Ocagli Honoria, Lanera Corrado, Franzoi Marco, Monachesi Chiara, Zgheib Rebecca, Belluco Simone, Dacasto Mauro, Gregori Dario, Baldi Ileana
Unit of Biostatistics, Epidemiology, and Public Health, Department of Cardiac Thoracic Vascular Sciences and Public Health, University of Padova, via Loredan 18, Padova, 35131, Italy.
Laboratory of Food Chain Safety and Quality, Istituto Zooprofilattico Sperimentale Delle Venezie, Viale Fiume 78, 36100, Vicenza, VI, Italy.
Sci Data. 2024 Dec 28;11(1):1443. doi: 10.1038/s41597-024-04294-w.
This study presents a method for automating the retrieval of key identifies and links to toxicological data from the Joint FAO/WHO Expert Committee on Food Additives (JECFA) database using web scraping techniques. Although the method primarily serves as an automated indexing tool, facilitating organization and access to relevant reports, monographs, and specifications, it significantly enhances the efficiency of navigating the extensive JECFA database. Researchers can then perform more targeted and efficient searches, although additional manual steps are required to extract and structure the detailed toxicological data. We developed R programming scripts to extract key information, such as chemical names, identifiers, and evaluation reports, from JECFA web pages. The resulting data set comprises 6552 records as of May 2024. We validated the dataset through a systematic comparison with manually collected data, ensuring its reliability. Instructions and code for accessing and processing the dataset, facilitating its reuse in research are provided. The code and dataset are openly available, enabling researchers to efficiently access and analyze toxicological data from the JECFA database.
本研究提出了一种方法，利用网络爬虫技术自动从联合国粮食及农业组织/世界卫生组织食品添加剂联合专家委员会（JECFA）数据库中检索关键标识以及与毒理学数据的链接。尽管该方法主要作为一种自动索引工具，便于组织和获取相关报告、专论及规范，但它显著提高了在庞大的JECFA数据库中导航的效率。研究人员随后可以进行更有针对性和高效的搜索，不过提取和构建详细毒理学数据还需要额外的人工步骤。我们开发了R编程脚本，从JECFA网页中提取化学名称、标识符和评估报告等关键信息。截至2024年5月，所得数据集包含6552条记录。我们通过与手动收集的数据进行系统比较来验证该数据集，确保其可靠性。提供了访问和处理该数据集的说明及代码，便于其在研究中重复使用。代码和数据集可公开获取，使研究人员能够高效地访问和分析JECFA数据库中的毒理学数据。
