Chronicling Interaction Design @srhhnry - Tumblr Blog

If we designed homes like we do #cities

Via James Ham ‏@evolvingcities

Synthesis from Interviews—first-pass

I’ve read through the six interviews I’ve conducted thus far, to pull out high level concepts, including overall structure of the methods, concerns to address, features to consider, and aspects of the ecosystem to be mindful of.

Loosely, here are those concepts, grouped by what they’ll help me think about.

Notes on Methodological Structure

How controlled are the environments? Start with controlled ones

How will I be able to tell what people are reacting to?

Don’t ask participants to articulate problems—ask them to describe the space or feel the space

Scalability

Concerns

Interests

Scaling the tech to what’s reasonable

Show outcomes

articulation and identification versus gut feeling

“more true to this project, you’re identifying variance”

Increase civic engagement for the historically marginalized

Reduce assumption in the interpretation of the biometric and video data by adding in additional data points—triangulation

Think of direct interactions with policy versus indirect, e.g. filling out a section 8 form versus living in public housing

Constituents who have the time and energy to give their voice are disproportionately represented

Is there a government service that is already mostly a positive experience? What are some small pieces that can be improved through this kind of data?

Consider the typing or characterization of the areas I’m looking at

Features to Consider

Showing content and connections

should I categorize the findings? How will I distill insight?

SMS tree structures have been successfully used in public settings, such as throughout the Ferguson protests

Bring in NYCHA housing data or narrow into one policy space, like NYCHA housing only

If I do narrow into NYCHA—what are the attributes that affect emotional well-being?

What are the baseline stressors to consider in a community?

Think about the primary piece of data you want to convey—use that to help structure the visualization.

I need a functional partner on the government side of things

Look for ways to create a shared government service model around design research

Concerns to Address

Diversity of opinion

Working with OpenData requires extensive expertise

All data can be manipulated—even raw emotional data (so be careful with my language)

Who owns the data I’m collecting? What is the transparency around the output?

Barrier around willingness to forsake privacy

Don’t assume bureaucrats are doing something wrong

Participation will be the biggest barrier

Ecosystem Aspects to be mindful of

Qualitative data is exciting

Use the data to create intrigue for civic decision makers

Examine how participatory budgeting works, and consider fitting project to that context

Community Boards and Townhall meetings are a type of competitor for my project

Insight versus impact—each has it’s own connotations and I should consider opting for the former

Government has a culture of expertise—integrating design research is part of a larger conversation

Participatory Budgeting practices need more expertise in the room.

Most civic innovation is in improving forms/paperwork

Consider policies that are timely or might be in the news

Policy decisions are driven by consultation

Residents are at the forefront of asking for NYCHA safety features

My proposed research could influence type/amount of contributors to safety implementations in NYCHA housing

#thesis

Summarizing Thesis: Feedback from classmates

Today in class, we quickly presented our projects, by summarizing in one sentence each, the following:

A summary of our project—the elevator pitch

Where we were with the prototype process

The most useful or interesting thing we’ve learned from user feedback

From there, our classmates gave us feedback by quickly jotting down notes on:

Based on our goals, what is the minimum viable prototype that will validate the concept?

What is the most important question we need to be asking ourselves?

What is the very next step we should take?

Here’s where my project netted out. I’ve collected the feedback and bold the items that are most meaningful to me, in their respective categories:

MVP:

Organizing policy makers to do this. Ask it(?)

Validated, tested prototype

Low-fi tools like texting

Case study on one policy that affects the lives of the citizen (and the citizen cares about it) using different sensor data

A walkthrough that shows how data is tracked (input) and translated into actionable visuals (output)—even better if it applies to a real policy

Demo a user case in which the user uses that system to solve a specific problem

Working prototype of some of your approaches

The research/design helps in version two of a policy or at least gives policy makers food for thought with empirical data

Demonstrate or show a video how methodology would create impact

Bulky but functional data collection device with analytics

click-through prototype with story/visuals around showing better experience or findings

EKG + your tool/app + your tool/app’s output

The most simple method/system mockup (a series of cards or website) of your method and apply it to test a simple and specific scenario

A comparison of how government makes decisions now versus how user input can and should impact their decision, showcasing how their feelings are captured

physical prototype to demo how data is collected and used

a usable prototype

small scale demo in hands of government users

Research diagram and possible usages and application

story or storytelling focused video

Next Step:

Adjust prototype/concept to specific NYCHA project

Identify what you will do with EKG waves to make the data more story-like for the policymakers

Get a hold of an EKG wearable and user test the questions/gain feedback for the prototype

Ability to test this with users and showing it to policymakers or higher ups with an array of motivations

Create a manual or tool set that allows people to provide notes on how they feel that day. Use this to see how they (gov) need to guide their questions

Different types of use cases?

Demonstrate to people wearing sensors that they can positively impact policy

Make physical or digital asset

User Journey

Test the high level prototype with decision makers

Figure out models/modes for having people track stuff

visualizing emotions

choose a specific scenario to test your method. Measure it’s effectiveness then iterate

Get policy makers and users in one room to help develop techniques

Start testing and iterating

Pair your long-term study with rapid usability tests

Researching and picking the policy and actually getting citizen to collect the data—wireframe how you will display it

Compare pros and cons (including tech and form factor) of data collection methods, including low-tech

determine achievable demo and consider scale

Question

What’s the actual form for how people will apply the methods?

Is EKG reliable enough? Is that data better than conversations?

How can you build out your tool for this specific scenario? Do you need additional functionality? Does everyone have a phone to participate?

What are the most important questions/issues for safety and for people living in NYCHA housing?

What is the platform in which government officials will view this data?

How to analyze the data in an objective way and translate into something meaningful for policymakers? What are they looking for?

How flexible and reliable (in terms of use) is biosensor technology to provide clean feedback?

What’s the relationship between people providing the data, and the people using the data? I feel you need to think about creating an eco-system and how to maintain this system so that each participant can benefit from it.

How are new policies tracked now/current users of the system?

What is lacking that your EKG solves for?

How do you convince government users the product offers value?

Why would people use this?

How can this become cheap, scalable and easy to implement?

Ideally, how would you verify correlation?

How easily will your idea be implemented?

Why is EKG important to the core concept? Feels like a bit of a disconnect.

How do you create and communicate long term consequence?

What level of information should you provide to the government?

How do you test EKG?

How do citizens see if what they are inputting is actually having an impact? What’s the feedback or incentive?

How do you incentivize people to wear EKG sensors and a camera? How do you manage all that data?

How will you showcase a method of research through interactions and a tool? Will it be for a very specific case?

#thesis

Yesterday I attended an OpenBCI brain scan event! The organizers, Babycastles and a neurotech group called Cortex, had participants go through an hour long vinyasa yoga session, with a brain scan before and after. They weren't looking to necessarily prove a hypothesis about the effects of yoga on the brain, but rather to examine all of the brain scans from the session to see if any useful patterns appeared. So really, this was more a test of the capabilities of the equipment. OpenBCI uses a Processing sketch to display the data in real-time.

The headbands they used employed four sensors and two ground points (attached to the ears), and were a bit cumbersome to put on. They definitely couldn't be used in a field setting such as a park or apartment complex. Additionally, I spoke with the organizer, and it was his opinion that anything active, like walking, would corrupt the data too much.

I asked about other devices, like the NeuroSky, and his opinion was that with only one contact point on the scalp, it was little more than a random number generator as multiple readings are how a device calibrates, or checks it's own readings. His favorite devices to date were the Muse and the Emotive, although the later requires a $450 investment in their software if you want the raw data.

Lastly, I described my project, and he thought I might not need EEG data, especially if I'm looking at stress. He thought EKG would be just as effective. This feedback has moved me in the direction of purchasing the BITalino board--it's plug and play with minimal build requirements, and has EKG, plus some other sensors like electrodermal (EDA). I'll reach out to the company to look for a discount, and likely order the board in the next day or so.

I'm still waiting to hear back from Muse about a donated eeg sensor, but I'm not waiting around. I'll also purchase a basic heart rate monitor to act as a backup.

#thesis #yogabrain #openbci #bitalino

Testing Thesis: Feedback from an expert in data-driven communication

On March 6th, I met with a director at an online news organization. I was interested in his take on presenting information with different audiences in mind, particularly an audience of decision makers in the public sector.

Here are a few key points from our conversation:

The idea has legs, and feels compelling

Think about how to provide context for any visualization

Similarly when designing visually, be sure to mitigate bias for the kind of story being told

A guiding metaphor helps when communicating large systemic stories

Similarly, another approach is threading the narrative between the near and far-view of a topic. Near-view is personal story whereas far-view is the system.

There is a tension of the map being the territory—how much do you reveal and how much is compressed into abstraction or story?

Think about how representative is this content, truly

My project feels like it’s trending toward the qualitative, so it might be worthwhile to just own that—the wonks already have the quantitative

Think about telling the story of a “A day in the life of a housing project”

When displaying the data, what is the primary piece of information? Space? Time What about having a map that shows emotional variance with clickable video? Versus showing the data over time

#thesis

Testing Thesis: Feedback from a public servant working in housing

On March 4th, I spoke with an employee at the New York City Housing Authority and she critiqued my thesis project. Her job at NYCHA involves increasing the caliber of design while also advising on the department’s projects based on her expertise in city planning.

Here’s what she had to say.

Regarding my focus on exploring investigating the effects of housing policy:

…In terms of the affordable housing—those are privately-owned and operated. Same with rent-stabilized. I think other factors—you’d have to control for a lot of things. Like I don’t think it’s rent-stabilized that will contribute, but you could…If I had to bet I would say there’s not much difference. In terms of the affordable housing units, some are mixed income and some are 100% affordable. Affordability also means a lot of different things—there’s other aspects of that. Be sure to pick what kind of level you want to look at.

So with NYCHA—there’s a question of how do we define NYCHA’s space? Is it public or private? I think there’s a lot of tension around how the space should be defined. And because it’s not clearly defined, there’s a lot of issue around how public that space should be treated. They haven’t determined the right balance between public and private.

Another element might be to ask a non-resident who is walking through a NYCHA campus to see how they feel. Or anyone who is walking through a neighborhood that is not theirs. The tension might be exacerbated by NYCHA’s reputations. And not all NYCHA developments are the same. The police keep records on the facilities. Some are safer than others.

She suggested that if I was going to target a single typology of building—I would need to consider the implications. In terms of NYCHA participation, it would be best to work with a community development group or the Tenant Association head directly and recruit participants. I would probably be better served if NYCHA wasn’t involved directly, but reached out to tenants associations instead.

She thinks it would be interesting because there’s so many different types of NYCHA buildings and so I might be served by looking at different NYCHA buildings. Where do people feel safer? What about non-residents?

There’s been a series of unfortunate accidents and crimes in some of these campuses.

Regarding the kind of information she would want to see from something like this?

…Talking to people in their home, and why they feel safe or don’t?

Does lighting affect emotional calm?

Another thing I could look at is to look at data before the mayor’s upcoming action plan is implemented and after the work is done. Or maybe look at points in time?

Some of the NYCHA sites already have Closed Circuit TVs, and Polo Ground houses already have blurred access control (unsure of what this is?)

I could maybe look at one campus that went through the MAP program.

Most of the cameras that have been installed….there’s 30 sites that have gotten CCTV this year and 49 last year.

There’s discretionary funds…it’s not like officials are just picking certain implementations, there’s consultation.

Regarding who she thinks might find this work useful?

She’s not sure what the research has been, but knows that residents have been asking for things like lighting.

She thinks I could present research to council people to help them inform their contributions to NYCHA.

One way to look at it, would be just to look at which groups are working with NYCHA.

She thinks my biggest challenges will be getting participation from residents, but it could be really interesting to compare sites with high/low crime and safety implementations.

Also, The ‘poor door’ is already a moot point, because there’s been commitments by the leadership to make sure that doesn’t happen again. So affordable housing policy isn’t as well, interesting.

#thesis

Testing Thesis: Feedback from an expert in civic innovation

On March 2nd, I met with a Director at 18F to get his initial feedback on the new direction of the project. The following is a sampling of his feedback:

Think of mass data visualization techniques vis a vis Jonathan Harris

“[This project] feels useable”

The more complicated the public policy, the more difficult it becomes to control for one variable.

There is no actual part of the process—everything is connected to everything else, but in terms of creating a usable chunk…what will be the more substantive problem is how can you see what they’re actually reacting to?

Most civic innovation is in improving forms and paperwork

Housing is much more interesting, but the data would certainly be cleaner from something like a recidivism class.

Start with a controlled environment then springboard in the uncontrolled environment.

He would be interested in public policy where you have to get a thing at a later date, like return to a department.

SNAP could be really interesting—“people hate feeling like they’re different. They blame themselves [for being on welfare].”

Avoid areas that are negatively designed already—instead, go for a more clean distribution of service delivery because you closed and got a loan.

The biggest thing is opportunity cost. So here in DC theres Code for America, and one of their most successful projects is that there are several forms for getting affordable housing. So the code for America brigade created an abstraction layer.

Maybe the move there is to grab people who are not in the affordable housing, but want to be.

This project is definitely bigger than a half-hour of my brain at the end of the day can contribute to.

Honestly what’s a lot less important than picking a policy is getting an advocate and a partner on the programmatic side. Find a functional partner on the other side of the table.

Just having acquiescence to access isn’t enough. Work really hard at finding a partner who is credible and interested in innovation.

Go to the Code for America brigades—they find good partners for this kind of work.

Civic Hall is a great resource as well.

Look for a policy where people are sort of fucking up but also doing things really well.

Look for ways to create a shared service model around design research.

#thesis

Testing Thesis: Feedback from a Public Servant

On February 27th, I spoke with a woman in the Department of Education. I explained to her that I was interested in using biometric data, and video to demonstrate what a day in the life of new yorkers really looks like, and that I wanted to demonstrate how public policy really affects people’s lives. After I walked her through some of the detail, I asked for her initial thoughts on the project.

She was curious about the testing aspect, and thought it felt like something IDEO would do. She was skeptical about how folks would opt-in and thought there’s something about the invasiveness of it, such as who owns the video? Does it get destroyed. She thought it felt like a barrier—our ability to record that data, or to find willing participants.

However, she could totally see the emergent technology aspect and wanted to know what type of research is there to suggest that’s the most meaningful way to capture that. Going back to the feeling of invasiveness, she also wanted to know if there are there other types of data that would garner similar information. For example, there are some methodologies in HCD where people do photoblogs and the researcher texts every hour.

Some additional points she made regarding the study:

What are the baseline stresses? Is it out of the ordinary for what these stresses are?

It seems like it’s a high barrier to get someone to participate in this

People bring their own biases and heuristics to analyzing what they’re actually experiencing. The video requires a lot of interpretation. If there’s a way to triangulate it might be more powerful.

Leaving all of that interpretation to the researcher, whoever they may be, they’re going to interpret a different action than the person.

SMS is such a low energy action that there’s no reason to not include it.

Then a larger question, are you looking for causality or not. Be mindful about the type of language you choose. Maybe it’s insight versus impact, as those two things have very different connotations.

She thinks any type of service where there’s interaction between a government and constituent is useful. Voting, DMV, marriage license—there’s direct interaction which takes you a step closer to understanding the impact versus a policy that might not impact that person directly on that particular day.

Recidivism, homelessness—the things that are less visible to the average person. There’s also things like the post office.

Think of extreme cases versus average.

Regarding the use of design in the public sector:

There’s a larger challenge of arguing for the usefulness of this.

At a lot of institutions there’s a culture of expertise. They’re really prepared to make research and experience-based decisions on policy. The other side of this are coming from the design + tech world, wherein the thought is that you really need to go out and see the people and be on the ground.

It’s a huge culture shift, so any of the work around this has to be part of a larger conversation of how policy makers embedded in a culture of expertise break out of that.

I think it would be interesting to talk to bureaucrats. You’re assuming they’re doing something poor.

Policymakers have been jaded.

Regarding my goal of mitigating the loudest voices:

“Professional parents” is a role in policy, and their voice is different than the average person, because they have the time and energy to give their voice.

How are local community groups actually bringing in the voice of the community?

Look at the participatory budgeting model. How are communities choosing their priorities?

She wishes they had more expertise in the room to help the groups make a better decision.

These meetings are open to the public so you can just show up. Not all districts do this. Brad Lander’s office does participatory budgeting, and they aside a million dollars every year in that district. Voting happens in April.

#thesis

(slightly) new direction

On February 25th, I met with my thesis advisor and after a lengthy discussion, we found a slightly stronger direction for thesis. Here are a few quick notes. I'll expand on the concept after I finalize the tech and design direction.

New Concept: Capture the emotional valance of a user experience when they’re interacting with a government policy.

Notes:

Policy is the common denominator

Global Lives Project 24 hour film in the lives of citizens

Visually see anxiety levels increase and decrease

“We can’t fathom how it feels to be poor in New York”

Have a visual representation of the emotional journey of their constituents

Objective

Anything self-measured is going to subjective, by definition

What are the parsings?

Man and woman

Poor or rich?

Use the system to interpret what comes back

Put it on CL—a day in the life

People are used to being paid to be in studies

Punch up tech and design

Will people volunteer for this?

My next steps:

Verify all of the tech, and understand the limitations and range of information

Put together a run-down of tech

Verify housing as the policy, or select another policy to focus on

Devise the actual experiences we’ll be logging

#thesis

Testing Thesis: Feedback from a Data & Policy Expert

On February 25th I met with a woman who give technology support to a collaboration of non-profits that do electoral work, legislative advocacy, and other policy work. She also works on donor reporting, mapping, and working with small community-based organizations.

Her background is in statistics, data analysis, and technical implementation. She bridges the gap between the technical data side to package insights.

(My idea has shifted slightly, so her feedback is outdated, but still useful.)

I walked her through my idea and some of the visual outputs, and her first through was to bring up the concept of Participatory Budgeting (PB). For example, in New York City, the local government sets aside $1 million as a slush fund. The community then proposes and votes on the issues they want to implement. She suggested I check out community organizations like The Fortune Society, Community Voices Heard, DRUM, and FURY. She also mentioned ABHIKAAR and KWAN which is based in Queens.

One of the issues with PB is that what people perceive as problems might not be actual problems. Like needing a streetlight. The bigger problem might actually be traffic flow. So a resident might say, they need a streetlight, but it doesn’t fit into the larger system.

PB practice wants residents to walk around a community and submit a problem via their smartphone. But she wasn’t sure the identification of problems is the best route. Maybe the better thing for a community is to have something new. For example, maybe instead of identifying problems, it’s important to understand if locations are stressful.

She also advised me to think of renaming my product to have a communities of opportunity name. I need a name for this particular type of geographical emotional data and for the snapshot of the information. She also said, “more true to this project, you’re identifying variance in emotional temperature based on geography in order to adjust agendas to get those ‘temperatures’ from bad to good. It gives people a way to talk about it.”

She was interested in how is a civic decision makers actions affects the category of variable of the emotional data. To the end she advised me to understand the schema of categorization and present that as well.

Regarding participants, she mentioned that the people who bring up issues are white and male. They feel like they have to be heard. This project could increase civic engagement from historically marginalized. That was good feedback to hear, as it was my intention with the concept to elicit more representative feedback from residents.

The conversation turned to technology implementation. She thought I should really look into SMS as it can get really advanced, and in many cases be more useful than an app. Her projects have had tremendous success with SMS. She said the services can do things like ask “How are you feeling. 1-5.” Then, based on the number they give back, one can dig deeper to ask (e.g. if it’s a 1) “Text back if you feel unsafe.” These kinds of SMS trees have been used in Ferguson.

Textizen is the service they use. The other service is Revere or Revolution messaging. Additionally, you can run the cross streets through a Geocoder API to figure out the user’s polling place, for example.

We then discussed bringing in Open Data. She said, it’s not even that you need expertise to work with OpenData (you do), it’s also not updated regularly—you need an API. It’s such a mess. It’s really hard to search for something. She suggested I focus on one data set, like 311 noise complaints, or NYCHA housing data.

More so, she also suggested I not frame OpenData as a competitor—but rather contextualize it in an overview of the existing landscape. It’s complementary or a resource. There are lots of others services to consider as a competitor. Like IssueVoter. My project is also in some ways replacing the public forum. A community board meeting is a kind of competitor.

When I mentioned that one of my goals was to ensure this data couldn’t be co-opted, she said, “I get what you’re going for, but I think all data can be manipulated. You don’t have a hard algorithm, so you will be making judgment calls. How people respond in polling is hard data. But the way you ask the question and hard tab the results is manipulation.”

So my next steps, are to make that algorithm transparent. The algorithm can be flexible but the outcomes can’t be.

#thesis

Some recent examples of structuring the output of the various streams of data the platform would handle. Also, a first pass at mocking up graphical faces as data. In the next week, I'm running these mock-ups past a few people who would be potential users to get their feedback on the efficacy of the graphics and the quality of the details.

#thesis

Recap: Example Target User and Use Case

Last week's class was a working session on users and use cases for our products. I feel like we might still be just reiterating the full concepts at first, but the session was still really useful. Most of what I worked on with my classmates, Mickey and Nga, were on the user experience of someone on the data collection side of things. We talked about the kind of information the participant would want to see on an ongoing basis, how they might want to see the ways in which their data compares to others, and what incentives they would need to keep logging information.

We also talked about visual elements, such as a home page, and the set-up for the mobile application.

I got some pretty good ideas from the session, and in no particular order, here are the elements I'm going to develop further:

Explore developing more nuanced graphical features of face data as the written data gets more detailed.

Ensure there is a dashboard for both types of users (aggregate and personal).

Think about the individual participant wanting to see how they compare against others.

Revisit Moves as inspiration for creating a daily log of events

Can the participant go back to the log at the end of the day to fill in information they didn't want to fill in at the time it was requested?

Should the aggregate dashboard show the total number of participants for that area?

How will I display time scale for the data? Is it defaulted to one day? one week?

Mobile app interface idea:

Question on top (What does this place feel like?),

One touch answer option (two text options or a spectrum?)

Contextual photo (showing two different types of spaces)

Follow up question of why? people can fill in if they want or revisit

Think about a full city map as the homepage, and then having the researcher click into a discrete area

What triggers the mobile app?

Changes in emotion--is this even feasible with current sensor?

Changes in location

Time passing

What is the form factor of the wearable?

What is the interaction around taking the device off and on?

#thesis

Testing Thesis: Feedback from Public Servants

On Thursday I spoke with a civil servant for the Los Angeles department of Parks and Recreation. I sent him a pitch deck and walked him through the project. It was humbling to see how nervous I was to talk about my ideas with someone outside of the world of design. However, once I got over the initial guilt of feeling as if I was wasting this person's time with goofy future concepts, the presentation went more smoothly. Overall, his reaction was promising, and he offered some great feedback for how to make the concept stronger and articulate the problem space more clearly.

Feedback included:

Articulating the Problem Space

Most civil servants hate attending townhall meetings because it's often the same loud person monopolizing the conversation, and there's not a lot to learn there. People would appreciate a more fluid type of data

A lot of huge open data sets require data scientists to tell you what they say. Being able to present data that shows where anxiety is as well as the potential context for it alleviates a lot of that middle man interpretation.

People working in the public sector want access to more public space data, not necessarily data around stores or home or places of work. That's where they have the most power to change things. Inherently, this data is harder to capture because it's not tied to monetary incentive like with market research for say, retail.

He was interested in seeing the results of a local survey showing how people feel about their governments—where do people feel unheard? This survey could set the stage, with real data, for demonstrating how my platform could act as an intervention.

Even more meta than the problem of setting the agenda—include some specific goals that this project aims to solve, perhaps out of the aforementioned survey.

Making the concept stronger:

He wanted to know how detailed the smiley face metric could get. While he really likes the graphical, illustrative idea, he wanted to see more nuance.

I need to have more examples within the pitch deck. This will help with eliciting feedback on the efficacy of using abstraction to convey emotion.

I'm in the process of scheduling more interviews like this one, as well as starting to dig in on the process of building out the app/SMS system for the qualifying data set.

#thesis

(Updated) Prototype Plan

Geomote

Geomote is a tool to help public policy makers understand the emotional ‘temperature’ of the community they’re serving.

Geomote aims to answer the following: When faced with data that puts people first and reflects the emotional state of actual citizens, civic decision makers will be more conscientious of the consequences of their actions. The platform incorporates biometric sensor data, which is qualified through user reactions on a mobile app. These user data points are further contextualized with Open Data. All three data streams are synthesized into an easy-to-read dashboard geared toward professionals in the public sector.

PROTOTYPE SCHEDULE

Prototype 1 (first three weeks)

Components: February 13

Design of the project

System Overview

Plan for use of sensors

Concepting and Brainstorm: Final Ideation February 16

Pitch deck

Set up pitch meetings with users to look for the following:

Anecdotal feedback

What would you use this for?

Help create the qualifying questions

Still To-Do

User Testing of Idea with public servants due by February 23

Procure or build sensors: February 31

Create bank of qualifying questions for mobile app/SMS: February 31

Find four people who will collect data for the research phase: February 31

Prototype 2 (three weeks)

Research and data collection phase

One week with two users out in the field interacting with their neighborhoods, the EEG data collection, and qualifying questions via mobile (either SMS or test iOS app)

Second week with a separate set of users interacting with those three elements of place, sensor, and mobile data.

Third week is spent working with the data and processing it into rough data visualizations

If possible, sending out the pitch deck to more government/policy workers to get feedback

Prototype 3 (final three weeks)

Building out dashboard

Data Visualization

Website creation or static mock-ups finalized,

dependent on timelines and resources

Visual Design

User testing of the dashboard on users (public servants)

#thesis

Recap: Competitor Assessment and Finding the Gaps

Last week I sat with two classmates, and together the three of us presented our thesis concepts to each other, with the goal of exposing gaps between our ideas and the ideas of our "competitors".

I found the session useful as I was able to explain like-minded projects. But my thesis project is focused on an incredibly niche field (civic hacking + design), so the projects really served as support structures for showing the worth of my idea ("Look! Other people have thought of this!")

That said, it was useful to have something to point to for my classmates' projects, as an idea to refute or incorporate into their own. I'm sure that was the case for my compatriots as well.

But at the end of the day, I wasn't really staking a claim in the competitive landscape, but more so testing validity through proxy projects.

#thesis

Thesis: What did I do this week?

1) Reflections on Alternate Prototype

Last week we were tasked with creating an alternative low-fidelity prototype for thesis class. I focused on the citizen side of data collection and tried to develop an alternative way to engage a user in answering questions on how they feel about their environment. It turned out being a bit silly.

I created a tree diagram akin to Choose Your Own Adventure, wherein the user would step through a series of questions which ultimately would create a story scenario. For example, the first question I asked was “What did the studio feel like today?” and depending on the answer there were four different environments that would create the backdrop for the ensuing story. Quite literally, I loaded a background photo on the projector screen in our classroom. The four options fell along a spectrum of Good, Mundane, Exciting, or Bad, with images of a tropical island, laundromat, 1920’s party, or Mad Max-esque desert pairing respectively.

The next question was on whether anyone in the studio had been helpful. The response of yes or no brought up a sidekick that was either awesome (like Jay Gatsby for the party setting) or not all all helpful (like a drunk party girl wearing a cheap flapper costume). This question got at the social dimension of a space.

There were a few more questions and photos, but ultimately the prototype felt contrived and a bit of a stretch. I think I’ll stick to more concrete representations of feeling and mood, and leave the weirder story analogies for another project.

I really enjoyed Amy’s prototype though, and honestly might borrow aspects of the swipe interaction (thanks, Amy! thanks, Tinder!), as that feels more cohesive as an interaction. I’ve also started to articulate how this project will work around both mobile and sensor tech, with the two modes working together to provide more comprehensive data. This pairing means I can reduce how “heavy” each mode feels (or what is required of the build in terms of both interaction and data collection).

Moving Forward—Iteration

My next step is to articulate and map out the whole system of what I’m proposing. I need to do this for peace of mind, but also because a pitch deck for the idea is a good idea. Per the suggestion of my thesis advisor I’m aiming to present the idea to a few potential users for feedback on the overall idea, and potential features or directions to include in the data collection phase.

2) Experience Mapping—The 5 E's Framework

Defining the Framework

Step 1: Determine the experience to be mapped

I’m going to map two user journeys—one is a citizen, a data collector, the other is policy maker, a data analyst. The experience map will start at discovering the platform, will move through the process of signing up to contribute data, collecting data, and then into the aggregation of data, visualization, and user interaction with the dashboard or final presentation of the data.

Step 2: Set the scope

The scope of this project is ultimately proof-of-concept. Does this idea have legs, and can I get something useful out of data and research? I want to explore the full system of the design, so accordingly the quality, or depth of the project, will not be as high.

Step 3: What’s the point of view?

Given the dual perspectives of the project, the point of view for this project requires some ethical thinking. How are people being represented in the data visualization? What’s the separation between personal and aggregate experiences? What are the points or moments of feedback for both the data collectors and data analyzers? Can they in some way talk to one another? There are lots of questions here

Step 4: Set boundaries

My main interests are in the data collection methods and results. But really, I’m excited to see how I fare when it comes to visualizing the data. My strength is not in visual design, so this will be a good opportunity to stretch those skills, even while recognizing that this will likely be the aspect of the project I’m least happy with.

3) PROTOTYPE PLAN MAP

Where have I been?

I’ve explored concepts and ideas around Open Data, Open Government, tracking and mapping emotions, bio-data, sensors, mobile, and civic engagement.

Here are my guiding concepts:

Take the temperature of a community

Think Nielsen rating, not Iron ring

Firms like bottlenose and blue state digital are relying heavily on social media

Twitter NLP = People reacting in space, not TO space

Real-time isn’t available currently

Social media war room

Think about the final data product the way you think about the weather—what’s the clearest way to get the information without diving in?

This is a case study of people and place

DON’T BE EXTRACTIVE

Color hue Dashboard

5-D maps

Fuck creating behavior change—take a step back to reality

“Fascism at every corner” (don’t do this)

Civic tech projects are all aspirational, but they all inevitably simplify to the point of absurdity

Agenda setting

What is the research?

How is that absorbed?

What is the political will?

Will this be passed onto a junior politician?

Don’t need to teach those who already have the issue as part of their platform

This is a more successful route

There is rarely a monolith of an organizer within a community

Sentiment analysis avoids advocacy pitfalls

Create feedback loops in civic tech—take the temperature of a community

Measure how our policies are making people feel

Communities provide the data; politicians absorb the information

Snap polling is problematic; not passive

Politicians need a simple website

Blow out the logical conclusions of all of this

Where am I going?

I need to finalize exact sensors to use in collecting emotional data. This is my top priority, as I’ll need to either procure or build the sensors I’ll be using by the end of February. My next priority is getting the idea in front of some subject matter experts. After that, I’ll decide on what’s important, but tentatively I’m looking at refining my approach to the mobile aspects.

I haven’t yet fully explored the data visualizations. I should also think about exploring something like Crimson Hexagon, a social media aggregator, to see if I can integrate social media into the dashboard I’m creating. This is a last step though, and can be left out if need be.

So research and user testing is a high priority, followed by prototyping and research design.

TENTATIVE PROTOTYPE SCHEDULE

Prototype 1

Components: February 13

Design of the project

System Overview

Plan for use of sensors

Final Product: February 16

Pitch deck

Set up meetings with users

Anecdotal feedback

What would you use this for?

Help create the qualifying questions

User Testing of Idea with public servants: February 23

Procure or build sensors: February 31

Bank of qualifying questions: February 31

Prototype 2

Research and data collection

Working with data and processing it into rough data visualizations

User testing throughout

Prototype 3

Building out dashboard

User testing of the product on public servants

#thesis

Always-Iterating-Thesis-Concept Statement

So far, my thesis project is:

FOR

Policy makers, journalists with a local beat, people interested in urban life and city issues

WHO HAVE

trouble understanding how government PRIORITIZES policy need, or wants to UNDERSTAND their own reactions to certain places, or RESEARCH the reactions of other users, or IMPLEMENT human centered design to urban planning

IN A

Data-driven, mobile and sensor market

THAT

examines location from a deeply personal and emotive perspective, emphasizing inquiry, and de-emphasizing assumption about place.

UNLIKE

other players in the Open Data and Civic Tech fields, who are starting from what data is available and machine-readable, and not from the user needs.

THE PRODUCT

Will help to focus the agenda of what gets attention in a city of many needs, by highlighting reaction trends and shaping where policy researchers and makers focus their own resources.

Product Lifecycle (What’s a lifecycle look like?)

A resident of a neighborhood might:

Turn on App

Run app in the background

Have passive bio-data being collected

run errands

visit new places

stay at home

enter in qualitative data periodically (growing investment with the system)

stop entering in data altogether (drop off)

Investigate data visualizations and aggregate results from the user base

What can you leave out?

I can leave my ideological stance on open government aside. Inherent to the project is an approach to open government that I don’t need to necessarily articulate or spend time theorizing. Additionally, I can make the data collection components of the project modular—so if I have time I can focus on a second phase of integrating social media, but it’s not an indelible element. I can also make modular the different types of active collection—so that the highest priority gets taken care of first (e.g. iOS app versus SMS for feature phones)

What would you like your next prototype to achieve?

I would like the next prototype to validate the idea and give me direction for iteration. This means being able to get feedback on the full scope of the system from a few key users in the public sector. I also want to know whether the dimensions of emotional valence resonate with users (am I leaving things out? am I using the right language or the right visuals?)

#thesis

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