Search and Retrieval Strategies in the Systematic Literature Search. Terminologies and Taxonomies in Information and Library Sciences

URN to cite this document:: urn:nbn:de:bvb:355-epub-325560
DOI to cite this document:: 10.5283/epub.32556

Merz, Anne-Kathrin ; Knüttel, Helge

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Date of publication of this fulltext: 05 Apr 2016 12:13

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Abstract

Abstract

Background
Systematic literature searches (SLS) are a core element of systematic reviews (SR) in the Evidence Based Medicine. For reasons of quality assurance, they ideally follow a strict methodology: they have not only to be comprehensive, exhaustive and error-robust, but also documented by protocol. Main sources for systematic reviews are original works, usually published in journals and referenced in bibliographic databases. Due to systematic distortions of the literary landscape (1), clinical trial registries and grey literature as sources of information are becoming increasingly relevant the recent years. This makes searching a resource-consuming process in which the development of optimal and reproduceable search strategies with a focus on optimizing recall and precision is a crucial task (2).
Successful efforts were made to support individual steps of the LSP through text mining applications (3–7), but a systematic classification of those methods and tools in the context of search and retrieval processes is still missing (4, 5), as well as a complete framework of effective strategies in SLS (8).
Objectives
Since the 1970’s a variety of models are used to describe search processes and design information retrieval systems (9–15). Some of these were referenced in the methodology of SR’s (16, 17), but they have not yet been critically verified concerning the appropriateness to describe seeking processes in SR’s (16). Connecting the views of information and library sciences makes a sustainable contribution to the understanding of seeking and searching in systematic literature.
Methods
Our work bases on a comprehensive literature review on the methodology of SLS and observational studies with focus on tactics for search terms identification and the development of search strategies using bibliographic databases. It presents a comparison and classification of terminologies and taxonomies of SLS’s in both research directions and combines them into a common model.
Conclusions
Our future model may be useful as a theoretical base for the development of software systems that can automate and simplify single aspects of the systematic literature searches.

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