Diagrams of Power

Wednesday, July 11, 2018 - 7:00pm to Sunday, September 30, 2018 - 7:00am

Diagrams of Power
July 11 to September 29, 2018

Group exhibition featuring work by Joshua Akers, The Anti-Eviction Mapping Project, Josh Begley, Joseph Beuys, Vincent Brown, Bureau d'études, DataMade, Department of Unusual Certainties, W. E. B. Du Bois, Estudio Teddy Cruz + Fonna Forman, Forensic Architecture, Iconoclasistas, Julie Mehretu, Lize Mogel, Margaret Pearce, Philippe Rekacewicz, Visualizing Impact, and more.

Curated by Patricio Dávila

Diagrams of Power showcases art and design works using data, diagrams, maps and visualizations as ways of challenging dominant narratives and supporting the resilience of marginalized communities.


Diagrams of Power is produced with the support of OCAD University's Office of the Faculty of Design, Public Visualization Lab and Nexus Investments.

Diagram of Power's public workshops and research engagement events is supported by the Social Sciences and Humanities Research Council of Canada.

Onsite Gallery gratefully acknowledges that the new gallery construction project is funded in part by the Government of Canada's Canada Cultural Spaces Fund at Canadian Heritage, the City of Toronto through a Section 37 agreement and Aspen Ridge Homes; with gallery furniture by Nienkämper. Onsite Gallery logo by Dean Martin Design.


Image: Forensic Architecture, The Ayotzinapa Case: A Cartography of Violence (still), 2017. Video, 18 min. 24 sec.

Venue & Address: 
Onsite Gallery (199 Richmond St. W., Ground Floor)
416-977-6000 x456
 Image: Forensic Architecture, The Ayotzinapa Case: A Cartography of Violence (still), 2017. Video, 18 min. 24 sec.

Dr. Sara Diamond to speak at TUX

Tuesday, January 16, 2018 - 12:30pm to 2:00pm

In her lecture, Data Visualization – Fundamental 21st Century Knowledge, Dr. Diamond will discuss the significance of visualization design and data analytics in the age of Big Data.

A video of the talk will be available on the TUX YouTube channel

The Toronto User Experience group is an organization dedicated to bringing together and building of a community of HCI researchers in and around Toronto. It presently has members from as far east as Queen’s University in Kingston, and as far west as Waterloo.

Tux comes together biweekly, usually at the MaRS Discovery District or at the University of Toronto for talks. Each talk is preceded by a reception made possible by the group’s generous sponsors. Talks at Tux are in one of two categories: Tux member presentations, and Sanders Series Invited Lectures.


Venue & Address: 
MaRS Discovery District 101 College St, Toronto

Visualizing Emergence

A project currently in development, Visualizing Emergence seeks to explore and visualize phenomena of emergence in data representing technologically mediated human communication and exchange within a techno-social complex adaptive system (CAS).

Using textual analysis and other data as substrate, research will focus on data from CIV-DDD partners, IBM Cognos and public sources, possibly including Twitter and other accessible APIs. In time we expect to aggregate data from additional sources. Leveraging senior researcher and student contributions from OCAD and York Universities, the project will explore and exploit a synthesis of scientific, artistic and aesthetic techniques, with software from partners including IBM / Cognos.

Project challenges include:

  • Finding the right data set; evaluating data quality
  • Representing, managing multi-variant data
  • Models, metaphors; legibility, navigation

Visualizing Emergence will examine model-based scientific visualization of complex data sets as well as emergent systems, data mining techniques and visualization. We will test, review and select the most appropriate software approach for developing the data models and generating dynamic results. The work will also deliver findings tied to the following CIV-DDD project aims: appropriateness of 2D or 3D visualizations, visualization aesthetics, and use of specific vs. generic tools.


For more information, please visit http://slab.ocadu.ca/project/visualizing-emergence .

Visualizing Emergence is supported by NCE-GRAND. This project is funded in part by the Centre for Information Visualization and Data Driven Design established by the Ontario Research Fund (ORF).


Photograph of sLab members Greg Van Alstyne and Trevor Haldenby working at a table
NCE logo
Monday, October 23, 2017 - 11:45am
Lab Member: 
Greg Van alstyne

Synthesizing and Visualizing Climate Vulnerability Assessments Data for the Region of Peel

The Peel Climate Alliance needed to synthesize multiple data-rich climate change vulnerability assessments and present the result to the region’s council for resources allocation and prioritization. The members of the Alliance had several competing priorities and too many messages, resulting in inefficient communication with decision makers.

By taking Alliance members through the Megamap process we were able to agree on prioritization criteria, identify the target decision makers and their profiles, distil messaging, and visualize relevant data in a large Megamap to be presented to various decision makers.


  • Establish criteria for prioritization among the diverse members of the Alliance
  • Streamline the communications process between expert departments and decision makers
  • Visualize pertinent data for decision support



To achieve project objectives we began by taking participants through a foresight workshop in order to communicate possible features and use such foresight as basis for negotiating common prioritization criteria.

Working with a joint team of the Alliance and rLab, we identified the critical target audiences and their characteristics. We then put the key messages proposed by each member of the Alliance through an evaluation process and facilitated a reduction in the number of messages. This process resulted in a few strategically important messages which satisfied all members.

We then visualized pertinent data in a large synthesizing Megamap, including the profiles of the target audiences, the agreed-upon key messages, and the rich data collected by the member organizations.


This Project was implemented as usual with a joint team including members from rLab and all Alliance members.

Image of the Peel Region mega map created by the rLab and Alliance members
Monday, September 25, 2017 - 10:45am
Lab Member: 
Nabil Harfoush

Patricio Dávila

Patricio Dávila is a designer, artist and educator. He is currently Associate Professor in Design and Associate Dean at OCAD University. He is also member of the OCADU Mobile Media Lab and Visual Analytics Lab. Patricio is director of Public Visualization Lab. His doctoral research focused on developing a theoretical framework for examining data visualization as assemblages of subjectivation and power.

SharcNet & OCAD's VizDay 2008

Wednesday, November 5, 2008 - 1:30pm to 8:00pm

Data visualisation allows invisible data to be made visible through the creation of meaningful images. At VizDay 2008, experts in data, information and scientific visualization will share examples of and insights into their work in order to introduce the benefits of visualization to academia and industry.

Speakers will provide case studies in the physical sciences, biological and science and the social sciences. The contributions of art, design and cognitive science to visualisation will be discussed.

VizDay provides an opportunity for participants to discuss the tools, techniques and technologies of data, information and scientific visualization.

VizDay 2008 is produced through a collaboration between the Ontario College of Art & Design and the SharcNET Collaboration and Visualization Committee. Supporters include ORION/ORANO; CANARIE, IBM.

For a complete list of speakers and to register, visit the website below.

Venue & Address: 
Room 284, Level 2 100 McCaul St., Toronto, Ontario
Free (please register)


Three related factors appear to be relevant in allowing an understanding of online behaviors: attention (the time that individuals and groups expend); influence (the relationships between ideas, products and behaviors) and affect (the emotions and sentiments that are expressed in relation to ideas and products). The extraction of accurate data, then the analysis of these factors in online behavior, and the charting and representation of relationships between these factors poses a significant challenge. For one thing, these factors need to be related to specific content. Data analytics and visualization tools are needed to represent each factor and to chart these relationships. There is very little research to date that works across these fields. This large-scale project seeks to shed light on each element of online social media practice and to then draw relationships between these elements.

Research Description:

People perform topic-based content exploration on large-scale social media systems. Such sites continue to expand rapidly. For example, Twitter continues to grow around the globe at a record pace. Just a year ago, they delivered 65 million Tweets a day. Today, they generate over 200 million Tweets per day. One year ago, there were approximately 150,000 registered Twitter apps. Now, there are more than one million. Facebook has more than 800 million active users of which more than 50% log on to Facebook in any given day where the average user has 130 friends. Seventy-seven percent of active Internet users read blogs. At the same time specialized media companies, brand development agencies and brands have developed social media applications that allow their users to communicate and at the same time, allow them to track the resulting data.

Editorial and business leaders see value in understanding the emotional tone, influences, attention span and diversity of their various sections and offerings, contributors and readers. Attention and influence, for example, currently directly impact advertising dollar interest in an article. In going digital, media publications have added commentary in the form of opinion blogs by its core of writers as well as ample opportunity for readers to vote and comment. Currently a majority of online media allow readers to express their thoughts and opinions on content through social media commentary. This information can impact advertising sales, decisions on style and relatedness of writers and design and even the kind of influence that different sections, authors or columns may have. Editorial leadership is eager to better manage the means for reader commentary. At the same time it is valuable to understand any underlying patterns that suggest reasons for specific emotional tone. Discovering sentiments, patterns and relationships embedded in articles as well as comments is important for tracking the newspaper’s role in shaping public opinion on contemporary issues and the ways that readers interact with these opinions. It can help media analysts better understand the impact of sentiments on news events. What is more, new tools, on multiple platforms can be developed for media users that allow them to shape their emotional content and respond to others, and chart the influence of their ideas, media patterns and behaviors.

For almost a decade contemporary brands have relied on a growing direct dialogue with their consumer base through social media, and gamification (direct play as a means of polling). These relationships engender loyalty and provide a rich source of data to understand and predict consumer behaviors. Consumer opinion that is expressed in response to new offerings, system breakdowns, or customer service is of critical importance in a world where viral trends erupt quickly with significant impact. Events and opinion outside of an immediate enterprise can have a direct impact in a social media era. Marketing and advertising companies analyze consumer attitudes and relationships to brands for trend analysis and product development. The technology of “predictive analytics” is being fine-tuned by digital media and ICT companies with new offerings such as inferSYTEMS. While the technology of monitoring is becoming more sophisticated, the underlying assumptions of analysis have not changed dramatically for many years, continuing to rely on twentieth century psychology structures. Brands and media analysis companies seek to bring together social media data with data that tracks consumer behaviors – in specific their attention to media, to products and services and their consumption patterns.

In some areas, e.g., healthcare, free-form texts are the most common form of valuable data. These data range from doctor’s notes, descriptions of patient histories, to healthcare-related messages posted by patients on social media such as blogs, bulletin boards, and discussion forums. Such narrative text data contain the most valuable information for physicians to use in their practice and for public and government agencies to make their healthcare-related decisions. Recently, the New York Times reported on a study by MIT researchers, which showed that companies included in their study that adopted data-driven decision-making achieved 5-6% higher productivity than those that did not.

Since data are continuously generated every day in large volumes, the sheer amount of data is too overwhelming for humans to read and analyze manually. Automatic text analysis tools are in great need to discover the hidden information trapped inside the free-form texts. For example, a tool that identifies and analyzes the healthcare-related posts in social media can detect public opinions, activities and preferences in healthcare-related issues.

Understanding consumer opinion of reliability and service quality across an industry like banking can have an impact on a specific company’s quality of service as well as enabling an entire industry to improve. Natural language analysis, data mining and information retrieval are key techniques that can be used to build such text analysis tools.

It is difficult to discern meaning by extracting information piece by piece. We hypothesize that taking a data-driven design approach to visualizing content would make the aggregate meanings more apparent. The advantage of working with this partially processed data is that issues of confidentiality do not arise since any confidential or client information has been abstracted from the media. A second advantage is that research can also focus on visualization and design issues rather than duplicate commercially available linguistic parsing capabilities.

Colourful lines from design piece
Colourful lines from design piece
Colourful lines from design piece
Monday, September 14, 2015 - 3:45pm
Lab Member: 
Dr. Sara Diamond


Stacked-stacked bar graph is the working title of a visualization that builds on the strengths of a stacked bar graph. Where a stacked bar graph allows for a visual comparison of the parts to the whole, our proposed visualization further divides the parts to allow for additional points of comparison.

For more information, see:
Szigeti, S., Patrasc, J., Schnitman, D., and Diamond, S. 2014. “The Stacked-Stacked Bar Graph: A New Twist on an Old Visualization.” IEEE InfoVis Proceedings.

Stacked-stacked bar graph is the working title of a visualization that builds on the strengths of a stacked bar graph.
Stacked-stacked bar graph is the working title of a visualization that builds on the strengths of a stacked bar graph.
Monday, September 14, 2015 - 3:45pm
Lab Member: 
Dr. Sara Diamond
Dr. Steve Szigeti
Joana Patrasc
David Schnitman


MAKING DATA FELT is a research-creation project of experimental data visualization/data materialization, designed to explore the affective dimensions of statistical information. The project appropriates low-cost DIY ‘maker tools’ (such as laser engravers, 3D printers, and thermal printers) for the creation of open-source data visualization solutions that allow research-practitioners to ‘make data felt’ by highlighting the social, political, and ethical stakes that are often overlooked in statistical information.

The project asks how we can translate impenetrable statistical information back into meaningful affective experiences. Dr. Zeilinger's visualization experiments will yield aesthetic artifacts built from statistical data that is otherwise presumed to be disembodied, alienating, and impersonal. MAKING DATA FELT foregrounds the critical, cultural, and social stakes encoded in such data, and plays with the reversal of the obfuscatory, dehumanizing effects of numerically encoded statistics.

The first iteration of the project mines publicly available data regarding the time/place/duration/intensity of the 2014 aerial bombardments of the Gaza Strip, and uses a custom-made laser engraver to etch the data points into paper maps of the region, partially destroying the maps in the process. The installation thus ‘performs’ a tangible and emotionally charged reenactment of the destruction encoded in the statistical information, and lends a body, shape, duration, and smell to the otherwise faceless data.

Making Data Felt Image 1
Making Data Felt Image 1
Thursday, February 5, 2015 - 9:15pm
Lab Member: 
Dr. Martin Zeilinger

Fetal Alcohol Visualizing

Working with large sets of intricate and comprehensive data, this research takes a highly interdisciplinary approach to dissecting the discourses that surround fetal alcohol spectrum disorders (FASD). Novel correlations across data collected from stakeholder groups, derived using advanced visual analytics tools, help to better inform new strategies for communicating FASD. The interdisciplinary approach to this project grants the researchers with the ability to employ creative methods of study; the design of striking infographics and innovative simulation technologies will serve the production of provocative public performance in an effort to refresh the dialogue on FASD.


Red and green DNA testing visualization
Friday, April 12, 2013 - 3:30pm
Lab Member: 
Paula Gardner
Patricio Davila
Lawrence Kwok
Tim Bettridge
Maggie Chan
Marjan Verstappen
Harjot Bal
Shuting Chang