Rankings are a popular and universal approach to structuring otherwise unorganized collections of items by computing a rank for each item based on the value of one or more of its attributes. This allows us, for example, to prioritize tasks or to evaluate the performance of products relative to each other.
While the visualization of a ranking itself is straightforward, its interpretation is not, because the rank of an item represents only a summary of a potentially complicated relationship between its attributes and those of the other items. It is also common that alternative rankings exist which need to be compared and analyzed to gain insight into how multiple heterogeneous attributes affect the rankings. Advanced visual exploration tools are needed to make this process efficient.
In our paper we present a comprehensive analysis of requirements for the visualization of multi-attribute rankings. Based on these considerations, we propose LineUp - a novel and scalable visualization technique that uses bar charts. This interactive technique supports the ranking of items based on multiple heterogeneous attributes with different scales and semantics. It enables users to interactively combine attributes and flexibly refine parameters to explore the effect of changes in the attribute combination. This process can be employed to derive actionable insights as to which attributes of an item need to be modified in order for its rank to change.
Additionally, through integration of slope graphs, LineUp can also be used to compare multiple alternative rankings on the same set of items, for example, over time or across different attribute combinations. We evaluate the effectiveness of the proposed multi-attribute visualization technique in a qualitative study. The study shows that users are able to successfully solve complex ranking tasks in a short period of time.
Samuel Gratzl, Alexander Lex, Nils Gehlenborg, Hanspeter Pfister, and Marc Streit
LineUp: Visual Analysis of Multi-Attribute Rankings - Best Paper Award
IEEE Transactions on Visualization and Computer Graphics (InfoVis '13), vol. 19, no. 12, pp. 2277–2286, 2013.
Samuel Gratzl @ InfoVis '13
In the examples and demos we have used three datasets:
The supplementary material contains the result of the user study.
We have prepared a cheat sheet containing a description of the user interface elements and interactions in LineUp.
In addition, as a non-commercial research group we are interested in who uses LineUp to what end. We therefore ask you to provide us with some details about you and your field. We will keep your data confidential and only contact you if you are ok with it.
LineUp is part of the Caleydo framework.
LineUp runs on Windows, Linux and Mac OS X. We regularly test on Windows 7, Ubuntu/Kubuntu of the latest versions and Mac OS X Lion (10.7).
More installation details can be found at the Caleydo Installation Instructions.
LineUp requires the latest version of Oracle Java 7 (>= 1.7.0_40).
Also, please note that LineUp is an application using high-end computer graphics. While it works on a wide range of graphics cards and systems, dedicated graphics cards from NVidia or AMD are strongly recommended (for example, a graphics card better of the NVidia Geforce 8 series or better should be fine). Also make sure that you have the latest drivers installed. Download NVidia or AMD drivers.
The current version is LineUp-3.1.1. This version includes a custom data loader.
The current experimental version is 3.1.3-alpha1. This version allows you to save/load projects and to export your current LineUp table as a plain text file.
We wish to thank Blake T. Walsh, Günter Öller and the anonymous paper reviewers for their input.
This work was supported in part by the Austrian Research Promotion Agency (840232), the Austrian Science Fund (J 3437-N15), the Air Force Research Laboratory and DARPA grant FA8750-12-C-0300, and the United States National Cancer Institute (U24 CA143867).