This journal will publish original work in the emerging interdisciplinary field of information geometry, with both a theoretical and computational emphasis. Information geometry connects various branches of mathematical science in dealing with uncertainty and information based on unifying geometric concepts. Furthermore, it demonstrates the great potential of abstract thinking and corresponding formalisms within many application fields. Theoretical topics of interest will include, but are not limited to, the Fisher–Rao metric, the Amari–Chentsov tensor, alpha geometry, dual connections, exponential and mixture geodesics, divergence functions, information and entropy functions, convex analysis, Hessian geometry, information projections, q-statistics and deformed exponential/logarithm, algebraic statistics, optimal transport geometry, and related topics. The authors and audience of this journal will be interdisciplinary, coming from the many disciplines that inspire the development of information-geometric methods and benefit from their application, including mathematics, statistics, machine learning, neuroscience, information theory, statistical and quantum physics, control theory and optimization, complex networks and systems, theoretical biology, cognitive science, mathematical finance, and allied disciplines. Content published in this journal is peer reviewed (Single Blind). AMS Mathematical Citation Quotient: 1.60 (2019).