Navigating Data For Complexity︎︎︎
June 2023, Workshop Seminar
MIT Senseable Cities 


How might we apply data-driven tools & strategies to effectively navigate the urban heat island effect & optimize resource utilization, inturn enhancing the overall comfort & well-being of residents?



Data Slots, Analysis, Tools(Neo4J) & Visualisation, Trend Analysis & Forecast, UX Tools, Ethics & TradeOffs, Branding & Strategy, Speculative Design   







1. Project Overview 


The workshop equipped us with the expertise and tools to creatively address urban challenges using data analysis. This data could be gathered through various means such as sensors, surveys, APIs etc. As designers, our task extended beyond ideation. We had to craft solutions that not only tackled real-world issues but also navigated ethical considerations and user privacy concerns adeptly.




Workshop Brief By Martina Mazzarello, PostDoc Researcher @ MIT Senseable Cities

Turning big data into urban stories & actionable tools, while making sense of complex & dynamic information flows, untapping it’s potential in designing better ways of living. 





2. The Big Idea


Coolscape




Rooted in these guidelines, Coolscape uses temperature mapping to identify local hotspots in the defined area. It then crafts effective mitigation strategies by analyzing human-vehicle activity, infrastructure data (buildings, materials), environmental factors like air quality & lastly greenery data (no.of trees, water bodies etc). Simulations and modeling visualize these solutions, presenting urban plans and optimized materials, including projected temperatures, post-implementation.

Strategies include defining ventilation perimeters, integrating green technologies into infrastructure, and altering materials/colors to minimize heat absorption. Coolscape tailors strategies for specific areas, prioritizing cost-effectiveness and sustainability. Coolscape strategically harnesses Google Maps for human-vehicle insights and weather data, complemented by third-party Meteorological Data APIs. Accurate local mapping is ensured through its proprietary temperature & air quality sensors. In alignment with ethical principles, Coolscape accesses authorized municipal infrastructure data exclusively, showcasing its commitment to privacy and meaningful tradeoffs. 


Lastly, free standing feedback meters monitor resident’s perception of heat and comfort level ranging from, “ cold, comfortable, slightly hot, very hot”. This accounts for the kind of mitigation strategies favoured by residents, making coolscape optimise accordingly.  




3. The Process

 

A Journey with Data-Driven Solutions, Tools, & Applications


Data-driven solution in cities : MIT-SCL case studies and real-world applications. Selection & critical analysis of similar case studies. Knowledge & exposure to current realities, progress & possible projections.

 




From Data to Ideation: An interactive exercise to design stories with data. 


Pitching ideas based on selected data slots, Selecting best ideas, Learning about the trade-off between privacy and benefits in data-driven solutions. Iterating key idea based on learnings.
Idea Generation: Data Slots ->  




Data Challenges & Design Solutions  


Starting from the final idea to a deconstructed data-driven idea “Coolscape”. Framing personas, human & urban interactions while also defining the technology & data behind them.




Demystifying Meta Data


Data description: which specific data traces are left for each step of the user experience and urban interaction. Simplifying meta-complexity into clear tabulation of categories & subcategories like actor, operations, data cards & its attributes. Further categorisation of Jobs to be done at each step of user+urban interactions. 
Download Data Tables* Here
 1. Meta Data -> 
 2. Jobs to be done -> 

Refer Coolscape Section

Partial screenshots of the metadata breakdown: refer steps of the user journey to see input/output of data at each stage.   





4. Conclusion 



At this stage, it was all about asking the right questions to further refine the concept. 
 

What are the benefits & trade-offs of Coolscape? Can we strike a balance, where the weighing scale tips towards the benefits?







5. Data Visualisation & KPI’S 




How can we decrease the data invasiveness of our application?



Could this be done by leveraging softwares that already collect the information we want, like perhaps Google Map’s API, so that data isn’t collected unnecessarily as it already exists?
Data Visualisation ︎︎︎


What are the projected KPI’s of Coolscape?