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This study takes a multidimensional approach to citation analysis, examining citations in multiple subfields of engineering, from both scholarly journals and doctoral dissertations. The three major goals of the study are to determine whether there are differences between citations drawn from dissertations and those drawn from journal articles; to test a methodology incorporating both internal and external citation sources; and to explore the citation habits of researchers in science, technology, engineering, and mathematics (STEM) subfields. The results reveal variations in how STEM subfields conduct research in career and academic settings and are more nuanced than internal or external citation data alone can provide. The results have practical collection development implications.

Making collections decisions within the constraints of shrinking budgets and an ever-expanding universe of materials has today's academic libraries searching for strategic ways to manage resources. In this environment it is vital that libraries clearly communicate to a wide range of stakeholders, including parent institutions and funding bodies, the distinct value of collections. Ensuring that data-informed analysis directly links collections decisions to the priorities of the institution and its users is crucial to these efforts. During this session, participants were given a broad overview of the current collections assessment landscape; hands-on exercises for mapping assessment goals to available data sources and tools; an overview of project management approaches; and specific strategies for clearly communicating results of collections analysis to different stakeholders.

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