Toward a Montreal Sustainability Dashboard

The dashboard will be a platform for integrating sustainability knowledge at the regional scale to improve research, policy making and public engagement.

The McGill Sustainability Systems’ Adapting Urban Environments for the Future team is currently working on the development of a Montreal-based interactive sustainability tool. The Montreal Sustainability Dashboard will be a platform for integrating sustainability knowledge at the regional scale to improve research, policy making and public engagement, building on the group’s integrative program of research on urban sustainability as a means to mobilize more inclusive and sustainable cities. In this context, sustainability includes various environmental, political, and socio-economic factors including transit and mobility, social equity and justice, demographic distribution, and sustainable development indicators.

In this blog post, we wish to demystify the following questions: What are Sustainability Dashboards? Are there any gaps in the existing literature, tools, or approaches? How can the Montreal Sustainability Dashboard bridge the gap to ensure sustainability thinking meets local needs and practice?

What are Sustainability Dashboards?

There has been significant research conducted on data-driven dashboards, their applications and possible impacts. Our research is centred on urban or city dashboards as well as specifically sustainability dashboards.

While dashboards are useful and powerful for making sense of certain aspects of city life and predicting future scenarios, they are not neutral technical tools. They are tools that are framed within our socio-political contexts. As such, using real-time data coupled with dynamic data visualization as communication tools is effective in dashboards as they can have a positive impact on people’s energy consumption behaviour. The Living Labs model and other bottom-up approaches are useful and effective in smart city contexts as they make room for multiple stakeholders and voices to be considered. Qualitative scenario modeling can serve as a useful way to integrate qualitative data as well as change the users’ thinking.


Further reading

Kitchin, Rob, Tracey P. Lauriault, and Matthew W. Wilson, eds. Understanding spatial media. Sage, 2017.

Kourtit, Karima, and Peter Nijkamp. "Big data dashboards as smart decision support tools for i-cities–An experiment on stockholm." Land use policy 71 (2018): 24-35.

Whitton, John, Ioan Mihangel Parry, Mito Akiyoshi, and William Lawless. "Conceptualizing a social sustainability framework for energy infrastructure decisions." Energy Research & Social Science 8 (2015): 127-138.


Summary of Existing Sustainability Dashboard Initiatives

Several sustainability dashboards or online data visualization tools already exist in North America as well as other parts of the world. These initiatives can generally be grouped into six categories.

1. Large-scale national and international sustainability-driven organizations with data components include large-scale names, such as 100 Resilient Cities and the Canada Smart Cities Challenge. They encompass overarching themes of sustainability with a focus on cities. While the initiatives themselves are not necessarily data-driven, they often have data-based components or projects using sustainability and resiliency data. Example: SDGs Global Dashboard

2. Data-based government-led Initiatives within national and regional agencies stem from government agencies and focus on the technical aspects of data collection and representation in sustainability data. Many specifically center on the development of a sustainability dashboard to visualize data. These are sometimes in collaboration with outside partner agencies or corporations. Example: New Zealand Sustainability Dashboard Project

3. City-based sustainability initiatives from municipal governments and other organizations often include projects comprising the visualization of various sustainability indicators through so-called interactive web-based mapping platforms or other dashboard platforms. While the majority of these initiatives allow for interaction with the data through selection of layers, none of them provide real-time data, nor do they allow the user to customize the experience. Example: Surrey Sustainability Dashboard

4. Campus-Based and Academic Projects and Studies often use the campus as a living lab for data collection and analysis or as the basis for research projects and studies related to sustainability indicators. These initiatives often examine energy consumption, water usage, and transit modes for their respective populations, sometimes using real-time data collection and visualization to change behaviours. Example: CityChrone (Politecnico di Torino)

5. Community-Based Local Mapping/Visualization Organizations and Initiatives tackle the visualization of data through online mapping platforms. The ones noted in this study focus on the socio-economic components of sustainability. They generally involve the input of census data for the identified indicators with the ability to view relevant statistical information alongside the map. Example: Policy Map

6. Independent or private organizations working on sustainability initiatives exist that fall outside of the aforementioned types, including foundations and private enterprises. Some of these do not have explicit data visualization projects, or the data component of their sustainability work may not be clear. Others, such as PREPdata, specialize in visualizing data for sustainability and resilience purposes.

The majority of these initiatives visualize pre-existing data and display statistical analyses based on those data. These two pieces comprise what many dashboards refer to as interactive. A few initiatives have options to create new scenarios or input new data, but these are the exception. A few also incorporate real-time data, usually limited to energy data for buildings.



Are there any gaps in the existing literature, tools, or approaches?

The literature points to the success of interactive and dynamic data visualization methods in encouraging the use of data-driven dashboards, as well as their impact on the users. The literature further emphasizes the need for more holistic and publically-oriented approaches to dashboards to reflect the community’s needs. What we see in existing initiatives, however, is a gap in sustainability dashboards going beyond the visualization of pre-existing data at static scales. The current models employ primarily static data without the incorporation of real-time or dynamic data or local data collection methods. The data used are communicated sometimes without full relevance to the local community. Public engagement methods in the development of dashboards is rare, and other efforts to increase transparency remain unclear. This leaves room for a more future-oriented, scalable and interactive model based on and reflective of community members and the issues they face.


How can the Montreal Sustainability Dashboard bridge the gap to ensure sustainability thinking meets local needs and practice?

One of the Montreal Sustainability Dashboard’s primary objectives it to create an interdisciplinary platform, both within the data and information used and in the process of developing and sustaining the dashboard. Combining different data types will allow greater flexibility in the level of interactivity of the dashboard, including the incorporation of dynamic data and visualization. Employing a participative, community-driven approach throughout the development of the dashboard will further allow the dashboard to incorporate quantitative and qualitative data directly relevant to and reflective of the local community in the present and future. Throughout the process, the dashboard additionally aims to remain as transparent as possible, encouraging interaction between individuals all levels of society. This will also ensure a scalable model that can be shared with other organizations, municipalities, and governments.


The methodology employed in this project is geared specifically towards ensuring a practical, user-friendly, and relevant tool that is accessible at all scales in Montreal. The methodology therefore addresses both technical aspects necessary to achieve the end product envisioned, as well as operating under the assumption that the standard methodology for interactive dashboard projects does not result in an inclusive, equitable output for the users. With the dashboard, we envision people interacting with different aspects of the city and the dashboard which will in turn inform them of their behaviour and actions needed to have a sustainable city.

With this knowledge, the Montreal Sustainability dashboard aims to include the following points:

  • The dashboard should include many types of data from different sources (City of Montreal, Greenness and Biodiversity Data, HydroQuebec, Public/Private Transportation such as STM, RTM, social media etc.).
  • Artificial Intelligence (AI) would play a pivotal role in harnessing data, with emphasis on drawing upon unfiltered raw data.
  • It is important that the dashboard reveal privacy marked data after obtaining the consent of users whose personal data are gathered.
  • The architecture of the dashboard should be inclusive so as to connect other relevant APIs such as Open Data Portal of the City of Montreal. It should also consider the benefits and drawbacks of different available dashboard creations tools such as Rstudio Shiny Dashboard, Plotly, ArcGIS Operations Dashboard, Tableau.
  • Different levels of accessibility to data should be defined according to right of stakeholders.
  • There should be an agreed and publicly-transparent governance structure and terms of use and access to the dashboard.
  • The dashboard should be tailored to the needs of the geographic community and should have the ability to generate predictions about the future outcomes of evolving social norms.
  • The dashboard should remain an equitable process and tool from development to completion, taking into consideration the needs of marginalized residents and communities.

Lastly, the dashboard will be designed in a way that allows users to see the impact of their actions and choices on people in other parts of the world. Flows from resource external stocks to Montreal and from Montreal to other parts of the world ideally will be traceable, and the dashboard itself will be scalable from the Montreal context to other urban areas, communities, and individuals facing similar sustainability questions and goals.



Robin Basalaev-Binder acts as qualitative research associate taking a leading role in developing and implementing several aspects of the Montreal Sustainability Dashboard, including: Identifying qualitative urban sustainability research and working with the postdoctoral researcher to integrate this research into the design of the Sustainability Dashboard; Working with community stakeholders across the Montreal region to ensure that the MLL is responsive to local needs and interests; Conducting research on worldwide initiatives comparable to the dashboard, and liaising with international researchers and policymakers to identify opportunities for collaboration and scaling; Ensuring an equitable and inclusive process during the development and output of the dashboard. This includes finding new ways of integrating qualitative data and human experience into the development and data-collection and visualization of the project. Particular emphasis is placed on ensuring the inclusion of visible minorities, aboriginal and indigenous communities, and other marginalized populations in the development, processing, output, and continuation of the dashboard.

Hossein Chavoshi is the project lead of Montreal Sustainability Dashboard and a postdoctoral research fellow at the McGill University Faculty of Science. He is also a special editor with the McGill Journal of Sustainable Development Law. He holds a PhD degree from Ghent University in GIScience. Hossein has previously worked (intern) as a data analyst at the City of Montreal. He has experience in projects intersecting urban problems where the knowledge and understanding of patterns/trends in a dynamic and complex context are inevitable.

Main image: Jiaqian AirplaneFan

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