Scientometrics
Volume/Issue:
Volume 83: Issue 3
Rete-netzwerk-red: analyzing and visualizing scholarly networks using the Network Workbench Tool
Authors:
Katy Börner Indiana University Cyberinfrastructure for Network Science Center, School of Library and Information Science Bloomington IN USA

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Weixia Huang Indiana University Cyberinfrastructure for Network Science Center, School of Library and Information Science Bloomington IN USA

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Micah Linnemeier Indiana University Cyberinfrastructure for Network Science Center, School of Library and Information Science Bloomington IN USA

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Russell Duhon Indiana University Cyberinfrastructure for Network Science Center, School of Library and Information Science Bloomington IN USA

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Patrick Phillips Indiana University Cyberinfrastructure for Network Science Center, School of Library and Information Science Bloomington IN USA

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Nianli Ma Indiana University Cyberinfrastructure for Network Science Center, School of Library and Information Science Bloomington IN USA

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Angela Zoss Indiana University Cyberinfrastructure for Network Science Center, School of Library and Information Science Bloomington IN USA

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Hanning Guo Indiana University Cyberinfrastructure for Network Science Center, School of Library and Information Science Bloomington IN USA

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Mark Price Indiana University Cyberinfrastructure for Network Science Center, School of Library and Information Science Bloomington IN USA

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Pages:
863–876
Online Publication Date:
05 Jan 2010
Publication Date:
01 Jun 2010
Article Category:
Research Article
DOI:
https://doi.org/10.1007/s11192-009-0149-0
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
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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.

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Cover Scientometrics
Scientometrics
Print ISSN:
0138-9130
Online ISSN:
1588-2861

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Manuscript submission: http://www.editorialmanager.com/scim/

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Scientometrics
Language English
Size B5
Year of
Foundation		 1978
Volumes
per Year		 1
Issues
per Year		 12
Founder Akadémiai Kiadó
Founder's
Address		 H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Publisher Akadémiai Kiadó
Springer Nature Switzerland AG
Publisher's
Address		 H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
CH-6330 Cham, Switzerland Gewerbestrasse 11.
Responsible
Publisher		 Chief Executive Officer, Akadémiai Kiadó
ISSN 0138-9130 (Print)
ISSN 1588-2861 (Online)

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