This study employs Google trends and data from the web of science to evaluate the popularity, growth, and impacts of visual analytics (VA) as a research field and data science technique. The paper undertakes quantitative analyses and visualization of the temporal trends, from VA's emergence in 2000 to the end of 2019. The trend analysis helps to forecast future growth in the research and practice of VA. The study highlights four outcomes. First, there is a robust direct relationship among the variables, including VA's growth on the Google trends, the scientific literature production (SLP), and usage of the published documents. Second, the SLP's growth pattern highlights VA's popularity as an emerging field with an overall annual increase of 17.4%. The high citation counts of the published scholarship indicate a significant impact and a continuous growth of the VA field. Third, VA contributes to diverse disciplines other than computer science and information systems, from business and economics to engineering, healthcare, biomedical and chemical sciences, and arts and humanities. VA helps researchers and practitioners in multidisciplinary fields analyze multidimensional data, enhance data visualization, knowledge discovery, generating insights, and make informed decisions. On the reverse, other disciplines contribute to propelling VA's popularity through research productivity, usage, and citation impacts. Finally, a trend analysis predicts sustained future growth of VA technology in research and practice to dissect and sensemaking of the increasingly massive and complex data structures, which is now the norm in many fields.

中文翻译：

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视觉分析研究和实践的普及和增长的多标准分析，以及对未来轨迹的预测

这项研究利用Google趋势和科学网络中的数据来评估视觉分析（VA）的普及性，增长和影响，并将其作为研究领域和数据科学技术。从VA的出现到2000年底至2019年底，本文对时间趋势进行了定量分析和可视化。趋势分析有助于预测VA的研究和实践的未来增长。该研究突出了四个结果。首先，变量之间存在稳固的直接关系，包括VA在Google趋势上的增长，科学文献产量（SLP）和已发布文档的使用情况。其次，SLP的增长模式突出显示了VA作为新兴领域的受欢迎程度，其总体年度增长率为17.4％。已发表的奖学金被引用次数很高，表明VA领域产生了重大影响并持续增长。第三，从商业和经济学到工程学，医疗保健，生物医学和化学科学以及艺术和人文科学，VA都为计算机科学和信息系统以外的各种学科做出了贡献。VA帮助多学科领域的研究人员和从业人员分析多维数据，增强数据可视化，知识发现，产生见解并做出明智的决策。相反，其他学科则通过提高研究效率，使用和引文影响来推动VA的普及。最后，趋势分析预测VA技术在研究和实践中的持续未来增长，以剖析和感化日益庞大和复杂的数据结构，