We propose the development of an Exploratory Data Analysis (EDA) dashboard to provide users with a comprehensive and interactive platform for exploring the PINCH data. This dashboard will enable users to gain insights, identify trends, and uncover patterns within the data.
Key Features
- Data Exploration: Users can browse through all available data in the database, allowing them to familiarize themselves with the dataset and identify areas of interest.
- Descriptive Statistics: Generate tables with summary statistics for selected data for easy reference and publication-ready export formats (e.g., CSV, Excel, LaTeX).
- Time Series Analysis: Users can investigate time series data to spot potential trends or anomalies within the data.
- Geographical Visualization: The capacity to view the geographical distribution of variables, providing valuable context for understanding spatial relationships.
- Modeling and Pattern Detection: Integration with machine learning algorithms (e.g., Decision Trees, Random Forest, Linear/Logarithmic Regression) to enable users to run models directly from within the dashboard and uncover associations and patterns in the data.
Implementation
We already have a skinned-down version of the dashboard available as a proof of concept.
The prototype can be accessed at: https://app-eda-dashboard.cloud.sdu.dk/
This prototype demonstrates the basic functionality and potential of the dashboard.
Benefits
The Exploratory Data Analysis Dashboard will accelerate exploratory data analysis and hypothesis generation/testing by providing an intuitive interface for interacting with the data. It will make data more accessible and usable for a wider range of users, enabling more users to access and derive insights from the data. The dashboard will improve the efficiency and reproducibility of research by streamlining common data analysis tasks and facilitating sharing of results.