🏺 QuantWealth Guide (documentation)

1. Overview

QuantWealth is a web-browser application for quantifying and visualizing wealth display and inequality in archaeological contexts such as graves (count data) and physical measures (e.g. house floor area). It provides a data-driven approach to estimate the exclusivity ("Prestige") values of grave goods and other archaeological features, without requiring subjective fixed-point value systems.

Important disclaimer: This app is just a calculator. Wealth can be expressed in many other ways not captured in this app, and fragile organic materials are often missing archaeologically, which can skew results, so interpret the app's results and diachronic overview patterns with caution and look into the context of each data point on this app.

NB: The app will only store your results and derived data or your input data if you actively add these to the atlas and fill out the popup form. No other data or plots are stored. I do heavily recommend to at least store the derived plots and derived data if adding results to the map for minimal reproducibility.

The aim of this app is to capture as much wealth display as broadly as possible, with commonly produced, and relatively low quality, data:

For other (multivariate) ways of capturing grave wealth, that require more detailed data, see Nørtoft 2022 from which the "Prestige" (exclusivity) value approach for counts in this app is derived.

Key Features

• Prestige Value Calculation: Automatically estimates the exclusivity of grave good types (and other count data) based on their co-occurrence patterns for adults and subadults respectively
• Inequality Measures: Computes Gini coefficients and visualizes wealth distributions and Lorenz curves, separately for adults and subadults
• Physical Size Analysis: Calculates inequality from e.g. house floor area data (or any other physical measure)
• Interactive Time Atlas: Maps voluntarily donated results geographically and temporally
• Trend Analysis: Generates on-the-fly trend plots for user-defined regions and time ranges

2. Data Preparation

Grave Goods Data Format

Your input file should be a CSV or Excel file with the following structure (any other columns than Grave ID can be any type of count data), for example:

• First column: Unique identifier (Grave ID)
• (Optional) coordinate columns: 'lat' and 'lng' columns (more accurate if adding results to the map, and for multiple sites a centroid of the coordinates is created)
• (Optional, recommended) adult/subadult columns: For graves, it is recommended to include adult_count and subadult_count columns which lets the app automatically calculate prestige values based on adults only (but adult-based values are applied to both adult and subadult graves), and separate calculation for subadult-exclusive grave goods. Subadult-exclusive grave good types are appended to the boxplot with a '*' in front. This avoids the proportion of subadult graves (typically with less grave goods) affecting the overall result, and also lets the app calculate inequality measures for adults and subadults separately which is recommended (e.g. Nørtoft/Rohrlach forthcoming; Brummack forthcoming).
• Other columns: Numeric counts for each grave good type (or presence/absence as 1/0)
• Empty cells or zeros: Indicate absence of that item

Physical Sizes Data Format

For physical size analysis, use a simpler two-column format, with optional non-numerical metadata from column 3 onwards:

• First column: Unit identifier
• Second column: Floor area in square meters (m²)

Want to submit your results to the atlas, and already have coordinates?
For both physical sizes (e.g. houses) and grave goods/features (counts), the app autodetects coordinate columns if named lng (longitude) and lat (latitude), in decimal degrees, e.g. Paris is: 2.3522 (Longitude: East of Greenwich, England), 48.8566 (Latitude: North of Equator).
If you have graves aggregated from multiple sites with small sample sizes (less than c. 30, such as grave mounds or small cemeteries), the app will automatically find the centroid of your different coordinates.

3. Grave Goods Workflow

QuantWealth supports separate analysis of adult and subadult (child) graves, allowing researchers to examine wealth inequality patterns across age groups.

Data Format

To enable age-separated analysis, include one or both of these columns in your data:

• adult_count: Number of adult individuals in the grave (empty = 0)
• subadult_count: Number of subadult individuals in the grave (empty = 0)

Grave classification rules:

• Adult grave: adult_count ≥ 1 (even if subadults are also present)
• Subadult-only grave: adult_count = 0 AND subadult_count ≥ 1
• Unknown age: Both columns empty or missing → treated as adult

When you upload a file with these columns, QuantWealth will automatically detect them and check the corresponding boxes in the interface.

Prestige Calculation with Age Data

When age columns are present, prestige values are calculated as follows:

1. Adult-derived prestige: Prestige values for grave good types are calculated from adult graves (including graves with unknown age) and applied to ALL graves (including subadults).
2. Subadult-exclusive types: Grave good types that appear ONLY in subadult graves receive their own prestige calculation based on the subadult grave data. These types are marked with an asterisk (*) in the boxplot and appear at the end of the x-axis.

Per-Capita Wealth Division

To account for multiple individuals in a single grave, wealth is divided by the number of adult individuals:

• Adult graves: (prestige_total + subadult_count) / adult_count
• Subadult-only graves: prestige_total / subadult_count

Note: For adult graves containing subadults, each subadult adds +1 to the wealth before division. This reflects the interpretation that depositing a child in an adult's grave represents a symbolic action of relational wealth for the adult.

4. Physical Sizes (e.g. house floor area) Workflow

The physical sizes analysis is simpler since it works directly with physical measurements rather than derived exclusivity values.

5. Understanding the Results

What is Exclusivity (Prestige)?

In QuantWealth, exclusivity refers to the tendency of a grave good type to appear in graves with many other types. The logic is:

• Items found primarily in "wealthy" graves (high TOT scores) receive higher exclusivity values
• Items found in "poor" graves (low TOT scores) receive lower exclusivity values
• This is data-driven and specific to each dataset, allowing for cultural and temporal variation in perceived value

The Three Wealth Measures

What is the Gini Coefficient?

The Gini coefficient is a measure of inequality ranging from 0 to 1:

• 0 = Perfect equality (everyone has the same wealth)
• 1 = Perfect inequality (one person has all the wealth)

What is Absolute Gini?

The Absolute Gini (e.g. Bandyopadhyay 2018) multiplies the Gini coefficient by the mean wealth:

This contextualizes inequality by overall wealth levels. Two societies with similar relative Ginis may have very different Absolute Ginis if the general amount of wealth (mean wealth to avoid sample size differences) is different between them, in which case one society may have a larger absolute wealth gap. Thus, the Absolute Gini can help to show growing wealth gaps when comparing multiple case studies over time.

How to Read the Lorenz Curve

The Lorenz curve shows the cumulative share of wealth (y-axis) held by the cumulative share of the population (x-axis):

• The grey diagonal line represents perfect equality
• The further the curve bows below the diagonal, the greater the inequality
• The Gini coefficient equals twice the area between the curve and the diagonal
• The Lorenz curve can help to interpret the Gini by showing where the wealth is concentrated in a given case study
• The QuantWealth app shows a Lorenz curve and relative Gini coefficients for each of the three grave wealth measures (TOT+1 (red), prestige value types (blue), and prestige + count bonus (green)) to compare results of the different methods

What is CAI?

In the Trend Plot you may see the CAI measure. The Composite Archaeological Inequality index (CAI, by Oka et al. 2018) combines any available relative inequality measures between 0 and 1:

This geometric mean (inspired by the Human Development Index) provides a composite inequality measure when both types of data are available for a region (within a 300 year span). It appears in trend plots when more than one Gini result exists within the selected area and time frame.

6. The Map & Time Atlas

Map Markers

• Green circles: Grave goods inequality results
• Purple circles: Physical size inequality results
• Circle size: Scaled by sample size
• Color intensity: Reflects the Absolute Gini value

Time Slider

Use the time slider at the bottom of the map to filter results by time period. Only results whose date range is within the selected range will be displayed. You can also move your chosen time window by dragging somewhere within the chosen range, or simply press play and watch the map visualization.

Layer Toggles

Use the checkboxes in the top-right corner to show/hide grave results or physical size results independently. You can also switch basemaps in the same corner.

Popup Information

Click on any marker to see detailed information including:

• Culture/period name
• Gini coefficients (relative and absolute)
• Mean wealth
• Sample size
• Date range
• Contributor information
• Links to view plots and download data (if available)

7. Trend Plots

Creating a Trend Plot

1. Use the drawing tools (rectangle or polygon) to draw an area on the map
2. Adjust the time slider to your desired time range
3. Click "Show Inequality Trend" to generate the plot

Interpreting the Trend Plot

The trend plot shows normalized values (0-1 scale) for selected metrics:

Automatic Updates

The trend plot automatically updates when you:

• Change the time slider range
• Draw a new area on the map

8. Further Reading

For the theoretical background and methodological details behind QuantWealth, see:

• Nørtoft, M. (2026 preprint). QuantWealth.eu - an online app for easy quantitative wealth and inequality studies. SocArXiv. https://doi.org/10.5334/jcaa.86
• Nørtoft, M. (2022). A New Framework for Quantifying Prehistoric Grave Wealth. Journal of Computer Applications in Archaeology, 5(1), 123–139. https://doi.org/10.5334/jcaa.86
• Nørtoft, M. & Rohrlach, A.B. (forthcoming). Modelling Grave Wealth and Inequality in the Czech Republic.

Key References on Archaeological Inequality

• Kohler, T.A. & Smith, M.E. (Eds.). (2018). Ten Thousand Years of Inequality: The Archaeology of Wealth Differences. University of Arizona Press.
• Oka, R. et al. (2018). Dreaming Beyond Gini: Methodological Steps Toward a Composite Archaeological Inequality Index. In Kohler & Smith (Eds.), pp. 67–95.
• Borgerhoff Mulder, M. et al. (2010). Intergenerational Wealth Transmission and Inequality in Premodern Societies. Current Anthropology, 51(1), 65–83.
• Bandyopadhyay, Sanghamitra (2018). The Absolute Gini Is a More Reliable Measure of Inequality for Time Dependent Analyses (Compared with the Relative Gini) Economics Letters, 162, 135–139. https://doi.org/10.1016/j.econlet.2017.07.012
• Brummack, Sven. forthcoming. Studien zur Ungleichheit. Kupferzeitliche Gräberfelder in Südosteuropa 4800-3800 calBC. PhD thesis, Freien Universität Berlin, Berlin.