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Personas
yasminehilout edited this page Sep 30, 2024
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Why Climate and Data Scientists as New Personas
Further Refinement and Stakeholder Discussions
- Job Title: Incident Management Team (IMT) Commander
- Responsibilities: Leading wildfire fighting operations, making critical decisions on resource allocation, and overseeing evacuation efforts. For example, using real-time data from satellite and radar sources to make rapid decisions on crew deployment.
- Seniority Level: Senior
- Primary Industry: Emergency Response / Wildfire Management
- Region: Kamloops at the Provincial Wildfire Coordination Centre (PWCC).
- Country: Canada
- Cultural Factors: Strong commitment to environmental protection and disaster preparedness due to frequent wildfires.
- Age Range: 35-50 years
- Gender: Female
- Education: Bachelor’s Degree in Fire Science or Emergency Management
- Family Status: Likely has a family; may need work-life balance due to long hours during wildfire seasons.
- User Goals: To efficiently manage resources and make informed decisions to mitigate the impact of wildfires.
- Professional Objectives: Improve the safety and effectiveness of wildfire operations and protect communities.
- Key Values: Efficiency, accuracy, collaboration, safety
- Cultural/Ethical Considerations: Prioritizes human life, property, and environmental protection.
- Primary Motivators: Reducing the impact of wildfires, ensuring the safety of firefighters and civilians, and effectively managing wildfire suppression.
- Triggers: The need for timely, accurate information during wildfire events.
- Challenges: Receiving fragmented data from different tools and systems that slow down decision-making.
- Barriers to Success: Limited access to real-time integrated information, coordination between jurisdictions.
- Devices: Desktop in the command center; mobile devices in the field.
- Software Tools: Current wildfire management tools, propagation models, GIS (geographic information system) systems.
- Tech-Savviness: Proficient but relies on user-friendly, intuitive tools.
- Concerns: Data reliability and speed of updates, ease of communication across multiple agencies.
- Job Title: Provincial Wildfire Command Center Operator
- Responsibilities: Monitoring live data on wildfires, coordinating with field teams, supporting the Incident Commander by providing relevant information. Using the consolidated dashboard which our product should be, Mark can provide real-time updates of what is going on.
- Seniority Level: Mid-level
- Primary Industry: Emergency Response / Provincial Wildfire Management
- Region: Edmonton
- Country: Canada
- Cultural Factors: Familiar with cross-jurisdictional operations between provinces due to wildfires that cross provincial borders.
- Age Range: 30-45 years
- Gender: Male
- Education: Bachelor's Degree in Geography or Environmental Science
- Family Status: Likely married with young children.
- User Goals: To provide accurate, real-time wildfire data to commanders and ensure effective communication with field teams.
- Professional Objectives: Improve coordination and data integration to enhance response time.
- Key Values: Real-time data accuracy, clear communication, rapid decision-making.
- Cultural/Ethical Considerations: Strong focus on collaboration and public safety.
- Primary Motivators: Reducing response times and ensuring that commanders have all the necessary information.
- Triggers: The need for fast, reliable data during a wildfire emergency.
- Challenges: Data is often delayed or fragmented, making it difficult to provide timely updates to commanders.
- Barriers to Success: Lack of seamless integration between data sources.
- Devices: Desktop systems, large monitors for data visualization in command centers.
- Software Tools: Satellite data integration, weather monitoring tools, fire modeling software.
- Tech-Savviness: Technically proficient, but prefers simple, visual tools for data interpretation.
- Concerns: System latency or failure during critical moments, complicated user interfaces.
- Job Title: Wildfire Training Coordinator
- Responsibilities: Training new IMT commanders using simulated wildfire environments, conducting workshops and “war games” for wildfire preparation.
- Seniority Level: Senior
- Primary Industry: Wildfire Training / Emergency Preparedness
- Region: The Canadian Interagency Forest Fire Centre (CIFFC), based in Winnipeg, Manitoba
- Country: Canada
- Cultural Factors: Focuses on multi-jurisdictional cooperation for large-scale disaster scenarios.
- Age Range: 40-55 years
- Gender: Male
- Education: Master’s Degree in Emergency Management or a related field
- Family Status: Married with older children.
- User Goals: To provide realistic training environments that prepare IMT commanders for real-world wildfire scenarios.
- Professional Objectives: Improve the preparedness and decision-making of wildfire commanders.
- Key Values: Realism in training, accuracy, operational readiness.
- Cultural/Ethical Considerations: Strong belief in the importance of disaster preparedness and teamwork.
- Primary Motivators: Creating effective training scenarios that closely mimic real-world conditions.
- Triggers: The need to train commanders for increasingly severe wildfire seasons.
- Challenges: Difficulty replicating complex wildfire scenarios with existing tools.
- Barriers to Success: Limited access to accurate real-time data for training simulations.
- Devices: Desktop systems, virtual reality tools to ensure trainees are familiar with the platform's predictive capabilities.
- Software Tools: Simulation software, fire propagation models, geographic information systems (GIS).
- Tech-Savviness: Highly experienced with simulation technologies.
- Concerns: Whether the platform can fully replicate the complexity of real wildfire scenarios, scalability for multi-jurisdictional training.
The previous personas were designed for the app intended for submission to the CSSP's call for proposals. However, now that we are focusing on CRIM (the Computer Research Institute of Montreal), the primary users are no longer field workers and fire responders. Instead, the main users are data scientists and climate scientists. Therefore, while the first four personas were relevant to the project in its original form, we now emphasize the last two personas, given the research-oriented nature of the project.
These personas are not static. As we continue discussions with stakeholders, the personas may evolve to become more precise, and additional personas might emerge as the project develops, especially as new functionalities are implemented.
- Job Title: Climate Scientist
- Responsibilities: Analyzing climate patterns, understanding the impact of climate change on wildfire behaviors, contributing to research that forecasts future wildfire risks based on historical data.
- Seniority Level: Senior Researcher
- Primary Industry: Climate Science / Environmental Research
- Region: Ottawa, ON
- Country: Canada
- Cultural Factors: Strong commitment to research that addresses climate change and its environmental impacts.
- Age Range: 40-55 years
- Gender: Female
- Education: PhD in Climate Science or Environmental Studies
- Family Status: Likely married with children.
- User Goals: To use past wildfire and climate data to analyze trends, predict future wildfire behavior, and contribute to climate change research.
- Professional Objectives: Publish findings on the intersection of climate change and wildfire behavior, and provide data-driven insights for policy recommendations.
- Key Values: Data accuracy, sustainability, long-term environmental planning.
- Cultural/Ethical Considerations: Strong belief in the importance of addressing climate change through research and public policy.
- Primary Motivators: Using accurate data to make predictions about future climate risks and wildfire occurrences.
- Triggers: The need for comprehensive historical data on wildfire events and climate patterns to strengthen her research.
- Challenges: Incomplete or fragmented historical data on wildfires, difficulty accessing climate data correlated with wildfire events.
- Barriers to Success: Lack of consolidated datasets across multiple jurisdictions and data sources.
- Devices: Desktop computer, high-performance data analysis systems.
- Software Tools: Data visualization tools, GIS, statistical modeling software.
- Tech-Savviness: Very experienced with data analysis and visualization software.
- Concerns: Data gaps or inaccuracies in past wildfire datasets, limitations in the platform's ability to integrate climate variables with wildfire events.
- Job Title: Data Scientist
- Responsibilities: Cleaning, processing, and analyzing large datasets related to wildfire occurrences, extracting meaningful insights from past data to support predictive models and visualizations.
- Seniority Level: Mid-level
- Primary Industry: Data Science / Environmental Analytics
- Region: Calgary, AB
- Country: Canada
- Cultural Factors: Highly collaborative and data-driven work environment, emphasis on environmental sustainability and data accuracy.
- Age Range: 30-40 years
- Gender: Male
- Education: Master’s Degree in Data Science or a related field
- Family Status: Likely single or married with no children.
- User Goals: To utilize past wildfire data for building predictive models, identifying trends, and supporting real-time visualizations.
- Professional Objectives: Ensure data accuracy and reliability to improve wildfire management systems and forecast future risks.
- Key Values: Data integrity, efficiency, innovation.
- Cultural/Ethical Considerations: Focuses on producing high-quality data analysis that can inform public policy and disaster management strategies.
- Primary Motivators: Creating accurate models that can forecast wildfire risks based on historical data and developing algorithms that improve decision-making for wildfire response.
- Triggers: The availability of new data sources or advances in wildfire prediction models.
- Challenges: Dealing with incomplete or inconsistent historical data, difficulties integrating multiple data sources (satellite, topographic, meteorological).
- Barriers to Success: Data latency or inaccuracies that can affect the reliability of models and visualizations.
- Devices: Desktop workstation with powerful computing capabilities.
- Software Tools: Uses machine learning models to identify wildfire spread patterns, relying on reliable, high-quality historical data to develop more accurate forecasts.
- Tech-Savviness: Highly experienced in data manipulation, modeling, and visualization.
- Concerns: Lack of access to real-time data or unreliable historical data, complexity in integrating wildfire and climate datasets into one platform.
As mentioned before, these personas are not fully defined, particularly in terms of their technology use, challenges, and barriers to success. With further discussions with stakeholders, we will gain a clearer understanding of the problems and needs of the users, especially regarding similar existing products that our project aims to improve upon.