Introducing the Big Knowledge to Use (BK2U) challenge.
Journal:
Annals of the New York Academy of Sciences
Published Date:
Oct 17, 2016
Abstract
The purpose of the Big Data to Knowledge initiative is to develop methods for discovering new knowledge from large amounts of data. However, if the resulting knowledge is so large that it resists comprehension, referred to here as Big Knowledge (BK), how can it be used properly and creatively? We call this secondary challenge, Big Knowledge to Use. Without a high-level mental representation of the kinds of knowledge in a BK knowledgebase, effective or innovative use of the knowledge may be limited. We describe summarization and visualization techniques that capture the big picture of a BK knowledgebase, possibly created from Big Data. In this research, we distinguish between assertion BK and rule-based BK (rule BK) and demonstrate the usefulness of summarization and visualization techniques of assertion BK for clinical phenotyping. As an example, we illustrate how a summary of many intracranial bleeding concepts can improve phenotyping, compared to the traditional approach. We also demonstrate the usefulness of summarization and visualization techniques of rule BK for drug-drug interaction discovery.
Authors
Keywords
Animals
Computational Biology
Data Mining
Decision Making, Computer-Assisted
Drug Interactions
Humans
Image Interpretation, Computer-Assisted
Image Processing, Computer-Assisted
Intracranial Hemorrhages
Knowledge Bases
Models, Neurological
Pharmaceutical Preparations
Systematized Nomenclature of Medicine
Terminology as Topic
Translational Research, Biomedical