Visual Analytics: Definition, Process, and Challenges

By Daniel A. Keim, Gennady L. Andrienko, Jean-Daniel Fekete, Carsten Görg, Jörn Kohlhammer, G. Melançon. Information Visualization, 2008

1,218 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Signal Processing

View Paper: https://www.semanticscholar.org/paper/edc62dd7276e23c81219678ae7f3ea6bf3e19e24

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Citations in the corpus

Visual analytics of movement: An overview of methods, tools and procedures (2013, neutral): “Visual analytics, movement, geovisualization, spatio-temporal data, information visualization”
CRISP-DM Twenty Years Later: From Data Mining Processes to Data Science Trajectories (2021, background): “…the non-inferential part of “business intelligence” (e.g., building a data warehouse and obtaining aggregated tables, cubes and other graphical representations from the data) [50], but also those that follow more exploratory or interactive scenarios, such as those common in visual analytics [51].”
Leading teachers' perspective on teacher-AI collaboration in education (2023, positive): “…that provides a reference for the TAC across different tasks in teaching practice to foster the constructive evaluation, correction, and improvement of data analysis processes and decision-making in a combination of human teacher and AI’s respective distinct capabilities (Keim et al., 2008).”
Informed Machine Learning – A Taxonomy and Survey of Integrating Prior Knowledge into Learning Systems (2019, neutral): “Visual analytics combines analysis techniques and interactive visual interfaces to enable exploration of –and inference from– data [127].”
Visual tools and narratives: new ways to improve financial literacy* (2014, methodology): “The visual tool allowed interactivity and therefore supported reasoning about data through ‘what if’ analysis (i.e., analysis based on key visual analytics concepts – see Thomas and Cook, 2005; Keim et al., 2008).”
A unified foundation for business analytics (2014, background): “…[31] • Marketing Analytics [32,33] • Customer Analytics [34,35] • Service Analytics [36] • Human Resource Analytics [37,38] • Talent Analytics [39] • Process Analytics [40] • Supply Chain Analytics [41,42] • Risk Analytics [43] • Financial Analytics [44] Generally, those who work in one of…”
Social media analytics - Challenges in topic discovery, data collection, and data preparation (2018, methodology): “Visual analytics integrates interactive visualisations and the automated processing of data (Keim et al., 2008).”
Visual Interaction with Deep Learning Models through Collaborative Semantic Inference (2019, background): “This approach is centered around the core design principles for visual analytics, which integrates visualization and analytics in a human-centered interface [42].”
Social big data: Recent achievements and new challenges (2015, background): “Although both areas have been intensively studied with regard to large, distributed, heterogeneous, and streaming data fusion [144] and data visualisation and analysis [145] , the current, rapid evolution of social media sources jointly with big data technologies creates some particularly interestin”
Generative Adversarial Networks–Enabled Human–Artificial Intelligence Collaborative Applications for Creative and Design Industries: A Systematic Review of Current Approaches and Trends (2021, background): “One of the notable aspects of many of the works that we have reviewed is that users get instantaneous visual feedback based on their input (Keim et al., 2008).”
A Survey of Visual Analytics Techniques and Applications: State-of-the-Art Research and Future Challenges (2013, methodology): “The key steps include data transformation, visual mapping/layout, model-based analysis, and user interactions according to the widely-accepted visual analytics model[2].”