DS4ALL: All you need for democratizing data exploration and analysis - Archive ouverte HAL Access content directly
Conference Papers Year : 2021

DS4ALL: All you need for democratizing data exploration and analysis

Abstract

Today, large amounts of data are collected in various domains, presenting unprecedented economic and societal opportunities. Yet, at present, the exploitation of these data sets through data science methods is primarily dominated by AI-savvy users. From an inclusive perspective, there is a need for solutions that can democratise data science that can guide non-specialists intuitively to explore data collections and extract knowledge out of them. This paper introduces the vision of a new data science engine, called DS4ALL (Data Science for ALL), that empowers users who are neither computer nor AI experts to perform sophisticated data exploration and analysis tasks. Therefore, DS4ALL is based on a conversational and intuitive approach that insulates users from the complexity of AI algorithms. DS4ALL allows a dialogue-based approach that gives the user greater freedom of expression. It will enable them to communicate using natural language without requiring a high level of expertise on data-driven algorithms. User requests are interpreted and handled internally by the system in an automated manner, providing the user with the required output by masking the complexity of the data science workflow. The system can also collect feedback on the displayed results, leveraging these comments to address personalized data analysis sessions. The benefits of the envisioned system are discussed, and a use case is also presented to describe the innovative aspects.
Fichier principal
Vignette du fichier
ds4eiw_2021.pdf (775.85 Ko) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-03621357 , version 1 (28-03-2022)

Identifiers

Cite

Paolo Bethaz, Khalid Belhajjame, Genoveva Vargas-Solar, Tania Cerquitelli. DS4ALL: All you need for democratizing data exploration and analysis. 2021 IEEE International Conference on Big Data (Big Data), Dec 2021, Orlando, United States. pp.4235-4242, ⟨10.1109/BigData52589.2021.9671883⟩. ⟨hal-03621357⟩
50 View
149 Download

Altmetric

Share

Gmail Mastodon Facebook X LinkedIn More