Design and Implementation of Support Production Logging Comprehensive Interpretation System Platform

2012 ◽  
Vol 457-458 ◽  
pp. 1326-1330
Author(s):  
Jiang Wu ◽  
Juan Ni ◽  
Xiao Jiao Yuan
Keyword(s):  
Data Management ◽  
Service Management ◽  
Information Gathering ◽  
Basic Information ◽  
Major Function ◽  
Design And Implementation ◽  
Data Formats ◽  
Integrated Platform ◽  
Interpretation System ◽  
Management Work

With the continuous development of logging interpretation technology, the basic information gathering from the logging, the logging documents and case knowledge, the result data from logging interpretation and so on are increasing massively, logging data management has gradually become an important oil-service management work. The Comprehensive interpretation of production logging support system platform develops in this paper, which major function lies in it provides an integrated platform for well logging data management, it provides software and data support for kinds of interpretation. At the same time it realizes the demand for process different data formats.

Reproducibility and efficiency in handling complex neurophysiological data

Neuroforum ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Michael Denker ◽  
Sonja Grün ◽  
Thomas Wachtler ◽  
Hansjörg Scherberger
Keyword(s):  
Best Practices ◽  
Data Management ◽  
Data Integrity ◽  
Behavioral Neuroscience ◽  
Data Set ◽  
Data Publication ◽  
Electrophysiological Data ◽  
Data Formats ◽  
Neurophysiological Data ◽  
Community Effort

Abstract Preparing a neurophysiological data set with the aim of sharing and publishing is hard. Many of the available tools and services to provide a smooth workflow for data publication are still in their maturing stages and not well integrated. Also, best practices and concrete examples of how to create a rigorous and complete package of an electrophysiology experiment are still lacking. Given the heterogeneity of the field, such unifying guidelines and processes can only be formulated together as a community effort. One of the goals of the NFDI-Neuro consortium initiative is to build such a community for systems and behavioral neuroscience. NFDI-Neuro aims to address the needs of the community to make data management easier and to tackle these challenges in collaboration with various international initiatives (e.g., INCF, EBRAINS). This will give scientists the opportunity to spend more time analyzing the wealth of electrophysiological data they leverage, rather than dealing with data formats and data integrity.

An Integrated Platform for Skin Cancer Heterogenous and Multilayered Data Management

2021 ◽  
Vol 45 (1) ◽  
Author(s):  
Ilias Maglogiannis ◽  
Georgia Kontogianni ◽  
Olga Papadodima ◽  
Haralampos Karanikas ◽  
Antonis Billiris ◽  
...  
Keyword(s):  
Skin Cancer ◽  
Data Management ◽  
Integrated Platform

Knowledge as a Service Framework for Collaborative Data Management in Cloud Environments - Disaster Domain

2016 ◽  
pp. 183-209 ◽  
Author(s):  
Katarina Grolinger ◽  
Emna Mezghani ◽  
Miriam A. M. Capretz ◽  
Ernesto Exposito
Keyword(s):  
Data Management ◽  
Service Oriented Architecture ◽  
Global Scale ◽  
Heterogeneous Data ◽  
Information Gathering ◽  
Current Data ◽  
Cloud Data ◽  
Related Data ◽  
Disaster Data ◽  
Service Oriented

Decision-making in disaster management requires information gathering, sharing, and integration by means of collaboration on a global scale and across governments, industries, and communities. Large volume of heterogeneous data is available; however, current data management solutions offer few or no integration capabilities and limited potential for collaboration. Moreover, recent advances in NoSQL, cloud computing, and Big Data open the door for new solutions in disaster data management. This chapter presents a Knowledge as a Service (KaaS) framework for disaster cloud data management (Disaster-CDM), with the objectives of facilitating information gathering and sharing; storing large amounts of disaster-related data; and facilitating search and supporting interoperability and integration. In the Disaster-CDM approach NoSQL data stores provide storage reliability and scalability while service-oriented architecture achieves flexibility and extensibility. The contribution of Disaster-CDM is demonstrated by integration capabilities, on examples of full-text search and querying services.

The Design and Implementation of Documentation Projects for Spoken Languages

2018 ◽  
pp. 146-167 ◽  
Author(s):  
Shobhana Chelliah
Keyword(s):  
Data Management ◽  
Planning Process ◽  
Institutional Support ◽  
Community Member ◽  
Language Documentation ◽  
Design And Implementation

The goal of this chapter is to provide a blueprint for planning a language documentation project. The scope is limited to the documentation of languages with average vitality but the chapter has relevance to other levels of endangerment as well. Language documentation is improved by key partnerships. By seeking out a supportive network of similarly motivated researchers, the language documenter can learn how to sequence and budget for documentation activities and how to plan workflow and data management so that dissemination and archiving goals are met. Implementing a documentation project as a lone academic or community member is possible, but having partners with complementary expertise can lead to the best results. Creating such teams requires funding and infrastructure so seeking out financial and institutional support is also part of the planning process for a documentation project.

VSDMIP: virtual screening data management on an integrated platform

2008 ◽  
Vol 23 (3) ◽  
pp. 171-184 ◽  
Author(s):  
Rubén Gil-Redondo ◽  
Jorge Estrada ◽  
Antonio Morreale ◽  
Fernando Herranz ◽  
Javier Sancho ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Data Management ◽  
Integrated Platform

scholarly journals Intelligent Data Management and Security in Cloud Computing

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3458
Author(s):  
Lidia Ogiela ◽  
Marek R. Ogiela ◽  
Hoon Ko
Keyword(s):  
Data Management ◽  
Data Sharing ◽  
Service Management ◽  
Secret Data ◽  
Data Services ◽  
New Class ◽  
Management Processes ◽  
Confidential Data ◽  
Shared Secret ◽  
Linguistic Methods

This paper will present the authors’ own techniques of secret data management and protection, with particular attention paid to techniques securing data services. Among the solutions discussed, there will be information-sharing protocols dedicated to the tasks of secret (confidential) data sharing. Such solutions will be presented in an algorithmic form, aimed at solving the tasks of protecting and securing data against unauthorized acquisition. Data-sharing protocols will execute the tasks of securing a special type of information, i.e., data services. The area of data protection will be defined for various levels, within which will be executed the tasks of data management and protection. The authors’ solution concerning securing data with the use of cryptographic threshold techniques used to split the secret among a specified group of secret trustees, simultaneously enhanced by the application of linguistic methods of description of the shared secret, forms a new class of protocols, i.e., intelligent linguistic threshold schemes. The solutions presented in this paper referring to the service management and securing will be dedicated to various levels of data management. These levels could be differentiated both in the structure of a given entity and in its environment. There is a special example thereof, i.e., the cloud management processes. These will also be subject to the assessment of feasibility of application of the discussed protocols in these areas. Presented solutions will be based on the application of an innovative approach, in which we can use a special formal graph for the creation of a secret representation, which can then be divided and transmitted over a distributed network.

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