From: Big Data <[log in to unmask]>
Sent: 03 November 2015 10:01
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Subject: Call for Papers: Special Issue on Visualization in Data Science

[This special issue is expected to be published in March 2016.]<http://click.liebertpubmail.com/?qs=f73ace2b5cd0f3cf961434a94c5085b21c7466b4655da337224e51e7b31b78bf3a7276edf1f66b7c>
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Big Data<http://click.liebertpubmail.com/?qs=f73ace2b5cd0f3cfd6fb1aee87a3308fdf2fb48a561277363fda558313a80c966164b0ae828b9448>

Editor-in-Chief: Vasant Dhar

The Journal editorial team invites you to publish your manuscript in Big Data special issue on Visualization in Data Science.

Manuscript submissions due: January 1, 2016
For questions, please contact Guest Editors:

Enrico Bertini<mailto:[log in to unmask]>
Assistant Professor
NYU Polytechnic School of Engineering
Department of Computer Science and Engineering

Ross Maciejewski<mailto:[log in to unmask]>
Assistant Professor
Arizona State University
School of Computing, Informatics & Decision Systems Engineering

Adam Perer<mailto:[log in to unmask]>
Research Scientist
IBM T.J. Watson Research Center

This Big Data<http://click.liebertpubmail.com/?qs=f73ace2b5cd0f3cf14a57d87dcbcee6803e60b7d671c3b52d52815025e55180eff4c585596697ee3> special issue on Visualization in Data Science, expected to be published in March 2016, will showcase research in which data visualization is used to solve a data science problem. The special issue has a primary aim to describe and discuss:

1. Successful examples of data visualization use in data science problems, especially cases in which the impact of visualization can be assessed or quantified.

2. Visualization methods data science practitioners can use and adopt to improve data model generation, parameterization, testing, deployment and understanding.

The work to be highlighted in this issue should demonstrate impact and potential for visualization to improve data science. Papers that focus on real problems, use real data, and are deployed in real settings (or are in the process of being deployed) are especially welcome.

Areas of focus include, but are not limited to:

  *   Visualization as a way to gain insight into machine learning models
  *   Interactive visual machine learning methods and systems
  *   Visualization for feature extraction and feature selection
  *   Visualization for data preparation and data quality
  *   Visualization for model building, parameterization and testing
  *   Visualization as a means to communicate data science results to third parties
  *   Visualization as a tool for data science education and explanation
  *   Theoretical models and taxonomies modeling the use of visualization in data science
  *   Evaluation methods for visualization in data science
  *   Case studies describing the use of visualization to solve real-world data science problems (e.g., in healthcare, bioinformatics, security, business, finance, city management)

Following the tradition of the top-tier visualization conferences, we accept technical papers of the following types:

  *   Novel methods and techniques that integrate interactive visualization with automated data analysis.
  *   Theoretical models and taxonomies describing the use of visualization in data science.
  *   Evaluation and empirical research demonstrating advantages and possible disadvantages of using visualization in data science.
  *   Case studies describing the deployment and use of visualization in a real-world data science problem.

We also accept well-articulated and thorough position papers that highlight existing challenges and/or propose future solutions for the use of visualization in data science.

We encourage institutions and organizations that may not typically write research papers to submit to this special issue. We are especially interested in papers discussing the use of visualization in real-world settings. In addition to submissions from academia and corporations, we encourage submissions from government agencies, non-profits, and foundations.

Advantages of publishing in Big Data include:

  *   Fast and user-friendly electronic submission
  *   Maximum exposure: accessible in 170 countries worldwide
  *   Rapid, high-quality peer review
  *   Open Access options available

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