The growing availability of open access ecological data that follow FAIR principles (Findable, Accessible, Interoperable, and Reusable) have the potential to advance the democratization of ecology and the environmental sciences. Many coordinated research and observation networks that provide open data, such as the US Long Term Ecological Research (LTER) network, the National Ecological Observatory Network (NEON), the Global Lake Ecological Observatory Network (GLEON), the US Critical Zone Observatories (CZO), and others, are adopting FAIR data principles. These organizations play a critical role by providing a wealth of high-quality data spanning broad spatial and temporal extents used in cross-cutting interdisciplinary synthesis projects (e.g., US LTER Network Office and the 2019 NEON Science Summit synthesis working groups) and as resources for open educational material (e.g., lessons developed by Faculty Mentoring Networks on QUBES Hub). However, increasingly open and FAIR data also present the challenge of separating the ecologist from the place. Knowledge of a study site’s historical context is crucial for shaping and prioritizing relevant research questions, designing a study, and interpreting data. For example, investigators at each of the US LTER sites have an intimate knowledge of place (e.g., disturbance history, land use history, socioeconomic motivations for conservation and management decisions) that is required to successfully design long-term studies to collect and interpret ecological data relevant to important questions at their respective sites.The overall goal of this session is to bring together ecologists and environmental scientists with different perspectives on how historical context and local knowledge are necessary for (1) designing data collection strategies, (2) interpreting ecological data, and/or (3) predicting how ecosystems will respond in future climate and land use scenarios. These considerations are especially important now with the growing (re)use of open data in ecological research. The speakers will address questions, such as: What are sources of historical context and local knowledge that ecologists should consider—that are often missed? What are success stories where historical context and/or local knowledge have provided crucial pieces of information necessary for interpreting ecological data? What resources are available that synthesize site histories, land use histories, or local knowledge to provide context for open data? Where can we prioritize efforts to make ecology and environmental science more inclusive to people from diverse and underrepresented backgrounds who can provide diverse contexts and lenses through which ecological data can be interpreted?