Call for papers

The DataWiz workshop aims to collect research papers on several topics related to data visualization as one of the fundamental aspects for the analysis and display of the collected information. We are interested in collecting novel researches focused on approaches, techniques and tools able to improve the user experience related to the interaction with data, from the information visualization point of view.

The core concept of DataWiz workshop is the intrinsic connection between data visualization and data science, the study of extraction of knowledge and meaning from data.

 

All submissions should be formatted according to the official ACM SIG proceedings template and submitted via EasyChair. The review process will not be blind, therefore it is not necessary for submissions to be anonymized. Please be sure to submit keywords via EasyChair.

Submission category: research papers (4-6 pages), presenting innovative research ideas, preliminary results, system prototypes or industry showcases. Link or demo in attachment are preferred.

All accepted papers will be included in the Extended Proceedings of ACM Hypertext 2014 that will be published open-access at CEUR-WS.

 

All submitted papers must:

* be written in English;
* contain author names, affiliations, and email addresses;
* be in PDF (make sure that the PDF can be viewed on any platform).

 

LIST OF TOPICS INCLUDES, BUT IS NOT LIMITED TO:

  • data visualization and the Web
  • interactive data exploration
  • zooming, navigation and manipulation techniques
  • interfaces for computational sociology
  • scalable computational frameworks for data visualization
  • data streaming and real-time visualizations
  • geo-referenced data analysis
  • social media graphical analysis
  • visualization of mobility patterns
  • representation of human behavior
  • 2D and 3D representations of complex data
  • data journalism
  • representation and visualization of:
    • networks and other relational or structured data
    • time-varying and other multi-dimensional data sets
    • large amounts of text, multimedia content and other unstructured data

 

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