docs: add initial documentation for Getty Images data source

docs/getty-images-data-source.md

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+# Getty Images as a Data Source
+
+## Overview
+
+The Getty Images API provides access to information about a very large
+collection of visual content, including images, illustrations, and videos
+from Getty Images and iStock.
+
+Instead of providing the actual media files, the API focuses on returning
+metadata. This metadata describes the content, its creator, and how it is
+licensed or restricted for use. Because of this, the API can be useful for
+studying patterns in licensed creative works without storing or distributing
+the media itself.
+
+---
+
+## Proposed Queries
+
+Using the Getty Images API, several types of queries could be explored to
+understand creative content at a high level.
+
+For example, it is possible to:
+
+- Search for visual content using keywords or subject terms to understand
+  common themes or topics.
+- Filter content by asset type, such as images, illustrations, or videos.
+- Query assets based on licensing or usage restrictions to compare different
+  license models.
+- Retrieve metadata for specific assets using their unique identifiers.
+
+These types of queries help describe how creative works are organised,
+categorised, and licensed across a large content library.
+
+---
+
+## Data Returned
+
+When a query is made, the Getty Images API returns structured metadata about
+each asset. This metadata typically includes:
+
+- A unique identifier for the asset
+- A title or short description of the content
+- Information about the creator or contributor
+- Details about the license model or usage restrictions
+- Keywords or categories associated with the content
+- The type of asset, such as image or video
+
+This information provides context about the content and how it can be used,
+without requiring access to the actual media files.
+
+---
+
+## Relevance to Quantifying the Commons
+
+The metadata provided by the Getty Images API could support the goals of
+Quantifying the Commons by enabling analysis of licensed creative works at
+scale.
+
+For example, this data could help examine trends such as the distribution of
+license types, the kinds of creative content being produced, or how content
+is categorised over time. By focusing on metadata rather than media files,
+the project can analyse creative ecosystems while respecting usage and
+licensing constraints.