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Steps Toward Large-Scale Data Integration in the Sciences: Summary of a Workshop [Pehme köide]

  • Formaat: Paperback / softback, 58 pages, kõrgus x laius: 229x152 mm
  • Ilmumisaeg: 01-Aug-2010
  • Kirjastus: National Academies Press
  • ISBN-10: 0309154421
  • ISBN-13: 9780309154420
Teised raamatud teemal:
  • Formaat: Paperback / softback, 58 pages, kõrgus x laius: 229x152 mm
  • Ilmumisaeg: 01-Aug-2010
  • Kirjastus: National Academies Press
  • ISBN-10: 0309154421
  • ISBN-13: 9780309154420
Teised raamatud teemal:
Steps Toward Large-Scale Data Integration in the Sciences summarizes a National Research Council (NRC) workshop to identify some of the major challenges that hinder large-scale data integration in the sciences and some of the technologies that could lead to solutions. The workshop was held August 19-20, 2009, in Washington, D.C.





The workshop examined a collection of scientific research domains, with application experts explaining the issues in their disciplines and current best practices. This approach allowed the participants to gain insights about both commonalities and differences in the data integration challenges facing the various communities. In addition to hearing from research domain experts, the workshop also featured experts working on the cutting edge of techniques for handling data integration problems. This provided participants with insights on the current state of the art. The goals were to identify areas in which the emerging needs of research communities are not being addressed and to point to opportunities for addressing these needs through closer engagement between the affected communities and cutting-edge computer science.

Table of Contents



Front Matter 1 Introduction 2 The Current State of Data Integration in Science 3 Improving Current Capabilities for Data Integration in Science 4 Success in Data Integration 5 Workshop Lessons References Appendixes Appendix A: Workshop Agenda Appendix B: Workshop Participants
1 Introduction
1(5)
2 The Current State Of Data Integration In Science
6(12)
Data Integration Goals
6(2)
Size and Other Characteristics of Some Scientific Data Sets
8(2)
Complexity of Data Sets
10(1)
Distributed Nature of the Data
11(1)
Metadata
12(1)
Data-Integration Tools
13(2)
Crosscutting Discussion
15(3)
3 Improving Current Capabilities For Data Integration In Science
18(13)
Federators
21(3)
Resource Description Framework
24(2)
MapReduce and Its Clones
26(2)
Data Management for Scientific Data
28(3)
4 Success In Data Integration
31(4)
Freebase
32(1)
Melbourne Health
32(1)
Science Commons and NeuroCommons
33(1)
Bio2RDF
34(1)
5 Workshop Lessons
35(3)
REFERENCES
38(5)
APPENDIXES
A Workshop Agenda
43(4)
B Workshop Participants
47