{ Linked Paleo Data }

LiPD (Linked PaleoData) is an open data standard for sharing, reusing, and analyzing paleoclimate datasets. Each LiPD file packages tabular proxy data alongside rich structured metadata in a portable, validated archive — letting scientists spend less time managing data and more time doing science.

LiPD is supported by libraries for R (lipdR) and Python (pylipd), a browser-based editor (LiPD Studio), and a growing community archive at LiPDverse.

A technical description of the format for developers is available on the Format page.

Dataset Structure

Getting Started

Software

LiPD is supported by libraries for R and Python, and a browser-based editor. Choose what fits your workflow.

lipdRR package

Read, write, and validate LiPD files in R. Works seamlessly with data frames and the tidyverse.

install.packages("lipdR")
 GitHubDocs
pylipdPython package

Read, write, and validate LiPD files in Python. Integrates with pandas, NumPy, and Pyleoclim.

pip install pylipd
 GitHub
LiPD PlaygroundBrowser-based editor

Create, upload, and edit LiPD files directly in your browser. No installation required.

Open Playground

Find Data

LiPDverse

The community archive for LiPD datasets. Browse thousands of paleoclimate records by archive type, variable, region, and age range. Download individual files or entire collections.

Visit LiPDverse

Create and Edit Files

LiPD Playground

The Playground provides a structured form editor for all LiPD metadata fields, built-in validation feedback, CSV data entry, and one-click download of the finished file.

For programmatic or batch creation, use lipdR or pylipd to build LiPD objects from data frames or dictionaries and write them to disk.

Open Playground

Analyze Data

Once you have data loaded via lipdR or pylipd, these packages extend your analysis capabilities.

GeoChronRR package

Age modeling, time series analysis, and visualization for paleoclimate data. Integrates Bchron, Bacon, and other age models.

 GitHub
actRR package

Abrupt change detection and climate reconstruction with rigorous uncertainty quantification.

 GitHub
PyleoclimPython package

Spectral analysis, wavelet transforms, mapping, and visualization for paleoclimate time series.

 GitHub

FAQ

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About Us

Julien Emile-Geay

Principal Investigator

Department of Earth Science

University of Southern California

Nicholas McKay

Principal Investigator

School of Earth Sciences and Environmental Sustainability

Northern Arizona University

Deborah Khider

Department of Earth Science

University of Southern California