Understanding how species and ecosystems respond to climate change requires spatially and temporally rich data for a diverse set of species and habitats, combined with models that test and predict responses. Yet current study is hampered by the long-known problems of inadequate management of data and insufficient description of analytical procedures, especially in the field of ecology. Despite recent institutional incentives to share data and new data archiving infrastructure, many ecologists do not archive and publish their data and code. Given current rapid rates of global change, the consequences of this are extreme: because an ecological dataset collected at a certain place and time represents an irreproducible set of observations, ecologists doing local, independent research possess, in their file cabinets and spreadsheets, a wealth of information about the natural world and how it is changing. Although large-scale initiatives will increasingly enable and reward open science, we believe that change demands action and personal commitment by individuals – from students and PIs. Herein, we outline the major benefits of sharing data and analytical procedures in the context of global change ecology, and provide guidelines for overcoming common obstacles and concerns. If individual scientists and laboratories can embrace a culture of archiving and sharing we can accelerate the pace of the scientific method and redefine how local science can most robustly scale up to globally relevant questions.