Despite the recognized need to increase interdisciplinary collaboration, there are few information resources available to provide researchers with an overview of scientific communities--topics under investigation by various groups, and patterns of collaboration among groups. The tools that are available are designed for expert social network analysts and are difficult for non-experts to use. As a result, it may be challenging for researchers to take a step back and understand the broader research landscape beyond their own social and professional connections. In response to this problem we have developed Sciologer, a software platform based on principles of social network theory. Sciologer is designed to allow non-experts to explore social communities. When applied to bibliographic data, Sciologer generates network diagrams of authors, collaborative groups, published articles, institutions, grants, keywords and other elements in the scientific community. We conducted a formative evaluation of the prototype with six neuroscience and six obesity researchers. The purpose of the evaluation was to determine (1) whether researchers are able to interpret the diagrams appropriately and make reasonable inferences about the scientific community; and (2) whether they find the system useful, and for what purposes. We captured participants' inferences using a think-aloud protocol, and used sublanguage analysis to code and count inferences. We also used a semi-structured interview and a survey informed by the Technology Acceptance Model to assess researchers' perceptions of the prototype system's case of use and usefulness. In response to prompts, the researchers made inferential observations pertaining to the diagram: its overall shape, its components, prominent icons, and the number of visible clusters. They also made inferences pertaining to the social community: researchers and groups, experts, collaboration among groups, and peripheral groups. Participants also independently made a variety of inferences about the breadth of scope of research topics, geographic locations of institutions, topics covered by journals, and other aspects of the scientific community. Perceptions of the system's usefulness and ease of use were favorable, and although they found the system output to be visually complex, most participants indicated the system offered information of value beyond a traditional PubMed search. Well-designed systems that allow researchers to understand the activity of various research groups, and collaboration among groups, have the potential to improve interdisciplinary collaboration and accelerate scientific progress. The results of this evaluation provide rich data to inform the development of visual interfaces for non-experts to explore social communities. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]