A data story typically integrates data facts from multiple perspectives and
stances to construct a comprehensive and objective narrative. Tuttavia,
retrieving these facts demands time for data search and challenges the
creator’s analytical skills. In questo lavoro, we introduce DataScout, an
interactive system that automatically performs reasoning and stance-based data
facts retrieval to augment the user’s statement. Particularly, DataScout
leverages an LLM-based agent to construct a retrieval tree, enabling
collaborative control of its expansion between users and the agent. The
interface visualizes the retrieval tree as a mind map that eases users to
intuitively steer the retrieval direction and effectively engage in reasoning
and analysis. We evaluate the proposed system through case studies and in-depth
expert interviews. Our evaluation demonstrates that DataScout can effectively
retrieve multifaceted data facts from different stances, helping users verify
their statements and enhance the credibility of their stories.

Questo articolo esplora i giri e le loro implicazioni.

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