Understanding who wants to use public information and why is one of the best things cities can do to improve the impact and relevance of their open data programs. To support that goal, the Sunlight Open Cities team helps city staff develop open data user personas. Ideally this is informed by in-depth user research, but city staff can also develop preliminary personas faster and more affordably by drawing on their experiences working with residents.
We’ve now held three user persona workshops: one at What Works Cities on Tour in Charlotte, NC in November, one at What Works Cities on Tour in Downey, CA in early March, and one for city department staff in Winston-Salem, NC later in March.
At each of these workshops we led participants through a series of exercises to help them think about who who might be most interested in open data now, and who might interested in open data in the future if they had some help.
These are only preliminary personas and every city is unique. However, as cities begin thinking more regularly about open data users, there is an opportunity to build collective knowledge. We wanted to share these preliminary personas to spark ideas and inspiration for open data staff in other cities.
So, just what kinds of preliminary personas have workshop participants been creating with the Open Cities team? Here’s a round up of all the personas that have been created in our workshops so far:
Personas from our workshop in Winston-Salem
In Winston-Salem, our workshop included about 16 city staff from a variety of city departments, including the Police Department, the City Manager’s Office, the Community Development Department, Human Resources, Budget and Evaluation, and the City Attorney’s Office. Winston-Salem staff generated personas based on their experiences with real people from the community that they encountered regularly. Here’s what they came up with:
- William the Home Buyer (low community impact; medium data skills): William is a 35 year old seeking purchase I home in the city, and researching the best places to live. He is seeking crime data, purchase history, and other neighborhood-level information to help him compare neighborhoods, but may have trouble interpreting raw data or even knowing what data is available.
- Passionate Professional (medium-low community impact; medium-high data skills): This resident is a professional, who is concerned about information about their neighborhood. In particular they like to use data—including quality of life indicators, zoning data, and other statistical information—to weigh in on city projects that may affect the quality of life where they live, such as the location of a cell phone tower.
- City Staff (low community impact; high data skills): This city staffer is seeking data related to the task that that they’ve been assigned by their manager: creating a report. The data they need are usually very specific but because of the silos that exist between city departments, they are often not able to find it.
- Local Journalist (high community impact; medium-high data skills): The local journalist makes various inquiries of city hall, ranging from the very specific to the general. They frequently engage with various city departments to obtain data and information related to their stories and beat. Depending on the story, data shared with the journalist can have a large community impact.
At What Works Cities on Tour in Downey, CA, our workshop included about 14 city staff from a variety of departments including Economic Development, the mayor’s office, city manager’s office, finance, purchasing, and innovation and technology. This workshop was specifically for cities in southern California, including Long Beach, Rancho Cucamonga, Palmdale, Riverside, and Los Angeles, as well as special guests Boulder, CO.
Attendees had general ideas of the types of people out there and their information needs and were able to start identifying their goals. Here is an overview of the personas they constructed:
- Solution-seeker innovating (medium community impact, high data skills): This person is an entrepreneur, an app developer, someone who is trying to find solutions with tech and data and needs as much information as possible to build their tool or product.
- Resident problem-solving (low-medium community impact, medium-high data skills): This person has a personal goal that they want to achieve, whether it’s improving the local ecological environment or getting a bike lane built in their neighborhood. They generally have a small-scale project or goal in mind, but they need information to make their case.
- Community activist advocating (high community impact, high data skills): This user type includes advocates, organizers, or organized residents who have long-term policy or social goals that they raise regularly at public meetings. They need regular, consistent information to make policy recommendations to city council. They often need regular information around zoning, planning, development, etc.
- Journalist reporting: Depending on the reporter’s beat, journalists need consistent access to information related to their coverage area. They cover updates in strategy-level issues at the City, as well as lawsuits, crimes, and local interest pieces. They regularly need meeting minutes, agendas, salary and spending information, and sometimes more specific items like crime reports or housing development info.
- Community/land developer working (medium community impact, medium data skills): This person regularly asks for the same items: permits, zoning, inspections, code compliance, construction, environmental assessments, etc. Cities could easily predict what they need and provide that in advance so they don’t have to ask.
- Staff investigating: Sometimes your stakeholder comes from inside City hall. Other departments tend to ask for data from one another just to figure out and coordinate with their coworkers across the City.
About 15 city staff participated in our personas workshop at What Works Cities on Tour in Charlotte, NC. These staff came from cities across North Carolina including Cary, Charlotte, Concord, Durham, Greensboro, High Point, Wake Forest, and Winston-Salem, as well as Gresham, OR. They also represented a variety of city departments—including Human Resources, Marketing, Code Enforcement, Economic Development, Planning, Budget and Performance, Information Technology, GIS, City Council, Budget, and Offices of Innovation.
Participants were able to brainstorm a number of real community members with information needs and draw from their experiences with these individuals to develop the following preliminary personas:
- Alexandria, the Concerned Citizen: Alexandria is a middle-aged community organizer and home owner. She requests data regularly from the police department—including crime data / incidents by geographic area. She is also interested in neighborhood asset data from Community Planning and Economic Development. As a result of her frequent requests, some city staff think of her as “needy”. She is a heavy data user with high tech skills, and she uses those skills to share data and recordings of public meetings on social media. Although she is high-tech herself, she is often organizing low-tech members of the community, which sometimes causes problems when it comes to the legibility of city data.
- Tyler, the Data Journalist (understanding of open data – high; attitudes toward open data – positive; influence on the community – high): Tyler is a 35 year old reporter working for the local newspaper, “The Observer), Tyler’s goal is to support evidence-based reporting. He often wants data that are not found on the Open Data Portal and might be heard saying “get out of the way of me and my data” or “the portal is unhelpful.” His background and education are in storytelling and data analysis. He can be found surfing the city open data portal on a regular basis, where he often builds heat maps and other visualizations and uses the APIs. He is know to challenge the City and his name is known around City Hall.
- Charlie, the Concerned Contractor (understanding of data – high, attitude – high, influence – high, tech skills – low): Charlie is an independent contractor who seeks out a lost of properties in the city that have been issued an order to demolish a structure. Charlie this data to support his business, reviewing the list of properties published on the city’s external website to reach out to property owners to offer his demolition services. Charlie likes to go directly to the website to locate the information, but wishes it were updated more regularly.
- Paula, the Problem-Solving Partner (understanding of open data – moderate; attitude – enthusiastic; influence – high): Paula is an institutional non-profit partner working on a particular issue, who has formed a community coalition of nonprofits with a shared goal. The coalition is looking for actionable insights they can bring to their work. While they would be well equipped to use data, they have limited staff time and capacity and often don’t know what data is available—or if they do, have trouble accessing and understanding it. Good metadata, knowledgeable contacts within city hall, and support for the coalition’s issue area might all go a long way in helping Paula and her partners use city data.
Common trends so far, and an open resource for tracking open data users
All three of the workshops produced a preliminary persona for a local journalist and two of the three produced residents facing challenges or advocating or city staff as users of open data themselves. These commonalities suggest that the kinds of users and uses faced in one city are likely to have relevance to open data programs in another.
In order to to continue building this collective body of knowledge for all cities, we’ve created an open Google Sheet of all open data user personas created at our workshops so far. Check it out to see more details about these users and their information needs.
We’re very interested to expand this to include personas beyond our workshops too. If your city has created open data users, we’d love to hear about them! Send us an email about them and we’ll add them to our tracker so other cities can see and learn from them as well.