Data Stories

In collaboration with Open Cities Lab

Design Brief
Design a way to tell a human story of the city that incorporates experiential data and quantitative data.

Design Phase 1
Using primary and secondary research methods to build foundational concepts.

Designers
Lyu Min, Aria, Yuning, Heng, Riya, Malaika, Ananya Manish

Research Methodologies
Literature Survey, Directed storytelling

Key words
Lived Stories, Data Gaps, NHS Waiting Time Data

Unraveling the brief

The 7 week project in collaboration with the open cities lab started with us unravelling the brief and dividing it into three segments.

The What

Design a way to tell human stories that incorporate experiential data and quantitative values.
Craft immersive, accessible and inclusive narratives.

The Why

Access to timely and relevant data engages residents and informs decision makers.
Traditional data capture fails to tell the lived stories leading to gaps between reality and data.

Open Cities Lab, An Introduction

OCL is a non-profit open and non-partisan organisation that combines the use of action research, co-design, data science, and technology with civic engagement to enable the development of inclusive cities and urban spaces.

For a deep dive we decided to interview two key team members: Ayanda Mlhanga (Product Owner) and Lerato Mosehle (UI Designer).

The How

The interview helped us understand the ethos and process behind OCL’s work. It also helped us roughly define our future steps:

Conduct a literature survey to deep dive into how data is manifested in the real world.
Use open sources to choose a set of data that is relevant to the people of this city (London).
Using pertinent research methods to capture qualitative data around the same topic to capture real stories.
Iterate to create immersive narratives that can engage residents and inform decision makers. Validate design using user testing.
Create a system that can be applied elsewhere.

Analysing the storytelling of Open Cities Lab‘s dashboard

What does the Data tell us?

Informs us about the impact of flood in regards to missing people, injuries, dwellings affected and damaged, and people in care centers.
Used maps, icons, colours and font variations to communicate the information in a clear and impactful way.

What does the Data not tell us?

What‘s behind the number？(stories/experiences)
What does these numbers mean to people？(Impact of information)
How can we reveal more than numbers？(design for vivid/engaging/inclusive data)

Literature Review

We conducted the literature review in four overlapping areas around data.

1. Data and Design

“Our society looks at the world through data, but data doesn’t have to live in a dusty database, it can come alive on city streets, galleries, museums and parks”

Looking at the work of artists and designers like Jason Forrest and Jen Ray was a great example of creating accessible narratives using data in the streets of New York that were provoking conversations.

2. Data as Culture

“PUBLIC’s core mission is to help governments reimagine digitally-enabled public services to deliver better for citizens. One of the most powerful tools we can leverage to achieve this mission is data.”

This section of the research shed light on data and dashboard being used as a major decision making tool for action and impact by governments and public organisations across the globe.

Inclusivity, Accessibility and Transparency of Data

“Policy and data scientists have paid ample attention to the amount of data being collected and the challenge for policymakers to use and utilize it. However, far less attention has been paid towards the quality and coverage of this data specifically pertaining to minority groups.”

If public policies are driven by data the question arises upon the credibilty of that data and the data collectors. Multiple research papers here highlight the under-representation of race and ethenic minorities in data collection especially in the healthcare industry.

Gap between Human Stories and Data Points

“All of these stakeholders are seeking data, but there is a wide gulf between the day-to-day experience of a person living in poverty and the work of an international policymaker at an organization like the United Nations.”

The last section talks about data gaps and to complement the research papers here build a case for integration of lived experiences as a solution for these gaps. This integration could support approaches that align with the needs of those intended to use them.

Identifying issues in the health care system in London

It was during the literature survey that our interest was piqued with topics pertaining to healthcare data. We also came across multiple instagram articles like these:

As an outsider, I was myself quite sceptical about the NHS services in London. I had only heard concerning things about the same, though my limited sources were fellow international students and thus, I felt my view was biased.

Our group thus decided to go to the source and ask residents about their experience with the NHS. We initiated a human search engine outside the St. Thomas Hospital and asked people “How was their experience with the NHS?”

We were expecting to hear a lot of complaints, but to our surprise all the participants had positive stories to share about their experience. When probed about their waiting time most of them said that they didn't mind as they were quite satisfied in the end.

Along with the human search engine insights we also looked into news articles and social media posts related to the NHS and realised a lot of discussion around the waiting time.

Clearly there seemed to be a gap between the collected data and the human stories.

How is the wait time data presented and what the data dosen’t tell us？

Waiting time in the NHS is a macro topic and in the first week it was important for us to narrow down to what part of the NHS we are focussing on. We decided to gather data around the waiting time in Accidents and Emmergency department in the NHS hospitals.

What does the Data tell us?

Maximum percentage of people wait for over 4 hours in the A and E.
There is a high percentage of people who wait over 4 hours in the A and E during the night time (9pm to 5am)
The data highlights the positive aspects more visually, for example brightest colour is used to indicate wait time for less than 1 hour and the dullest colour is used to indicate wait time of over 4 hours.

What doesn’t the Data tell us?

What do the people (patients and staff) experience during the waiting time?
What Does the wait time feel like and why?
How does it impact people?

References

Peng, Q. (2017). Storytelling Tools in Support of User Experience Design. Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems. [online] doi:https://doi.org/10.1145/3027063.3027121.

Dunne, A. and Raby, F. (2013). Speculative Everything : Design, Fiction, and Social Dreaming. Erscheinungsort Nicht Ermittelbar: Mit Press.

Tan, Z., & Hertz, G. (2019). Transforming Shoes: Storytelling Through Artifacts and Design as Narrative. doi:10.35010/ecuad:15109

Lee Roy Beach and Wise, J.A. (2022). The Theory of Narrative Thought. Cambridge Scholars Publishing.

Norman, D.A. (2004). Emotional design : why we love (or hate) everyday things. New York: Basic Books.

Forni, S. (2016). Narrating objects, collecting stories. International Journal of Heritage Studies, 23(6), pp.604–605. doi:https://doi.org/10.1080/13527258.2016.1274673.

Mager, C. and Matthey, L. (2015). Tales of the City. Storytelling as a contemporary tool of urban planning and design. Articulo, (Special issue 7). doi:https://doi.org/10.4000/articulo.2779.

The Blueprints