Data visualization literacy can be defined as "the ability and skill to read and interpret visually represented data in and to extract information from data visualizations" (Lee, et al., 2017, p.552). Within the information science profession, data visualization literacy is an emerging and increasingly important competency within the workforce (Wright, et al., 2012; Carlson, et al., 2015; Federer, 2018). To date, there appear to be no studies addressing the data visualization literacy skills within library and information science (LIS) students, soon to be information professionals. The purpose of this quantitative study was to compare the perceived data visualization literacy skills of LIS students with their actual skills. Competency theory (Kruger & Dunning, 1999) was used as the framework for the study design and analysis of the collected data. From a participant sample of 466 currently enrolled information science students at ALA-accredited ALISE member institutions, 347 of these completed all of the required activities: the Visualization Literacy Assessment Tool (VLAT), survey demographics questions, and self-estimated scores. Findings show that 73% of participants who completed the survey and assessment scored in the top absolute quartile, and significantly underestimated their performance. However, specific gaps in relation to data visualization types (e.g., stacked bar charts and stacked area charts) were discovered, along with decreased competency as question difficulty increased. The fact that self-estimates were lower than the actual VLAT scores is contrary to competency theory findings, and information literacy studies utilizing competency theory (Kruger & Dunning 1999; Gross, & Latham, 2007, 2009, 2012; Michalak, et al., 2017). This difference may be the result of the limitation of self-selected online participants, in that participants who anticipated they would not do well on the VLAT simply may have chosen not to participate, or they dropped participation as question difficulty increased within the VLAT. To build upon or challenge the findings of this study and to attain a broader understanding of data visualization literacy skills, further research is needed, including replication studies with new cohorts of LIS students, student populations in other disciplines, and working LIS professionals. [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://bibliotheek.ehb.be:2222/en-US/products/dissertations/individuals.shtml.]