DRAT: Data risk assessment tool for university–industry collaborations

IF 2.4 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE DataCentric Engineering Pub Date : 2020-12-11 DOI:10.1017/dce.2020.13
J. Sikorska, S. Bradley, M. Hodkiewicz, R. Fraser
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引用次数: 2

Abstract

Abstract For research in the fields of engineering asset management (EAM) and system health, relevant data resides in the information systems of the asset owners, typically industrial corporations or government bodies. For academics to access EAM data sets for research purposes can be a difficult and time-consuming task. To facilitate a more consistent approach toward releasing asset-related data, we have developed a data risk assessment tool (DRAT). This tool evaluates and suggests controls to manage, risks associated with the release of EAM datasets to academic entities for research purposes. Factors considered in developing the tool include issues such as where accountability for approval sits in organizations, what affects an individual manager’s willingness to approve release, and how trust between universities and industry can be established and damaged. This paper describes the design of the DRAT tool and demonstrates its use on case studies provided by EAM owners for past research projects. The DRAT tool is currently being used to manage the data release process in a government-industry-university research partnership.
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DRAT:大学与产业合作的数据风险评估工具
在工程资产管理(EAM)和系统健康领域的研究中,相关数据驻留在资产所有者(通常是工业公司或政府机构)的信息系统中。对于学者来说,为了研究目的访问EAM数据集可能是一项困难且耗时的任务。为了促进更一致的方法来发布与资产相关的数据,我们开发了数据风险评估工具(DRAT)。该工具评估并建议控制与为研究目的向学术实体发布EAM数据集相关的风险。在开发工具时考虑的因素包括诸如组织中审批的责任在哪里,影响单个管理者批准放行的意愿的因素,以及大学和行业之间的信任如何建立和破坏。本文描述了DRAT工具的设计,并演示了它在EAM所有者为过去的研究项目提供的案例研究中的使用。DRAT工具目前正在政府-工业-大学研究伙伴关系中用于管理数据发布过程。
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来源期刊
DataCentric Engineering
DataCentric Engineering Engineering-General Engineering
CiteScore
5.60
自引率
0.00%
发文量
26
审稿时长
12 weeks
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