Transforming from information overload to information excitement using the Pearl Harvesting Information Retrieval Framework

Article type
Authors
Sandieson R1
1Western University , Canada
Abstract
Background: Information overload derives from a number of sources including an expanding body of research that is more dispersed across journals and databases (Hall 2004). Traditional information retrieval strategies are cumbersome in the digital environment (Arendt 2009; Sandieson 2010). The Pearl Harvesting Information Retrieval Framework solution (PHIRF; Sandieson 2006; 2010; 2013) is a design science approach that uses rich-text searches based on synonym clusters. Synonym clusters include ALL the terms used by researchers and indexers to identify a topic. Term harvesting is accomplished from a broad range of sources to avoid the bias of using a restricted set of search terms, which is a potential problem with existing search term development.
Present Study: There has been a recent dramatic production and evolution of systematic reviews and research databases have not kept pace with indexing these. Common search strategies to search for systematic reviews use 'systematic review' OR 'meta analysis' OR 'literature review'. The term 'review' is recommended, but has very low precision. In the present study the PHIRF was used to produce a comprehensive synonym cluster for systematic reviews.
Results: The Pearl Harvesting systematic review synonym cluster contained 25 terms and produced 57% more citations than the combined standard search terms (excluding 'review'; using .af) in MEDLINE. When paired with a synonym cluster for autism, the PH search produced 1146 citations versus 685 using the standard search. In PsycINFO, the PHIRF search produced 90% more systematic review citations than the standard search (using ALL). The PHIRF search produced 4104 systematic review citations for autism versus 3716 using the standard method.
Conclusions:
Pearl Harvesting improved the number of citations retrieved for systematic reviews in two sample databases. Synonym clusters, once established, are placed in a public wiki for anyone to use. Our experience of teaching people how to do PHIRF searches is that when they experience comprehensive, relevant results they transform from a state of information overload to information excitement.