A complete pipeline for systematic bibliometric mapping of occupational health and safety (OHS) evidence. Starting from reference files exported from major bibliographic databases such as Web of Science, Scopus, PubMed, Dimensions, EBSCO, and others, 'orisma' automates ingestion, deduplication, relevance filtering, occupational risk category extraction, bibliometric analysis, and report generation. The package is related to bibliometric science mapping and evidence synthesis workflows described by Aria and Cuccurullo (2017) <doi:10.1016/j.joi.2017.08.007>, Westgate (2019) <doi:10.1002/jrsm.1374>, and Lajeunesse (2016) <doi:10.1111/2041-210X.12472>, but adds a domain-specific occupational safety and health layer. The package implements three original bibliometric indicators: (1) the Worker-Risk Disconnection Index (WRDI), measuring the proportion of studies that characterise an occupational risk without including direct worker exposure data; (2) the Risk Category Saturation Index (RCS), measuring the relative over- or under-representation of each risk category relative to a uniform baseline; and (3) the Material-Gap Profile (MGP), measuring the ratio between a material's known hazard potential and its coverage in the occupational health literature. Two additional preventive intelligence indicators are provided: (4) the Abstract Sufficiency Score (ASS, 0-5), a cumulative hierarchical index of the preventively useful information contained in an abstract; and (5) the Bridge Article Score (0-5), identifying studies that simultaneously address technology, hazardous agent, worker population, exposure measurement, and preventive recommendations. Risk categories are extracted using a built-in occupational risk dictionary of 58 categories anchored in ISO 45001:2018, INSST, NIOSH, and EU-OSHA frameworks, organised in six blocks: Safety, Industrial Hygiene, Ergonomics, Psychosociology, Biological Hazards, and Emerging Technologies. The dictionary is user-extensible. Outputs include bilingual HTML reports, occupational risk sheets, priority reading rankings, guided extraction matrices for systematic review, and reproducibility certificates with MD5 hashes.
Package details |
|
|---|---|
| Author | Raúl Aguilar Elena [aut, cre] (ORCID: <https://orcid.org/0000-0001-8656-8155>), Ana Delgado-Garcia [aut] |
| Maintainer | Raúl Aguilar Elena <raguilar@universidadviu.com> |
| License | MIT + file LICENSE |
| Version | 0.1.0 |
| URL | https://github.com/Aguilar-Elena/orisma |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.