DOI: 10.5061/dryad.wdbrv15zn
title: The FAIR database: facilitating access to public health research literature

description: Objective: In public health, access to research literature is critical to
 informing decision making and to identify knowledge gaps. However,
 identifying relevant research is not a straightforward task since public
 health interventions are often complex, can have positive and negative
 impacts on health inequalities and are applied in diverse and rapidly
 evolving settings. We developed a ‘living’ database of public health
 research literature to facilitate access to this information using Natural
 Language Processing tools. Materials and Methods: Classifiers were
 identified to identify the study design (e.g. cohort study or clinical
 trial) and relationship to factors that may be relevant to inequalities
 using the PROGRESS-Plus classification scheme. Training data was obtained
 from existing MEDLINE labels and from a set of systematic reviews in which
 studies were annotated with PROGRESS-Plus categories. Results: Evaluation
 of the classifiers showed that the study type classifier achieved average
 precision and recall of 0.803 and 0.930 respectively. The PROGRESS-Plus
 classification proved more challenging with average precision and recall
 of 0.608 and 0.534. The FAIR database uses information provided by these
 classifiers to facilitate access to inequality-related public health
 literature. Discussion: Previous work on automation of evidence synthesis
 has focussed on clinical areas rather than public health, despite the need
 being arguably greater. Conclusion: The development of the FAIR databased
 demonstrates that it is possible to create a publicly accessible and
 regularly updated database of public health research literature focused on
 inequalities. The database is freely available
 (https://eppi.ioe.ac.uk/eppi-vis/Fair).
description: 1978 papers that had been included in systematic reviews
 previously were identified for training and testing the machine learning
 model. Please see the paper and website for further information.
description: # The FAIR Database:Facilitating Access to Public Health Research
 Literature
 [https://doi.org/10.5061/dryad.wdbrv15zn](https://doi.org/10.5061/dryad.wdbrv15zn) ## Description of the data and file structure ## The file is in .tsv format with the following headers: PaperId: the Microsoft Academic number for the paper PaperTitle: the title of the paper Citations: a list of Microsoft Academic numbers for the papers in the paper's bibliography coFoS: Microsoft Academic 'fields of study' / Topics Authors: the authors of the paper Abstract: the abstract of the paper PublicationDate: the date of publication DocType: the type of document FamilyId: not used RecordId: not used CN: not used Incl: not used Lang: not used V: volume I: issue DOI: DOI JN: journal title PG: pages Y: year of publication URLs: URLs where the full text paper may be downloaded umls: not used Place: PROGRESS-Plus category Race: PROGRESS-Plus category Occupation: PROGRESS-Plus category Gender: PROGRESS-Plus category Religion: PROGRESS-Plus category Education: PROGRESS-Plus category Socioeconomic: PROGRESS-Plus category Social Plus: PROGRESS-Plus category ## Access information Other publicly accessible locations of the data: * https://eppi.ioe.ac.uk/cms/Default.aspx?tabid=3830 Data was derived from the following sources: * Microsoft Academic (now OpenAlex)