewardship (DS) is a critical issue in the last few decades. Digital assets include any artifacts in digital forms. Government agencies, companies and individuals possess massive digital assets that are rapidly growing in amount. These assets require appropriate and strategic management to ensure long-term accessibility. The difficulty of digital asset management lies mainly in the rapid changes of information technology (IT), yet related issues such as the administration systems and information techniques must be taken into consideration at the same time. In government agencies or organizations, digital assets that need to be preserved include Electronic Record (ER) and Digital Archive (DA) of various topics. Information containing in ER and DA is comprised of text and varied multimedia formats, and they may be preserved by different database systems and operating systems. Such diverse problems revolving around digital asset management have become significant issues for the academic research.
To learn about the intellectual structure of specific academic fields is a quantitative method to recognize the research issues of that field. Bibliometrics provides several tools for analyzing the intellectual structure, and co-word analysis is among one of them. Existing digitalized academic databases have provided enormous data for co-word analysis. The most representative academic database nowadays has been Web of Science (WoS) provided by Thomson Reuters. Later on, Google Scholar (GS) database developed by Google provides a new technique for collecting academic research data. WoS and GS databases employ different judgment rules and academic data collection strategies. WoS employs expert judgment is more rigorous in data collection, while GS uses algorithm judgement and is more open and diverse in data collection. Several different bibliometric methods have been applied to collect literature required for co-word analysis among assorted academic databases. These methods include queries by keywords, analyses of research paper contents collected from major journals, or a mixture of both ways. In this study, four different methods were adopted to collect literature for analysis: (1) locating major DS journals in WoS, (2) querying with keywords in ER- and DS-related journals, (3) querying with keywords in WoS, and (4) querying with keywords in GS, respectively. The analysis of the pros and cons of these four methods can be used as a reference for future researchers using bibliometric measures. In addition, this study investigated the intellectual structure of digital asset management and its related fields.
The outcomes of this study may provide a reference to digital asset management agencies and to academic research of digital information or record management as well. The results showed that the research topics related to digital asset management include Information System and Management; Knowledge, Archive and Library; Patient Care and Health Care; Government and Community's History; Standard and Framework; Algorithm; and Hospital and Medical Record. By means of the research topic classifications, researchers may identify research issues and themes in digital asset management by categories.
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