Visual Analysis of Streaming Data with SAVI and SenseMAP

Xu, K., Nguyen, P. & Fields, B. (2015). Visual Analysis of Streaming Data with SAVI and SenseMAP. 2014 IEEE Conference on Visual Analytics Science and Technology (VAST), ISSN 2325-9442

[img]
Preview
Text - Draft Version
Download (760kB) | Preview

Abstract

wo tools were developed for the analysis tasks in the VAST Challenge 2014 Mini-Challenge 3: Social Analytics VIsualiszation (SAVI) and Sense Making with Analytic Provenance (SenseMAP).

The SAVI provides linked timeline and geospatial view of the message streams. It allows search and filter based on text analysis, such as named entity extraction and sentiment analysis, and enable analyst to identity interesting events, tracking them temporally and geospatially, and find related information.

The SenseMAP allows analysts to record finding, together with the visualisations that lead to it, and generate hypotheses and con- struct narratives. The entire sense making process is captured so it is possible to go back to any previous reasoning state and share or playback the process. The fact that complex investigations are often carried out by several people working collaboratively is supported in our tools by allowing several people to use SAVI concurrently on the same dataset. Used in this mode, each users analyses are kept separate. However, the SenseMap tool supports collaboration and sharing of hypothesis and narrative structures. Each users findings are avail- able to others, and the findings of different users can be compared, combined, merged, and so on, to produce a collective analytic re- sult.

The key insights that informed the design were firstly, that it was important to see and interact with dataset from different perspec- tives, and secondly that an essential part of an investigation is the construction and representation of a narrative.

Publication Type: Conference or Workshop Item (Paper)
Additional Information: © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
Publisher Keywords: Image color analysis, Cognition, Histograms, Data visualization, Organizations, Geospatial analysis, Visualization
Departments: School of Mathematics, Computer Science & Engineering > Computer Science
URI: http://openaccess.city.ac.uk/id/eprint/19059

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics