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Quality of Research Information in RIS Databases: A Multidimensional Approach

机译:RIS数据库中研究信息的质量:多维方法

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For the permanent establishment and use of a RIS in universities and academic institutions, it is absolutely necessary to ensure the quality of the research information, so that the stakeholders of the science system can make an adequate and reliable basis for decision-making. However, to assess and improve data quality in RIS, it must be possible to measure them and effectively distinguish between valid and invalid research information. Because research information is very diverse and occurs in a variety of formats and contexts, it is often difficult to define what data quality is. In the context of this present paper, the data quality of RIS or rather their influence on user acceptance will be examined as well as objective quality dimensions (correctness, completeness, consistency and timeliness) to identify possible data quality deficits in RIS. Based on a quantitative survey of RIS users, a reliable and valid framework for the four relevant quality dimensions will be developed in the context of RIS to allow for the enhancement of research information driven decision support.
机译:为了在大学和学术机构中永久建立和使用RIS,绝对有必要确保研究信息的质量,以便科学系统的利益相关者可以为决策提供充分而可靠的基础。但是,为了评估和提高RIS中的数据质量,必须有可能对其进行测量并有效地区分有效和无效的研究信息。由于研究信息非常多样并且以各种格式和上下文出现,因此通常很难定义什么数据质量。在本文的上下文中,将检查RIS的数据质量,或者说它们对用户接受度的影响,以及客观的质量维度(正确性,完整性,一致性和及时性),以识别RIS中可能的数据质量缺陷。在对RIS用户进行定量调查的基础上,将在RIS的背景下为四个相关质量维度开发一个可靠有效的框架,以增强研究信息驱动的决策支持。

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