Demo Data from EDBT 2026 / reviewers in the wild / expert
Jize Bi
dblp:381/6106
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Medical and health informatics · 100% | |
| Databases, data mining, and information retrieval
1 paper |
Data stream processing · 100% | |
| Computer graphics and multimedia
1 paper |
Visualization and visual analytics · 100% |
Topics — the 1 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Visualization and visual analytics
health data visualization |
0.2 | 1 | 2024 | Wearables for Health (W4H) Toolkit for Acquisition, Storage, Analysis and Visualization of Data from Various Wearable Devices · ICDE 2024 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Wearables for Health (W4H) Toolkit for Acquisition, Storage, Analysis and Visualization of Data from Various Wearable DevicesabstractThe Wearables for Health Toolkit (W4H Toolkit) is an open-source platform that provides a robust, end-to-end solution for the centralized management and analysis of wearable data. With integrated tools and frameworks, the toolkit facilitates seamless data acquisition, integration, storage, analysis, and visualization of both stored and streaming data from various wearable devices. The W4H Toolkit is designed to provide medical researchers and health practitioners with a unified framework that enables the analysis of health-related data for various clinical applications. We provide an overview of the system and demonstrate how it can be used by health researchers to import and analyze a wide range of wearable data and perform data analysis, highlighting the versatility and functionality of the system across diverse healthcare domains and applications. Arash Hajisafi, Maria Despoina Siampou, Jize Bi, Luciano Nocera, Cyrus Shahabi |
ICDE | 3 |