Usage Experience and Capabilities of the VEGA-Science System

Currently, when satellite data volumes grow rapidly and exceed petabyte values and their quality provides reliable analysis of long-term time series, traditional data handling methods assuming local storage and processing may be impossible to implement for small or distributed research teams. Thus, new methods based on modern web technologies providing access to very large distributed data archives are gaining increasing importance. Furthermore, these new data handling solutions should provide not just access but also analysis and processing features, similar to desktop solutions. This paper describes the VEGA-Science web GIS—an open-access novel tool for satellite data processing and analysis. The overview of its architecture and basic technical components is given, but most attention is paid to examples of actual system application for various applied and research tasks. In addition, an overview of projects using the system is given to illustrate its versatility and further development directions are considered.

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Towards Self-Service GIS—Combining the Best of the Semantic Web and Web GIS

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi9120753 ◽

2020 ◽

Vol 9 (12) ◽

pp. 753

Author(s):

Alexandra Rowland ◽

Erwin Folmer ◽

Wouter Beek

Keyword(s):

Semantic Web ◽

Information Science ◽

Geographic Information ◽

Web Gis ◽

Distributed Data ◽

Geospatial Information ◽

Semantic Web Technologies ◽

Web Technologies ◽

Rapid Transition ◽

Self Service

The field of geographic information science has grown exponentially over the last few decades and, particularly within the context of the pervasiveness of the internet, bears witness to a rapid transition of its associated technologies from stand-alone systems to increasingly networked and distributed systems as geospatial information becomes increasingly available online. With its long-standing history for innovation, the field has adopted many disruptive technologies from the fields of computer and information sciences through this transition towards web geographic information systems (GIS); most interestingly in the context of this research is the limited uptake of semantic web technologies by the field and its associated technologies, the lack of which has resulted in a technological disjoint between these fields. As the field seeks to make geospatial information more accessible to more users and in more contexts through ‘self-service’ applications, the use of these technologies is imperative to support the interoperability between distributed data sources. This paper aims to provide insight into what linked data tooling already exists, and based on the features of these, what may be possible for the achievement of self-service GIS. Findings include what visualisation, interactivity, analytics and usability features could be included in the realisation of self-service GIS, pointing to the opportunities that exist in bringing GIS technologies closer to the user.

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STORM ICE OIL WIND WAVE WATCH SYSTEM (SIOWS): WEB GIS APPLICATION FOR MONITORING THE ARCTIC

Proceedings of International Conference "Managinag risks to coastal regions and communities in a changinag world" (EMECS'11 - SeaCoasts XXVI) ◽

10.31519/conferencearticle_5b1b93852689d4.28131112 ◽

2017 ◽

Author(s):

Alexander Myasoedov ◽

Sergey Azarov ◽

Ekaterina Balashova ◽

...

Keyword(s):

Satellite Data ◽

Wind Wave ◽

Arctic Region ◽

Web Gis ◽

The Arctic ◽

Flexible Tool ◽

In Situ Data ◽

Current State ◽

Watch System

Working with satellite data, has long been an issue for users which has often prevented from a wider use of these data because of Volume, Access, Format and Data Combination. The purpose of the Storm Ice Oil Wind Wave Watch System (SIOWS) developed at Satellite Oceanography Laboratory (SOLab) is to solve the main issues encountered with satellite data and to provide users with a fast and flexible tool to select and extract data within massive archives that match exactly its needs or interest improving the efficiency of the monitoring system of geophysical conditions in the Arctic. SIOWS - is a Web GIS, designed to display various satellite, model and in situ data, it uses developed at SOLab storing, processing and visualization technologies for operational and archived data. It allows synergistic analysis of both historical data and monitoring of the current state and dynamics of the "ocean-atmosphere-cryosphere" system in the Arctic region, as well as Arctic system forecasting based on thermodynamic models with satellite data assimilation.

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Application of geoinformation technologies for arranging a satellite monitoring system

Geodesy and Cartography ◽

10.22389/0016-7126-2019-943-1-110-118 ◽

2019 ◽

Vol 943 (1) ◽

pp. 110-118

Author(s):

A.A. Kadochnikov

Keyword(s):

Remote Sensing ◽

Satellite Data ◽

Remote Sensing Data ◽

Web Gis ◽

Nature Management ◽

Satellite Monitoring ◽

Technological Support ◽

Sensing Data ◽

Territorial Planning ◽

Operational Information

Today, remote sensing data are an important source of operational information about the environment for thematic GIS, this data can be used for the development of water, forestry and agriculture management, in the ecology and nature management, with territorial planning, etc. To solve the problem of ensuring the effective use of the space activities’results in the Krasnoyarsk Territory a United Regional Remote Sensing Center was created. On the basis of the Center, a new satellite receiving complex of FRC KSC SB RAS was put into operation. It is currently receiving satellite data from TERRA, AQUA, Suomi NPP and FENG-YUN satellites. Within the framework in cooperation with the Siberian Regional Center for Remote Sensing the Earth, an archive of satellite data from domestic Resource-P and Meteor-M2 satellites was created. The work considers some features of softwaredevelopment and technological support tools for loading, processing and publishing remote sensing data. The product is created in the service-oriented paradigm based on geoportal technologies and interactive web-cartography. The focus in this article is paid to the peculiarities of implementing the software components of the web GIS, the efficient processing and presentation of geospatial data.

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Efficacy of Alternative Data Handling Methods of OBM Researchers

Journal of Organizational Behavior Management ◽

10.1300/j075v18n04_01 ◽

1999 ◽

Vol 18 (4) ◽

pp. 1-4 ◽

Cited By ~ 1

Author(s):

Thomas C. Mawhinney

Keyword(s):

Data Handling ◽

Handling Methods

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Missing Data Handling Methods

The Wiley Handbook of Psychometric Testing ◽

10.1002/9781118489772.ch6 ◽

2018 ◽

pp. 139-185 ◽

Cited By ~ 2

Author(s):

Craig K. Enders ◽

Amanda N. Baraldi

Keyword(s):

Missing Data ◽

Data Handling ◽

Handling Methods

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Grid Data Handling

IT Policy and Ethics ◽

10.4018/978-1-4666-2919-6.ch014 ◽

2013 ◽

pp. 294-321

Author(s):

Alexandru Costan

Keyword(s):

Fault Tolerance ◽

Data Storage ◽

Large Scale ◽

File Systems ◽

Future Research ◽

Distributed Data ◽

Data Handling ◽

Grid Data ◽

Distributed Data Storage ◽

Grid Environments

To accommodate the needs of large-scale distributed systems, scalable data storage and management strategies are required, allowing applications to efficiently cope with continuously growing, highly distributed data. This chapter addresses the key issues of data handling in grid environments focusing on storing, accessing, managing and processing data. We start by providing the background for the data storage issue in grid environments. We outline the main challenges addressed by distributed storage systems: high availability which translates into high resilience and consistency, corruption handling regarding arbitrary faults, fault tolerance, asynchrony, fairness, access control and transparency. The core part of the chapter presents how existing solutions cope with these high requirements. The most important research results are organized along several themes: grid data storage, distributed file systems, data transfer and retrieval and data management. Important characteristics such as performance, efficient use of resources, fault tolerance, security, and others are strongly determined by the adopted system architectures and the technologies behind them. For each topic, we shortly present previous work, describe the most recent achievements, highlight their advantages and limitations, and indicate future research trends in distributed data storage and management.

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