Number of Software tools in Information Visualization is sky rocketing. End-users have different factors that affect their decision to select a software tool and how it will meet their requirements. This questionnaire and Responses will help to thorough understand factors that affect non-technical people and end users when selecting Information Visualization software tool. These will be the main input to a new model that can categorize Information Visualization tools. Consequently, end users will get list of candidate tools that meet their visualization requirement. https://goo.gl/forms/nr9EatyDRNh4Hon43 All questions are direct and clear, though we ask you to try to answer each of them as best as you can. This work is under supervision of researchers at the University of Kadir Has/ Turkey. If you have questions or comments, please contact Mr. Omran (20151708049@stu. khas.edu.tr), Dr. Yetkin (fatih.yetkin@khas.edu.tr). Thanks! On Tue, Feb 5, 2019, 1:00 PM <infovis-request@infovis.org wrote:
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Today's Topics:
1. Deadline extended to 1 Apr 2019 - CFP: IEEE CG&A Special Issue on "Provenance and Logging for Sense Making" (Kai Xu)
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Message: 1 Date: Mon, 4 Feb 2019 17:22:54 +0000 From: Kai Xu <K.Xu@mdx.ac.uk> To: "chi-Announcements@acm.org" <chi-Announcements@acm.org>, "ieee_vis@listserv.uni-tuebingen.de" <ieee_vis@listserv.uni-tuebingen.de>, "infovis@infovis.org" <infovis@infovis.org> Cc: Melanie Tory <mtory@tableau.com>, Jean-Daniel Fekete <Jean-Daniel.Fekete@inria.fr>, "T.J. Jankun-Kelly" <tjk@acm.org> Subject: [Infovis] Deadline extended to 1 Apr 2019 - CFP: IEEE CG&A Special Issue on "Provenance and Logging for Sense Making" Message-ID: <62DE8865-BCEA-498A-963B-9621592DF144@mdx.ac.uk> Content-Type: text/plain; charset="utf-8"
Hi All,
Just a quick note that the special issue deadline is now extended to 1 April 2019 (it was 1 Mach 2019).
Regards,
Guest Editors Kai Xu (k.xu@mdx.ac.uk), Middlesex University Melanie Tory (mtory@tableau.com), Tableau Research T.J. Jankun-Kelly (tjk@acm.org), Mississippi State University Jean-Daniel Fekete (Jean-Daniel.Fekete@inria.fr), INRIA Unit? de Recherche Saclay
On 18 Jan 2019, at 23:25, Kai Xu <K.Xu@mdx.ac.uk> wrote:
CFP: IEEE CG&A Special Issue on "Provenance and Logging for Sense Making"
Submission: 1 April 2019 Publication: November/December 2019
https://publications.computer.org/cga/2018/10/02/special-issue-provenance-lo...
Sense making is one of the biggest challenges in data analysis faced by both the industry and the research community. It involves understanding the data and uncovering its model, generating a hypothesis, selecting analysis methods, creating novel solutions, designing evaluation, and also critical thinking and learning wherever needed. The research and development for such sense making tasks lags far behind the fast-changing user needs. As a result, sense making is often performed manually and the limited human cognition capability becomes the bottleneck of sense making in data analysis and decision making.
A recent advance in sense making research is the capture, visualization, and analysis of provenance information. Provenance is the history and context of sense making, including the data/analysis used and the users? critical thinking process. It has been shown that provenance can effectively support many sense making tasks. For instance, provenance can provide an overview of what has been examined and reveal gaps such as unexplored information or solution possibilities. Besides, provenance can support collaborative sense making and communication by sharing the rich context of the sense making process.
Besides data analysis and decision making, provenance has been studied in many other fields, sometimes under different names, for different types of sense making. For example, the Human-Computer Interaction community relies on the analysis of logging to understand user behaviors and intentions; the WWW and database community has been working on data lineage to understand uncertainty and trustworthiness; and finally, reproducible science heavily relies on provenance to improve the reliability and efficiency of scientific research.
For this special issue, we are soliciting papers that describe innovative research, design, system/tools, and viewpoints regarding the collection, analysis, and summarization of provenance information to support the design and evaluation of novel techniques for sense making across different application domains:
? Use cases of provenance and logging information, such as: ? Supporting sense making; ? Understanding user sense making activities and/or evaluation of sense making tools; ? Supporting collaborative sense making; ? Providing sense making transparency and reproducibility ? Research related to the challenges in capturing the required provenance information, such as: ? The complex provenance information required for different use cases; ? Automatic capture of high-level provenance such as human thinking and reasoning; ? Software architecture for provenance capture for both new and existing systems. ? Research related to the analysis and visualization of provenance data, such as: ? Visualization and summarization of provenance information; ? Machine learning and Nature Language Processing techniques that can help analysis of provenance data. ? The ethical and privacy implications of the collection, storage, and analysis of provenance data and their impact on the design of the techniques and software.
We are aware that the deadline is close. Please contact Kai ( k.xu@mdx.ac.uk) if you would like to make a submission but may not meet the deadline.
Guest Editors Kai Xu (k.xu@mdx.ac.uk), Middlesex University Melanie Tory (mtory@tableau.com), Tableau Research T.J. Jankun-Kelly (tjk@acm.org), Mississippi State University Jean-Daniel Fekete (Jean-Daniel.Fekete@inria.fr), INRIA Unit? de Recherche Saclay
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