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Data Model Patterns: A Metadata Map

Data Model Patterns: A Metadata Map not only presents a conceptual model of a metadata repository but also demonstrates a true;

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The Map Library in New Millennium

In this authoritative and comprehensive new work, an international panel of experts cover a wide range of issues relating to map;

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Metadata Solutions

a comprehensive, start-to-finish guide to implementing metadata solutions. Leading data management consultant Adrienne Tannenbaum covers the;

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Database Modeling Step by Step

contemporary topics, the book opens with relational data modeling and ends with BigData database modeling following a road map of the evolution;

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Business Metadata: Capturing Enterprise Knowledge

, repository (metadata data warehouse) managers as well as vendors that have a metadata component as part of their systems or tools.

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Metadata

Find out what makes metadata an exciting addition to resource description Metadata: A Cataloger's Primer provides catalog librarians and;

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A proposed Web Indexing Model Based on Metadata

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Fundamentals of Data Warehouses

results of the European DWQ project, it offers a conceptual framework by which the architecture and quality of data warehousing efforts can be;

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Metadata and Semantic Research

presented were carefully reviewed and selected from 82 submissions. The papers are organized in the following tracks: metadata, linked data;

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Metadata and Semantics Research

are organized in several sessions and tracks: Digital Libraries, Information Retrieval, Linked and Social Data, Metadata and Semantics for;

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Digital Interactive TV and Metadata

services and content of digital TV effi. ciently and in a consumer-friendly way. Metadata means that the data are accompanied by other data which;

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Metadata

generate it every day. It is not, Pomerantz tell us, just data about data. It is a means by which the complexity of an object is represented in a;

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Relational and XML Data Exchange

Data exchange is the problem of finding an instance of a target schema, given an instance of a source schema and a specification of the;

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Big Data for Chimps

Hadoop. You'll gain a practical, actionable view of big data by working with real data and real problems. Perfect for beginners, this book's;

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Foundations of Data Exchange

mappings themselves? The last question is also known under the name 'metadata management', since mappings represent metadata, rather than data;

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Online GIS and Spatial Metadata

organizational challenges. Users no longer require specialized and expensive hardware, software and data, and they can access a GIS readily from almost;

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Implementing CDISC Using SAS

Shostak have updated their popular Implementing CDISC Using SAS, the first comprehensive book on applying clinical research data and metadata to;

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Implementing CDISC Using SAS

Shostak have updated their popular Implementing CDISC Using SAS, the first comprehensive book on applying clinical research data and metadata to;

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Data Model Resource Book Volume 3

Resource Book, Volume 3 Len and Paul look beneath the superficial issues of data modeling and have produced a work that is a must for every;

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Managing Metadata in Web-scale Discovery Systems

, METS, MODS, RDF and more. In Managing Metadata in Web-Scale Discovery Systems, editor Louise Spiteri and a range of international experts;

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MapReduce Design Patterns

some of the common design mistakes when modeling your Big Data architecture. This book also provides a complete overview of MapReduce that;

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Selection Models for Nonignorable Missing Data

is developed. This approach is unique in literature. The proposed model is extended to a model for longitudinal data.;

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A New Approach to English Pedagogical Grammar

This book proposes Meaning-order Approach to Pedagogical Grammar (MAP Grammar) as a practical pedagogical approach in ESL and EFL contexts;

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Concept Mapping

Looking for an easier path to care planning? Create a map! Concept mapping is a clear, visual, and systematic model for gathering and;

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Machine Learning Design Patterns

. You'll learn how to: Identify and mitigate common challenges when training, evaluating, and deploying ML models Represent data for different;

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Metadata and Semantic Research

data; metadata and semantics for agriculture, food, and environment; digital humanities and digital curation; cultural collections and;

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Using Artificial Neural Networks for Analog Integrated Circuit Design Automation

sizing as a direct map from specifications to the devices' sizes. Two separate ANN architectures are proposed: a Regression-only model and a;

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