Visualizing the Structure of Science

ISBN-13: 9783540697275 / Angielski / Twarda / 2007 / 312 str.

Benjamin Vargas-Quesada; Felix De Moya-Anegon

Opis

This book presents a methodology for visualizing large scientific domains. Authors Moya-Anegon 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.

Recenzje

From the reviews:

"Numerous aspects of the book are unequivocally so new ... . Just about anyone involved in Information Technology and Documentation Sciences will be fascinated by this new approach ... . The well-stocked Bibliography will permit novices an easy entry into this new research field ... . The book's excellent overview of a difficult subject matter is highly recommended to experts. ... the philosophy, methodology, technology, science and pedagogy presented are unique and important! To the authors: congratulations!" (Karl H. Wolf, International Journal of General Systems, 2008)

Spis treści

Visualization.- Visualization of Scientific Information and Domain Analysis.- Methodological Aspects Previous to Scientography.- Material Used.- Methodology.- Results.- Discussion.- Epilogue.

Blurb

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.