Our Partners

We selected several individuals and groups to work with who shared our vision for clean design, data rich content and the desire to communicate scientific content as broadly as possible.

Sterling Larrimore Graphic Design

Sterling Larrimore was instrumental for shaping our brand, honing our aesthetic and ultimately created our logo for Holos. She outlines her vision for the logo in her infographic.

  • Karthik Ram, co-founder of ROpenSci and creator of the ecoengine R package.

At rOpenSci we are creating packages that allow access to data repositories through the R statistical programming environment that is already a familiar part of the workflow of many scientists. Our tools not only facilitate drawing data into an environment where it can readily be manipulated, but also one in which those analyses and methods can be easily shared, replicated, and extended by other researchers.

We develop open source R packages that provide programmatic access to a variety of scientific data, full-text of journal articles, and repositories that provide real-time metrics of scholarly impact. Visit our packages section for a full list of production and development versions of packages.

Since 2001, SF-based Stamen Design has shown consistent design and technical leadership in live data visualization and interactive mapping.
We pursue clients around the world who are ready to communicate seriously (or playfully) about their data with the public, and our experimental artistic work is in the permanent collection of the Museum of Modern Art. Building and contributing to open source software projects is a key part of Stamen’s practice.
We’ve found a way of working that lets all three of these areas support and reinforce each other. Commercial work sustains our business. Art & experimentation keep us on the cutting, bleeding edge. And we pay it all forward with open source development and education. 

Macroeco: Ecological pattern analysis in Python

  • Justin Kitzes
  • Mark Wilber

Macroeco provides a comprehensive set of functions for analyzing empirical patterns in ecological data, predicting patterns using theory and models, and comparing empirical patterns to theory. Many major macroecological patterns can be analyzed using this package, including the species abundance distribution, the species and endemics area relationships, several measures of beta diversity, and many others.