Research on data summarization techniques such as coreset and sketch constructions is growing rapidly these days, and not only in its original community, theoretical computer sciences and mathematics, but also in more modern fields that use huge amounts of data from sensors, such as machine and deep learning. In recent years, we have also seen more and more papers in applied fields such as robotics, graphics, and computer vision, and new related theories in areas such as differential privacy, cryptographic, compressed sensing, and signal processing.
Due to this multidisciplinary research, results sometimes fall between the cracks: Theory-oriented people may not appreciate experimental results, while practitioners may not be interested in or understand tedious mathematical proofs. Often, by the time reviews are available and your journal version is published, the results have already been improved upon and become obsolete.
This Special Issue is dedicated to all types of aspects in sensor data summarization, including new provable constructions, related approximation algorithms, applications to streaming and parallel computations, software implementations, and systems that are based on such techniques.
Our goal is to have an exciting Special Edition with interesting high-quality results with an efficient reviewing process that is both professional and relatively fast.