Data-Driven Personas

Problem

The North American Regional Climate Change Assessment Program (NARCCAP) made terabytes of high resolution climate scenario data available to researchers worldwide. The generation of the data were complicated and misuse or miscalculations of the datasets could have dramatic consequences. We wanted to make sure we were delivering the data in an efficient way and assisting our data users in the most useful and appropriate ways.

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Constraints

The team I worked with felt they had a good understanding of our data community (users). Also, I hadn’t heard of UX research in a formalized way at this time. Rather, I was working towards a masters in Social Science (psychology and communication). I spent most of my time focusing on the intersection of physical and social sciences research methods.

Team

  • Linda Mearns – Principal Investigator
  • Seth McGinnis – Co-Investigator
  • Larry McDaniel – Lead Scientist
  • Melissa Bukovsky – Model Downscaling Specialist
  • Toni Rosati – Data Community Liaison (UX Researcher)

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Process, Research Design

I walked into this project after conceptual groups were already created. It was my job as the Data Community Liaison to validate assumptions and build out data-driven personas. I gathered data in 4 ways.

  1. I handled most of the communication and signups for our annual workshop. I had users label themselves when applying for the meeting. I then used their research (poster, talk, abstract) and had conversations with them in order to cross-reference their category with my understanding of the category.
  2. I was also in charge of new registrations, our user directory, and encouraging new research teams we called “topic pods”. By examining (data mining?) our uses’ research and collaboration behavior, I began to get a sense of how keywords they used related to more generalized groupings for personas.
  3. Part of my job was also technical support, customer service, and building educational tools. I used my regular communications with users as a qualitative repository of pain points and potential solutions. I also took it upon myself to ask deeper questions about the context in which problems arose.
  4. My network grew tremendously because of NARCCAP and several other science organizations I was a part of. I was able to recruit Hazard Impacts Researchers and Policymakers for deeper interviews about their work. Looking back, I was doing something very close to Mental Model research.

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Key Findings

We originally thought that Hazard Impacts Researchers and Policy Makers were similar enough to be lumped together. After talking with several from each group, it was clear that they were quite unique.

Results

NARCCAP was able to use these 4 personas to ensure that all users were represented in our work at future workshops and in the breadth of educational materials we offered.

Our growing data community and variety of users helped secure several rounds of funding – including from organizations that we would not have originally expected would be interested.

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