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Repurposing legacy data = innovative...

Berman, Jules J.,

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Repurposing legacy data = innovative case studies /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Repurposing legacy data/ Jules J. Berman.
Reminder of title:	innovative case studies /
Author:	Berman, Jules J.,
Published:	Amsterdam ;Elsevier, : 2015.,
Description:	1 online resource (vi, 160 p.) :ill.
[NT 15003449]:	Front Cover; Repurposing Legacy Data; Copyright Page; Contents; Author Biography; 1 Introduction; 1.1 Why Bother?; 1.2 What Is Data Repurposing?; 1.3 Data Worth Preserving; 1.4 Basic Data Repurposing Tools; 1.4.1 A Simple Text Editor; 1.4.2 Simple Programming Skills; 1.4.3 Data Visualization Utilities; 1.5 Personal Attributes of Data Repurposers; 1.5.1 Data Organization Methods; 1.5.2 Ability to Develop a Clear Understanding of the Goals of a Project; References; 2 Learning from the Masters; 2.1 New Physics from Old Data; 2.2 Repurposing the Physical and Abstract Property of Uniqueness.
[NT 15003449]:	2.3 Repurposing a 2,000-Year-Old Classification2.4 Decoding the Past; 2.5 What Makes Data Useful for Repurposing Projects?; References; 3 Dealing with Text; 3.1 Thus It Is Written; 3.2 Search and Retrieval; 3.3 Indexing Text; 3.4 Coding Text; References; 4 New Life for Old Data; 4.1 New Algorithms; 4.2 Taking Closer Looks; 4.3 Crossing Data Domains; References; 5 The Purpose of Data Analysis Is to Enable Data Reanalysis; 5.1 Every Initial Data Analysis on Complex Datasets Is Flawed; 5.2 Unrepeatability of Complex Analyses; 5.3 Obligation to Verify and Validate.
[NT 15003449]:	5.4 Asking What the Data Really MeansReferences; 6 Dark Legacy: Making Sense of Someone Else's Data; 6.1 Excavating Treasures from Lost and Abandoned Data Mines; 6.2 Nonstandard Standards; 6.3 Specifications, Not Standards; 6.4 Classifications and Ontologies; 6.5 Identity and Uniqueness; 6.6 When to Terminate (or Reconsider) a Data Repurposing Project; References; 7 Social and Economic Issues; 7.1 Data Sharing and Reproducible Research; 7.2 Acquiring and Storing Data; 7.3 Keeping Your Data Forever; 7.4 Data Immutability; 7.5 Privacy and Confidentiality; 7.6 The Economics of Data Repurposing.
Subject:	File organization (Computer science) -
Online resource:	https://www.sciencedirect.com/science/book/9780128028827
ISBN:	9780128029152 (electronic bk.)

Repurposing legacy data = innovative case studies /
Berman, Jules J.,

Repurposing legacy datainnovative case studies /[electronic resource] :Jules J. Berman. - Amsterdam ;Elsevier,2015. - 1 online resource (vi, 160 p.) :ill. - Computer science reviews and trends. - Computer science reviews and trends..

Includes bibliographical references and index.

Front Cover; Repurposing Legacy Data; Copyright Page; Contents; Author Biography; 1 Introduction; 1.1 Why Bother?; 1.2 What Is Data Repurposing?; 1.3 Data Worth Preserving; 1.4 Basic Data Repurposing Tools; 1.4.1 A Simple Text Editor; 1.4.2 Simple Programming Skills; 1.4.3 Data Visualization Utilities; 1.5 Personal Attributes of Data Repurposers; 1.5.1 Data Organization Methods; 1.5.2 Ability to Develop a Clear Understanding of the Goals of a Project; References; 2 Learning from the Masters; 2.1 New Physics from Old Data; 2.2 Repurposing the Physical and Abstract Property of Uniqueness.

Repurposing Legacy Data: Innovative Case Studies takes a look at how data scientists have re-purposed legacy data, whether their own, or legacy data that has been donated to the public domain. Most of the data stored worldwide is legacy data-data created some time in the past, for a particular purpose, and left in obsolete formats. As with keepsakes in an attic, we retain this information thinking it may have value in the future, though we have no current use for it. The case studies in this book, from such diverse fields as cosmology, quantum physics, high-energy physics, microbiology, psychiatry, medicine, and hospital administration, all serve to demonstrate how innovative people draw value from legacy data. By following the case examples, readers will learn how legacy data is restored, merged, and analyzed for purposes that were never imagined by the original data creators.

English.

ISBN: 9780128029152 (electronic bk.)Subjects--Topical Terms:

560051
File organization (Computer science)
Index Terms--Genre/Form:

542853
Electronic books.

LC Class. No.: QA76.9.F5 / B47 2015eb

Dewey Class. No.: 005.74/1

Repurposing legacy data = innovative case studies /
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245 1 0 $a Repurposing legacy data $h [electronic resource] : $b innovative case studies / $c Jules J. Berman.
260 $a Amsterdam ; $a Boston : $b Elsevier, $c 2015.
300 $a 1 online resource (vi, 160 p.) : $b ill.
490 1 $a Computer science reviews and trends
504 $a Includes bibliographical references and index.
505 0 $a Front Cover; Repurposing Legacy Data; Copyright Page; Contents; Author Biography; 1 Introduction; 1.1 Why Bother?; 1.2 What Is Data Repurposing?; 1.3 Data Worth Preserving; 1.4 Basic Data Repurposing Tools; 1.4.1 A Simple Text Editor; 1.4.2 Simple Programming Skills; 1.4.3 Data Visualization Utilities; 1.5 Personal Attributes of Data Repurposers; 1.5.1 Data Organization Methods; 1.5.2 Ability to Develop a Clear Understanding of the Goals of a Project; References; 2 Learning from the Masters; 2.1 New Physics from Old Data; 2.2 Repurposing the Physical and Abstract Property of Uniqueness.
505 8 $a 2.3 Repurposing a 2,000-Year-Old Classification2.4 Decoding the Past; 2.5 What Makes Data Useful for Repurposing Projects?; References; 3 Dealing with Text; 3.1 Thus It Is Written; 3.2 Search and Retrieval; 3.3 Indexing Text; 3.4 Coding Text; References; 4 New Life for Old Data; 4.1 New Algorithms; 4.2 Taking Closer Looks; 4.3 Crossing Data Domains; References; 5 The Purpose of Data Analysis Is to Enable Data Reanalysis; 5.1 Every Initial Data Analysis on Complex Datasets Is Flawed; 5.2 Unrepeatability of Complex Analyses; 5.3 Obligation to Verify and Validate.
505 8 $a 5.4 Asking What the Data Really MeansReferences; 6 Dark Legacy: Making Sense of Someone Else's Data; 6.1 Excavating Treasures from Lost and Abandoned Data Mines; 6.2 Nonstandard Standards; 6.3 Specifications, Not Standards; 6.4 Classifications and Ontologies; 6.5 Identity and Uniqueness; 6.6 When to Terminate (or Reconsider) a Data Repurposing Project; References; 7 Social and Economic Issues; 7.1 Data Sharing and Reproducible Research; 7.2 Acquiring and Storing Data; 7.3 Keeping Your Data Forever; 7.4 Data Immutability; 7.5 Privacy and Confidentiality; 7.6 The Economics of Data Repurposing.
520 $a Repurposing Legacy Data: Innovative Case Studies takes a look at how data scientists have re-purposed legacy data, whether their own, or legacy data that has been donated to the public domain. Most of the data stored worldwide is legacy data-data created some time in the past, for a particular purpose, and left in obsolete formats. As with keepsakes in an attic, we retain this information thinking it may have value in the future, though we have no current use for it. The case studies in this book, from such diverse fields as cosmology, quantum physics, high-energy physics, microbiology, psychiatry, medicine, and hospital administration, all serve to demonstrate how innovative people draw value from legacy data. By following the case examples, readers will learn how legacy data is restored, merged, and analyzed for purposes that were never imagined by the original data creators.
546 $a English.
588 0 $a Print version record.
650 0 $a File organization (Computer science) $3 560051
650 0 $a Database management. $3 527442
650 0 $a Information storage and retrieval systems. $3 576262
655 4 $a Electronic books. $2 lcsh $3 542853
830 0 $a Computer science reviews and trends. $3 2152115
856 4 0 $u https://www.sciencedirect.com/science/book/9780128028827