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dku-infosci301-Autumn2026/worldbank_china_health

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App README

China Health Indicators Data Story

An interactive, browser-based data visualization exploring selected health indicators for China over time.

The project presents the same underlying country-level data through three complementary visual forms:

  • —Slope Graph — compares a selected indicator between two years.
  • —Dumbbell Plot — emphasizes the distance between the baseline and target year.
  • —Ranked Dot Plot — places all available observations for the selected indicator along a time axis.

Users can select an indicator and comparison years, then click individual data points to inspect the underlying observation.

Data Source

The visualization uses:

Hugging Face Dataset: https://huggingface.co/datasets/electricsheepasia/asia-world-bank-health-indicators-for-china

The dataset is a curated/repackaged collection of World Bank health-related indicators for China.

Original producer: World Bank Group

The underlying dataset contains country-level observations with fields including:

  • —country_name
  • —country_iso3
  • —year
  • —indicator_name
  • —indicator_code
  • —value
  • —esa_source
  • —esa_processed

The dataset covers multiple health and population-related indicators across a long historical period. The visualization does not invent, interpolate, or simulate observations.

How the Visualization Works

When the page is opened, the application automatically retrieves the dataset from the Hugging Face Hub and prepares the records needed for the visualization.

The interface then:

  1. 1.Loads the available data.
  2. 2.Identifies valid China (CHN) observations.
  3. 3.Groups observations by indicator and year.
  4. 4.Lets the user choose an indicator and two comparison years.
  5. 5.Generates the three chart views.
  6. 6.Allows individual data points to be selected for a detailed view.

The page is designed so that users do not need to install Python, Node.js, npm, or any other software.

Charts

1. Slope Graph

The Slope Graph connects the selected indicator's value at the baseline year to its value at the target year.

This makes increases and decreases between the two selected years immediately visible.

2. Dumbbell Plot

The Dumbbell Plot displays the baseline and target observations as two endpoints connected by a line.

It provides another way to focus on the magnitude and direction of change.

3. Ranked Dot Plot

The Ranked Dot Plot displays all available observations for the selected indicator across the historical time range.

This makes it easier to see the broader temporal pattern rather than only the two selected years.

Units

Indicator units depend on the selected World Bank indicator. Examples include:

  • —Years
  • —Percentage of GDP
  • —Per 1,000 people
  • —Per 1,000 live births
  • —Per 100,000 live births
  • —Births per woman
  • —Current US dollars per capita

The visualization displays the unit associated with the selected indicator rather than treating different indicators as if they shared a common measurement scale.

Data Processing

The website performs lightweight client-side processing:

  • —Filters records to China using country_iso3 = CHN.
  • —Converts year and value fields to numeric values where needed.
  • —Combines the available dataset splits.
  • —Removes exact duplicate observations.
  • —Sorts observations chronologically.
  • —Uses only observed values supplied by the dataset.

No missing values are filled with fabricated numbers, and no interpolation is used to create observations that are not present in the source data.

Limitations

This visualization should be interpreted as a descriptive exploration of country-level health indicators, not as evidence of individual-level health outcomes or causal relationships.

Important limitations include:

  • —The observations are country-level aggregates.
  • —The dataset does not provide micro-level environmental exposure tracking.
  • —Country-level trends cannot establish individual- or neighborhood-level causation.
  • —Different indicators may have different coverage periods and missing years.
  • —The underlying data originates from the World Bank and associated international data sources and has not been independently validated by this visualization project.
  • —Differences in definitions, reporting practices, data quality, and collection methods may affect comparisons across years.

For methodological details and the original source documentation, consult the dataset and its upstream sources.

Technology

The website is a static browser application built with:

  • —HTML
  • —CSS
  • —Vanilla JavaScript
  • —Hugging Face Dataset APIs
  • —Browser-compatible data processing

It does not require a Python backend, Node.js server, npm build process, or local database.

Accessibility and Interaction

The interface includes:

  • —Responsive layouts
  • —Keyboard-focusable controls
  • —Readable contrast
  • —Accessible buttons for interactive data points
  • —Modal details for individual observations
  • —Loading and error states
  • —Responsive chart sizing

Attribution

Data source:

World Bank Group, accessed through the curated Hugging Face dataset:

https://huggingface.co/datasets/electricsheepasia/asia-world-bank-health-indicators-for-china

Dataset curator/repackager:

Electric Sheep Asia

Please refer to the original dataset documentation for the most complete information about provenance, methodology, licensing, and limitations.

License

The upstream Hugging Face dataset is distributed under CC BY 4.0 according to its dataset card.

Please consult the upstream dataset page for the current licensing terms and attribution requirements:

https://huggingface.co/datasets/electricsheepasia/asia-world-bank-health-indicators-for-china