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*** APOLOGIES FOR CROSS POSTINGS ***

CALL FOR PAPERS
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IEEE Transactions on Big Data (TBD): http://www.computer.org/web/tbd
Special Issue on Big Scholar Data Discovery and Collaboration
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Important Dates:
** Mar. 31, 2015:  Paper Submission Due
** Jul. 1, 2015:  Author Notification
** Aug. 15, 2015: Revision Submission Due
** Oct. 1, 2015:  Camera-Ready Due

Editor-in-Chief
Qiang Yang, Hong Kong University of Science and Technology

Guest Editors
Yu-Ru Lin, University of Pittsburgh ([log in to unmask])
Hanghang Tong, Arizona State University ([log in to unmask])
Jie Tang, Tsinghua University ([log in to unmask])
K. Selçuk Candan, Arizona State University ([log in to unmask])

## Overview ##
Academics and researchers worldwide continue to produce large numbers of
scholarly documents including papers, books, technical reports, etc. and
associated data such as tutorials, proposals, and course materials. The
abundance of data sources enables researchers to study scholarly
collaboration at a very large scale. The ever increasing diversity of
disciplines and complexity of research problems, particularly
multi-disciplinary research, requires collaboration. Besides the
traditional venues of collaboration where scholars typically meet annually
at conferences or meetings, the Internet provides a wide range of platforms
for scholars to engage with other scholars. These new platforms include
academic search-oriented Web engines such as Google Scholar, social media
sites such as Academia.edu, ResearchGate and Mendeley, more interactive
social sites such as Twitter and Facebook, and Wiki-style virtual
collaboration sites. These services allow scholars to share academic
resources, exchange opinions, follow each other’s research, keep up with
current research trends, and build their professional networks. Researchers
increasingly realize that scholarly achievements should not merely be the
final published articles. The datasets used in study and many other
intermediary results are equally important for supporting research.
Therefore, a set of rapidly developing research topics, research data
management, data curation/stewardship, data sharing policy, etc. are
becoming important issues for research communities. This special issue aims
at bringing together researchers with diverse interdisciplinary backgrounds
interested in scholarly big data. In addition, this special issue will
feature a “Scholar Data Challenge” associated with a dataset consisting
over 2 million papers and more than 8 million citation relationships.
Submissions with a use of this dataset are optional. More details can be
found at: http://aminer.org/big-scholar-challenge/

## Topics ##
The topics of interest include, but are not limited to:
* Data analytical tools for studying scholarly discovery and collaboration,
including:
  - New approaches to measure and predict the impact of research and
researchers in a particular fields of study;
  - Searching and mining large digital libraries, repositories for
scholarly publications and patents and linking to other data sources such
as funded proposals and patents;
  - Novel data search and mining tools for studying scholarly collaboration
structure using big data, including scalable graph mining, etc.;
  - Data infrastructure that supports scalable computation, e.g., document
indexing with cloud computing services;
  - Algorithms for accessing, extracting and recommending scholarly
articles, experts and findings.
* Online scholar data platforms and systems consideration for scholarly
discovery and collaboration, including:
  - Heterogenous data source integration, especially with open-access,
novel datasets (e.g., Wikipedia, government census data, patent data, etc.);
  - Storage, indexing and query processing for research data;
  - Design considerations for effectively support scholars’ engagement in
using online and social platforms;
  - Social and collaborative support for scholarly discovery and
collaboration;
  - Privacy and security issues and management in online scholarly
collaboration.
* Digital data curation and management for scholarly discovery and
collaboration, including:
  - Issues and solutions to data curation, management, and archival;
  - Existing practices for managing research data;
  - Scalability and usability of managing research data
  - Research reproducibility and data sharing policy.
* Other aspects of scholarly discovery and collaboration, including:
  - Design of next generation collaboration platforms;
  - Information professionals’ role in engaging in online scholarly
collaboration;
  - Cultural and community acceptance and evaluation of activities in
online scholarly collaboration.

## Scholar Data Challenge ##
One of the greatest challenges is the difficulty of collecting massive
research dataset in the public domain. Hence, in addition to the above
topics, this special issue will feature a “Scholar Data Challenge”
associated with a dataset consisting over 2 million papers and more than 8
million citation relationships. The goal is to encourage approaches from
different fields to explore the disparate facets of the same datasets in
order to stimulate an interdisciplinary yet more focused research
discussion. Submissions with a use of this dataset are optional.
Information about the dataset can be found at:
http://aminer.org/big-scholar-challenge/

## Submission Information ##
All manuscripts must be directly submitted via the IEEE TBD submission web
site: https://mc.manuscriptcentral.com/tbd-cs
Submissions must follow instructions for formatting and length as regular
paper described at: http://www.computer.org/web/tbd/author

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