A suggested data structure for transparent and repeatable reporting of bibliographic searching

Academic searching is integral to research activities: (1) searching to retrieve specific information, (2) to expand our knowledge iteratively, (3) and to collate a representative and unbiased selection of the literature. Rigorous searching methods are vital for reliable, repeatable and unbiased searches needed for these second and third forms of searches (exploratory and systematic searching, respectively) that form a core part of evidence syntheses. Despite the broad awareness of the importance of transparency in reporting search activities in evidence syntheses, the importance of searching has been highlighted only recently and has been the explicit focus of reporting guidance (PRISMA-S). Ensuring bibliographic searches are reported in a way that is transparent enough to allow for full repeatability or evaluation is challenging for a number of reasons. Here, we detail these reasons and provide for the first time a standardised data structure for transparent and comprehensive reporting of search histories. This data structure was produced by a group of international experts in informatics and library sciences. We explain how the data structure was produced and describe its components in detail. We also demonstrate its practical applicability in tools designed to support literature review authors and explain how it can help to improve interoperability across tools used to manage literature reviews. We call on the research community and developers of reference and review management tools to embrace the data structure to facilitate adequate reporting of academic searching in an effort to raise the standard of evidence syntheses globally.

Automated summary

Academic searching plays a crucial role in research activities, providing specific information, expanding knowledge, and selecting representative literature. A standardized data structure can facilitate transparent and comprehensive reporting of search histories, thereby improving the quality of evidence syntheses.