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Micheline Elias

dblp:31/10055 · DBLP profile ↗
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3ranked-venue papers
3as first author
0since 2021 · last 2013
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 3 · 3 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Visualization and visual analytics · 100%
Human-computer interaction and pervasive computing
1 paper
User interface design and tools · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Visualization and visual analytics › interaction techniques
annotation
0.112012
Annotating BI visualization dashboards: needs & challenges · CHI 2012
Visualization and visual analytics › interactive visualization
visualization dashboard
0.112012
Annotating BI visualization dashboards: needs & challenges · CHI 2012

Methods — techniques the papers use, named apart from their topics

prototype design · 0.3interviews · 0.3
YearPublicationVenuePosition
2013 Storytelling in Visual Analytics Tools for Business Intelligence
Micheline Elias, Marie-Aude Aufaure, Anastasia Bezerianos
INTERACT (3)1
2012 Annotating BI visualization dashboards: needs & challenges
abstract
Annotations have been identified as an important aid in analysis record-keeping and recently data discovery. In this paper we discuss the use of annotations on visualization dashboards, with a special focus on business intelligence (BI) analysis. In-depth interviews with experts lead to new annotation needs for multi-chart visualization systems, on which we based the design of a dashboard prototype that supports data and context aware annotations. We focus particularly on novel annotation aspects, such as multi-target annotations, annotation transparency across charts and data dimension levels, as well as annotation properties such as lifetime and validity. Moreover, our prototype is built on a data layer shared among different data-sources and BI applications, allowing cross application annotations. We discuss challenges in supporting context aware annotations in dashboards and other visualizations, such as dealing with changing annotated data, and provide design solutions. Finally we report reactions and recommendations from a different set of expert users.
Micheline Elias, Anastasia Bezerianos
CHI1
2011 Exploration Views: Understanding Dashboard Creation and Customization for Visualization Novices
Micheline Elias, Anastasia Bezerianos
INTERACT (4)1