Abstract

A fundamental goal of the geological sciences is the deep understanding of planetary evolution. Recent research employing large and growing data resources in mineralogy, petrology, paleobiology, paleotectonics, geochemistry, and proteomics underscores the intertwined influences of life and rocks on Earth’s evolution. We therefore are exploring “big-data” approaches to longstanding problems in geology. Data-driven discovery depends on three key developments: (1) enhanced data resources in diverse geo- and bio-related fields; (2) development and implementation of powerful analytical and visualization methods; and (3) creative framing of questions related to the evolving geosphere and biosphere in space and time.

We are especially interested in visualization methods that illustrate multiple attributes of complex systems. In particular, network analysis provides a dynamic, quantitative, and predictive visualization framework for employing “big data” to explore complex and otherwise hidden higher-dimensional patterns of diversity and distribution in mineralogy, paleobiology, and protein structures. Network analysis facilitates quantitative comparison of coexistence patterns simultaneously among hundreds of mineral or fossil species and their localities, exploration of varied paragenetic modes of mineral groups, investigation of changing patterns of mineral and fossil occurrence through deep time, and comparisons of lithologies from different planets and moons. Network analysis, furthermore, represents an effective visual approach to teaching and learning in Earth and planetary sciences.