Topics
Topics are the anchor for most Trendtracker exploration workflows.
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)
- Find a topic set (optional but useful for scoping): call
GET /topic-setswith aquerythat matches the area you care about, and copy theidof a relevant topic set from the response. - Search topics, including “risks”: call
GET /topicswithquery=risksto surface risk-related topics. AddtopicSetIds(one or more IDs from step 1) to limit results to that set. - Go deeper: use a topic’s
idwithGET /topics/{topic_id}/relatedfor adjacency in the graph, or pass those topic IDs astopicIdsin proof-point, fact, and manifestation request bodies.
Recommended endpoints
- List or search topic sets —
GET /topic-sets(use thequeryparameter to find sets by keyword). - Search topics by keyword —
GET /topicswithquery. AddtopicSetIdsto filter results to specific topic sets. Useskipandtakefor paging. - Related topics —
GET /topics/{topic_id}/relatedto expand context around a topic you already have. - Downstream data — reuse one or more topic IDs as
topicIdsin proof points, facts, and manifestations.