Evaluating a Taxonomy of Textual Uncertainty for Collaborative Visualisation in the Digital Humanities

The capture, modelling and visualisation of uncertainty has become a hot topic in many areas of science, such as the digital humanities (DH). Fuelled by critical voices among the DH community, DH scholars are becoming more aware of the intrinsic advantages that incorporating the notion of uncertaint...

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Autores principales:	Alejandro Benito-Santos, Michelle Doran, Aleyda Rocha, Eveline Wandl-Vogt, Jennifer Edmond, Roberto Therón
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	human–computer interaction digital humanities cultural heritage information visualisation data modelling uncertainty taxonomy Information technology T58.5-58.64
Acceso en línea:	https://doaj.org/article/8aa28e713cd54eed857d14f37c5d08bf
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spelling	oai:doaj.org-article:8aa28e713cd54eed857d14f37c5d08bf2021-11-25T17:58:23ZEvaluating a Taxonomy of Textual Uncertainty for Collaborative Visualisation in the Digital Humanities10.3390/info121104362078-2489https://doaj.org/article/8aa28e713cd54eed857d14f37c5d08bf2021-10-01T00:00:00Zhttps://www.mdpi.com/2078-2489/12/11/436https://doaj.org/toc/2078-2489The capture, modelling and visualisation of uncertainty has become a hot topic in many areas of science, such as the digital humanities (DH). Fuelled by critical voices among the DH community, DH scholars are becoming more aware of the intrinsic advantages that incorporating the notion of uncertainty into their workflows may bring. Additionally, the increasing availability of ubiquitous, web-based technologies has given rise to many collaborative tools that aim to support DH scholars in performing remote work alongside distant peers from other parts of the world. In this context, this paper describes two user studies seeking to evaluate a taxonomy of textual uncertainty aimed at enabling remote collaborations on digital humanities (DH) research objects in a digital medium. Our study focuses on the task of free annotation of uncertainty in texts in two different scenarios, seeking to establish the requirements of the underlying data and uncertainty models that would be needed to implement a hypothetical collaborative annotation system (CAS) that uses information visualisation and visual analytics techniques to leverage the cognitive effort implied by these tasks. To identify user needs and other requirements, we held two user-driven design experiences with DH experts and lay users, focusing on the annotation of uncertainty in historical recipes and literary texts. The lessons learned from these experiments are gathered in a series of insights and observations on how these different user groups collaborated to adapt an uncertainty taxonomy to solve the proposed exercises. Furthermore, we extract a series of recommendations and future lines of work that we share with the community in an attempt to establish a common agenda of DH research that focuses on collaboration around the idea of uncertainty.Alejandro Benito-SantosMichelle DoranAleyda RochaEveline Wandl-VogtJennifer EdmondRoberto TherónMDPI AGarticlehuman–computer interactiondigital humanitiescultural heritageinformation visualisationdata modellinguncertainty taxonomyInformation technologyT58.5-58.64ENInformation, Vol 12, Iss 436, p 436 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	human–computer interaction digital humanities cultural heritage information visualisation data modelling uncertainty taxonomy Information technology T58.5-58.64
spellingShingle	human–computer interaction digital humanities cultural heritage information visualisation data modelling uncertainty taxonomy Information technology T58.5-58.64 Alejandro Benito-Santos Michelle Doran Aleyda Rocha Eveline Wandl-Vogt Jennifer Edmond Roberto Therón Evaluating a Taxonomy of Textual Uncertainty for Collaborative Visualisation in the Digital Humanities
description	The capture, modelling and visualisation of uncertainty has become a hot topic in many areas of science, such as the digital humanities (DH). Fuelled by critical voices among the DH community, DH scholars are becoming more aware of the intrinsic advantages that incorporating the notion of uncertainty into their workflows may bring. Additionally, the increasing availability of ubiquitous, web-based technologies has given rise to many collaborative tools that aim to support DH scholars in performing remote work alongside distant peers from other parts of the world. In this context, this paper describes two user studies seeking to evaluate a taxonomy of textual uncertainty aimed at enabling remote collaborations on digital humanities (DH) research objects in a digital medium. Our study focuses on the task of free annotation of uncertainty in texts in two different scenarios, seeking to establish the requirements of the underlying data and uncertainty models that would be needed to implement a hypothetical collaborative annotation system (CAS) that uses information visualisation and visual analytics techniques to leverage the cognitive effort implied by these tasks. To identify user needs and other requirements, we held two user-driven design experiences with DH experts and lay users, focusing on the annotation of uncertainty in historical recipes and literary texts. The lessons learned from these experiments are gathered in a series of insights and observations on how these different user groups collaborated to adapt an uncertainty taxonomy to solve the proposed exercises. Furthermore, we extract a series of recommendations and future lines of work that we share with the community in an attempt to establish a common agenda of DH research that focuses on collaboration around the idea of uncertainty.
format	article
author	Alejandro Benito-Santos Michelle Doran Aleyda Rocha Eveline Wandl-Vogt Jennifer Edmond Roberto Therón
author_facet	Alejandro Benito-Santos Michelle Doran Aleyda Rocha Eveline Wandl-Vogt Jennifer Edmond Roberto Therón
author_sort	Alejandro Benito-Santos
title	Evaluating a Taxonomy of Textual Uncertainty for Collaborative Visualisation in the Digital Humanities
title_short	Evaluating a Taxonomy of Textual Uncertainty for Collaborative Visualisation in the Digital Humanities
title_full	Evaluating a Taxonomy of Textual Uncertainty for Collaborative Visualisation in the Digital Humanities
title_fullStr	Evaluating a Taxonomy of Textual Uncertainty for Collaborative Visualisation in the Digital Humanities
title_full_unstemmed	Evaluating a Taxonomy of Textual Uncertainty for Collaborative Visualisation in the Digital Humanities
title_sort	evaluating a taxonomy of textual uncertainty for collaborative visualisation in the digital humanities
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/8aa28e713cd54eed857d14f37c5d08bf
work_keys_str_mv	AT alejandrobenitosantos evaluatingataxonomyoftextualuncertaintyforcollaborativevisualisationinthedigitalhumanities AT michelledoran evaluatingataxonomyoftextualuncertaintyforcollaborativevisualisationinthedigitalhumanities AT aleydarocha evaluatingataxonomyoftextualuncertaintyforcollaborativevisualisationinthedigitalhumanities AT evelinewandlvogt evaluatingataxonomyoftextualuncertaintyforcollaborativevisualisationinthedigitalhumanities AT jenniferedmond evaluatingataxonomyoftextualuncertaintyforcollaborativevisualisationinthedigitalhumanities AT robertotheron evaluatingataxonomyoftextualuncertaintyforcollaborativevisualisationinthedigitalhumanities
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Evaluating a Taxonomy of Textual Uncertainty for Collaborative Visualisation in the Digital Humanities

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