3 edition of Research to support intelligent data management found in the catalog.
Research to support intelligent data management
by National Aeronautics and Space Administration, National Technical Information Service, distributor in [Washington, DC, Springfield, Va
Written in English
|Series||[NASA contractor report] -- CR-1999-209464., NASA contractor report -- NASA CR-209464.|
|Contributions||United States. National Aeronautics and Space Administration.|
|The Physical Object|
Access to a fully-integrated quality management database across your value chain. Hierarchy structures support to site-specific reporting and multi-site and division results. Data import or export to outside sources such as your ERP, PLM, CRM, and HR systems. Staging support to migrate reports from development to validation to production. Prospects for Research Data Management Martin Halbert The challenge of ensuring long-term preservation of and ac-cess to the outputs of scientific research, especially data sets produced by publicly funded research projects, has become a prominent topic .
Research Data Management and Support Make your research data discoverable with University of Leicester, Institutional Data Repository powered by Figshare. Share this page: Navigation. Research Data Figshare for Data user guide; What is Research Data Management?. Guide to Intelligent Data Analysis How to Intelligently Make Sense of Real Data. Authors but starving for knowledge" the branch of research known as data analysis has emerged, and a considerable number of methods and software tools have been developed. Provides a review of the basics of classical statistics that support and justify many.
Intelligent Data Mining and Fusion Systems in Agriculture presents methods of computational intelligence and data fusion that have applications in agriculture for the non-destructive testing of agricultural products and crop condition ns cover the combination of sensors with artificial intelligence architectures in precision agriculture, including algorithms, bio-inspired. Research data management (RDM), a term that encompassess activities related to the storage, organization, documentation, and dissemination of data*1, is central to eﬀorts aimed at maximizing the value of scientiﬁc investment (e.g. Holdren ) and addressingCited by: 3.
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Examination of financial statements for the year ended December 31, 1973, Federal Home Loan Bank Board, Federal Home Loan Banks, Federal Savings and Loan Insurance Corporation
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functions of international conflict
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The number of images including remote sensing data, mammograms, CAT scans, NMR's, fingerprints, commercial radar, etc., generated daily in both the public and the private sector is increasing dramatically.
Digital scanners and other devices are used to convert these images to digital arrays allowing them to be represented on a computer. The Library Research Support team's checklists for new projects provide guidance on how to comply with funders' policies for Research Data Management and Open Access publishing both while bidding for funding and once funding has been awarded.
Data intelligence is a new interdisciplinary field that synthesizes areas such as big data management, data mining, machine learning, human-computer interaction, and data visualization.
Research in data intelligence aims to provide theories, methodologies, technologies, and systems for obtaining insightful and actionable intelligence from data. Intelligent big data analytics is an emerging paradigm in the age of big data, analytics, and artificial intelligence (AI).
This chapter explores intelligent big data analytics from a managerial Author: Zhaohao Sun. Quantum is committed to delivering intelligent data management for genomics, bioinformatics and medical imaging workflows—from data capture to analysis to archive and beyond.
With storage infrastructure that provides the right combination of speed, scale, access and cost, we enable you to focus on what you do best—science.
Intelligent Data Analysis for e-Learning: Enhancing Security and Trustworthiness in Online Learning Systems addresses information security within e-Learning based on trustworthiness assessment and prediction.
Over the past decade, many learning management systems have appeared in. The book is divided into five major parts: Part I “Fundamentals and Concepts” details the motivation behind and core concepts of real-time linked dataspaces, and establishes the need to evolve data management techniques in order to meet the challenges of enabling data ecosystems for intelligent systems within smart : Springer International Publishing.
enhanced as data management ensures that research data and records are accurate, consistent, complete, authentic and reliable. It also allows for reproducibility of results. As a side effect data management planning streamlines data handling and can Figure 1: Loss of.
The latest research on this subject is concisely presented within the book, with several figures to support the text. Will be of interest to attendees of The Intelligence and Security Informatics conference series, which include IEEE International Conference on Intelligence and Security Informatics (IEEE ISI).
For the aspiring Data Management Professional, or indeed for anyone involved in framing or executing a data project, DAMA International () and this book the “Data Management Body of Knowledge v2” is an excellent starting point/5(75).
Goal: Research Centre for Big Data Analytics and Intelligent Systems (BAIS) has been founded today. BAIS aims to develop novel techniques. A marketing decision support system (sometimes abbreviated MKDSS) is a decision support system for marketing activity. The system is used to help businesses explore different scenarios by manipulating already collected data from the past events.
It consists of information technology, marketing data, systems tools,and modeling capabilities that enable the it to provide predicted outcomes from. This monograph presents new intelligent data management methods and tools, such as the support vector machine, and new results from the field of inference, in particular of causal modeling.
In 11 well-structured chapters, leading experts map out the major tendencies and future directions of. Intelligent Software Agents and Creativity. Implementing and Integrating Management Support Systems.
Organizational and Societal Impacts of Management Support Systems. For managers interested in Decision Support Systems, Computerized Decision Making, and Management Support Systems.
Data Management for Researchers includes sections on: * The data problem – an introduction to the growing importance and challenges of using digital data in research.
Covers both the inherent problems with managing digital information, as well as how the research landscape is changing to give more value to research datasets and by: 5.
The series "Advances in Intelligent Systems and Computing" contains publications on theory, applications, and design methods of Intelligent Systems and Intelligent Computing.
learning paradigms, machine ethics, intelligent data analysis, knowledge management, intelligent agents, intelligent decision making and support, intelligent network.
Best practices involving multi-source data integration into a single-view, semantic-search enabled knowledge repository, Enterprise Business Intelligence, and Big Data Analytics Data Visualization Creative visualization and interaction with unified data, real-time charting & reporting, and DIY dashboards using proprietary and industry-standard.
Intelligent Data Management Consulting & Services i-DM, Intelligent Data Management Consulting & Services is a foundation for world class data centers, and enterprise systems.
Our team specializes in data integration within the data center infrastructure, critical facility systems, and enterprise management used in IoT & Big Data applications.
About the Author. Fern Halper, Ph.D., is well known in the analytics community, having published hundreds of articles, research reports, speeches, webinars, and more on data mining and information technology over the past 20 is also co-author of several “Dummies” books on cloud computing, hybrid cloud, and big data.
She is VP and senior research director, advanced. The purpose of this book is to bring together researchers in related fields such as information systems, distributed artificial intelligence (AI), intelligent agents, machine learning, collaborative work, to explore various aspects of IIS design and implementation, as well as to share experiences and lessons learned in deploying intelligent.
What is Intelligent Data? Definition of Intelligent Data: Data that are automatically acquired through advanced application technologies (smart sensors, intelligent transducers, electronic gadgets, equipment with advanced functionalities, etc.), systematically processed, and are presented in a meaningful form for active sharing, further assessments, and following interpretations.The Dell™ Intelligent Data Management (IDM) strategy is being delivered platforms, features, and technologies in part to avoid increasing support costs.
Yet each refresh can involve complex data migrations and additional expenditures for the repurchase of software licenses. Managing Research Data. Graham Pryor, editor. Data management is an active process by which digital resources remain discoverable, accessible and intelligible over the longer term, a process that invests data and datasets with the potential to accrue value as assets enjoying far wider use than their creators may have anticipated.