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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.