The Relational Nature of Information: Why Information Is Neither Matter nor Energy
What is information, and where does it exist? Contemporary theories typically treat information as a measurable quantity (Shannon), a physical resource (Landauer), or a semantic entity (Floridi). This paper proposes a complementary ontological perspective: information is neither an intrinsic property of matter nor of physical structure alone, but an emergent property of a relation established between systems through a shared structural code. To clarify this distinction, a four-layer conceptual framework is introduced, separating matter, structure, coding, and information into irreducible yet dependent categories. Matter provides the physical substrate; structure organizes that substrate; coding establishes relational correspondences between structures; and information emerges only when those correspondences are successfully interpreted. This framework explains why identical physical configurations may constitute information for one system while remaining mere physical structures for another. The paper develops the Relational Information Principle, according to which no isolated physical structure can be identified with information independently of a coding relation. The proposal unifies examples from telecommunications, genetics, language, computation, and consciousness under a common relational ontology, while remaining compatible with formal approaches such as the Theory of Axiomatic Necessity (TNA). Rather than redefining information in statistical or semantic terms, this work addresses a different question: the ontological status of information itself, arguing that information is fundamentally a relational phenomenon rather than an intrinsic property of physical objects.
Authors
- Claudio Bresciano (ORCID: https://orcid.org/0009-0009-3218-0599)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-06-30
- DOI
- https://doi.org/10.5281/zenodo.21079700
- Primary Topic
- Computability, Logic, AI Algorithms
- Type
- article
- Field-Weighted Citation Impact
- 0.00