Knowledge with sources, context and a path to correction.
Dknowledge connects the papers, architecture, decisions and evidence of Drayker. Its longer-term design links public, project and personal knowledge under distinct access and provenance rules.
Knowledge records should retain their origin, scope, revision history and relevant dependencies, so that a correction can prompt review of the conclusions built on it.
Shared memory becomes more useful when people can inspect how it was formed, challenge it and carry corrections forward.
When a measurement is corrected, a project should be able to locate the analysis and decision that used it and record whether their conclusions still hold. This is an illustration of the proposed design.
Dknowledge is the memory of it: what has been decided, tried, learned and discarded, still attached to its sources.
The argument in full is on the manifesto; the economy page states plainly what contributing here earns and what it does not.
The systemic final form of Dknowledge is described as evolutionary knowledge graphs — a version of the knowledge layer that is more than a graph of linked documents, and more complex than a wiki can be. Requirements, decisions and evidence stay connected by trust derived from evidence rather than from position; the graph evolves with the system, so the memory of the network is not a snapshot but a living structure — the same fractal logic Dk is designed around, applied to knowledge itself. Today Dknowledge is pages, papers and roadmaps connected to their sources. What it becomes is a structure that only exists as the whole.
Each scale of the intelligence carries its own knowledge: Dk Personal is connected to the person's personal Dknowledge, Dk Global to global Dknowledge, and every organization and project has its own Dknowledge in connection with a specialized Dk. Dknowledge is not one repository of everything — it is the pattern repeated at every scale, and the global Dknowledge is the junction of them all.
One of the conceptual bases for that pattern is E.C.H.: Expansion, Complexity and Harmony. Expansion admits relevant experience, data and knowledge without treating accumulation as the goal. Complexity connects entries to sources, decisions, hypotheses and other relations. Harmony checks coherence and integrity while keeping contradictions visible; it may integrate a new entry, keep alternatives contextualized, or conclude that the previous state must be reconstructed. The cycle repeats at personal, project and global scales.
Learning crosses scales in two distinct ways. In anonymous federated learning, raw experience stays at its originating instance while patterns or model updates circulate with depersonalized metadata. Global Dknowledge can therefore hold broader context and deeper learned structure without becoming a collection of personal histories; when a pattern is validated independently in other instances, its weight in global learning becomes progressively stronger. In deliberate contribution, a person or unit chooses to share knowledge, evidence or narrative under explicit permissions and provenance. Neither route makes private context common property, and the federated route still requires a re-identification threat model before implementation.
Importantly, memory is corrigible and contestable. An individual member retains sovereign authority to inspect, contest, and correct algorithmic inferences made by their agent, revoking associations or exporting their relational memory graph without platform lock-in.
Dk and Dknowledge remain distinct. Dk coordinates, reasons and proposes actions over the available context. Dknowledge preserves the evolving state, provenance, permissions and decision lines needed to reconstruct what the system knew and why it changed. Epistemologically, Dknowledge operates under the core Drayker principle: kind to people, relentless with ideas — protecting the unconditional dignity and situated context of every human participant, while holding every technical hypothesis, proof, and allocation to uncompromising empirical verification. Economic models documented here reflect the strict tri-spherical separation: common capacity reserves, project-linked temporary custody, and personal member balances (Dktron) immune to inactivity forfeiture.
- Current orientation — what is publicly available now, what remains architecture, and how founding governance works.
- Papers — organised by main project rather than by date or author: Dk, ecosystem, organization.
- Historical roadmap — older structures and planning documents preserved as context, not a current schedule or commitment.
- CONTRIBUTING — how to collaborate.
- Code of conduct.
Main projects sit in priority and time queues; effort and resources treat them as the priority. Projects outside that set can be opened and proposed by any contributor through DFMPProject.
Dknowledge is the connective tissue: Dk is the intelligence, DFM is the method, PAP is the durable environment for projects and applications, and DAF is a transitional governance experiment — and this is where what they mean, what is being designed and what was decided stay traceable to their sources.
A complex system needs memory that can be followed, not just information that can be stored. That is the whole reason this repository exists.
It is the memory the rest of the ecosystem reads from and writes to. The Dk intelligence draws on it for architecture and decisions. Papers and resolutions from DFMP are documented here. The Academy reads from it and feeds learning back. Evidence from open science and projects in transition from Emergence land here. Even the historical roadmaps are kept — dated, and separated from current work — because the reasoning is worth reading even when the phase has passed.
The most complete documentation in the Drayker ecosystem — start with Current orientation if you are new. It is also the oldest: parts of the roadmap and several papers predate the current shape of the projects, so read dates before treating anything as current.
Open an issue. Issues small enough for one person to finish carry the open-function label and appear on the board at drayker.org. Reading a paper and writing down where it no longer matches reality is a genuinely useful contribution here.
Other languages: Português · Español — both currently behind this English version.
DFMP and DAF describe proposed collaboration and governance architecture. Drayker's current founding-phase governance is documented in draykerdk/.github, and the work is primarily voluntary.