Communities and ecologists facing environmental justice and other socio-ecological issues can mutually benefit from utilizing big data.  Communities in general, and cities in particular, are increasingly instrumented, interconnected and intelligent, in the sense that large data sets are drawn from a range of sources that are assembled and shared among stakeholders. While large data sets can be used to support operational decisions, the general public often have difficulty accessing, analyzing and interpreting the data, thus posing critical challenges in gaining support to implement data-driven decisions. For example, decision-makers faced with the complexity of big data often lack ecological literacy, thus limiting their ability to interpret data within a socio-ecological framework. Additionally, there is the challenge of shifting a public overwhelmed by the scientific process and big data sets to a public that understands the value and need for data-driven decisions. And, iniquities may arise because the data sets are often only reflective of and accessible to groups in power, while public perception of the data can be strongly influenced by political interests which have conflicting goals, e.g., political interests that have benefited from the status quo. The persistent resistance by a large fraction of voters and politicians in addressing major ecological issues, e.g., climate change, clean energy, and pollution, demonstrates the need for public engagement and inclusion if we are to achieve the benefits of these large data sets. Public engagement through citizen science, non-formal education, leadership development programs and working with environmental justice and faith-based communities all show promise for building partnerships with scientists to make ecological issues and data gathering accessible and understandable to individuals and groups. This session explores case studies, best practices and challenges to more-inclusively engage students and the general public with ecologists in collecting, analyzing, interpreting and applying large data sets to address socio-ecological issues. Ultimately, this bridge-building strives to develop a more scientifically literate society and produce resilient communities that will demand data-driven decisions from their political and community leaders.