Graphing has long counted as one of the quintessential process skills that scientists apply independently of particular situations. However, recent expert/expert studies showed that when asked to interpret graphs culled from undergraduate courses of their own disciplines, scientists were far from perfect in providing interpretations that a course instructor would have accepted as correct. Drawing on five years of fieldwork, the present study was designed to investigate graphs and graph-related skills in scientific research. In addition to the fieldwork, a think-aloud protocol was used to elicit scientists' graph interpretations both on familiar and unfamiliar graphs. The analyses show that graph-related skills such as perceiving relevant graphical detail and interpreting the source of this detail emerge in the research process and are related to the scientists' increasing familiarity with a research object, instrumentation, and their understanding of the transformation process that turns raw data into graphs. When scientists do not know the natural object represented in a graph and are unfamiliar with the details of the corresponding data collection protocol, they often focus on graphical features that do not pertain to the phenomenon represented and therefore do not arrive at the correct interpretations. Based on these data, it is proposed that graphs are not only the outcomes of scientific research but also, in important ways, constitute representations that bear metonymic relations to the research context, most importantly to instrumentation, natural phenomenon, and the mathematical transformations used to produce the graphs from the raw data. I draw on the semantics of symbolic systems for articulating competencies and breakdowns in scientists' graphing-related practices.