Toward a big-data approach for reconstructing regional to global paleogeography and tectonic histories: Preface

Abstract

Geoscience has come to an era of addressing system-scale big science questions through synthesising the rapidly expanding bodies of discipline-based global databases, while sharply discipline-focused in-depth research is conducted to test hypotheses based on such syntheses. Such big-data oriented research has been further empowered by rapid developments in machine-learning-based artificial intelligence (AI) over recent years. This special issue presents some outcomes of IGCP 648 Supercontinent Cycles and Global Geodynamics (2015–2020) that feature work taking a big-data approach to address regional to global geotectonic issues. Papers in this volume have topics ranging from (1) the building of global palaeomagnetic and other geoscience databases, (2) development of statistical approaches and methods for using big-data analysis to address geoscience questions with quantified confidence estimation, (3) examples of applying big-data analysis to synthesise regional geotectonic and palaeographic reconstructions, (4) using big-data approaches to evaluate the chemical evolution of Earth's mantle and its lead isotope system, to (5) using multiple global datasets and geodynamic synthesis to reconstruct ancient Earth history that includes a full-plate reconstruction with palaeolongitude constraints back to 2 billion years, and related geodynamic evolution featuring a hypothesised first-order mantle structure evolution since 1.7 billion years ago.