Access to the Neotoma Paleoecological Database Through R

Access paleoecological datasets from the Neotoma Paleoecological Database using the published API (< http://api.neotomadb.org/>). The functions in this package access various pre-built API functions and attempt to return the results from Neotoma in a usable format for researchers and the public.

Parse a BibTeX File to a Data Frame

Parse a BibTeX file to a data.frame to make it accessible for further analysis and visualization.

Create Lightweight Schema.org Descriptions of Data

The goal of 'dataspice' is to make it easier for researchers to create basic, lightweight, and concise metadata files for their datasets. These basic files can then be used to make useful information available during analysis, create a helpful dataset "README" webpage, and produce more complex metadata formats to aid dataset discovery. Metadata fields are based on the 'Schema.org' and 'Ecological Metadata Language' standards.

Data Sets for Historians

These sample data sets are intended for historians learning R. They include population, institutional, religious, military, and prosopographical data suitable for mapping, quantitative analysis, and network analysis.

Managing Larger Data on a GitHub Repository

Because larger (> 50 MB) data files cannot easily be committed to git, a different approach is required to manage data associated with an analysis in a GitHub repository. This package provides a simple work-around by allowing larger (up to 2 GB) data files to piggyback on a repository as assets attached to individual GitHub releases. These files are not handled by git in any way, but instead are uploaded, downloaded, or edited directly by calls through the GitHub API. These data files can be versioned manually by creating different releases. This approach works equally well with public or private repositories. Data can be uploaded and downloaded programmatically from scripts. No authentication is required to download data from public repositories.

Read and Write ODS Files

Read ODS (OpenDocument Spreadsheet) into R as data frame. Also support writing data frame into ODS file.

Create Useful .gitignore Files for your Project

Simple interface to query gitignore.io to fetch gitignore templates that can be included in the .gitignore file. More than 450 templates are currently available.

High Performance Interface to 'GBIF'

A high performance interface to the Global Biodiversity Information Facility, 'GBIF'. In contrast to 'rgbif', which can access small subsets of 'GBIF' data through web-based queries to a central server, 'gbifdb' provides enhanced performance for R users performing large-scale analyses on servers and cloud computing providers, providing full support for arbitrary 'SQL' or 'dplyr' operations on the complete 'GBIF' data tables (now over 1 billion records, and over a terabyte in size). 'gbifdb' accesses a copy of the 'GBIF' data in 'parquet' format, which is already readily available in commercial computing clouds such as the Amazon Open Data portal and the Microsoft Planetary Computer, or can be accessed directly without downloading, or downloaded to any server with suitable bandwidth and storage space. The high-performance techniques for local and remote access are described in < https://duckdb.org/why_duckdb> and < https://arrow.apache.org/docs/r/articles/fs.html> respectively.

An R Interface to 'figshare'

An R interface to 'figshare'.

Interface to the 'Open Science Framework' ('OSF')

An interface for interacting with 'OSF' (< https://osf.io>). 'osfr' enables you to access open research materials and data, or create and manage your own private or public projects.