Engaging learners with complex unfamiliar datasets is a known challenge in Data Science education. One promising phenomenon investigated in related work is perspective-taking. A first-person "actor" perspective can help facilitate group and individual sensemaking by mediating observations and actions taken by learners. Here we investigate how museum visitors made use of an actor perspective when exploring an open-ended, interactive data map museum exhibit. We use a mix of qualitative and quantitative empirical methods to explore how actor perspective-taking (APT) may mediate joint sensemaking around data visualizations. By applying interpretive coding to 54 conversations wherein APT naturalistically emerged, we identify 3 distinct self-to-data relationships constructed via APT: "role-play", "projection", and "orientation". A further analysis explores how APT was embedded in joint sensemaking of the visualized data. Twelve APT-mediated sensemaking processes are identified; two ("extrapolating" and "noticing absence") were used in conjunction with multiple APT self-to-data relationships, while the remaining ten (e.g., "enacting", "spatially characterizing", "generalizing") were exclusively used with specific self-to-data APT relationships. We use these empirical findings to generate hypotheses about how APT and associated sensemaking processes may support Data Science learning goals.