1 research outputs found
Urania: Visualizing Data Analysis Pipelines for Natural Language-Based Data Exploration
Exploratory Data Analysis (EDA) is an essential yet tedious process for
examining a new dataset. To facilitate it, natural language interfaces (NLIs)
can help people intuitively explore the dataset via data-oriented questions.
However, existing NLIs primarily focus on providing accurate answers to
questions, with few offering explanations or presentations of the data analysis
pipeline used to uncover the answer. Such presentations are crucial for EDA as
they enhance the interpretability and reliability of the answer, while also
helping users understand the analysis process and derive insights. To fill this
gap, we introduce Urania, a natural language interactive system that is able to
visualize the data analysis pipelines used to resolve input questions. It
integrates a natural language interface that allows users to explore data via
questions, and a novel data-aware question decomposition algorithm that
resolves each input question into a data analysis pipeline. This pipeline is
visualized in the form of a datamation, with animated presentations of analysis
operations and their corresponding data changes. Through two quantitative
experiments and expert interviews, we demonstrated that our data-aware question
decomposition algorithm outperforms the state-of-the-art technique in terms of
execution accuracy, and that Urania can help people explore datasets better. In
the end, we discuss the observations from the studies and the potential future
works