Visualizing Uncertainty in Flow Diagrams: A Case Study in Product Costing
Zana Vosough, Dietrich Kammer, Mandy Keck, Rainer Groh: Visualizing Uncertainty in Flow Diagrams: A Case Study in Product Costing. Proceedings of the 10th International Symposium on Visual Information Communication and Interaction, VINCI '17 ACM, New York, NY, USA, 2017, ISBN: 978-1-4503-5292-5, (Best Paper Award).
Abstract
Business Intelligence applications often handle data sets that contain uncertain values. In this work we focus on product costing, which deals with the average costs of product components -- that vary significantly based on many factors such as inflation, exchange rates, and commodity prices. After experts provide the uncertainty information for single items, decision makers need to quickly understand the cost uncertainties within the hierarchical data structure of the complete product.
To provide this kind of quick overview, we propose a holistic visualization that contains both data and uncertainty. Since Flow diagrams are suitable to visualize tree data structures associated with value attributes, we focus on incorporating uncertainty information directly into these diagrams. Interviews with product costing experts led us to base our solution on Sankey diagrams.
We chose three visualization techniques that are able to convey uncertainty information to the user: Color-code, Gradient, and Margin. We contribute a user study, which involved solving different product costing tasks using these three different visualizations. From the recorded error rates and subjective feedback, we designed an integrated approach that combines elements from all three distinct techniques.
@conference{UncertaintyPC,
title = {Visualizing Uncertainty in Flow Diagrams: A Case Study in Product Costing},
author = {Zana Vosough and Dietrich Kammer and Mandy Keck and Rainer Groh},
url = {http://doi.acm.org/10.1145/3105971.3105972},
doi = {10.1145/3105971.3105972},
isbn = {978-1-4503-5292-5},
year = {2017},
date = {2017-08-14},
booktitle = {Proceedings of the 10th International Symposium on Visual Information Communication and Interaction},
pages = {1--8},
publisher = {ACM},
address = {New York, NY, USA},
series = {VINCI '17},
abstract = {Business Intelligence applications often handle data sets that contain uncertain values. In this work we focus on product costing, which deals with the average costs of product components -- that vary significantly based on many factors such as inflation, exchange rates, and commodity prices. After experts provide the uncertainty information for single items, decision makers need to quickly understand the cost uncertainties within the hierarchical data structure of the complete product.
To provide this kind of quick overview, we propose a holistic visualization that contains both data and uncertainty. Since Flow diagrams are suitable to visualize tree data structures associated with value attributes, we focus on incorporating uncertainty information directly into these diagrams. Interviews with product costing experts led us to base our solution on Sankey diagrams.
We chose three visualization techniques that are able to convey uncertainty information to the user: Color-code, Gradient, and Margin. We contribute a user study, which involved solving different product costing tasks using these three different visualizations. From the recorded error rates and subjective feedback, we designed an integrated approach that combines elements from all three distinct techniques.},
note = {Best Paper Award},
keywords = {Information Visualization, Parallel Sets},
pubstate = {published},
tppubtype = {conference}
}
Visualizing Uncertainty in Flow Diagrams: A Case Study in Product Costing
Abstract
Business Intelligence applications often handle data sets that contain uncertain values. In this work we focus on product costing, which deals with the average costs of product components -- that vary significantly based on many factors such as inflation, exchange rates, and commodity prices. After experts provide the uncertainty information for single items, decision makers need to quickly understand the cost uncertainties within the hierarchical data structure of the complete product.
To provide this kind of quick overview, we propose a holistic visualization that contains both data and uncertainty. Since Flow diagrams are suitable to visualize tree data structures associated with value attributes, we focus on incorporating uncertainty information directly into these diagrams. Interviews with product costing experts led us to base our solution on Sankey diagrams.
We chose three visualization techniques that are able to convey uncertainty information to the user: Color-code, Gradient, and Margin. We contribute a user study, which involved solving different product costing tasks using these three different visualizations. From the recorded error rates and subjective feedback, we designed an integrated approach that combines elements from all three distinct techniques.
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BibTeX (Download)
@conference{UncertaintyPC, title = {Visualizing Uncertainty in Flow Diagrams: A Case Study in Product Costing}, author = {Zana Vosough and Dietrich Kammer and Mandy Keck and Rainer Groh}, url = {http://doi.acm.org/10.1145/3105971.3105972}, doi = {10.1145/3105971.3105972}, isbn = {978-1-4503-5292-5}, year = {2017}, date = {2017-08-14}, booktitle = {Proceedings of the 10th International Symposium on Visual Information Communication and Interaction}, pages = {1--8}, publisher = {ACM}, address = {New York, NY, USA}, series = {VINCI '17}, abstract = {Business Intelligence applications often handle data sets that contain uncertain values. In this work we focus on product costing, which deals with the average costs of product components -- that vary significantly based on many factors such as inflation, exchange rates, and commodity prices. After experts provide the uncertainty information for single items, decision makers need to quickly understand the cost uncertainties within the hierarchical data structure of the complete product. To provide this kind of quick overview, we propose a holistic visualization that contains both data and uncertainty. Since Flow diagrams are suitable to visualize tree data structures associated with value attributes, we focus on incorporating uncertainty information directly into these diagrams. Interviews with product costing experts led us to base our solution on Sankey diagrams. We chose three visualization techniques that are able to convey uncertainty information to the user: Color-code, Gradient, and Margin. We contribute a user study, which involved solving different product costing tasks using these three different visualizations. From the recorded error rates and subjective feedback, we designed an integrated approach that combines elements from all three distinct techniques.}, note = {Best Paper Award}, keywords = {Information Visualization, Parallel Sets}, pubstate = {published}, tppubtype = {conference} }