{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T11:30:08Z","timestamp":1770982208219,"version":"3.50.1"},"reference-count":0,"publisher":"Project MUSE","issue":"3","license":[{"start":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T00:00:00Z","timestamp":1770940800000},"content-version":"vor","delay-in-days":12,"URL":"https:\/\/www.crossref.org\/license"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["lib"],"published-print":{"date-parts":[[2026,2]]},"abstract":"<jats:p xml:lang=\"en\">abstract: Data literacy transcends disciplinary boundaries, yet academic libraries often struggle to provide inclusive support that bridges science, technology, engineering, and mathematics (STEM) approaches with humanities and social sciences needs. At Carnegie Mellon University Libraries, we have developed an interdisciplinary approach to data literacy that addresses this challenge. Drawing on our individual expertise in arts and humanities, anthropology and archaeology, and psychology and social sciences, we support diverse disciplines by equipping researchers with the skills needed to work meaningfully with data. Our approach positions data literacy at the intersection of critical thinking, technical competence, and ethical awareness\u2014emphasizing that all data emerges from specific social, cultural, and political contexts. This paper examines our implementation strategies, including individual consultations, workshops, core competency development, and course-embedded instruction. We demonstrate how data literacy can be contextualized across disciplines while challenging STEM-centric models that privilege quantitative over qualitative approaches. Our work has influenced university policy and enhanced student engagement with data concepts, particularly in communication and critical assessment. Through an analysis of our experiences, we offer a perspective for other librarians seeking to develop similar educational initiatives that empower researchers across academic communities, recognizing that effective data literacy instruction must respect diverse epistemologies while building essential capacities for participation in data-driven discourse.<\/jats:p>","DOI":"10.1353\/lib.2026.a983009","type":"journal-article","created":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T10:26:50Z","timestamp":1770978410000},"page":"470-490","source":"Crossref","is-referenced-by-count":0,"title":["Fostering Data Literacy by Bridging Interdisciplinary Divides: Three Perspectives on Data Literacy Support at the University Level"],"prefix":"10.1353","volume":"74","author":[{"given":"Charlotte Kiger","family":"Price","sequence":"first","affiliation":[]},{"given":"Emma","family":"Slayton","sequence":"additional","affiliation":[]},{"given":"Di","family":"Yoong","sequence":"additional","affiliation":[]}],"member":"147","container-title":["Library Trends"],"original-title":[],"language":"en","deposited":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T10:26:53Z","timestamp":1770978413000},"score":1,"resource":{"primary":{"URL":"https:\/\/muse.jhu.edu\/article\/983009"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2]]},"references-count":0,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2026,2]]}},"URL":"https:\/\/doi.org\/10.1353\/lib.2026.a983009","relation":{},"ISSN":["1559-0682"],"issn-type":[{"value":"1559-0682","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,2]]}}}