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PUblications Metadata Augmentation (PUMA) pipeline

Lookup NU author(s): Dr Olly Butters, Dr Becca Wilson, Hugh Garner, Tom Burton



This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


© 2021 Butters OW et al.Cohort studies collect, generate and distribute data over long periods of time - often over the lifecourse of their participants. It is common for these studies to host a list of publications (which can number many thousands) on their website to demonstrate the impact of the study and facilitate the search of existing research to which the study data has contributed. The ability to search and explore these publication lists varies greatly between studies. We believe a lack of rich search and exploration functionality of study publications is a barrier to entry for new or prospective users of a study's data, since it may be difficult to find and evaluate previous work in a given area. These lists of publications are also typically manually curated, resulting in a lack of rich metadata to analyse, making bibliometric analysis difficult. We present here a software pipeline that aggregates metadata from a variety of third-party providers to power a web based search and exploration tool for lists of publications. Alongside core publication metadata (i.e. author lists, keywords etc.), we include geocoding of first authors and citation counts in our pipeline. This allows a characterisation of a study as a whole based on common locations of authors, frequency of keywords, citation profile etc. This enriched publications metadata can be useful for generating study impact metrics and web-based graphics for public dissemination. In addition, the pipeline produces a research data set for bibliometric analysis or social studies of science. We use a previously published list of publications from a cohort study as an exemplar input data set to show the output and utility of the pipeline here.

Publication metadata

Author(s): Butters OW, Wilson RC, Garner H, Burton TWY

Publication type: Article

Publication status: Published

Journal: F1000Research

Year: 2021

Volume: 9

Online publication date: 12/04/2021

Acceptance date: 02/04/2018

Date deposited: 11/06/2021

ISSN (print): 2046-1402

ISSN (electronic): 1759-796X

Publisher: F1000 Research Ltd


DOI: 10.12688/f1000research.25484.2


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