- The deadline for submission (of regular papers) is extended to Jan 22,
2016.

- There will be a show-and-tell session for participants to demonstrate
their Big Scholarly Data tools and visualization systems. MSR is about to
demonstrate Microsoft Academic Graph/API (research.microsoft.com/mag) in
this session.

 

 

[Please accept our apologies if you received multiple copies of this call]

 

CALL FOR PAPERS

 

BigScholar 2016

The Third WWW Workshop on Big Scholarly Data: Towards the Web of Scholars

http://msclab.org/bigscholar/

 

A workshop of WWW 2016 (The 25th International World Wide Web Conference)

Montreal, Canada, April 11-15, 2016

 

Researchers worldwide are currently producing more and more scholarly data
of various types such as papers, books, patents, etc. Such data are big data
by nature. For example, the DBLP Computer Science Bibliography and the
Microsoft Academic Graph/API (research.microsoft.com/mag) provide
bibliographic information on major computer science journals and
proceedings. DBLP and MAG index more than 3 and 100 million articles,
respectively, with records containing title, pages, years and authors’
information, etc. Concurrently, scholars are associated with various
academic activities such as conferences, workshops, congresses, peer review
and so on. Such scenarios have motivated us to also explore the Web of
Scholars in the context of big scholarly data on a global scale. It is
imperative and vital for researchers to drive their knowledge towards the
innovative generation of values from Big Scholarly Data. The emerging
worldwide Web of Scholars demands a re-evaluation of existing techniques,
such as data mining, recommender systems and social network analysis.
Furthermore, there is the demand for novel ways of developing algorithms,
methods and techniques to foster the analysis and interpretation of social
environments such as academic collaboration networks. 

 

The BigScholar 2016 workshop aims at bringing together researchers and
practitioners working on Big Scholarly Data to discuss what are emerging
research issues and how to explore the Web of Scholars. Several core
challenges, such as the tools and methods for analyzing and mining scholarly
data will be the main center of discussions at the workshop. The goal is to
contribute to the birth of a community having a shared interest around the
Web of Scholars and exploring it using data mining, recommender systems,
social network analysis and other appropriate technologies. 

 

The workshop will be a full-day workshop. The format of the workshop will
include one invited talk (keynote), research and position paper
presentations,one discussion panel, and a show-and-tell session for
participants to demonstrate their Big Scholarly Data tools and visualization
systems. Short videos accompanying a live demonstration are highly
encouraged. The workshop will be held in April 2016 in Montreal, Canada, in
conjunction with the 25th International World Wide Web Conference (WWW
2016).

 

In this workshop, we will explore the most promising areas of research in
big scholarly data, with focus on major foci of the rapidly emerging field
of the Web of Scholars. This workshop also seeks to answer noteworthy
research questions such as: 

- How to model the Web of scholars?

- How to connect scholars on the Web? 

- How to measure impact of publications, researchers, groups, or
institutions? 

- How to visualize Big Scholarly Data for insights and analytics?

- How to utilize the Web of Scholars to improve the way research is being
done?

 

Researchers are welcome to submit highly interesting and quality papers that
address these questions above and other topics below which may include, but
are not limited to: 

- Academic social network analysis

- Scientific measurement

- Scholarly data management

- Digital infrastructures for accessing scholarly data

- Methods and tools for analyzing and visualizing big scholarly data

- Indexing, searching, and mining scholarly data

- Connecting scholars using a Web approach

- Paradigms to promote scientific collaboration

- Scientific trends prediction

- Web tools and techniques for big scholarly data

- Systems, platforms, and services exploring the Web of Scholars

- Applications and use cases of big scholarly data

 

 

IMPORTANT DATES:

Paper Submission Deadline: January 22, 2016

Author Notification: February 2, 2016 

Final Manuscript: February 8, 2016

 

SUBMISSION INSTRUCTIONS:

Authors are invited to submit original papers that must not have been
submitted to or published in any other workshop, conference, or journal. The
workshop will accept full papers describing completed work, work-in-progress
papers with preliminary results, as well as position papers reporting
inspiring and intriguing new ideas.  

 

All submitted papers must: 

* be written in English; 

* contain author names, affiliations, and email addresses; 

* be formatted according to the ACM SIG Proceedings
template(http://www.acm.org/sigs/publications/proceedings-templates) with a
font size no smaller than 9pt; 

* be in PDF (make sure that the PDF can be viewed on any platform), and
formatted for US Letter size; 

* occupy no more than six pages, including the abstract, references, and
appendices. 

 

It is the authors' responsibility to ensure that their submissions adhere
strictly to the required format. 

Submissions that do not comply with the above guidelines may be rejected
without review. 

 

All submissions will be peer-reviewed by members of the Program Committee
and be evaluated for originality, quality and appropriateness to the
workshop. At least one author of each accepted papers must present their
work at the workshop. All accepted and presented papers will be published in
the Companion Proceedings of the WWW 2016 conference, through the ACM
Digital Library. Extended versions of selected papers will be considered for
publication in special issues of SCI-index international journals. 

 

 

Please submit your paper here:

https://www.easychair.org/conferences/?conf=bigscholar2016

 

 

Organizers: 

Feng Xia, Dalian University of Technology, China

Huan Liu, Arizona State University, USA

Irwin King, The Chinese University of Hong Kong, Hong Kong

Kuansan Wang, Microsoft Research, USA

 

 

Contact Info:

Email: [log in to unmask]

 

 

 


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