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Simplifying complex network data collection.

Simplifying complex network data collection.

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.

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or keep scrolling to learn more

Download Now

or keep scrolling to learn more

Download Now

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 an app for survey design and for interviewing. Using these tools, researchers can easily design, capture, and export network data.

Architect

A desktop (macOS, Windows, Linux) 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.

Download Architect

Interviewer

A desktop/tablet 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.

Download Interviewer

A selection of tools to facilitate your research

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

Architect

A desktop (macOS, Windows, Linux) 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.

Download Architect

Interviewer

A desktop/tablet 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.

Download Interviewer

A selection of tools to facilitate your research

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

Architect

A desktop (macOS, Windows, Linux) 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.

Download Architect

Interviewer

A desktop/tablet 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.

Download Interviewer

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.

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.

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.

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.


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.

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.

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.

Projects

We have a number of ongoing projects which aim to either evaluate and enhance the software, provide new methods of deployment, or to create entirely new ways of collecting network data.

Partner Services

A project to map the needs of Partner Services, and evaluate the utility of Network Canvas as a public health tool to aid disease investigation and increase data quality.

Learn More

Fresco

Bringing Network Canvas interviews to the web! Fresco is a pilot project that will allow researchers to conduct Network Canvas interviews in a web browser.

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Studio


Taking Network Canvas to the cloud for the first time, Studio will enable remote interview deployment and collaborative protocol building in a browser, while also providing a data analysis API.

Taking Network Canvas to the cloud for the first time, Studio will enable remote interview deployment and collaborative protocol building in a browser, while also providing a data analysis API.

Learn More

Research Using Network Canvas

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

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

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

Understanding how social connectedness protects older adults' cognitive health: the role of social cognition

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.

Understanding how social connectedness protects older adults' cognitive health: the role of social cognition

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.

Understanding how social connectedness protects older adults' cognitive health: the role of social cognition

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.

Justice Community Opioid Innovation Network (JCOIN)

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

This JCOIN project 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: University of Kentucky, University of Chicago, and Yale University.

Justice Community Opioid Innovation Network (JCOIN)

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

This JCOIN project 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: University of Kentucky, University of Chicago, and Yale University.

Justice Community Opioid Innovation Network (JCOIN)

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

This JCOIN project 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: University of Kentucky, University of Chicago, and Yale University.

Community network-driven COVID-19 testing of vulnerable populations in the Central US

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+).

Community network-driven COVID-19 testing of vulnerable populations in the Central US

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+).

Community network-driven COVID-19 testing of vulnerable populations in the Central US

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+).

Team

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

Kate Banner

Northwestern University

Kate Banner

Northwestern University

Kate Banner

Northwestern University

Michelle Birkett

Northwestern University

Michelle Birkett

Northwestern University

Michelle Birkett

Northwestern University

Caden Buckhalt

Northwestern University

Caden Buckhalt

Northwestern University

Caden Buckhalt

Northwestern University

Noshir Contractor

Northwestern University

Noshir Contractor

Northwestern University

Noshir Contractor

Northwestern University

Bernie Hogan

University of Oxford

Bernie Hogan

University of Oxford

Bernie Hogan

University of Oxford

Patrick Janulis

Northwestern University

Patrick Janulis

Northwestern University

Patrick Janulis

Northwestern University

Joshua Melville

Northwestern University

Joshua Melville

Northwestern University

Joshua Melville

Northwestern University

Gregory Phillips II

Northwestern University

Gregory Phillips II

Northwestern University

Gregory Phillips II

Northwestern University

Previous Developers

Jamie Chung, Bryan Fox, Rebecca Madsen, Steve Mckellar, Matt Meshulam

Scientific Advisors

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

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

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

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

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

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.

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.

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

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

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

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 to be funded through a grant from the National Institutes of Health.


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.