Data Genome: An Abstract Model for Data Evolution

机译：数据基因组：数据进化的抽象模型

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Modern information systems often process data that has been transferred, transformed or integrated from a variety of sources. In many application domains, information concerning the derivation of data items is crucial. Currently, a kind of metadata called data provenance is investigated by many researchers, but collection of provenance information must be maintained explicitly by dataset maintainer or specialized provenance management system. In this paper we investigate the problem of providing support of derivation information for applications in dataset itself. We put forward that every dataset has a unique data genome evolving with the evolution of dataset. Data genome is part of data and records derivation information for data actively. The characteristics of data genome show that the lineage of datasets can be uncovered by analyzing theirs data genomes. We also present computations of data genomes such as clone, transmit, mutate and introject to show how data genome evolves to provide derivation information from dataset itself.

机译：现代信息系统通常会处理已从各种来源传输，转换或集成的数据。在许多应用领域中，有关数据项派生的信息至关重要。当前，许多研究人员正在研究一种称为数据来源的元数据，但是必须由数据集维护者或专门的来源管理系统明确维护来源信息的收集。在本文中，我们研究了为数据集本身中的应用程序提供派生信息支持的问题。我们提出，每个数据集都有一个独特的数据基因组，随着数据集的发展而发展。数据基因组是数据的一部分，并主动记录数据的派生信息。数据基因组的特征表明，通过分析其数据基因组可以发现数据集的世系。我们还介绍了数据基因组的计算，例如克隆，传输，变异和引入，以显示数据基因组如何演变以提供来自数据集本身的派生信息。

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《International Symposium on Intelligence Computation amp; Applications(ISICA'2007); 20070921-23; Wuhan(CN)》|2007年|P.601-610|共10页
会议地点 Wuhan(CN)
作者
Deyou Tang; Jianqing Xi; Yubin Guo; Shunqi Shen;
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作者单位

School of Computer Science Engineering, South China University of Technology, Guangzhou, 510641, China;

Department of Computer Science Technology, Hunan University of Technology, Zhuzhou, 412008, China;

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原文格式 PDF
正文语种 eng
中图分类人工智能理论;
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Data Genome: An Abstract Model for Data Evolution

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