국내외 연속간행물의 데이터 시각화 적합성 평가 연구

다국어 초록 (Multilingual Abstract)

Background: With the development of information and communication technology, the scale of information has increased, and we are in a big data environment. Data visualization designers in this era must have the ability to understand the nature of the data, to select the right chart, to communicate the data accurately, and to review and evaluate the data.
Methods: To find out how to evaluate data visualization suitability, we established data visualization suitability evaluation criteria through literature research. For each major error category, we organized the details of each error. Based on the derived data visualization suitability evaluation criteria, we evaluated 382 data visualization outputs of six domestic and international serial publications.
Results: Data visualization errors consist of misrepresentation, lack of clarity, counterintuitive, and visual clutter. The evaluation results showed that distortion of information and lack of clarity accounted for the highest percentage, followed by visual confusion and counterintuition. The most frequent error items were different for each medium, and it was inferred that the reason for such sporadic errors is the lack of accurate data visualization principles. The completeness of visualization depends on the competence of the designer for each medium.
Conclusions: Accurate and correct data visualization goes beyond the visualization skills of the designer and requires data literacy skills to read the data, to select charts that communicate it effectively, and to ensure that the charts are error-free. There is also a need to develop data visualization principles and checklists.