Policy Creation for Enterprise-Level Data Sharing

Briesemeister, Linda; Gustafson, Woodrow; Denker, Grit; Martin, April; Martiny, Karsten; Moore, Ron; Pavlović, Duško; John, Mark St.

doi:10.1007/978-3-030-22351-9_17

Cited by 6 publications

(2 citation statements)

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“…Recently, we have participated in the development of a framework for setting data sharing policies and evaluating their risks (Briesemeister et al, 2019;Myers et al, 2017;St. John et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Risk Surface: A Visualization of Data Sharing Risk for Enterprise Users

John

Gustafson

Martin

et al. 2019

Proceedings of the Human Factors and Ergonomics Society Annual

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Enterprises share a wide variety of data with different partners. Tracking the risks and benefits of this data sharing is important for avoiding unwarranted risks of data exploitation. Data sharing risk can be characterized as a combination of trust in data sharing partners to not exploit shared data and the sensitivity, or potential for harm, of the data. Data sharing benefits can be characterized as the value likely to accrue to the enterprise from sharing the data by making the enterprise’s objectives more likely to succeed. We developed a risk visualization concept called a risk surface to support users monitoring for high risks and poor risk-benefit trade-offs. The risk surface design was evaluated in a series of two focus groups conducted with human factors professionals. Across the two studies, the design was improved and ultimately rated as highly useful. A risk surface needs to 1) convey which data, as joined data sets, are shared with which partners, 2) convey the degree of risk due to sharing that data, 3) convey the benefits of the data sharing and the trade-off between risk and benefits, and 4) be easy to scan at scale, since enterprises are likely to share many different types of data with many different partners.

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Section: Introductionmentioning

confidence: 99%

Risk Surface: A Visualization of Data Sharing Risk for Enterprise Users

John

Gustafson

Martin

et al. 2019

Proceedings of the Human Factors and Ergonomics Society Annual

Self Cite

View full text Add to dashboard Cite

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“…This research is part of a larger effort to develop concepts and technologies for evaluating the risks of enterprise data sharing and then tailoring data sharing to the situation via sophisticated yet easy to use tools for specifying data sharing policies in machine-readable formats (Briesemeister, et al, 2019;Martiny, et al, 2021;St. John, et al, 2019).…”

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confidence: 99%

A Decision Support Tool for Assessing Trust in an Enterprise Data Sharing Partner

John

Young

2021

Proceedings of the Human Factors and Ergonomics Society Annual

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Enterprises need to trust that data they share with other enterprises is not exploited maliciously and cause harm. We describe the development and evaluation of a decision support tool for assessing trust in a partner enterprise. The tool is composed of ten statements spanning four well-established organizational trust factors: ability, integrity, benevolence, and vulnerability. Users rate the statements about a partner enterprise and then rate their trust in the partner enterprise. The tool focuses users on these trust factors and mentally prepares them to make the trust rating. As a first evaluation of the tool, participants read 25 statements each about enterprises in three fictional countries and rated their trust without the tool, using only their intuitions. Then they rated three more enterprises while using the tool. The tool led to trust ratings that were significantly closer to the constructed, expected ratings, and participants rated the tool as useful.

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