Many digital databases housed on the web today are organized in ways that are problematic for systems researchers, primarily because they are prearranged for conventional, reductionistic, linear, statistically-aggregated re- search. To make use of such data, systems researchers need an intermediary, e-scientific framework that can translate their digital data into a “systems-oriented” format, so that this data can be modeled and analyzed from a complex systems perspective. We have designed just such an intermediary framework, called the SACS Toolkit. The SACS Toolkit helps systems researchers translate and use digital data trapped in non-useful formats through its unique systems-based ontology and methodology. In the current article, we demonstrate the utility of the SACS Toolkit by applying it to a digital case study: a web-based, community health science database we are currently researching. We begin our article with a bit of background, including a review of e-social science and, more specifically, the SACS Toolkit. Next, we provide a brief description of our digital case study and the challenges it presented us; followed by an explanation of how we used the SACS Toolkit to solve our challenges. We end with a summary of how other systems researchers working with digital data may find the SACS Toolkit useful.