Publications by Mirjana Pavlovic

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Advances in data acquisition technologies and supercomputing for large-scale simulations have led to an exponential growth in the volume of spatial data. This growth is accompanied by an increase in data complexity, such as spatial density, but also by mor ...

Nowadays, massive amounts of point cloud data can be collected thanks to advances in data acquisition and processing technologies such as dense image matching and airborne LiDAR scanning. With the increase in volume and precision, point cloud data offers a ...

Researchers in several scientific disciplines are struggling to cope with the masses of data resulting from either increasingly precise instruments or from simulation runs on ever more powerful supercomputers. Efficiently managing this deluge of data has b ...

Nowadays, massive amounts of point cloud data can be collected thanks to advances in data acquisition and processing technologies like dense image matching and airborne LiDAR (Light Detection and Ranging) scanning. With the increase in volume and precision ...

With large-scale simulations of increasingly detailed models and improvement of data acquisition technologies, massive amounts of data are easily and quickly created and collected. Traditional systems require indexes to be built before analytic queries can ...

Many scientific and geographical applications rely on the efficient execution of spatial joins. Past research has produced several efficient spatial join approaches and while each of them can join two datasets, the problem of efficiently joining two datase ...

Spatial joins are becoming increasingly ubiquitous in many applications, particularly in the scientific domain. While several approaches have been proposed for joining spatial datasets, each of them has a strength for a particular type of density ratio amo ...

Scientists in all disciplines increasingly rely on simulations to develop a better understanding of the subject they are studying. For example the neuroscientists we collaborate with in the Blue Brain project have started to simulate the brain on a superco ...

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 ...

Mirjana Pavlovic

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Time- and Space-Efficient Spatial Data Analytics

Dictionary Compression in Point Cloud Data Management

Enabling Scientific Discovery Via Innovative Spatial Data Management

Dictionary Compression in Point Cloud Data Management

QUASII: QUery-Aware Spatial Incremental Index

GIPSY: Joining Spatial Datasets with Contrasting Density

TRANSFORMERS: Robust Spatial Joins on Non-Uniform Data Distributions

Data-driven Neuroscience: Enabling Breakthroughs Via Innovative Data Management

Space Odyssey - Efficient Exploration of Scientific Data