Make Your Data Work Twice: A Practical Guide to FAIR Research Data for Dental Researchers

This presentation provides a 10-step practical workflow for dental researchers and PhD students to implement FAIR (Findable, Accessible, Interoperable, Reusable) data management in their research projects. The workflow covers the full research data lifecycle: planning (research question, Data Management Plan, project folder structure), collecting (forms-based data entry, raw data preservation), processing (anonymization with sdcMicro and Amnesia, analysis in R, codebook generation with dataMaid), and sharing (packaging data with README and license, publishing in Zenodo or institutional repositories, citing datasets with DOI). The presentation builds on findings from Uribe et al. (2022), which showed that only 1.5% of dental research articles shared data and that FAIR compliance averaged 32.6%. It includes runnable R code examples for all recommended packages (tidyverse, janitor, skimr, gtsummary, dataMaid, sdcMicro, here, prodigenr, quarto), a README template for clinical-epidemiological dental research, and a Quarto document demonstrating the anonymization pipeline.