COMMUNICATING CONCEPTUAL AND COGNITIVE UNCERTAINTY WITH HERMENEUTICS AND SEMIOTICS: EXAMPLES FROM STRATIGRAPHIC APPLICATIONS

Geologic knowledge is derived from the observation of physical phenomena as filtered through human cognitive processes. The nature of geology, as a synthetic science, requires scientists to assess meaning of data by assembling objects and ideas into a coherent and meaningful system. From the earliest collection stage, it should be recognized that an observer’s working hypotheses, past experiences, training, and personality influence the description and interpretation of data. Whether consciously or subconsciously, geologists analyze their own confidence in and relevance of data.

This study presents a method to represent uncertainty in interpretations. Examples are provided from outcrop and subsurface investigations. Elements from the fields of hermeneutics, semiotics and information science provide a framework for communicating a geologist’s confidence and uncertainty in observations and interpretations. Hermeneutics is the study of interpretation, encompassing how and why an observer places meaning to objects and ideas. Within modern hermeneutics, semiotics elucidates how meaning arises from the process of perceiving and interpreting objects. An interpretation is influenced by the level of confidence in pertinent measurements (or confidence factor) and perceived relevance of these data to an interpretation (or relevance factor). Both aspects are expressed as a value from 0 to 1, where 1 implies the attribute's value is known with absolute certainty. These quantities are similar to probabilities, but are meant to communicate estimates of confidence in human reasoning.

Conveying estimates of certainty and relevance to other geologists and non-geologists increases the transparency of the process of interpreting information. Certainty values provide the professional geologist valuable insight into their colleagues’ research. For the non-geologist, confidence measurements provide an estimate useful in predicting risk. For example, engineers and product mangers for an oil exploration unit may not fully understand or recognize the importance of the various data the geologist observes, yet they rely on petroleum geologists’ final interpretations to decide when and where to look for natural resources.