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Broadly, the information science field has grown to encompass a more extensive set of data science competencies as the role of data, data literacy, and data visualization has grown. Schwabish explains, "now more than ever, content must be visual if it is to travel far" (2021). Through coding selected years across 20 years of JASIST journal, from the years 2001, 2006, 2011, 2016, and 2021; we were able to not only inventory the proportion of images that are data visualizations but also to identify trends and changes over time in the data visualizations contained in JASIST publications. Findings suggested that overall, the importance and complexity of data visualizations in publications increased over the date range studied. Additionally, as data visualizations were used more often, they were observed to become more complex. Still, once distilled into their simplest forms, a limited variety of data visualizations was used across the dataset. Therefore, there is a clear need for increased data literacy targeted toward complex data visualizations. Furthermore, opportunities exist to improve the types of data visualizations used in academic writing.
Data Comprehension, Data Visualization, Data Literacy
Data Comprehension, Data Visualization, Data Literacy
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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