Ramon Antonio Rodriges ZalipynisNational Research University Higher School of Economics | HSE · School of Software Engineering
Ramon Antonio Rodriges Zalipynis
PhD
About
25
Publications
2,231
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
145
Citations
Publications
Publications (25)
Earth data is essential for global environmental studies. Many Earth data types are naturally modeled by multidimensional arrays (tensors). Array (Tensor) DBMSs strive to be the best systems for tensor-related workloads and can be especially helpful for Earth data engineering, which takes up to 80% of Earth data science. We present a new quantum Ar...
Array DBMSs operate on N -d arrays. During the Data Ingestion phase, the widely used mosaic operator ingests a massive collection of overlapping arrays into a single large array, called mosaic. The operator can utilize sophisticated statistical and machine learning techniques, e.g. Canonical Correlation Analysis (CCA), to produce a high quality sea...
Geospatial array DBMSs operate on georeferenced N -d arrays. They provide storage engines, query parsers, and processing capabilities as their core functionality. Traditionally, those have been too heavy for a Web browser to support. Hence, Web Applications, mostly Geographic Information Systems (GISs), run array management on their server back-end...
Array DBMSs operate on big N -d arrays. Cellular automata (CA) work on a discrete lattice of cells, essentially on N -d arrays. CA facilitate decision support as they realistically simulate complex phenomena including road traffic, fire spread, and urban growth. Array DBMSs can bring numerous benefits to the CA domain via a "database approach": pow...
Array DBMSs strive to be the best systems for managing, processing, and even visualizing big N -d arrays. The last decade blossomed with R&D in array DBMS, making it a young and fast-evolving area. We present the first comprehensive tutorial on array DBMS R&D. We start from past impactful results that are still relevant today, then we cover contemp...
Computer networks are veins of modern distributed systems. Array DBMS (Data Base Management Systems) operate on big data which is naturally modeled as arrays, e.g. Earth remote sensing data and numerical simulation. Big data makes array DBMS to be distributed and highly utilize computer networks. The R&D area of array DBMS is relatively young and m...
This paper describes a new system which uses the Jupyter Lab development environment as the base for a graphical user interface (GUI). The system extends it to provide geospatial environmental data (geodata) processing functionality. We aim to make environmental data exploration in diverse domains including precision agriculture, hazard monitoring,...
Geospatial array DBMSs handle big georeferenced arrays. Due to the geospatial data peculiarities, many queries have tunable parameters with values not known in advance: users gradually tune them until they get a satisfactory result. This generates a series of queries with slightly different structures and very similar outputs. Modern array DBMSs sp...
Immense volumes of geospatial arrays are generated daily. Examples of such include satellite imagery, numerical simulation, and derivative data avalanche. Array DBMS are one of the prominent tools for working with large geospatial arrays. Usually the arrays natively come as raster files. ChronosDB is a novel distributed, file based, geospatial arra...
Earth remote sensing imagery come from satellites, unmanned aerial vehicles, airplanes, and other sources. National agencies, commercial companies, and individuals across the globe collect enormous amounts of such imagery daily. Array DBMS are one of the prominent tools to manage and process large volumes of geospatial imagery. The core data model...
An array DBMS streamlines large N-d array management. A large portion of such arrays originates from the geospatial domain. The arrays often natively come as raster files while standalone command line tools are one of the most popular ways for processing these files. Decades of development and feedback resulted in numerous feature-rich, elaborate,...
A raster is the primary data type in Earth science, geology, remote sensing and other fields with tremendous growth of data volumes. An array DBMS is an option to tackle big raster data processing. However, raster data are traditionally stored in files, not in databases. Command line tools have long being developed to process raster files. Most too...
Satellite imagery have always been “big” data. Array DBMS is one of the tools to streamline raster data processing. However, raster data are usually stored in files, not in databases. Respective command line tools have long been developed to process these files. Most of the tools are feature-rich and free but optimized for a single machine. The app...
Earth remote sensing has always been a source of “big” data. Satellite data have inspired the development of “array” DBMS. An array DBMS processes N-dimensional (N-d) arrays utilizing a declarative query style to simplify raster data management and processing. However, raster data are traditionally stored in files, not in databases. Respective comm...
Abstract:
Nowadays environmental science experiences tremendous growth of raster data: N-dimensional (N-d) arrays coming mainly from numeric simulation and Earth remote sensing. An array DBMS is a tool to streamline raster data processing. However, raster data are usually stored in files, not in databases. Moreover, numerous command line tools exis...
Доклад посвящен системам ChronosServer и Climate Wikience, а также пакету RWikience. ChronosServer – отечественная распределенная система для массового одновременного доступа к растровым данным в своих исходных файловых форматах. Система предназначена для работы на компьютерном кластере, который состоит из оборудования широкого потребления. Файлы р...
Веб-приложения и особенно Web ГИС приобретают все большую популярность. На сегодняшний день, работа с растровыми данными дистанционного зондирования Земли в веб-браузерах ограничивается только визуализацией изображений, которые сгенерированы на стороне сервера. Даже такие тривиальные задачи как изменение палитры изображения влечет за собой активное...
Explosive growth of raster data volumes in numerical simulations, remote sensing and other fields stimulate the development of new efficient data processing techniques. For example, in-situ approach queries data in diverse file formats avoiding time-consuming import phase. However, after data are read from file, their further processing always take...
The spring-to-summer transition is of special importance in long range forecasting, as the general circulation transitions to a less energetic regime. This affects the Midwestern United States in a profound way, since agriculture is very sensitive to the variability of weather and climate. Beginning at the local scale, surface temperature observati...
Climate Wikience is a desktop application for fast 3D visualization and analysis of retrospective climate reanalysis and Earth remote sensing data. For its several distinct features and certain tasks an analyst may prefer it to other tools. The features include rich collection of environmental variables readily available "out-of-the-box", one-click...
The book is devoted to a generalized view of the state of surface waters Lugansk region The book summarizes information about water bodies of Lugansk region data from the catalog of the classification of water objects and the features of the retrospective and cosmic monitoring of surface water quality.
To date, all remote sensing data are represented and stored as temporal sequences of separate “snapshots” – rasters or grids. This makes impossible to quickly obtain a time series of a variable values for the full available period for a region of a coordinate grid. Trend research – one of the most important topics in Earth science – becomes extreme...
ChronosServer runs on a cluster of commodity hardware and possesses scalability, high availability, and fault tolerance properties. It turns vast amounts of already existing data into actionable intelligence with no changes to the source data files. ChronosServer discovers files on cluster nodes, analyses their structure, and provides format indepe...