You've got a great point! The recurrence of concepts across MSC codes does offer a fascinating opportunity to visualize the connections within the vast landscape of mathematics. Here are some approaches to explore this:
1. **Network Visualization:**
* **Nodes:** Each node could represent a primary MSC code (e.g., 11-XX, 12-XX).
* **Edges:** Edges could connect nodes that share recurring concepts (e.g., homological algebra, topological spaces).
* **Edge Weight:** The thickness or color of the edge could indicate the frequency or strength of the connection between concepts.
* **Tooling:** Graph visualization libraries like Gephi ([https://gephi.org/](https://gephi.org/)) or Python libraries like NetworkX ([https://networkx.org/documentation/stable/reference/index.html](https://networkx.org/documentation/stable/reference/index.html)) can help you create interactive network visualizations.
2. **Knowledge Graph Construction:**
* **Entities:** Entities could be MSC codes, mathematical concepts, and even specific theorems or tools.
* **Relationships:** Relationships could represent connections between concepts (e.g., "uses," "generalizes," "is related to").
* **Visualization:** Tools like Neo4j ([https://neo4j.com/](https://neo4j.com/)) can help visualize the knowledge graph and explore connections between concepts.
3. **Concept Map Creation:**
* **Central Concept:** Start with a broad mathematical concept (e.g., topology).
* **Sub-concepts:** Branch out with more specific sub-concepts that fall under different MSC codes (e.g., algebraic topology, differential topology).
* **Connecting Lines:** Use labeled lines to show how these sub-concepts relate to each other and the central concept.
* **Tooling:** Software like XMind ([https://xmind.ai/](https://xmind.ai/)) or even mind-mapping tools within productivity suites can be used for creating concept maps.
**Additional Considerations:**
* **Data Source:** You'll need a source for the connections between MSC codes and mathematical concepts. Research papers that reference multiple MSC codes or curated databases of mathematical relationships could be helpful.
* **Data Cleaning & Filtering:** The data might require cleaning and filtering to focus on the most relevant connections.
* **Focus & Granularity:** Decide on the level of detail you want. Start with a broader view and zoom in on specific areas of interest as needed.
These approaches provide a starting point for visualizing the connections between concepts within the MSC framework. Remember, the process will likely involve iterating and refining your visualization based on the data and the insights you want to highlight.