How Was Nomismata Built? The Data Model.

At the foundation of Nomismata lies a carefully structured data model, which defines the types of data contained in the database and the relationships between them. Rather than inventing a new framework from scratch, the model was shaped by a thorough analysis of existing literature, ensuring that the database was structured around and built upon the sources that inform it.

Defining the Core Objects

The examination of scholarly works identified the key objects that needed to be represented in Nomismata:

1. FINDSPOT – The location where coins were discovered.
2. COIN – The individual numismatic objects recorded in the database.
3. MINT – The minting locations where coins were produced.
4. SOURCE – The historical or scholarly sources providing information on finds and coins.

A fifth object, CITY, was added to account for the georeferencing of both mints and coin finds, allowing for spatial analysis.

Structuring the Relationships

Organizing the data from historical sources in a logical and structured way was one of the most creative aspects of building Nomismata. The result was a network-based data model where objects are interconnected through defined relationships.

• Each object (e.g., COIN) is characterized by specific attributes.
  • Example: The COIN object includes attributes such as Denomination, Mint, Issuing Authority, etc.
• The possible values for each attribute are standardized in NODEGOAT’s Categories.
  • Example: The “Denomination” category contains predefined values like Solidus, Tremissis, Semissis, Miliaresion, 40 nummi, Follis, Hyperpyron, etc.
• This categorization ensures data consistency, preventing variations in terminology (e.g., “Solidus” vs. “Solido” or “Tremissis” vs. “Tremisse”).

Visualizing Relationships: The Role of Network Analysis

In the data model, the blue lines connecting object attributes to categories or other objects visually represent the relationships that structure the database. This approach reflects the interconnected nature of numismatic data, allowing researchers to analyze patterns over time and space.

Each attribute can serve as a search filter, making the database highly flexible for research. By combining attributes, users can refine their queries to extract precise historical and geographical insights.

Example search query:

“Show me all the 40 nummi minted in Constantinople and Nicomedia that were found in the Near East.”

By integrating structured data, georeferencing, and network visualization, Nomismata provides a powerful research tool for exploring the historical circulation of coins.