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Network Canvas Documentation

website·Indexed 31 days ago

https://documentation.networkcanvas.dev/

A suite of applications for researchers to collect network data, featuring Architect for designing interview protocols, Interviewer for conducting in-person interviews, and Fresco for data collection. The documentation covers protocol design, including variables, skip logic, network filtering, and the use of .netcanvas files, as well as implementation guides for methods like the Colored Eco-Genetic Relationship Map (CEGRM).

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What's inside Network Canvas

  1. Overview of the Geospatial Interface

    The Geospatial Interface is a name interpreter that captures geospatial data for alters in a participant's network. It allows users to select outlined areas on a map defined by a GeoJSON file. It is available in Architect, Interviewer, and Fresco (Schema v8+).

    Critical Requirement: This interface requires an active internet connection during the interview because it loads maps via Mapbox. It cannot be used for fully offline studies.

  2. Overview of Architect versions

    Architect is the protocol designer for Network Canvas and comes in two distinct versions. They share the same workflow but are not interchangeable:

    1. Architect (Browser-based): Runs entirely in a modern web browser with no installation required. It can be installed as a Progressive Web App (PWA) for offline use.
    2. Architect Classic: A downloadable desktop application.

  3. Overview of Forms in Network Canvas

    Forms are used in Network Canvas Architect to assign values to variables for egos, nodes, or edges. A form consists of one or more fields. Each field is a combination of a variable, an input control, a question prompt, and validation options. Forms are commonly used within Interfaces such as the Name Generator, Per Alter Form, and Ego Form.

  4. Overview of the Fresco study workflow

    Fresco is a web-based dashboard used to conduct studies based on interview protocols designed in Architect. The standard operational workflow consists of:

    1. Deploy Fresco: Set up your own instance of Fresco on your infrastructure.
    2. Upload protocols: Import .netcanvas files created in Architect.
    3. Add participants: Enroll participants individually, in bulk, or via anonymous recruitment.
    4. Conduct interviews: Share unique or anonymous URLs with participants for self-completion on their own devices.
    5. Monitor progress: Track study status via the dashboard.
    6. Export data: Download interview results once collection is complete.

  6. Overview of the Network Canvas research workflow

    Network Canvas provides an end-to-end workflow for surveying networks, consisting of three primary phases:

    1. Design Protocols: Define the interview questions and structure. This is managed via a protocol file.
    2. Collect Data: Execute the protocol through interviews. This can be done via researcher-controlled devices or remote participant completion.
    3. Analyze Data: Export collected network data into standard formats like CSV and GraphML for use in analysis packages such as R or Python.

  7. Overview of the Network Canvas suite

    Network Canvas is a free, open-source (GPLv3) suite of three applications designed to help researchers collect social network data, improve reproducibility, and simplify data export for statistical analysis. The suite consists of:

    1. Architect: Used for building interview protocols.
    2. Interviewer: Used in the field to collect data. It exists as a modern web-based app (recommended for new studies, supports schema 8) and an 'Interviewer Classic' downloadable version.
    3. Fresco: Used for deploying protocols directly in a web browser.

  8. Overview of the Network Canvas research workflow

    Network Canvas provides an end-to-end workflow for surveying networks, consisting of three primary phases:

    1. Design Protocols: Define the interview questions and structure. This is done by creating a protocol file using the Architect tool.
    2. Collect Data: Execute the protocol via interviews. This can be done using the Interviewer app (researcher-led) or Fresco (participant-led remote web deployment).
    3. Analyze Data: Export collected network data into standard formats like CSV and GraphML for use in analysis packages such as R or Python.

  9. Overview of Fresco for Network Canvas

    Fresco is a web-based platform that allows researchers to conduct Network Canvas interviews in a browser. It is 100% compatible with existing Network Canvas protocol files. Researchers upload a protocol to a private instance of Fresco and share a URL with participants, who can then complete the interview on their own device (desktop or laptop). All protocol, participant, and data management is handled via a secure, researcher-facing web dashboard.

  10. Overview of Name Generator Interfaces

    Name Generators are fundamental components in Network Canvas used to create nodes (alters) to describe entities in a study's network. They are available in Architect Classic, Architect, Interviewer Classic, Interviewer, and Fresco. These interfaces allow participants to nominate alters based on specific prompts, with the resulting nodes being stored according to the study's schema (v1+).

  11. Overview of the Fresco Interview Data API

    The Fresco Interview Data API provides read-only, programmatic access to interview and protocol data. It is designed for building automated export and analysis pipelines. Key characteristics include:

    • Read-only: Data can be listed and retrieved, but not modified.
    • JSON Responses: All responses are returned as JSON with a 200 OK status.
    • Timestamps: Uses ISO 8601 (UTC).
    • Versioning: All endpoints are located under the /api/v1/ path.
    • Instance-specific: Each deployment has its own base URL (e.g., https://your-fresco-instance.com).