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Exploring Data Value Assessment: A Survey Method and Investigation of the Perceived Relative Importance of Data Value Dimensions

机译:探索数据价值评估:对数据价值维度的感知相对重要性的调查方法和调查

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This paper describes the development and execution of a data value assessment survey of data professionals and academics. Its purpose was to explore more effective data value assessment techniques and to better understand the perceived relative importance of data value dimensions for data practitioners. This is important because despite the current deep interest in data value, there is a lack of data value assessment techniques and no clear understanding of how individual data value dimensions contribute to a holistic model of data value. A total of 34 datasets were assessed in a field study of 20 organisations in a range of sectors from finance to aviation. It was found that in 17 out of 20 of the organisations contacted that no data value assessment had previously taken place. All the datasets evaluated were considered valuable organisational assets and the operational impact of data was identified as the most important data value dimension. These results can inform the community's search for data value models and assessment techniques. It also assists further development of capability maturity models for data value assessment and monitoring. This is to our knowledge the first publication of the underlying data for a multi-organization data value assessment and as such it represents a new stage in the evolution of evidence-based data valuation.
机译:本文介绍了数据专业人员和学者数据价值评估调查的开发和执行。其目的是探讨更有效的数据价值评估技术,并更好地了解数据从业者数据价值维度的感知相对重要性。这很重要,因为尽管目前对数据值深入兴趣,但缺乏数据值评估技术,并且不清楚地了解单个数据值尺寸如何有助于数据值的整体模型。共有34个数据集在来自金融到航空的一系列部门的20个组织的实地研究中进行了评估。有人发现,在20个组织中有17个联系,没有先前发生过数据价值评估。评估的所有数据集被认为是有价值的组织资产,并且数据的操作影响被确定为最重要的数据值维度。这些结果可以通知社区的搜索数据价值模型和评估技术。它还有助于进一步开发数据价值评估和监测能力成熟度模型。这是我们了解多组织数据价值评估的底层数据的第一次出版,因此它代表了基于证据的数据估值的演变的新阶段。

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