<p>Scientists need a framework to become better communicators, to both non-scientists and to each other. Specifically, they need to explain what they do when they search for truth about the natural world and how they know when they have found a high-quality conceptual model for explaining some aspect of it. For observationally based science, we highlight four aspects of scientific expertise (<i>estimations of redundancy, data uncertainty, salience, and the confidence/doubt ratio</i>) that could be communicated to increase both understanding and trust in the scientific process. These aspects have a direct parallel in communication theory (<i>source, signal, and destination</i>). Geological processes in the natural world leave redundant patterns, which are the source of scientific understanding. Scientists evaluate the quality of this signal by estimating redundancy. Scientists characterize the uncertainty of the data (signal), which is a measure of the noise within a system. To come up with conceptual models, scientists evaluate and prioritize the salience of specific data sets, based on both the relevance of the data set and its uncertainties. The third attribute involves the construction and testing of conceptual models (destination). Scientific models are evaluated as a representation of the natural world, through the use of a confidence/doubt ratio. Although scientists are adept at conveying what they know (data, models), explicit description of how they know it (estimations of redundancy, data uncertainty, salience, and confidence/doubt ratios) can potentially facilitate effective communication to other scientists and laypeople.</p>