Publications by Eleni Tzirita Zacharatou

Efficient Bundled Spatial Range Queries

Anastasia Ailamaki, Farhan Tauheed, Thomas Heinis, Eleni Tzirita Zacharatou, Darius Sidlauskas

Efficiently querying multiple spatial data sets is a growing challenge for scientists. Astronomers query data sets that contain different types of stars (e.g., dwarfs, giants, stragglers) while neuroscientists query different data sets that model different ...

ASSOC COMPUTING MACHINERY2019

Efficient Query Processing for Spatial and Temporal Data Exploration

Eleni Tzirita Zacharatou

Core to many scientific and analytics applications are spatial data capturing the position or shape of objects in space, and time series recording the values of a process over time. Effective analysis of such data requires a shift from confirmatory pipelin ...

EPFL2019

Improving Spatial Data Processing by Clipping Minimum Bounding Boxes

Anastasia Ailamaki, Eleni Tzirita Zacharatou, Darius Sidlauskas

The majority of spatial processing techniques rely heavily on the idea of approximating each group of spatial objects by their minimum bounding box (MBB). As each MBB is compact to store (requiring only two multi-dimensional points) and intersection tests ...

IEEE2018

Interactive Visual Exploration of Spatio-Temporal Urban Data Sets using Urbane

Anastasia Ailamaki, Eleni Tzirita Zacharatou, Haoqiong Bian

The recent explosion in the number and size of spatio-temporal data sets from urban environments and social sensors creates new opportunities for data-driven approaches to understand and improve cities. Visual analytics systems like Urbane aim to empower d ...

2018

GPU Rasterization for Real-Time Spatial Aggregation over Arbitrary Polygons

Anastasia Ailamaki, Eleni Tzirita Zacharatou

Visual exploration of spatial data relies heavily on spatial aggregation queries that slice and summarize the data over different regions. These queries comprise computationally-intensive point-in-polygon tests that associate data points to polygonal regio ...

VLDB Endowment Inc.2017

Space Odyssey - Efficient Exploration of Scientific Data

Anastasia Ailamaki, Thomas Heinis, Mirjana Pavlovic, Eleni Tzirita Zacharatou, Darius Sidlauskas

Advances in data acquisition—through more powerful supercomputers for simulation or sensors with better resolution—help scientists tremendously to understand natural phenomena. At the same time, however, it leaves them with a plethora of data and the chall ...

ACM2016

RUBIK: Efficient Threshold Queries on Massive Time Series

Anastasia Ailamaki, Farhan Tauheed, Thomas Heinis, Eleni Tzirita Zacharatou

An increasing number of applications from finance, meteorology, science and others are producing time series as output. The analysis of the vast amount of time series is key to understand the phenomena studied, particularly in the simulation sciences, wher ...

2015