The ChallengeScholars working in the humanities and social sciences now find that they are working with ever larger data sets. We can already see the beginnings of a new genre, what we might call "big history"--the use of large-scale data in historical inquiry. The challenge before us is significant. The Aurora Engine at the heart of our project addresses a significant cyberinfrastructure research problem--developing an open source, community-driven system for assembling, sharing, editing, and analyzing spatio-temporal large-scale data in a wide range of formats.
We believe that history at all levels would benefit from a deeper engagement with the possibilities of seeing change over time and spatial relationships. Our goal is to make invisible histories much more visible, create models and visualizations about historical questions, and attempt to uncover patterns not otherwise apparent. We offer scholars a new form of communicating ideas based on up-datable interpretations and dynamically generated data.