Rete-netzwerk-red: analyzing and visualizing scholarly networks using the Network Workbench Tool
Katy Börner (),
Weixia Huang,
Micah Linnemeier (),
Russell J. Duhon,
Patrick Phillips,
Nianli Ma (),
Angela M. Zoss,
Hanning Guo and
Mark A. Price
Additional contact information
Katy Börner: Indiana University
Weixia Huang: Indiana University
Micah Linnemeier: Indiana University
Russell J. Duhon: Indiana University
Patrick Phillips: Indiana University
Nianli Ma: Indiana University
Angela M. Zoss: Indiana University
Hanning Guo: Indiana University
Mark A. Price: Indiana University
Scientometrics, 2010, vol. 83, issue 3, No 20, 863-876
Abstract:
Abstract The enormous increase in digital scholarly data and computing power combined with recent advances in text mining, linguistics, network science, and scientometrics make it possible to scientifically study the structure and evolution of science on a large scale. This paper discusses the challenges of this ‘BIG science of science’—also called ‘computational scientometrics’ research—in terms of data access, algorithm scalability, repeatability, as well as result communication and interpretation. It then introduces two infrastructures: (1) the Scholarly Database (SDB) ( http://sdb.slis.indiana.edu ), which provides free online access to 22 million scholarly records—papers, patents, and funding awards which can be cross-searched and downloaded as dumps, and (2) Scientometrics-relevant plug-ins of the open-source Network Workbench (NWB) Tool ( http://nwb.slis.indiana.edu ). The utility of these infrastructures is then exemplarily demonstrated in three studies: a comparison of the funding portfolios and co-investigator networks of different universities, an examination of paper-citation and co-author networks of major network science researchers, and an analysis of topic bursts in streams of text. The article concludes with a discussion of related work that aims to provide practically useful and theoretically grounded cyberinfrastructure in support of computational scientometrics research, education and practice.
Keywords: Scientometrics; Science of science; Evolution of science; Computational scientometrics; Data access; Algorithm scalability; Cyberinfrastructure; Scholarly Database; Network Workbench; Related tools; Open source; Open access (search for similar items in EconPapers)
Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)
Downloads: (external link)
http://link.springer.com/10.1007/s11192-009-0149-0 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:scient:v:83:y:2010:i:3:d:10.1007_s11192-009-0149-0
Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11192
DOI: 10.1007/s11192-009-0149-0
Access Statistics for this article
Scientometrics is currently edited by Wolfgang Glänzel
More articles in Scientometrics from Springer, Akadémiai Kiadó
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().