الملخص
Data journalism, the practice of using data analysis to surface newsworthy stories, depends increasingly on the ability of reporters and investigative journalists to uncover trends, disparities, and accountability narratives. In practice, exploring large structured datasets remains slow and brittle: journalists must navigate hundreds of variables across many datasets over years, understand data coding conventions, and write non-trivial analysis code while hypotheses evolve. Although LLMs are often touted as "ask in English, get SQL/answers," real newsroom workflows expose recurring failures, e.g., schema mismatches and drift, misread domain semantics and units, and silent assumptions. We present DataWeave, a system that addresses these needs by combining conversational interaction, schema grounding, analytical planning, and executable query generation to support exploratory analysis over structured data. Rather than treating LLMs as autonomous answer engines, DataWeave frames them as interactive partners whose outputs can be inspected, corrected, and steered as hypotheses shift. We present a case study with professional journalists using our system to analyze the U.S. Department of Education's Integrated Postsecondary Education Data System (IPEDS), a high-stakes public dataset with substantial domain semantics and frequent schema updates. We also report how deployment experience and iterative refinement shaped the current DataWeave architecture and its analytical workflow. Our findings distill design principles and deployment lessons for trustworthy human-LLM collaboration in structured data analysis.
الكلمات المفتاحية
الموضوع
بيانات النشر
- المجلة
- غير متاح
- وصول مفتوح
- وصول مفتوح أخضر
اقتبس هذه المقالة
APA 7
Bin Yousuf, R., Laxman, H., Shkremetko, V., Son, E., Verma, S., O'Leary, B., Subramony, V., Nazef, S., Elias, J., Coddington, R., Contakes, C., Riley, M., & Ramakrishnan, N. (2026). DataWeave: Deploying Human-LLM Analytics for Exploratory Structured Data Analysis. https://omanscience.com/ar/articles/dataweave-deploying-human-llm-analytics-for-exploratory-structured-data-analysis
MLA 9
Bin Yousuf, Raquib, et al. "DataWeave: Deploying Human-LLM Analytics for Exploratory Structured Data Analysis." https://omanscience.com/ar/articles/dataweave-deploying-human-llm-analytics-for-exploratory-structured-data-analysis.
شيكاغو (المؤلف–التاريخ)
Bin Yousuf, Raquib, Harith Laxman, Vitaliy Shkremetko, Eunice Son, Shambhavi Verma, Brian O'Leary, Venketesh Subramony, Sylvain Nazef, Jacquelyn Elias, Ron Coddington, Chris Contakes, Michael Riley, and Naren Ramakrishnan. 2026. "DataWeave: Deploying Human-LLM Analytics for Exploratory Structured Data Analysis." https://omanscience.com/ar/articles/dataweave-deploying-human-llm-analytics-for-exploratory-structured-data-analysis.
هارفارد
Bin Yousuf, R., Laxman, H., Shkremetko, V., Son, E., Verma, S., O'Leary, B., Subramony, V., Nazef, S., Elias, J., Coddington, R., Contakes, C., Riley, M. and Ramakrishnan, N. (2026) 'DataWeave: Deploying Human-LLM Analytics for Exploratory Structured Data Analysis', Available at: https://omanscience.com/ar/articles/dataweave-deploying-human-llm-analytics-for-exploratory-structured-data-analysis.
فانكوفر
Bin Yousuf R, Laxman H, Shkremetko V, Son E, Verma S, O'Leary B, et al. DataWeave: Deploying Human-LLM Analytics for Exploratory Structured Data Analysis. https://omanscience.com/ar/articles/dataweave-deploying-human-llm-analytics-for-exploratory-structured-data-analysis
IEEE
R. Bin Yousuf, H. Laxman, V. Shkremetko, E. Son, S. Verma, B. O'Leary, V. Subramony, S. Nazef, J. Elias, R. Coddington, C. Contakes, M. Riley, and N. Ramakrishnan, "DataWeave: Deploying Human-LLM Analytics for Exploratory Structured Data Analysis," https://omanscience.com/ar/articles/dataweave-deploying-human-llm-analytics-for-exploratory-structured-data-analysis.