Empowering Users with Narratives: Examining the Efficacy of Narratives for Understanding Data-Oriented Conceptual Models

叙述的 计算机科学 概念框架 概念模型 授权 杠杆(统计) 分析 数据科学 知识管理 万维网 社会学 政治学 人工智能 社会科学 哲学 语言学 数据库 法学
作者
Merete Hvalshagen,Roman Lukyanenko,Binny M. Samuel
出处
期刊:Information Systems Research [Institute for Operations Research and the Management Sciences]
卷期号:34 (3): 890-909 被引量:11
标识
DOI:10.1287/isre.2022.1141
摘要

Elevator Pitch A quiet revolution is happening in the offices, cubicles, and boardrooms of the world. Non-IT professionals are becoming empowered by leveraging organizational data for analytics. We support this movement by offering a powerful way to make data more usable via a combination of graphical conceptual models with narratives. Longer Version We are witnessing a quiet revolution—the rise of empowered users. These non-IT professionals increasingly seek to leverage the ever-expanding amount of organizational data for analytics to support their initiatives, decisions, and actions. All too often, however, the enthusiasm of these users collides against the harsh reality—many of them lack sophisticated IT skills, and they struggle to find/access relevant data, understand their meaning, and extract and adapt them to meet their needs. We propose a powerful way to support empowered users with a combination of conceptual models and narratives. Conceptual models are diagrams that accurately and succinctly represent rules and patterns captured in data. Although somewhat intuitive, these models alone do not suffice, as interpreting them still requires some specialized IT knowledge. Hence, we add narratives—stories written in natural language. The narratives intuitively explain some of the challenging aspects of the conceptual models. We conducted a series of experiments and interviews with empowered users to assess our idea. These studies show the value of the conceptual models with narratives for understanding organizational data. Our work unlocks an important missing puzzle for further user empowerment—a way for non-IT professionals to get the most out of the data.
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