Harmonize Eye-Tracking, Pupillometry, Biometrics, and Psychometric Process Data R package eyeprocess version 0.11.1 Provides an extensible, vendor-neutral framework for importing, validating, harmonizing, transforming, visualizing, and modelling eye-tracking, pupillometry, behavioural, and biometric process data. The package uses explicit timebase and coordinate-space registries, preserves native fields and provenance, and offers first-class adapters for Gazepoint Analysis and Gazepoint Biometrics exports alongside generic and vendor-specific importers. Downstream tools support trial and area of interest reconstruction, signal-quality auditing, feature derivation, scanpath analysis, response-time and item-response workflows, and optional psychometric modelling engines. An integrated Gazepoint workflow produces quality-control evidence, media-trial reconstruction, plots, analysis-ready process tables, item response theory (IRT)-ready response structures, and reproducible reports. Brain Imaging Data Structure (BIDS) interoperability for eye-tracking and validation-release infrastructure support disk-backed storage, independent multi-vendor evidence, grouped validation, simulation calibration, model-equivalence audits, and explicitly experimental advanced psychometric process models. Research-scale infrastructure adds deterministic resumable Monte Carlo execution, atomic validation checkpoints, explicit advanced-model promotion gates, independent multi-vendor evidence registries, stable object contracts, partitioned disk-backed storage, optional probabilistic engines, and a fully synthetic multimodal benchmark for reproducibility testing. The measurement-intelligence programme adds probabilistic and compositional area of interest (AOI) analysis, measurement-uncertainty propagation, calibration and device-transportability audits, process reliability, phase-amplitude pupil registration, informative-missingness sensitivity, temporal and spatial process models, item-bank decision optimization, fairness monitoring, conditional process reference distributions, and evidence-provenance graphs. Software Depends: R (>= 4.1.0) Imports: graphics, grDevices, methods, splines, stats, utils, withr Suggests: brms, ggplot2, jsonlite, knitr, lme4, LNIRT, mirt, rmarkdown, TAM, arrow, diffIRT, GDINA, OpenMx, TraMineR, testthat (>= 3.0.0), callr, cmdstanr, eyetrackingR, future, future.apply, openssl, PupillometryR, rtdists, seqHMM, LSMjml, MASS, mgcv, nnet, survival, eRm, FactoMineR, mice, missForest, plm, psychotree, ranger, robfilter, tidyLPA, loo, posterior, targets, equateIRT, catR, mirtCAT Stefanos Balaskas <s.balaskas@ac.upatras.gr> Comprehensive R Archive Network (CRAN) Stefanos Balaskas [aut, cre] (ORCID: <https://orcid.org/0000-0003-2444-9796>) MIT + file LICENSE (https://CRAN.R-project.org/package=eyeprocess/LICENSE) 2026-09-28 application/tgz https://CRAN.R-project.org/package=eyeprocess doi:10.32614/CRAN.package.eyeprocess