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題名:數據質量評價述評
書刊名:情報理論與實踐
作者:張寧袁勤儉
出版日期:2017
卷期:2017(10)
頁次:135-139
主題關鍵詞:數據質量評價研究現狀Data qualityEvaluationResearch status
原始連結:連回原系統網址new window
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  • 被引用次數被引用次數:期刊(0) 博士論文(0) 專書(0) 專書論文(0)
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  • 共同引用共同引用:0
  • 點閱點閱:6
[目的/意義]從數據資產的視角來說,數據質量評價對于數據質量價值提升具有重要作用。對數據質量評價的模型、方法、評價主體和評價對象的相關研究進行述評,以期將數據質量評價研究引向深入。[方法/過程]采用文獻調研法,對國內外文獻進行系統脈絡梳理和整體內容述評。[結果/結論]目前研究普遍采用數據質量調查法確定多個維度指標,主要采用定性定量相結合的評價策略,并且逐步關注數據用戶的需求。現有研究存在"評價標準視角單一""多維指標之間的相關性欠缺論證""計算機自動化評價受數據體量增大的瓶頸限制"等問題,未來研究需關注"大數據環境下的數據質量評價模型建模""充分考慮數據使用者的需求和認知條件""非結構化數據的有效質量評價方式構建""規模半結構化數據質量評價的計算機自動評價的實現"。
[Purpose/significance] From the perspective of data assets,data quality evaluation plays an important role in improving the value of data quality.In order to deepen the research on data quality evaluation,this paper reviews relevant studies of data quality evaluation models,methods,evaluation subjects and evaluation objects.[Method/process] Both the domestic and foreign literatures are systematically combed by literature investigation.[Result/conclusion] Current researches generally use data quality survey method to determine the indexes of multiple dimensions,adopt the combination of qualitative and quantitative strategies for evaluation,and gradually pay attention to the needs of data users.There are some problems in the existing researches,such as "single standard of evaluation""insufficient argumentation of the correlation among multi-dimensional indicators"and "bottleneck limitation of computer automatic evaluation by data volume".Future researches need to focus on"modeling of data quality evaluation under big data environment""taking full account of data users’ demands and cognitive conditions""building effective quality evaluation methods for unstructured data"and"realizing the computer automatic evaluation of the semi-structured data quality".
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