rOpenSci Pre-Submission

[roaldarbol]

Submitting Author Name: Mikkel Roald-Arbøl
Submitting Author Github Handle: @roaldarbol
Other Package Authors Github handles: (comma separated, delete if none)
Repository: https://github.com/roaldarbol/animovement
Submission type: Pre-submission
Language: en

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

Scope

• Please indicate which category or categories from our package fit policies or statistical package categories this package falls under. (Please check one or more appropriate boxes below):

  Data Lifecycle Packages

  • 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
  • text analysis

  Statistical Packages

  • Bayesian and Monte Carlo Routines
  • Dimensionality Reduction, Clustering, and Unsupervised Learning
  • Machine Learning
  • Regression and Supervised Learning
  • Exploratory Data Analysis (EDA) and Summary Statistics
  • Spatial Analyses
  • Time Series Analyses
  • Probability Distributions

• Explain how and why the package falls under these categories (briefly, 1-2 sentences). Please note any areas you are unsure of:

  • The package currently has five main pillars: (1) Read movement date (primarily from video tracking, but also others), (2) Quality assurance (including various filtering methods, imputation, visual checks), (3) transformations (e.g. transforming between allocentric and egocentric reference frames), (4) calculate kinematics

• If submitting a statistical package, have you already incorporated documentation of standards into your code via the srr package?

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

• Those working in particular with video tracking of animals, primarily in neuroscience, ethology, behavioural ecology, but the package works just as well for e.g. tracking of cells.

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

• The package has some overlap with packages that describe animal movement from tag tracking, but differs on multiple points: Most importantly, there is no requirement for data to be in date-time stamps, in fact, we exclusively use "elapsed time" (numeric), and keep datetime as a metadata tag. We take inspiration from e.g. the {trajr} package. I work closely with developers of the movement Python package which we share several aims with.

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

• Any other questions or issues we should be aware of?: