Using concrete and realistic data in evaluating initial visualization designs

TY - GEN

T1 - Using concrete and realistic data in evaluating initial visualization designs

AU - Knudsen, Søren

AU - Pedersen, Jeppe Gerner

AU - Herdal, Thor

AU - Larsen, Jakob Eg

N1 - Conference code: 6

PY - 2016/10/24

Y1 - 2016/10/24

N2 - We explore means of designing and evaluating initial visualization ideas, with concrete and realistic data in cases where data is not readily available. Our approach is useful in exploring new domains and avenues for visualization, and contrasts other visualization work, which typically operate under the assumption that data has already been collected, and is ready to be visualized. We argue that it is sensible to understand data requirements and evaluate the potential value of visualization before devising means of automatic data collection. We base our exploration on three cases selected to span a range of factors, such as the role of the person doing the data collection and the type of instrumentation used. The three cases relate to visualizing sports, construction, and cooking domain data, and use primarily time-domain data and visualizations. For each case, we briefly describe the design case and problem, the manner in which we collected data, and the findings obtained from evaluations. Afterwards, we describe four factors of our data collection approach, and discuss potential outcomes from it.

AB - We explore means of designing and evaluating initial visualization ideas, with concrete and realistic data in cases where data is not readily available. Our approach is useful in exploring new domains and avenues for visualization, and contrasts other visualization work, which typically operate under the assumption that data has already been collected, and is ready to be visualized. We argue that it is sensible to understand data requirements and evaluate the potential value of visualization before devising means of automatic data collection. We base our exploration on three cases selected to span a range of factors, such as the role of the person doing the data collection and the type of instrumentation used. The three cases relate to visualizing sports, construction, and cooking domain data, and use primarily time-domain data and visualizations. For each case, we briefly describe the design case and problem, the manner in which we collected data, and the findings obtained from evaluations. Afterwards, we describe four factors of our data collection approach, and discuss potential outcomes from it.

KW - Evaluation

KW - InfoVis

KW - Methodology

KW - Personal visualization

KW - Pre-design empiricism

UR - http://www.scopus.com/inward/record.url?scp=84995477322&partnerID=8YFLogxK

U2 - 10.1145/2993901.2993917

DO - 10.1145/2993901.2993917

M3 - Article in proceedings

AN - SCOPUS:84995477322

SP - 27

EP - 35

BT - Proceedings of the Sixth Workshop on Beyond Time and Errors on Novel Evaluation Methods for Visualization

PB - Association for Computing Machinery

T2 - 6th Workshop on Beyond Time and Errors on Novel Evaluation Methods for Visualization

Y2 - 24 October 2016 through 24 October 2016

ER -