A Self-Ordering Research Ecosystem: Structural Analysis of a Triangular Coherence Anchor in a Multi-Record Zenodo Corpus

This paper documents a structural analysis of an 84-record research corpus hosted on Zenodo, examined as an integrated research ecosystem rather than a flat collection of independent publications.Using repository metadata, versioning relationships, internal cross-citation patterns, and usage dynamics, the analysis identifies persistent internal order that governs how the corpus evolves, renews, and maintains coherence over time.Three relationship classes—sequential, modular, and associative—are shown to be sufficient to describe the connective tissue of the corpus. Coherence is not uniformly distributed but concentrates in a triangular configuration formed by foundational definitions, boundary constraints, and diagnostic workflows.This configuration functions as a gyroscopic anchor, preserving logical integrity under renewal, inversion, and growth. Performance metrics such as views, downloads, and citations are observed to follow this structural map rather than drive it.The paper is descriptive rather than prescriptive, making no claims of optimization or ranking. Its purpose is to record how order can precede form in an open research repository, allowing large, evolving bodies of work to remain stable, interpretable, and extensible without central control. Keywords.research ecosystemself-ordering systemsstructural coherenceopen scienceZenodo corpus analysisversioning and lineagemodular research designcross-citation networksknowledge persistenceboundary-driven methodsdiagnostic workflowsemergent research structure