Knowledge Micrographs: A Scenario-Centered Architecture for Evaluation, Decision, and Action

Counts differ because each database indexes a different set of publications. We treat OpenAlex as the canonical count; Google Scholar is not shown (no API, and crawling it violates its ToS).

Knowledge graphs have become an important paradigm for representing heterogeneous entities, relationships, provenance, and contextual information. Yet many knowledge-graph architectures tend to optimize for representation, integration, retrieval, and inference rather than for the transition from knowledge to evaluation, decision, and action. Scenario planning provides structured methods for reasoning under uncertainty, but it is commonly conducted through documents, workshops, models, and narratives whose assumptions and dependencies are difficult to represent, update, compare, and reuse computationally.This preliminary discussion paper proposes knowledge micrographs as scenario-centered units intended to bridge these domains. A knowledge micrograph is a bounded, independently addressable, and composable knowledge structure whose boundary follows epistemic and decision relevance. It preserves the claims and evidence, methods and uncertainties, stakeholder perspectives and objectives, scenarios and constraints, possible actions and observed outcomes associated with a defined question or decision context, together with provenance and revision history.The proposed architecture supports a transition from graph representation toward scenario computation. Its functional lifecycle treats evaluation as producing explicit epistemic states, scenarios as organizing alternative futures, decisions as operating on those scenarios, and actions as generating evidence that updates the knowledge structure. Six overlapping analytical dimensions—ontological, epistemological, methodological, axiological, praxiological, and teleological—describe different aspects of the content represented within that lifecycle.The paper identifies unresolved design questions and presents an evaluation agenda for investigating a broader class of scenario-native knowledge systems. The proposal remains preliminary and has not yet been validated through an independent implementation or empirical study.