@inproceedings{bhattacharya-di-eugenio-2025-collaborative,
title = "Collaborative Data Exploration through Visualization: A Thesis Proposal Analyzing Impact of Conversational Assistants",
author = "Bhattacharya, Abari and
Di Eugenio, Barbara",
editor = "Ebrahimi, Abteen and
Haider, Samar and
Liu, Emmy and
Haider, Sammar and
Pacheco, Maria Leonor and
Wein, Shira",
booktitle = "Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 4: Student Research Workshop)",
month = apr,
year = "2025",
address = "Albuquerque, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.naacl-srw.48/",
doi = "10.18653/v1/2025.naacl-srw.48",
pages = "492--500",
ISBN = "979-8-89176-192-6",
abstract = "Data visualization is integral to any Exploratory Data Analysis (EDA) task. However, generating visualization requires expertise, presenting a steep learning curve and a significant cognitive load. Natural language interfaces for EDA aim to lower this barrier by allowing users to generate visualizations through natural language queries. However, complexity remains when EDA is performed collaboratively, requiring an environment to support multi-user interaction. In this thesis proposal, we discuss challenges in user-system interaction in a collaborative multi-user setup, such as errors in visualization generation due to misinterpretation of user requests. We hypothesize that a Conversational Assistant (CA) capable of understanding user-initiated clarification requests and generating accurate responses can improve user experience and support collaborative EDA tasks. To this end, we propose to develop such a CA (Figure tab:system{\_}issues) and evaluate it through a user study, thus examining its impact on user experience in a collaborative environment for EDA."
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<abstract>Data visualization is integral to any Exploratory Data Analysis (EDA) task. However, generating visualization requires expertise, presenting a steep learning curve and a significant cognitive load. Natural language interfaces for EDA aim to lower this barrier by allowing users to generate visualizations through natural language queries. However, complexity remains when EDA is performed collaboratively, requiring an environment to support multi-user interaction. In this thesis proposal, we discuss challenges in user-system interaction in a collaborative multi-user setup, such as errors in visualization generation due to misinterpretation of user requests. We hypothesize that a Conversational Assistant (CA) capable of understanding user-initiated clarification requests and generating accurate responses can improve user experience and support collaborative EDA tasks. To this end, we propose to develop such a CA (Figure tab:system_issues) and evaluate it through a user study, thus examining its impact on user experience in a collaborative environment for EDA.</abstract>
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%0 Conference Proceedings
%T Collaborative Data Exploration through Visualization: A Thesis Proposal Analyzing Impact of Conversational Assistants
%A Bhattacharya, Abari
%A Di Eugenio, Barbara
%Y Ebrahimi, Abteen
%Y Haider, Samar
%Y Liu, Emmy
%Y Haider, Sammar
%Y Pacheco, Maria Leonor
%Y Wein, Shira
%S Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 4: Student Research Workshop)
%D 2025
%8 April
%I Association for Computational Linguistics
%C Albuquerque, USA
%@ 979-8-89176-192-6
%F bhattacharya-di-eugenio-2025-collaborative
%X Data visualization is integral to any Exploratory Data Analysis (EDA) task. However, generating visualization requires expertise, presenting a steep learning curve and a significant cognitive load. Natural language interfaces for EDA aim to lower this barrier by allowing users to generate visualizations through natural language queries. However, complexity remains when EDA is performed collaboratively, requiring an environment to support multi-user interaction. In this thesis proposal, we discuss challenges in user-system interaction in a collaborative multi-user setup, such as errors in visualization generation due to misinterpretation of user requests. We hypothesize that a Conversational Assistant (CA) capable of understanding user-initiated clarification requests and generating accurate responses can improve user experience and support collaborative EDA tasks. To this end, we propose to develop such a CA (Figure tab:system_issues) and evaluate it through a user study, thus examining its impact on user experience in a collaborative environment for EDA.
%R 10.18653/v1/2025.naacl-srw.48
%U https://aclanthology.org/2025.naacl-srw.48/
%U https://doi.org/10.18653/v1/2025.naacl-srw.48
%P 492-500
Markdown (Informal)
[Collaborative Data Exploration through Visualization: A Thesis Proposal Analyzing Impact of Conversational Assistants](https://aclanthology.org/2025.naacl-srw.48/) (Bhattacharya & Di Eugenio, NAACL 2025)
ACL