Developing a Data Sharing Policy for a Partnership Project: A Case Study of the Évaluation en commun Project Supported by UQAM's Research Chair on Ecological Transition

As part of Montréal in Common, an innovation community led by the City of Montréal, the Research Chair on Ecological Transition helped partners in the food sector to assess and evaluate their projects. The participatory evaluation process for the food stream of Montréal in Common can be consulted on Praxis.

Following three co-construction workshops and personalized coaching sessions, the participatory evaluation process led to the development of a platform designed to bring together the partners’ data: Évaluation en commun . This platform includes:

  • a form-creation tool where partners can collate their data;
  • a database;
  • as well as a dashboard that presents processed data in various forms (graphs, boxes, etc.).
Screenshot of the Évaluation en commun platform dashboard

The aim of this platform is to pool evaluation data from projects in the Montreal food system and, subsequently, to visualize this data.

A Data Sharing Policy for the Évaluation en commun Platform

Reaching an agreement on common data storage and access mechanisms quickly became a necessity. This objective led the team, which includes the Conseil du Système alimentaire montréalais, to take a broader look at the governance of the data generated by its projects. To this end, the team worked on the development of a pdf Politique-de-partage-des-donnees-sur-la-plateforme-evaluation , in parallel with the creation of the evaluation data dashboard.

Do you face similar challenges in your own organization?

Learn more about the ideas proposed by UQAM's Research Chair on Ecological Transition regarding the governance of participatory evaluation data in this case study. 

Multiple Partners, Multiple Stakes: The Challenges of Data Governance in a Collaborative Project

During the targeted coaching sessions, the team examined the ethical issues, processes and tools required to successfully carry out the participatory evaluation approach and to disseminate the evaluation results in support of the Montreal food system.

The Chair was faced with two main challenges when setting up its data governance strategy: developing its data sharing policy and designing the dashboard:

  • Data governance made complex by the presence of several entities - The involvement of several organizations introduced challenges linked to different approaches, needs, concerns and willingness to share.

  • Ability to handle growing volumes of data - With the number of organizations involved in data collection set to increase in the future, the processes and tools in place need to be reliable and flexible.

Implementing Data Governance for a Collaborative Project With Public Outreach 

Évaluation en commun's data governance is characterized by its collaborative nature and its objective of public dissemination of the results. This approach raised ethical issues concerning confidentiality, data anonymization and the intellectual property of information shared on the platform.

"Data governance becomes complex when many parties are involved, each with their own perception of data sensitivity and the appropriate degree of sharing. The data sharing policy we developed during the targeted coaching helped cultivate a fruitful collaboration with our partners. It was essential to have their trust in this aspect of the participatory evaluation process!"  - Éliane Brisebois, Research Officer at the Research Chair on Ecological Transition. 

Questions Raised During the Development of the Data Sharing Policy

The UQAM Research Chair team considered several aspects of the data life cycle when developing its data sharing policy and the Évaluation en commun platform. Finding mechanisms that satisfy regulatory constraints, project needs, community outreach and partner requirements is no easy task!

 Here are the main questions raised during the targeted coaching sessions:

  • Intellectual property (IP) of data - How can we define the ownership of data shared on the platform by a variety of partners?
  • Data storage - How can we ensure that the data is stored securely and reliably to guarantee confidentiality and integrity? Who is responsible for it, during and after the Montréal in Common project?
  • Openness and data sharing - What type of data sharing would be most appropriate: closed, shared/restricted or open?
  • Sharing raw and processed data, anonymized or not - Does the data collected through the Évaluation en commun forms contain sensitive information? 
  • Data retention period - What are the future research needs, verification requirements (if any) and regulatory and legal requirements associated with the data collected as part of the participatory approach?

The Foundations of Évaluation en commun’s Data Governance

Over the course of the targeted support, the Évaluation en commun team was able to define the essential requirements in order to continue the initiative. The data sharing policy presented to the partners reflects the data governance decisions made for this project:

  • Intellectual property
    • Decision: The data shared on the dashboards and available for download will be licensed under a Creative Commons Attribution-Noncommercial 4.0 International (CC BY-NC 4.0) license.
    • Reason: The intellectual property of the data depends, in this context, on the fact that it is shared by several partners, and that the analysis and processing of this data therefore becomes a "commons" in itself.
  • Data storage and sharing 
    • Decisions:
      • The data will be associated with project names on the public dashboard, except for financial data, which will be aggregated and anonymized. 

      • Upon request only, the data can be shared in spreadsheet format, with the exception of data on financing and operating costs. 

    • Reasons: A number of data storage tools and managers have been considered for this type of project: the Chair team, public or private partners, non-profit organizations, an external service provider, an institutional archiving system, a data sharing service, or a cloud storage system. Data will not be anonymized when presented in public dashboards; each indicator will be treated on a case-by-case basis, and some may present aggregated data (e.g., an average with data from several projects). This may evolve according to the constraints posed by the integration of new indicators and participating organizations.

  • Data retention period 
    • Decision: The data will be kept indefinitely to enable longitudinal analysis of the various indicators.
    • Reason: The data retention duration depends on research and audit needs, as well as regulatory and legal requirements. If the data has a long-term scientific or social value, it is advisable to think about how to prepare it for reuse.

Lessons Learned by the Évaluation en commun Team From Their Discussions on Data Sharing and Storage

  1. Handling the data governance of a data partnership is more complex than that of a single organization.

    • Multiplying stakeholders makes data governance more challenging: managing data becomes complex when it involves several entities with divergent perspectives on data sensitivity and the appropriate level of sharing. However, a variety of stakeholders is essential to the success of many projects such as participatory evaluation.

  2. Balancing the participatory approach

    • The Chair's experience has highlighted the importance of striking a balance between decisions taken internally and those requiring consultation with external partners, so as not to over-solicit them. 

  3. Trust and transparency are your allies

    • Discussions with partners were central to the development of the data sharing policy. Establishing a relationship of trust was essential to obtaining quality data and fostering productive exchanges on data governance.

  4. A constantly evolving process

    • Data governance is a perpetual and evolving process. It is imperative to remain open to future changes and to persevere in the search for best practices, even in the face of challenges.

Impact of the Data Sharing Policy Implemented as Part of Évaluation en commun

The main challenges associated with data governance in the context of Évaluation en commun were rooted in the need to foster cooperation between partners, in order to contribute optimally to the participatory evaluation project.

"Thanks to this support, we have really taken a step forward in the governance of our data. The strategic orientation that the support sessions enabled us to adopt was crucial. Instead of rushing into potentially costly experiments, we were advised to adopt a thoughtful and relevant approach. This guidance laid a solid foundation for the rest of our project." - Éliane Brisebois, Research Officer at UQAM’s Research Chair on Ecological Transition.

She notes that the time invested has paid off invaluably. Given the inherent complexity of data governance, the targeted coaching sessions enabled the team to devote the time needed to understand the issues in depth. This led to the progression of the data sharing policy through consultations with partners in the participatory evaluation process. In the end, the development of the Évaluation en commun platform was carried out in accordance with the information and visibility needs of the collaborative project and its partners. The platform is a rich source of accurate and useful information for a wide audience, and will benefit the entire Montreal food system.

Are you planning to (re)think your data governance? Explore our other case studies to discover practical tips and advice. 

Remember that every step towards better data governance is a step towards more efficient use of your resources and more fruitful collaboration with your partners. It's never too late to start this journey towards continuous improvement.

About the Montréal in Common Data Governance Workstream 

As the lead of the Data Governance Workstream within Montréal in Common, Open North proposes a data governance journey to the innovation community in order to progressively operationalize the principles of the City of Montreal's Digital Data Charter. The program explicitly focuses on collecting, sharing and leveraging data to inform collective and individual decision-making. 

Montréal in Common brings together an innovation community led by the City of Montréal, whose partners are experimenting with solutions in food access, mobility and municipal regulations in a desire to rethink the metropolis. Thirteen projects are being implemented as part of Montréal in Common thanks to the $50 million prize awarded to the city by the Government of Canada as part of the Smart Cities Challenge.

Did you like this blog post? Would you like to know more about data governance? Not sure where to start? Find other resources, free training courses and more on our website: 

Author: Open North
Research and editorial contributions: Jérémy Diaz and Éliane Brisebois (UQAM)
We extend our thanks to all our partners and clients, whose work continuously expands and evolves our understanding of data governance and its best practices.

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