Michael Sedlmair, professor for Augmented Reality and Virtual Reality and managing director of the Institute of Visualization and Interactive Systems (VIS), is co-editor of Progressive Data Analysis. The newly published book addresses the benefits and challenges of dealing with growing datasets and the resulting complex computations by splitting long computations into a series of approximate results that improve over time. Published by the Eurographics Association, the book is now available online.
An introduction to a new paradigm in computing and a roadmap for further research
The rapid growth of data demands systems that can handle large-scale, complex datasets. While current hardware and software systems are designed for extensive storage, they often lack the responsiveness needed for effective exploratory data analysis (EDA). EDA, crucial in many application domains from network security to medicine, requires near-instant feedback to maintain analysts’ engagement. Progressive Data Analysis (PDA) addresses this by breaking down complex computations into quick, iterative approximations. This new paradigm lets users interact with evolving insights rapidly and fluidly. However, it also presents challenges, such as determining the optimal waiting time between first partial results and decision making or stabilizing the visualizations of the approximate results.
The book Progressive Data Analysis introduces PDA, discussing its technical and scientific benefits. By also examining the challenges posed by PDA, the book outlines a roadmap to make PDA a standard in big data exploration.
Open access publication
Progressive Data Analysis has been published by the Eurographics Association with a hard copy being available soon. The online version of the book is open access and can be downloaded from the Eurographics Digital Library: https://doi.org/10.2312/pda.20242707
| Contact | Michael Sedlmair |
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