Könyv Visualizing the Structure of Science Benjamín Vargas-Quesada

Visualizing the Structure of Science

Nyelv: Angol
Kötés: Kemény kötésű
Elérhetőség: Beszállítói készleten
Küldés 10-13 napon belül
57 446 Ft
This book presents a methodology for visualizing large scientific domains. Authors Moya-Anegón and V...

Információk a könyvről

Nyelv
Angol
Kötés
Könyv - Kemény kötésű
Kiadva
2007
oldal
312
EAN
9783540697275
ISBN
3540697276
Enbook ID
01567961
Súly
647
Méretek
155 x 235 x 22

Teljes leírás

This book presents a methodology for visualizing large scientific domains. Authors Moya-Anegón and Vargas-Queseda create science maps, so-called "scientograms", based on the interactions between authors and §their papers through citations and co-citations, using approaches such as domain analysis, social networks, cluster analysis and pathfinder networks. The resulting scientograms offer manifold possibilities.Constructing a great map of the sciences has been a persistent dream since the Middle Ages. In modern times this need has become even more urgent because of the requirement to combine and link research in adjacent areas, often resulting in new disciplines such as bioinformatics and nanotechnologies. Computer visualization helps humans to perceive and understand large and complex structures, such as molecular structures or data dependencies.§Vargas-Quesada and Moya-Anegón propose a methodology for visualizing large scientific domains. They create science maps, so-called "scientograms", based on the interactions between authors and their papers through citations and co-citations, using approaches such as domain analysis, social networks, cluster analysis and pathfinder networks. The resulting scientograms offer manifold possibilities. Domain analysts can discover the most significant connections between categories of a given domain, and they can also see how these categories are grouped into major thematic areas and how they are interrelated through a logical internal, while information scientists or researchers new to an area may appreciate a durable image of the essential structure of a domain.

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