Submitting Author Name: C. William Yao
Submitting Author Github Handle: @cwy20030
Other Package Authors Github handles: (comma separated, delete if none) @GVARESCO, @FBSportScience, @gsimonelliCA
Repository: https://github.com/cwy20030/ActiGlobe
Version submitted: 0.2.1
Submission type: Standard
Editor: @robitalec
Reviewers: @vincentvanhees, @cmaimone

Archive: TBD
Version accepted: TBD
Language: en

• Paste the full DESCRIPTION file inside a code block below:

Package: ActiGlobe
Type: Package
Title: Wearable Recording Processor for Time Shift Adjustment and Data Analysis
Version: 0.2.1
Authors@R: c(person("C. William", "Yao", email = "chun.william.yao.cnmtl@ssss.gouv.qc.ca", role = c("aut","cre","cph"), comment = c(ORCID="0000-0002-7234-7375")),
             person("Giorgio", "Varesco", email = "giorgio.varesco@umontreal.ca", role = c("aut","ctb"), comment = c(ORCID="0000-0001-9385-6972")),
			 person("François", "Bieuzen", email = "fbieuzen@insquebec.org", role = c("aut","ctb"), comment = c(ORCID="0000-0002-9690-9168")),
             person("Guido", "Simonelli", email = "guido.simonelli@umontreal.ca", role = c("aut","ctb","fnd"), comment = c(ORCID="0000-0002-5400-319X")))
Maintainer: C. William Yao <chun.william.yao.cnmtl@ssss.gouv.qc.ca>
Description: Cross-continental travel and local practices of daylight saving time can induce a time shift. When left unadjusted, it can lead to biases in interpreting wearable measures. This research tool streamlines data processing and analysis (e.g., cosinor analysis, circularized kernel density estimation) for longitudinal recordings. Together with additional features such as exporting daily wearable measures and creating visual reports, it aims to facilitate research on longitudinal wearable measurements. To learn its application, please refer to the provided vignettes for a brief tutorial. This tool is developed based on the methodology detailed in: Varesco, G., Yao, C. W., Dubé, E., Simonelli, G., Bieuzen, F., (2024) <doi:10.1113/ep092195>.
License: AGPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.3
Depends: 
    R (>= 4.2.0)
Date: 2025-10-14
Imports: 
    ggplot2,
    ggrepel,
    grDevices,
    gridExtra,
    hms,
    lubridate,
    readr,
    sandwich,
    utils,
    viridis,
    parallel,
    scales
Suggests:
    spelling, 
    ggthemes,
    knitr,
    rmarkdown,
    testthat (>= 3.0.0),
    zeallot
URL: https://github.com/cwy20030/ActiGlobe
BugReports: https://github.com/cwy20030/ActiGlobe/issues
ByteCompile: true
Config/testthat/edition: 3
NeedsCompilation: no
VignetteBuilder: knitr
Language: en-US

Scope

• Please indicate which category or categories from our package fit policies this package falls under: (Please check an appropriate box below. If you are unsure, we suggest you make a pre-submission inquiry.):

  • data retrieval
  • data extraction
  • data munging
  • data deposition
  • data validation and testing
  • workflow automation
  • version control
  • citation management and bibliometrics
  • scientific software wrappers
  • field and lab reproducibility tools
  • database software bindings
  • geospatial data
  • translation

• Explain how and why the package falls under these categories (briefly, 1-2 sentences):

ActiGlobe automates the data harmonization workflow for adjusting time shift during pre-processing (via BriefSum and TAdjust). It also supports parameter extraction for further rest-activity-based circadian analysis (e.g., CosinorM) and reproducible documentation (e.g., write.act) after segmenting the continuous recording by day (i.e., Act2Daily).

• Who is the target audience and what are scientific applications of this package?

ActiGlobe aims to facilitate researchers studying rest-activity-based circadian rhythms and human behavioral pattern based on longitudinal wearable measurements.

• Are there other R packages that accomplish the same thing? If so, how does yours differ or meet our criteria for best-in-category?

ActiGlobe is a strong candidate for rOpenSci review because it delivers an end‑to‑end, reproducible actigraphy workflow that combines robust preprocessing (including explicit DST and travel handling), multiple analytical strategies (parametric and KDE cosinor, bootstrapped uncertainty), and consolidated, FAIR‑aware reporting (per‑subject PDFs plus CSV outputs). Compared with other R packages in the domain, ActiGlobe’s distinguishing value is the combination of (a) explicit, auditable time‑change correction, (b) circadian modeling tuned for irregular/real‑world recordings, and (c) built‑in consolidated reporting and metadata export that support FAIR principles and reproducible pipelines.

• (If applicable) Does your package comply with our guidance around Ethics, Data Privacy and Human Subjects Research?

Yes.
ActiGlobe includes built‑in anonymization options, minimal‑export defaults, and provenance logging to support ethical handling of human subjects data. The package documentation and vignettes demonstrate how to produce de‑identified, FAIR‑ready outputs and remind users to obtain appropriate consent and institutional approvals before sharing data.

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• does not violate the Terms of Service of any service it interacts with.
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• contains a README with instructions for installing the development version.
• includes documentation with examples for all functions, created with roxygen2.
• contains a vignette with examples of its essential functions and uses.
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