Wiz
Wiz performs interactive visualization and multivariate analysis of large, high-dimensional datasets to support scientific interpretation and discovery.
Key Features:
- Interactive Visualization: Provides interactive exploration of complex datasets to reveal data relationships and patterns.
- 5D Visual Analytics: Enables visualization and interrogation of up to five data dimensions simultaneously for multifaceted data interactions.
- Multivariate Data Analysis: Implements multivariate analyses including principal component analysis (PCA) and linear discriminant analysis (LDA) for dimensionality reduction and discriminant assessment.
- Customizable Plots: Produces customizable plot types, layouts and filtering options and generates high-quality, publication-ready images.
- Scalable Data Handling: Employs visualization techniques designed to handle large volumes of data efficiently.
Scientific Applications:
- Materials discovery: Visualization and analysis of high-throughput materials datasets to identify candidate materials and trends.
- Industrial digitalization: Analysis and visualization of large industrial datasets within digitalization workflows.
- Artificial intelligence and big data analytics: Exploratory data analysis and visualization to support AI and big data model development and interpretation.
- High-throughput methodologies: Interpretation and interrogation of large-scale high-throughput experimental or computational datasets.
Methodology:
Implements interactive visualization and 5D visual analytics and performs multivariate analyses including PCA and LDA, using visualization techniques to handle large volumes of data.
Topics
Details
- License:
- MIT
- Programming Languages:
- Python
- Added:
- 1/18/2021
- Last Updated:
- 3/18/2021
Operations
Publications
Balzer C, Oktavian R, Zandi M, Fairen-Jimenez D, Moghadam PZ. Wiz: A Web-Based Tool for Interactive Visualization of Big Data. Patterns. 2020;1(8):100107. doi:10.1016/j.patter.2020.100107. PMID:33294864. PMCID:PMC7691393.
Documentation
User manual
https://wiz.shef.ac.uk/helpTraining material
https://wiz.shef.ac.uk/examplesLinks
Repository
https://github.com/peymanzmoghadam/Wiz