TransVis: Integrated Distant and Close Reading of Othello Translations

Alharbi, Mohammad Saqar; Laramee, Robert S; Cheesman, Tom

Abstract

Studying variation among time-evolved translations is a valuable research area for cultural heritage. Understanding how and why translations vary reveals cultural, ideological, and even political influences on literature as well as author relations. In this paper, we introduce a novel integrated visual application to support distant and close reading of a collection of Othello translations. We present a new interactive application that provides an alignment overview of all the translations and their correspondences in parallel with smooth zooming and panning capability to integrate distant and close reading within the same view. We provide a range of filtering and selection options to customize the alignment overview as well as focus on specific subsets. Selection and filtering are responsive to expert user preferences and update the analytical text metrics interactively. Also, we introduce a customized view for close reading which preserves the history of selections and the alignment overview state and enables backtracing and re-examining them. Finally, we present a new Term-Level Comparisons view (TLC) to compare and convey relative term weighting in the context of an alignment. Our visual design is guided by, used and evaluated by a domain expert specialist in German translations of Shakespeare.

Citation

Alharbi, M. S., Laramee, R. S., & Cheesman, T. (2022). TransVis: Integrated Distant and Close Reading of Othello Translations. IEEE Transactions on Visualization and Computer Graphics, 28(2), 1397-1414. https://doi.org/10.1109/tvcg.2020.3012778

• Journal Article Type: Article
• Acceptance Date: Aug 1, 2020
• Online Publication Date: Jul 29, 2020
• Publication Date: 2022-02
• Deposit Date: Jan 15, 2021
• Publicly Available Date: Jan 22, 2021
• Journal: IEEE Transactions on Visualization and Computer Graphics
• Print ISSN: 1077-2626
• Electronic ISSN: 1941-0506
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 28
• Issue: 2
• Pages: 1397-1414
• DOI: https://doi.org/10.1109/tvcg.2020.3012778
• Keywords: Signal Processing; Software; Computer Vision and Pattern Recognition; Computer Graphics and Computer-Aided Design
• Public URL: https://nottingham-repository.worktribe.com/output/5013044
• Publisher URL: https://ieeexplore.ieee.org/document/9152170
• Additional Information: © 2020 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.