محمد صقر محمد الحربي

البحوث المنشورة

TransVis: Integrated Distant and Close Reading of Othello Translations

https://ieeexplore.ieee.org/document/9152170

29/07/2020

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.

SoS TextVis: An Extended Survey of Surveys on Text Visualization (Extended paper)

20/02/2019

Text visualization is a rapidly growing sub-field of information visualization and visual analytics. There are many approaches and techniques introduced every year to address a wide range of challenges and analysis tasks, enabling researchers from different disciplines to obtain leading-edge knowledge from digitized collections of text. This can be challenging particularly when the data is massive. Additionally, the sources of digital text have spread substantially in the last decades in various forms, such as web pages, blogs, twitter, email, electronic publications, and digitized books. In response to the explosion of text visualization research literature, the first text visualization survey article was published in 2010. Furthermore, there are a growing number of surveys that review existing techniques and classify them based on text research methodology. In this work, we aim to present the first Survey of Surveys (SoS) that review all of the surveys and state-of-the-art papers on text visualization techniques and provide an SoS classification. We study and compare the 14 surveys, and categorize them into five groups: (1) Document-centered, (2) user task analysis, (3) cross-disciplinary, (4) multi-faceted, and (5) satellite-themed. We provide survey recommendations for researchers in the field of text visualization. The result is a very unique, valuable starting point and overview of the current state-of-the-art in text visualization research literature

المؤتمرات العلمية

The 24th International Conference on Information Visualization, (IV2020)                                

07/09/2020

Vienna, Austria

Paper presentation

AlignVis: Semi-Automotic Alignment and Visualization of Parallel Translations

Digital humanities and translation scholars utilize off-the-shelf tools to align multiple related translations. These tools generally rely solely on domain expert knowledge and do not exploit the recent advancements in computational linguistics and text mining. This paper presents AlignVis, a visual tool that provides a semi-automatic alignment framework to align multiple translations. It presents the results of using text similarity measurements and enables the user to create, verify, and edit alignments using a novel visual interface. The design consists of three main components: the alignment editor canvas, the post-edit area, and the user options panel. AlignVis exploits both close and distant reading and is designed to help digital humanities and translation scholars enhance the process of text alignment for multiple translations. The design of AlignVis is driven by iterative discussions with the domain expert which resulted in five benefits: presenting an overview of the aligned translations, support for multiple alignments, enhancement and acceleration of the alignment process, alignment refinement, and testing different similarity measurements. We evaluate AlignVis with domain expert feedback and a comparison with a standard alignment tool and computational and visual alignment tools.

The Computer Graphics and Visual Computing (CGVC) Conference 2018

12/09/2018

Swansea, UK

Paper presentation

SoS TextVis: A Survey of Surveys on Text Visualization

Text visualization is a rapidly growing sub-field of information visualization and visual analytics. There are many approaches and techniques introduced every year to address a wide range of tasks and enable researchers from different disciplines to obtain leading-edge knowledge from digitized collections. This can be challenging particularly when the data is massive. Additionally, the sources of digital text have spread substantially in the last decades in various forms, such as web pages, blogs, twitter, email, electronic publications, and books. In response to the explosion of text visualization research literature, the first survey article was published in 2010. Furthermore, there are a growing number of surveys that review existing techniques and classify them based on text research methodology. In this work, we aim to present the first Survey of Surveys (SoS) that review all of the survey and state-of-the-art papers on text visualization techniques and provide an SoS classification. We study and compare the surveys, and categorize them into 5 groups: (1) document-centered, (2) user task analysis, (3) cross-disciplinary, (4) multifaceted, and (5) satellite-themed. We provide survey recommendations for researchers in the field of text visualization. The result is a very unique, valuable starting point and overview of the current state-of-the-art in text visualization research literature.

https://doi.org/10.2312/cgvc.20181219

EuroVis 2017

12/06/2017

Barcelona, Spain

Paper presentation

Molecular Visualization of Computational Biology Data: A Survey of Surveys

Visualizations for computational biology have been developing for over 50 years. With recent advances in both computational biology and computer graphics techniques, these fields have witnessed rapid technological advances in the last decade. Thus, coping with the large number of scientific articles from both fields is a challenging task. Furthermore, there remains a gap between the two communities of visualization and computational biology, resulting in additional challenges to bridge the divide. A team of computational biology and visualization scientists attempts to address these challenges by presenting unified state-of-the-art reviews from both communities. We apply a variety of data-driven analysis to highlight links or differences between studies from both communities. This approach facilitates the identification of present and future challenges in visualizing and analyzing computational biology data. It offers a distinctive step forward in managing the literature on visualization of molecular dynamics and related simulation approaches.

https://diglib.eg.org/handle/10.2312/eurovisshort20171146