Edit and Validate Darwin Core Taxon Data

Edit and validate taxonomic data in compliance with Darwin Core standards (Darwin Core 'Taxon' class < https://dwc.tdwg.org/terms/#taxon>).

Positron Emission Tomography Time-Activity Curve Analysis

To facilitate the analysis of positron emission tomography (PET) time activity curve (TAC) data, and to encourage open science and replicability, this package supports data loading and analysis of multiple TAC file formats. Functions are available to analyze loaded TAC data for individual participants or in batches. Major functionality includes weighted TAC merging by region of interest (ROI), calculating models including standardized uptake value ratio (SUVR) and distribution volume ratio (DVR, Logan et al. 1996 ), basic plotting functions and calculation of cut-off values (Aizenstein et al. 2008 ). Please see the walkthrough vignette for a detailed overview of 'tacmagic' functions.

'OpenStreetMap' API

Interface to 'OpenStreetMap API' for fetching and saving data from/to the 'OpenStreetMap' database (< https://wiki.openstreetmap.org/wiki/API_v0.6>).

Convert European Regional Data

Motivated by changing administrative boundaries over time, the 'nuts' package can convert European regional data with NUTS codes between versions (2006, 2010, 2013, 2016 and 2021) and levels (NUTS 1, NUTS 2 and NUTS 3). The package uses spatial interpolation as in Lam (1983) based on granular (100m x 100m) area, population and land use data provided by the European Commission's Joint Research Center.

Downloading Supplementary Data from Published Manuscripts

Downloads data supplementary materials from manuscripts, using papers' DOIs as references. Facilitates open, reproducible research workflows: scientists re-analyzing published datasets can work with them as easily as if they were stored on their own computer, and others can track their analysis workflow painlessly. The main function suppdata() returns a (temporary) location on the user's computer where the file is stored, making it simple to use suppdata() with standard functions like read.csv().

Open Trade Statistics API Wrapper and Utility Program

Access 'Open Trade Statistics' API from R to download international trade data.

Spatial Parallel Computing by Hierarchical Data Partitioning

Geospatial data computation is parallelized by grid, hierarchy, or raster files. Based on 'future' (Bengtsson, 2024 ) and 'mirai' (Gao et al., 2025 ) parallel back-ends, 'terra' (Hijmans et al., 2025 ) and 'sf' (Pebesma et al., 2024 ) functions as well as convenience functions in the package can be distributed over multiple threads. The simplest way of parallelizing generic geospatial computation is to start from par_pad_*() functions to par_grid(), par_hierarchy(), or par_multirasters() functions. Virtually any functions accepting classes in 'terra' or 'sf' packages can be used in the three parallelization functions. A common raster-vector overlay operation is provided as a function extract_at(), which uses 'exactextractr' (Baston, 2023 ), with options for kernel weights for summarizing raster values at vector geometries. Other convenience functions for vector-vector operations including simple areal interpolation (summarize_aw()) and summation of exponentially decaying weights (summarize_sedc()) are also provided.

Read and Write C3D Motion Capture Files

A wrapper for the 'EZC3D' library to work with C3D motion capture data.

Find Free Versions of Scholarly Publications via Unpaywall

This web client interfaces Unpaywall < https://unpaywall.org/products/api>, formerly oaDOI, a service finding free full-texts of academic papers by linking DOIs with open access journals and repositories. It provides unified access to various data sources for open access full-text links including Crossref and the Directory of Open Access Journals (DOAJ). API usage is free and no registration is required.

Ergonomic Methods for Assessing Spatial Models

Assessing predictive models of spatial data can be challenging, both because these models are typically built for extrapolating outside the original region represented by training data and due to potential spatially structured errors, with "hot spots" of higher than expected error clustered geographically due to spatial structure in the underlying data. Methods are provided for assessing models fit to spatial data, including approaches for measuring the spatial structure of model errors, assessing model predictions at multiple spatial scales, and evaluating where predictions can be made safely. Methods are particularly useful for models fit using the 'tidymodels' framework. Methods include Moran's I ('Moran' (1950) ), Geary's C ('Geary' (1954) ), Getis-Ord's G ('Ord' and 'Getis' (1995) ), agreement coefficients from 'Ji' and Gallo (2006) (), agreement metrics from 'Willmott' (1981) () and 'Willmott' 'et' 'al'. (2012) (), an implementation of the area of applicability methodology from 'Meyer' and 'Pebesma' (2021) (), and an implementation of multi-scale assessment as described in 'Riemann' 'et' 'al'. (2010) ().