Simplifying complex network data collection.

Network Canvas provides free and open-source software for surveying networks, designed around the needs of both researchers and their participants.

Latest News:

Language localization in Network Canvas [Read more]

Network Canvas workshop at EUSN 2026 in Norrköping, Sweden [Read more]

The next generation of Network Canvas apps [Read more]

Joshua Melville awarded two years of NIH funding to maintain Network Canvas [Read more]

Network Canvas workshop at Sunbelt 2026 in Daytona Beach, Florida [Read more]

Get Started

or keep scrolling to learn more

A selection of tools to facilitate your research

We provide a complete end-to-end workflow for networks research, with apps for survey design and for interviewing. Using these tools, researchers can easily design, capture, and export network data.

Architect

A browser-based tool for visually designing Network Canvas interviews. Architect allows subject experts to focus on the design and implementation of their study, without needing to learn complex new technology.

Architect protocol editor showing an interview design
Interviewer home screen showing available Network Canvas protocols

Interviewer

A browser-based app for administering Network Canvas interviews in the field. Interviewer provides minimalist, participant-centric interfaces for all the data collection tasks associated with personal network interviewing.

Learn more

Our goal is to build a suite of tools for the research community that is high quality, free, safe for research, and built to last. Watch our project video to learn more about why we created Network Canvas, and visit our YouTube channel for more videos.

Design Principles

Underpinning all Network Canvas software is a set of five design principles. These principles are derived from our observations and experiences regarding the problems facing researchers wishing to design and conduct personal networks research.

Ontological flexibility

The software is designed with fundamental ontological flexibility. Simply put, this means that we do not presuppose anything about the nature of your interview.

Researchers are free to define the nodes and edges of their interviews, their attributes, the sequence of data collection tasks, as well as the way these tasks are explained to the participant.

In-person and interviewer-assisted

We believe that the presence of a trained interviewer who can facilitate the data collection task enables the collection of higher quality data.

The Network Canvas tools are therefore designed on the assumption that interviews occur in the presence of an interviewer, on an interviewer-controlled machine, and with the interviewer having been specifically trained in guiding the interview process.

An emphasis on design

Our software has been designed from the ground up to be as visually engaging and low burden as possible for participants.

We take design extremely seriously, and have drawn on HCI literature, as well as papers from the network analysis community, to create an interview experience that is simple for participants to understand, with clear, consistent, and tactile interactions guiding the data collection.

End-to-end workflow

Simplifying the process of collecting complex structural data requires not just an interview tool, but also a tool for designing these interviews. Together, these tools provide an end-to-end workflow which lowers the costs (both material and technical) of collecting network data.

Importantly, our tools do not require a high degree of technical knowledge to operate. Rather, they allow researchers to focus on using their subject expertise to design an effective interview experience.

Open-source community driven development

Key to sustaining this effort is input and collaboration with the community, both inside and outside of academia. For this reason, the network canvas tools are free to use and completely open-source (licensed under the GPL version 3).

We have implemented a community driven development program, and are eager to encourage feature development or other contributions from any interested third parties.

  1. University of Kentucky

    Justice Community Opioid Innovation Network (JCOIN)

    PI: Staton (UG1DA050069), PI: Wang (UG1DA050072), MPI: Pollack, Pho, Schneider (UG1DA050066)

    JCOIN utilizes Network Canvas for network data capture to examine how participants’ social support networks influence treatment outcomes for justice-involved participants across three JCOIN hubs.

  2. University of Kentucky

    Geographic variation in Addiction Treatment Experiences (GATE)

    PI: Oser (R01DA048876)

    The GATE study uses Network Canvas to identify the social network influences on the use of medication treatment for opioid use disorder (both in prison and after release) and adverse outcomes (i.e., relapse, overdose, recidivism) among both rural and urban persons with opioid use disorder over time.

Recent Publications Using Network Canvas

Network Canvas has facilitated research across a variety of disciplines, among an emerging network of authors. The 8 most recent publications are shown here. This list is automatically updated when we find new publications that use the software.

  1. Using Cognitive Interviewing to Assess the Feasibility and Acceptability of the Network Canvas Platform for Social Network Data Collection Among Adolescent and Young Adult Survivors of Cancer: Pilot Descriptive Study

    JMIR Formative Research

    Rao P, Rowe-Nicholls I, Lang G, Chen T, Verdery A, Koehly L, VanDyke E, Costigan H, Sekhar D, Bingen K, Dandekar S, Toepke C, King T, Birkett M, Van Scoy L

  2. Which Relationships Last? Predictors of Supportive Tie Retention and Network Structural Change in a Sober-Active Recovery Community

    Substance Use: Research and Treatment

    Patterson MS, Heinrich KM, Maddock JE, Dieckmann N

  3. Language Brokering and Bilingual Cognition: The Influence of Context on Bilingual Cognitive Processes

    University of California, Irvine Doctoral Dissertation

    Mendoza GA

  4. Sexual Partner Typologies Among Latino Men Living in Miami, Florida: A Multilevel Latent Class Analysis

    Archives of Sexual Behavior

    Despres L, Rodriguez E, Johnson AL, Bravo A, Vilchez L, Doblecki-Lewis S, Fallon S, Kanamori M

  5. Optimizing peer-led health interventions: A social network analysis approach for identifying influential fishermen in Malawi

    PLOS Global Public Health

    Mukoka M, Price A, Nliwasa M, Mhango O, Mwapasa M, Kumwenda MK, Twabi HH, Semphere R, Msosa TC, Msefula C, Choko AT, Harling G, Fielding K

  6. Exploring the relationship of remote work to social support and conflict: a study in Switzerland, Spain, Germany, and the Netherlands

    University of Geneva Master's Thesis

    Kalem Y

  7. Mediators of the effects of an HIV prevention advocacy training intervention on prevention advocacy among persons living with HIV in Uganda

    Journal of Behavioral Medicine

    Wagner GJ, Bogart LM, Matovu JKB, Gwokyalya V, Green HD Jr, Ninsiima S, Klein DJ, Okoboi S

  8. Collegiality among headteachers in the formation and sustainability of inter-organisational school networks

    British Journal of Sociology of Education

    Wyman I

Core Team

Our project team comprises individuals across a variety of disciplines and specializations.
Kate Banner

Kate Banner

Northwestern University

Michelle Birkett

Michelle Birkett

Northwestern University

Caden Buckhalt

Caden Buckhalt

Northwestern University

Noshir Contractor

Noshir Contractor

Northwestern University

Bernie Hogan

Bernie Hogan

University of Oxford

Patrick Janulis

Patrick Janulis

Northwestern University

Joshua Melville

Joshua Melville

Northwestern University

Gregory Phillips II

Gregory Phillips II

Northwestern University

Scientific Advisors

jimi adams, Rich D'Aquilla, Mike Bass, Martin Everett, Abel Kho, Carl Latkin, Brian Mustanski

Institutions

The software is being developed by a team of researchers and developers based at Northwestern University and the University of Oxford, as well as several external contracted developers. We are grateful for the prior and ongoing funding from the National Institutes of Health that make this work possible.

The intellectual property and copyright associated with the software is controlled by a registered not-for-profit, the Complex Data Collective, comprising the core project staff.

University of Oxford
Northwestern University
Complex Data Collective

What next?

Want to learn more?

We have created extensive documentation, covering all aspects of creating, deploying, and managing a study using Network Canvas.

Visit Documentation Site

Looking for help?

We have also recently launched a community website, where you can ask questions, report bugs, share your work, and get help from other researchers.

Visit Community Website

Keep in touch

If you would like to stay in touch with the project, and find out about events and releases as soon as they happen, we encourage you to join our mailing list, and to follow us on Twitter. We are considerate email partners, and will only ever use this list for important announcements.

Want to collaborate?

If you are interested in a formal academic or consultancy-based collaboration, please see our documentation article on the subject. Unfortunately, we're unable to offer unpaid consultancies due to limited bandwidth of a small team.

Explore Collaboration Options