Interpretation of Imprecision in Medical Data

Imprecision is an intrinsic part of all data types and even more so of medical data. In this paper, we revisit the definition of imprecision as well as closely related concepts of incompleteness, uncertainty, inaccuracy, and, in general, imperfection of data. We examine the traditional hierarchical approach to data, information, and knowledge in the context of medical data, which is characterized by heterogeneity, variable granularity and time-dependency. We observe that (1) imprecision has syntactic, semantic, and pragmatic aspects and (2) imprecision has its spectrum from most precise to most imprecise and unknown. We argue that interpretation of imprecision is highly contextual, and, furthermore, that medical data cannot be decoupled from their meanings and their intended usage. To address the contextual interpretation of imprecision, we present a framework for knowledge-based modeling of medical data, which comprises a semiotic approach, a fuzzy-logic approach, and a multidimensional approach.