Open data and data mining techniques have facilitated the analysis of how we practice ecology. These analyses provide insights into how the discipline of ecology is progressing and a means by which to distinguish successful from failing approaches that require reassessment. During my PhD, my colleagues and I used data mining methods to retrieve the p and R2 values for over 18,000 articles in ecology. This analysis revealed that ecology is becoming more statistically complex and R2 values are, on average, declining over time (Low-Décarie et al. 2014 Front. Ecol. Environ.). Our paper garnered much interest among ecologists, was the subject of numerous discussion groups, blog posts and a feature in Science Magazine News. Presently, I am working with colleagues from Dartmouth, Duke and University of North Carolina on a global, cross-taxa review of functional diversity. Our analyses suggest a rapid increase in the number of distinct functional diversity measures used in the literature across time, differences between terrestrial and aquatic studies, and geographic regions lacking functional diversity data – together suggesting strong system, habitat and geographic biases in the literature.