Introducing the Big Knowledge to Use (BK2U) challenge
Document Type
Article
Publication Date
1-1-2017
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.
Identifier
84991677434 (Scopus)
Publication Title
Annals of the New York Academy of Sciences
External Full Text Location
https://doi.org/10.1111/nyas.13225
e-ISSN
17496632
ISSN
00778923
PubMed ID
27750400
First Page
12
Last Page
24
Issue
1
Volume
1387
Grant
R01CA190779
Fund Ref
National Institutes of Health
Recommended Citation
Perl, Yehoshua; Geller, James; Halper, Michael; Ochs, Christopher; Zheng, Ling; and Kapusnik-Uner, Joan, "Introducing the Big Knowledge to Use (BK2U) challenge" (2017). Faculty Publications. 9862.
https://digitalcommons.njit.edu/fac_pubs/9862
