Per-flow measurement is a critical issue in computer networks, and one of its key tasks is to
count the number of packets in each flow (for big streaming data). The literature has …

Voluminous time-series data streams produced in continuous sensing environments impose
challenges pertaining to ingestion, storage, and analytics. In this study, we present a holistic …

Cardinality estimation is perhaps the simplest non-trivial statistical problem that can be
solved via sketching. Industrially-deployed sketches like HyperLogLog, MinHash, and PCSA …

Multi-spectral satellite images that remotely sense the Earth's surface at regular intervals are
often contaminated due to occlusion by clouds. Remote sensing imagery captured via …

Gridded spatial datasets arise naturally in environmental, climatic, meteorological, and
ecological settings. Each grid point encapsulates a vector of variables representing different …

Remote sensing of plant traits and their environment facilitates non‐invasive, high‐
throughput monitoring of the plant's physiological characteristics. However, voluminous …

Scientists use models to further their understanding of phenomena and inform decision-
making. A confluence of factors has contributed to an exponential increase in spatial data …

Exponential growth in spatial data volumes have occurred alongside increases in the
dimensionality of datasets and the rates at which observations are generated. Rapid …

One of the most powerful ways to explore data is to visualize it. Visualizations underpin data
wrangling, feature space explorations, and understanding the dynamics of phenomena …

Fueled by the proliferation of IoT devices and increased adoption of sensing environments
the collection of spatiotemporal data has exploded in recent years. Disk based storage …