There are all kinds of illusions in the world. Those that are orchestrated by humans (magic) and those enforced by the laws of nature (mirages). These both hold a common theme of creating a perception that something we think is true - is in fact false.
This can play a significant role in information management. It can affect how data is being accessed, what its true quality is, in terms of its intended usage, and it ultimately impacts how data is being governed.
Think about steganography. While encryption is an explicit way of hiding information, steganography does not tell you that information is being hidden. This gives you the illusion that there is no more that what you see, when in fact there is a hidden message. Only the people who know about the hidden information are likely to know how, and successfully extract it from the concealing medium.
A data mirage, however, is more a matter of opinion, and what I mean by opinion - is perception. What appears to one party as an accurate and complete account of an observation, may in fact be partial in the point of view of someone else. Like any natural mirage, this “opinion” is circumstantial and will depend on various “natural” factors such as different point-of-views, the taxonomy gap between topics, inconsistencies of data quality standards and the differences in objectives between the parties involved in the information exchange.
To manage the risk of “seeing” a data mirage, make sure you understand the differences between your language and that of your partner you are communicate with (think about: knowing your audience) ; ensure your service level agreements, or expectations, are explicit, not only in terms of the protocol being used but also in terms of the quality of the information as it relates to what is being measured and how; Finally, gain an understanding of what are the priorities of the other party you are communicating with, and what might be concealed from you, either intentionally or inadvertently.
Have you identified all the data mirages in your world? and are you sure you are truly separating data facts from data fiction?