Data Dissemination Strategy

We prioritize interoperability, long-term preservation, and decentralized resilience.

High-Level Overview

    flowchart TD
    classDef linkNode stroke:#0000EE,color:#0000EE,stroke-width:2px;
    subgraph mirrors [Mirrors & Preservation]
        SourceCoop[Source Cooperative]
        Tigris[Tigris]
        Community[Community]
        Cloudflare
        Zenodo[Zenodo]
        InternetArchive[Internet Archive]
        Metadata[FAIR Data Catalogue]
    end

    Sources[Open Data Sources]
    Processes[Data Packages]
    Artifacts[Systems-Ready Data]
    P2P["P2P Technology"]
    
    subgraph Consumers [Consumption]
        Users[Data People & Developers]
        Systems[Systems]
    end

    %% Flow with Animations
    Sources a1@<--> Processes
    a1@{animate: true, animation: slow}
    
    Processes a2@<--> Artifacts
    a2@{animate: true, animation: slow}
    
    Artifacts a3@<--> Metadata
    a3@{animate: true, animation: fast}

    Metadata a20@<--> SourceCoop
    a20@{animate: true, animation: slow}
    Metadata a21@<--> Tigris
    a21@{animate: true, animation: fast}
    Metadata a22@<--> Community
    a22@{animate: true, animation: fast}
    Metadata a23@<--> Zenodo
    a23@{animate: true, animation: slow}
    Metadata a24@<--> Cloudflare
    a24@{animate: true, animation: fast}
    Metadata a25@<--> InternetArchive
    a25@{animate: true, animation: slow}
    
    %% Mirror Connections
    mirrors a12@<--> Consumers
    a12@{animate: true, animation: slow}
    

    %% Hint, the FAIR Data Catalogue can also be decentralized 🤯
    %%Metadata a30@<--> P2P
    %%a30@{animate: true, animation: fast}
    mirrors a9@<--> P2P
    a9@{animate: true, animation: fast}

    %% P2P Connections
    P2P a10@<--> Consumers
    a10@{animate: true, animation: fast}
    
    style Sources fill:#FFB74D,stroke:#EF6C00,color:#000000
    style Artifacts fill:#B71C1C,stroke:#7F0000,color:#FFFFFF
    %% Opera concertmaster
    style Metadata fill:#B71C1C,stroke:#7F0000,color:#FFFFFF
    class Metadata Metadata
    style Processes fill:#B71C1C,stroke:#7F0000,color:#FFFFFF
    class Processes Processes
    style SourceCoop fill:#B71C1C,stroke:#7F0000,color:#FFFFFF
    style Tigris fill:#B71C1C,stroke:#7F0000,color:#FFFFFF
    style Cloudflare fill:#FFB74D,stroke:#EF6C00,color:#000000
    style Zenodo fill:#FFB74D,stroke:#EF6C00,color:#000000
    style Community fill:#B71C1C,stroke:#7F0000,color:#FFFFFF
    style P2P fill:#B71C1C,stroke:#7F0000,color:#FFFFFF
    style InternetArchive fill:#66BB6A,stroke:#2E7D32,color:#000000
    style Users fill:#B71C1C,stroke:#7F0000,color:#FFFFFF
    style Systems fill:#B71C1C,stroke:#7F0000,color:#FFFFFF
    
    %% Click Actions
	click P2P "https://tixati.com/specs/bittorrent" _blank
    click Tigris "https://d4c-pkgs.t3.storage.dev/" _blank
    click Sources "https://www.dataforcanada.org/#high-level-overview" _blank
    click Processes "https://www.dataforcanada.org/docs/d4c-pkgs/" _blank
    click Metadata "https://stac-utils.github.io/stac-geoparquet/latest/spec/stac-geoparquet-spec/" _blank
    click Zenodo "https://zenodo.org/communities/dataforcanada/" _blank
    click SourceCoop "https://source.coop/dataforcanada/" _blank
    click InternetArchive "https://archive.org/details/@diegoripley/uploads/" _blank

    %% APPLY STYLES TO LINKED NODES
    class Sources linkNode

Dissemination Process

Once data products reach a production-ready state, they enter a dissemination flow designed for permanence and performance:

Cloud-Native First: Priority is given to performant, system-to-system file formats (e.g., Parquet) to enable high-throughput applications without the need for local parsing.
Persistent Identification: Every dataset version is assigned a DOI for citation and immutability.
The FAIR Data Catalogue: Global metadata is aggregated into a single, queryable FAIR Data Catalogue. This catalog acts as the “brain” of the system, tracking all versions and DOIs, and directing users to the optimal source within our multi-tier storage network:
- Source Cooperative serves as our primary mirror for all datasets, including large-scale products like orthoimagery (see Funding and Governance).
- Zenodo serves as our repository for long-term academic preservation and provides a high-speed mirror for European users (see Funding).
- The Internet Archive is utilized strategically for specific datasets to ensure historical redundancy (see Funding).
- Data for Canada Infrastructure is utilized strategically for specific datasets of high-value.

Decentralized Distribution

We are piloting a P2P technology, to maximize infrastructure resilience. By leveraging the P2P HTTP consumption feature, users will be able to download simultaneously from Source Cooperative, Zenodo, Data for Canada infrastructure, and community peers. This ensures high availability without a single point of failure. Current laboratory work is available in the d4c-infra-distribution.

🏗️ Open Processing Architecture

We believe that true open data requires open production. To ensure the longevity and resilience of Canada’s data infrastructure, we treat our data pipelines as open source software artifacts. We provide the “blueprints” alongside the data, allowing any user to verify our work or rebuild the dataset from scratch on their own infrastructure.

The Blueprint Model

Our processing strategy relies on three immutable components to guarantee transparency:

Build Manifests: Every dataset version is accompanied by a strict manifest. This locks the exact “ingredients” used: the cryptographic hashes of the raw source files, the specific Git commit of the processing code, and the configuration parameters.
Environment Definitions: Rather than opaque binaries, we publish the exact Infrastructure as Code (IaC) definitions (e.g., Dockerfiles). This allows users to inspect the system context (GDAL versions, libraries, and dependencies) and build the environment themselves.
Deterministic Builds: By combining a Build Manifest with our Environment Definitions, any user can execute a deterministic build. This process guarantees a bit-for-bit identical copy of the official Data for Canada artifact, ensuring that the pipeline is independent of our specific servers.

Mirrored Source Artifacts: Crucially, we do not rely solely on external version control systems like GitHub, which may change or disappear. A complete snapshot of the processing code, environment definitions, and manifests is bundled with every data release. These source artifacts are replicated across Source Cooperative, Zenodo, the Internet Archive, Data for Canada infrastructure, and the community, ensuring that the method of creation is preserved with the same redundancy as the result.

Work in the Lab: Smart Nodes

To further democratize access and ensure the persistence of Canada’s open data, we are experimenting with the features defined in previous work done by other organizations.

A Smart Node functions as a “set-it-and-forget-it” volunteer server, an automated library branch for our data infrastructure.

Automated Mirroring: Unlike a standard download, a Smart Node automatically synchronizes with our central FAIR Data Catalog. It intelligently fetches new or “at-risk” datasets to ensure they remain available even if the central portal experiences downtime.
Volunteer-Powered Resilience: This model allows partner institutions (ex. universities, research labs) and public volunteers to donate bandwidth and storage. By running a Smart Node, contributors actively protect vital Canadian datasets from being lost or gated.
Dynamic Storage Management: The node software monitors network health to optimize resource usage. Leveraging the P2P technology’s capability for selective piece mapping, the node does not need to store the entire catalog. Instead, it identifies specific file indices or “rare” pieces within the metadata and sends granular REQUEST messages for only those blocks. This allows a node with limited storage (ex. 500GB) to provide critical redundancy for a much larger archive (ex. 50TB) by surgically targeting only the data that is currently under shared.

We are currently refining the concepts from smart-node-transmission to work seamlessly with our catalog, enabling a fully decentralized data mesh for Canadian geospatial information.

    graph TD
    Catalogue[("FAIR Data Catalogue")]
    SmartNode["Volunteer Smart Node<br/>(Limited Storage)"]
    P2PNetwork(["P2P Community Peers<br/>(Massive Data Pool)"])

    Catalogue -->|"1. Syncs metadata"| SmartNode
    
    note["Note: The Node does NOT<br/>download the whole file."]
    SmartNode -.- note

    SmartNode -->|"2. Sends granular REQUESTs for specific pieces only<br/>(e.g., 'Send Piece #804 of Dataset B')"| P2PNetwork
    
    P2PNetwork -.->|"3. Transfers ONLY the requested blocks"| SmartNode

    classDef node fill:#fff9c4,stroke:#fbc02d,stroke-width:2px,stroke-dasharray: 5 5;
    classDef network fill:#e8f5e9,stroke:#2e7d32,stroke-width:2px;
    
    style Catalogue fill:#B71C1C,stroke:#7F0000,color:#FFFFFF
    style P2PNetwork fill:#B71C1C,stroke:#7F0000,color:#FFFFFF
    style SmartNode fill:#B71C1C,stroke:#7F0000,color:#FFFFFF

    click Catalogue "https://stac-utils.github.io/stac-geoparquet/latest/spec/stac-geoparquet-spec/";
    click SmartNode "https://www.dataforcanada.org/infrastructure/";

Last updated on Monday, February 23, 2026 at 7:39 AM -0500

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