Topics

A topic is a concept Trendtracker tracks in its knowledge graph: technologies, markets, materials, and risk themes you can measure and compare. Examples include:

• precision fermentation
• edge AI
• solid-state batteries
• supply chain disruption (as a risk topic)

Most workflows start with topic discovery, then pass topic IDs from the responses into proof points, facts, manifestations, or Industry TSI.

Topic hierarchy

Topics are organized in a parent–child hierarchy. A child is a narrower concept under a broader parent; both are topics with their own IDs. For example, Generative AI is a child of artificial intelligence. When you search or browse, you work with the same topic model—use the returned IDs to query related topics or to scope proof points, facts, and manifestations.

Topic sets

Topics are grouped thematically in topic sets (for example, a set may group related technologies or a risk domain). A single topic can belong to one or more topic sets. Topic set IDs are useful to scope a topic search so results stay within a theme you care about.

How to use topics (typical flow)

1. Find a topic set (optional but useful for scoping): call GET /topic-sets with a query that matches the area you care about, and copy the id of a relevant topic set from the response.
2. Search topics, including “risks”: call GET /topics with query=risks to surface risk-related topics. Add topicSetIds (one or more IDs from step 1) to limit results to that set.
3. Go deeper: use a topic’s id with GET /topics/{topic_id}/related for adjacency in the graph, or pass those topic IDs as topicQuery in proof-point, fact, and manifestation request bodies. Region (GPE) IDs from the same search go in gpeQuery.

Recommended endpoints

• List or search topic sets — GET /topic-sets (use the query parameter to find sets by keyword).
• Search topics by keyword — GET /topics with query. Add topicSetIds to filter results to specific topic sets. Use skip and take for paging.
• Related topics — GET /topics/{topic_id}/related to expand context around a topic you already have.
• Downstream data — reuse one or more topic IDs as topicQuery in proof points, facts, and manifestations. Combine IDs with OR (union) or AND (intersection); see Topic query syntax. Pass GPE IDs as gpeQuery (GPE query syntax).