DigitalSEE-HistoricalDataViewer

Overview

DigitalSEE-HistoricalDataViewer is an interactive data visualization application built with Streamlit and connected to a Hugging Face Space. It provides an easy way to visualize and explore historical geographic data, integrating information like locations, descriptions, and author details on an interactive map. The app utilizes Folium for mapping and Streamlit Folium for rendering the maps within the Streamlit interface.

The application is structured into two main components: a file selection viewer (visualization.py) and an interactive map viewer (map_page.py), both designed to interact with a dataset hosted on GitHub.

Table of Contents

• Features
• Usage
• Installation
• Components
  • Visualization
  • Map Page
• Data Source
• License

Features

• File Selection Viewer: Allows users to select and view historical data files hosted on the project's main GitHub repository - DigitalSEE.
• Interactive Map Viewer: Displays geographic locations and information using a fully interactive map.
• Geographic Data Visualization: Visualizes latitude and longitude data, with descriptive information and author details.
• Multiple Map Layers: Users can switch between OpenStreetMap and CartoDB (light and dark mode).
• Marker Clustering: Pins multiple locations on the map using marker clusters for easy navigation.

Usage

1. File Viewer: Use the sidebar to choose a file to visualize from the list of available datasets.
2. Map Viewer: Explore the map to view locations, descriptions, and other details associated with historical sites. Click on the markers to read more about each site.

The application provides a powerful yet simple and user-friendly interface to explore and interact with historical data using a combination of text details and maps.

Installation

To run the DigitalSEE-HistoricalDataViewer locally, follow these steps:

1. Clone the Repository:

   git clone https://github.com/Bestroi150/DigitalSEE-HistoricalDataViewer.git cd DigitalSEE-HistoricalDataViewer

2. Install Dependencies: Make sure you have Python installed, then use pip to install required libraries.

   pip install streamlit folium streamlit-folium requests

3. Run the Application:
   streamlit run visualization.py

   This will start a local server, and you can access the app in your web browser.

Components

Visualization (visualization.py)

• Purpose: This page displays author and publication details of historical sites, alongside geographic data and a description of each entry.
• File Selection Sidebar: Allows users to select a JSON file from the dataset to view its contents.
• Map Rendering: If geographic coordinates are available for a selected entry, the app uses Folium to display the location on an interactive map.

Map Page (map_page.py)

• Purpose: Visualizes all the available geographic data on a map, with clusters of markers representing different locations.
• Full Screen & Layer Controls: Users can toggle fullscreen mode and switch between map layers.
• Marker Clustering: Each location in the dataset is represented as a marker, which can be clicked to reveal additional descriptive information.

Data Source

The data is hosted on GitHub in a JSON master file. The app fetches and parses the dataset from the following URL:

https://raw.githubusercontent.com/Bestroi150/DigitalSEE/main/JSON/EN.json

Each entry in the dataset includes:

• Filename: The identifier for the historical entry.
• Author Details: Information on the author and the publication.
• Geographic Coordinates: Latitude and longitude for mapping.
• Description: A brief summary of the historical site.

License

Creative Commons Attribution-ShareAlike 4.0 International. See the LICENSE file for more details.