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In archaeology, the meta-analysis of scientific dating information plays an ever-increasing role. A common thread among many recent studies contributing to this has been the development of bespoke software for summarizing and synthesizing data, identifying significant patterns therein. These are reviewed in this paper, which also contains open-source scripts for calibrating radiocarbon dates and modelling them in space and time, using the R computer language and GRASS GIS. The case studies that undertake new analysis of archaeological data are (1) the spread of the Neolithic in Europe, (2) economic consequences of the Great Famine and Black Death in the fourteenth century Britain and Ireland and (3) the role of climate change in influencing cultural change in the Late Bronze Age/Early Iron Age Ireland. These case studies exemplify an emerging trend in archaeology, which is quickly re-defining itself as a data-driven discipline at the intersection of science and the humanities.