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Literature-related discovery (LRD): Methodology

Technological Forecasting and Social ChangePublished 26 December 2007
Ronald N. Kostoff, Michael B. Briggs, Jeffrey L. Solka, Robert L. Rushenberg
Citations74
SJR quartileQ1
SJR score3.47
SNIP3.25

TL;DR

The generic methodology for identifying potential discovery candidates through ODS LRD, focusing mainly on its O DS LBD component, is described in this paper and a comprehensive flow chart showing the details of the systematic potential discovery generation process is presented.

Abstract

Literature-related discovery (LRD) is linking two or more literature concepts that have heretofore not been linked (i.e., disjoint), in order to produce novel, interesting, plausible, and intelligible knowledge. LRD has two components: Literature-based discovery (LBD) generates potential discovery through literature analysis alone, whereas literature-assisted discovery (LAD) generates potential discovery through a combination of literature analysis and interactions among selected literature authors. In turn, there are two types of LBD and LAD: open discovery systems (ODS), where one starts with a problem and arrives at a solution, and closed discovery systems (CDS), where one starts with a problem and a solution, then determines the mechanism(s) that links them. The generic methodology for identifying potential discovery candidates through ODS LRD, focusing mainly on its ODS LBD component, is described in this paper. A comprehensive flow chart showing the details of our systematic potential discovery generation process, including the evolution of the flow chart steps through each of the studies performed, is presented. Also shown is a vetting procedure that insures potential discoveries claimed are potential discoveries realized. The semantic filters that replace the numerical filters of other ODS LBD approaches are overviewed. The rationale for addressing the five topics studied (Raynaud's Phenomenon (RP), Cataracts, Parkinson's Disease (PD), Multiple Sclerosis (MS), and Water Purification (WP)) is summarized.

Keywords

Computer ScienceBiochemistry, Genetics and Molecular Biology