SIOS Data Management System: distributed data system for Earth System Science

2021 ◽  
Author(s):  
Dariusz Ignatiuk ◽  
Øystein Godøy ◽  
Lara Ferrighi ◽  
Inger Jennings ◽  
Christiane Hübner ◽  
...  
Keyword(s):  
Data Management ◽  
Management System ◽  
Data Access ◽  
Data Management System ◽  
Data Series ◽  
Data Systems ◽  
Earth System ◽  
Data Repositories ◽  
Earth System Science ◽  
System Science

<p>Svalbard Integrated Arctic Earth Observing System (SIOS) is an international consortium to develop and maintain a regional observing system in Svalbard and the associated waters. SIOS brings together the existing infrastructure and data of its members into a multidisciplinary network dedicated to answering Earth System Science (ESS) questions related to global change. The Observing System is built around “SIOS core data” – long-term data series collected by SIOS partners. SIOS Data Management System (SDMS) is dedicated to harvesting information on historical and current datasets from collaborating thematic and institutional data centres and making them available to users. A central data access portal is linked to the data repositories maintained by SIOS partners, which manage and distribute data sets and their associated metadata. The integrity of the information and harmonisation of data is based on internationally accepted protocols assuring interoperability of data, standardised documentation of data through the use of metadata and standardised interfaces by data systems through the discovery of metadata. By these means, SDMS is working towards FAIR data compliance (making data findable, accessible, interoperable and reusable), among other initiatives through the H2020 funded ENVRI-FAIR project (http://envri.eu/envri-fair/).</p>

Sensor Grid Enhancement with Data Management System for Ubiquitous Healthcare Computing

2013 ◽  
pp. 184-210
Author(s):  
Nikolaos Preve
Keyword(s):  
Data Management ◽  
Network Architecture ◽  
Management System ◽  
Data Access ◽  
Sensor Nodes ◽  
Data Management System ◽  
Biomedical Sensors ◽  
Communication Ability ◽  
Open Geospatial Consortium ◽  
Network Technologies

A Wireless Sensor Network (WSN) can be deployed to monitor the health of patients suffering from critical diseases. A wireless network consisting of biomedical sensors can also be implanted into the patient's body and can monitor the patients' conditions. These sensor devices, apart from having an enormous capability of collecting data from their physical surroundings, are also resource constraint in nature with a limited processing and communication ability. Therefore, it is necessary to integrate them with the Grid technology in order to process and store the collected data by the sensor nodes. This chapter proposes the SEnsor Grid Enhancement Data Management system, called SEGEDMA, ensuring the integration of different network technologies and the continuous data access to system users. The main contribution of this work is to achieve the interoperability of both technologies through a novel network architecture ensuring also the interoperability of Open Geospatial Consortium (OGC) and HL7 standards. According to the results SEGEDMA can be applied successfully in a decentralized healthcare environment.

Data management for earth system science

1997 ◽  
Vol 26 (1) ◽  
pp. 27-31 ◽  
Author(s):  
James Frew ◽  
Jeff Dozier
Keyword(s):  
Data Management ◽  
Earth System ◽  
Earth System Science ◽  
System Science

scholarly journals Bringing introspection into BlobSeer: Towards a self-adaptive distributed data management system

2011 ◽  
Vol 21 (2) ◽  
pp. 229-242 ◽  
Author(s):  
Alexandra Carpen-Amarie ◽  
Alexandru Costan ◽  
Jing Cai ◽  
Gabriel Antoniu ◽  
Luc Bougé
Keyword(s):  
Data Management ◽  
Management System ◽  
Large Scale ◽  
Data Access ◽  
Relevant Information ◽  
Data Management System ◽  
Specific Information ◽  
Distributed Data ◽  
Distributed Data Management ◽  
Self Adaptive

Bringing introspection into BlobSeer: Towards a self-adaptive distributed data management system Introspection is the prerequisite of autonomic behavior, the first step towards performance improvement and resource usage optimization for large-scale distributed systems. In grid environments, the task of observing the application behavior is assigned to monitoring systems. However, most of them are designed to provide general resource information and do not consider specific information for higher-level services. More precisely, in the context of data-intensive applications, a specific introspection layer is required to collect data about the usage of storage resources, data access patterns, etc. This paper discusses the requirements for an introspection layer in a data management system for large-scale distributed infrastructures. We focus on the case of BlobSeer, a large-scale distributed system for storing massive data. The paper explains why and how to enhance BlobSeer with introspective capabilities and proposes a three-layered architecture relying on the MonALISA monitoring framework. We illustrate the autonomic behavior of BlobSeer with a self-configuration component aiming to provide storage elasticity by dynamically scaling the number of data providers. Then we propose a preliminary approach for enabling self-protection for the BlobSeer system, through a malicious client detection component. The introspective architecture has been evaluated on the Grid'5000 testbed, with experiments that prove the feasibility of generating relevant information related to the state and behavior of the system.

scholarly journals <i>Preface</i>Earth System Science Data access, distribution and use for education and research

2006 ◽  
Vol 8 ◽  
pp. 1-1
Author(s):  
E. Cutrim ◽  
M. Ramamurthy ◽  
S. Nativi ◽  
L. Miller
Keyword(s):  
Data Access ◽  
Earth System ◽  
Science Data ◽  
Earth System Science ◽  
System Science

Risk Management on Information Security in ABC Company

2017 ◽  
Vol 4 (1) ◽  
pp. 62-66
Author(s):  
Luyen Ha Nam
Keyword(s):  
Risk Management ◽  
Information Security ◽  
Data Management ◽  
Management System ◽  
Risk Mitigation ◽  
Data Management System ◽  
Data Centre ◽  
Long Time ◽  
Mitigation Action ◽  
Better Than

From long, long time ago until nowadays information still takes a serious position for all aspect of life, fromindividual to organization. In ABC company information is somewhat very sensitive, very important. But how wekeep our information safe, well we have many ways to do that: in hard drive, removable disc etc. with otherorganizations they even have data centre to save their information. The objective of information security is to keep information safe from unwanted access. We applied Risk Mitigation Action framework on our data management system and after several months we have a result far better than before we use it: information more secure, quickly detect incidents, improve internal and external collaboration etc.

Benchmarking and Analyzing the Energy Consumption of Cloud Data Management System

2014 ◽  
Vol 36 (7) ◽  
pp. 1485-1499 ◽  
Author(s):  
Jie SONG ◽  
Tian-Tian LI ◽  
Zhi-Liang ZHU ◽  
Yu-Bin BAO ◽  
Ge YU
Keyword(s):  
Energy Consumption ◽  
Data Management ◽  
Management System ◽  
Data Management System ◽  
Cloud Data ◽  
Cloud Data Management
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