Literature DB >> 26357073

Personal Visualization and Personal Visual Analytics.

Dandan Huang, Melanie Tory, Bon Adriel Aseniero, Lyn Bartram, Scott Bateman, Sheelagh Carpendale, Anthony Tang, Robert Woodbury.   

Abstract

Data surrounds each and every one of us in our daily lives, ranging from exercise logs, to archives of our interactions with others on social media, to online resources pertaining to our hobbies. There is enormous potential for us to use these data to understand ourselves better and make positive changes in our lives. Visualization (Vis) and visual analytics (VA) offer substantial opportunities to help individuals gain insights about themselves, their communities and their interests; however, designing tools to support data analysis in non-professional life brings a unique set of research and design challenges. We investigate the requirements and research directions required to take full advantage of Vis and VA in a personal context. We develop a taxonomy of design dimensions to provide a coherent vocabulary for discussing personal visualization and personal visual analytics. By identifying and exploring clusters in the design space, we discuss challenges and share perspectives on future research. This work brings together research that was previously scattered across disciplines. Our goal is to call research attention to this space and engage researchers to explore the enabling techniques and technology that will support people to better understand data relevant to their personal lives, interests, and needs.

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Year:  2015        PMID: 26357073     DOI: 10.1109/TVCG.2014.2359887

Source DB:  PubMed          Journal:  IEEE Trans Vis Comput Graph        ISSN: 1077-2626            Impact factor:   4.579


  5 in total

1.  Visualization of Cardiac Implantable Electronic Device Data for Older Adults Using Participatory Design.

Authors:  Ryan Ahmed; Tammy Toscos; Romisa Rohani Ghahari; Richard J Holden; Elizabeth Martin; Shauna Wagner; Carly Daley; Amanda Coupe; Michael Mirro
Journal:  Appl Clin Inform       Date:  2019-09-18       Impact factor: 2.342

2.  Computational Intelligence for Medical Imaging Simulations.

Authors:  Victor Chang
Journal:  J Med Syst       Date:  2017-11-25       Impact factor: 4.460

3.  Persuasive Data Videos: Investigating Persuasive Self-Tracking Feedback with Augmented Data Videos.

Authors:  Eun Kyoung Choe; Yumiko Sakamoto; Yanis Fatmi; Bongshin Lee; Christophe Hurter; Ashkan Haghshenas; Pourang Irani
Journal:  AMIA Annu Symp Proc       Date:  2020-03-04

4.  Reconsidering the Device in the Drawer: Lapses as a Design Opportunity in Personal Informatics.

Authors:  Daniel A Epstein; Jennifer H Kang; Laura R Pina; James Fogarty; Sean A Munson
Journal:  Proc ACM Int Conf Ubiquitous Comput       Date:  2016-09-12

5.  A Systematic Method for Exploring Data Attributes in Preparation for Designing Tailored Infographics of Patient Reported Outcomes.

Authors:  Adriana Arcia; Janet Woollen; Suzanne Bakken
Journal:  EGEMS (Wash DC)       Date:  2018-01-24
  5 in total

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