D³: Data-Driven Documents
Related Experiment Video
Updated: May 28, 2026

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
Published on: February 23, 2019
Michael Bostock1, Vadim Ogievetsky, Jeffrey Heer
1Computer Science Department of Stanford University, Stanford, CA 94305, USA. mbostock@stanford.edu
Abstract:
Data-Driven Documents (D3) is a novel representation-transparent approach to visualization for the web. Rather than hide the underlying scenegraph within a toolkit-specific abstraction, D3 enables direct inspection and manipulation of a native representation: the standard document object model (DOM). With D3, designers selectively bind input data to arbitrary document elements, applying dynamic transforms to both generate and modify content. We show how representational transparency improves expressiveness and better integrates with developer tools than prior approaches, while offering comparable notational efficiency and retaining powerful declarative components. Immediate evaluation of operators further simplifies debugging and allows iterative development. Additionally, we demonstrate how D3 transforms naturally enable animation and interaction with dramatic performance improvements over intermediate representations.
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Data: Types and Distribution
Distributions in...
Data Collection III
The principles to begin the physical assessment include conducting a comprehensive or problem-related history in a quiet, well-lit room, emphasizing privacy and comfort for the patient.
Methods of Documentation III: PIE
Methods of Documentation I: Source-Oriented Records
In an SOR, each discipline involved in patient care maintains a separate medical record section. This record-keeping method enables easy tracking of patient progress and ensures healthcare staff have access to up-to-date information.
Key Attributes include the following:
Methods of Documentation IV: Focus Charting
It typically involves three columns for recording information:
Data Collection II
