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eSoN 2013 : Analyzing and Improving Collaborative eScience with Social Networks


When Oct 22, 2013 - Oct 22, 2013
Where Beijing, China
Submission Deadline Jul 5, 2013
Notification Due Jul 26, 2013
Final Version Due May 5, 2013
Categories    social networks   escience   collaboration

Call For Papers

Call for Papers: Analyzing and Improving Collaborative eScience with Social Networks (eSoN 13)
October 22, Beijing, China (
Co-Located with eScience 2013, October 22-25, Beijing, China (


Paper Submissions Due: July 5, 2013
Notification of Acceptance: July 26, 2013
Camera Ready Versions Due: August 5, 2013
Workshop: October 22, 2013


Social networking is profoundly changing the way that people communicate and interact on a daily basis. As eScience is inherently collaborative, social networks can serve as a vital means for supporting information and resource sharing, aiding discovery of connected researchers, improving communication between globally dispersed individuals, and even measuring scientific impact. Consequently, eScience systems are increasingly integrating social networking concepts to improve collaboration. For example, researcher profiles and groups exist in publication networks, such as VIVO, Google Scholar and Mendeley, and eScience infrastructures, such as MyExperiment, NanoHUB and GlobusOnline all utilize social networking principles to enhance scientific collaboration. In addition to incorporating explicit social networks, eScience infrastructures can also leverage implicit social networks extracted from relationships expressed in collaborative activities (e.g. publication authorship or citation networks).

This workshop aims to bring together researchers from a diverse range of areas to establish a new community focused on the application of social networking to analyze and improve scientific collaboration. There are two complementary areas of focus for this workshop 1) how to efficiently share information, infrastructure and software resources, such as data and tools through social networks, and 2) how to analyze and enhance scientific collaboration through implicit and explicit social networks, for example analyzing scientific impact through citation networks or improving collaboration by associating data and tools with networks of publications and researchers.


The topics of interest are, but not limited to, the use of social networks to analyze and improve collaborative eScience:
• The use of social networks and social networking concepts in eScience
• Social network applications used for eScience
• Social network based resource sharing and collaboration architectures
• New forms of collaborative computing and resource sharing
• Crowdsourcing of scientific applications using social media
• Social Cloud computing
• Novel applications of digital relationships and trust
• Definition of novel principals, models and methodologies for harnessing digital relationships
• Extraction of implicit social networks from scientific activities (e.g. publication, citation and grants)
• Analysis of collaborative scientific activity through social networks


Authors are invited to submit papers containing unpublished, original work (not under review elsewhere) of up to 8 pages of double column text using single spaced 10 point size on 8.5 x 11 inch pages, as per IEEE 8.5 x 11 manuscript guidelines.
Templates are available from:
Authors should submit a PDF file that will print on a PostScript printer. Papers conforming to the above guidelines can be submitted through the workshop's paper submission system:
At least one author of each accepted submission must attend the workshop and all workshop participants must pay the eScience 2012 registration fee. It is expected that all accepted papers will be published by the IEEE in the same volume as the main conference. All papers will be reviewed by an International Programme Committee (with a minimum of 3 reviews per paper). Papers submissions should be performed using the easychair system, by the date mentioned above.

• Kyle Chard, University of Chicago & Argonne National Laboratory, USA
• Tanu Malik, University of Chicago & Argonne National Laboratory, USA
• Simon Caton, Karlsruhe Institute of Technology, Karlsruhe, Germany
• Wei Tan, IBM T.J. Watson Lab, USA

• Christine Borgman, University of California, Los Angeles, USA
• Ian Foster, University of Chicago & Argonne National Laboratory, USA
• Gerhard Klimeck, Purdue University, USA
• Omer Rana, Cardiff University, UK

• Kris Bubendorfer, Victoria University of Wellington, New Zealand
• Junwei Cao, Tsinghua University, China
• Justin Cappos, Polytechnic Institute of New York, USA
• Zhen Chen, Tsinghua University, China
• Nicolas Kourtellis, University of South Florida, USA
• Xitong Li, MIT, USA
• Xuanzhe Liu, Peking University
• Nicholas Loulloudes, University of Cyprus, Cyprus
• Paolo Missier, Newcastle University, UK
• Iman Saleh Moustafa, University of Miami, USA
• Victoria Stodden, Columbia University, USA
• Jie Tang, Tsinghua University, China
• Michela Taufer, University of Deleware, USA
• Jianwu Wang, San Diego Supercomputer Center, USA
• Wenjun Wu, Beihang University, China
• Hui Zhang, Bejing University, China

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