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.

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


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.
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.
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.
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.
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.
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.
We are proud to say Network Canvas is being actively used in a number of federally funded grants in the United States, across a diverse set of research contexts, institutions, and funding bodies.

PIs: Pollack, Pho, Schneider (3UG1DA050066-02S1)
This project will implement and evaluate a COVID-19 testing approach that combines an evidence-based Social Network Testing Strategy (SNS) with community developed COVID-19 public health messages (SNS+).

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.

PIs: Krendl, Perry (R01AG070931)
This project utilizes Network Canvas to examine the relationship between older adults’ social networks and their social cognitive function, as well as the possibility that having better social cognitive function may be protective for general cognitive function.

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.
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.
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
Substance Use: Research and Treatment
Patterson MS, Heinrich KM, Maddock JE, Dieckmann N
University of California, Irvine Doctoral Dissertation
Mendoza GA
Archives of Sexual Behavior
Despres L, Rodriguez E, Johnson AL, Bravo A, Vilchez L, Doblecki-Lewis S, Fallon S, Kanamori M
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
University of Geneva Master's Thesis
Kalem Y
Journal of Behavioral Medicine
Wagner GJ, Bogart LM, Matovu JKB, Gwokyalya V, Green HD Jr, Ninsiima S, Klein DJ, Okoboi S
British Journal of Sociology of Education
Wyman I

Kate Banner
Northwestern University

Michelle Birkett
Northwestern University

Caden Buckhalt
Northwestern University

Noshir Contractor
Northwestern University

Bernie Hogan
University of Oxford

Patrick Janulis
Northwestern University

Joshua Melville
Northwestern University

Gregory Phillips II
Northwestern University
jimi adams, Rich D'Aquilla, Mike Bass, Martin Everett, Abel Kho, Carl Latkin, Brian Mustanski
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.


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