Week 3: Workshop 3 – Designing with Data (i.e., ‘things known or assumed as facts…)

What is this workshop about?
What does data look like? What data you need and how do you hunt and gather it? What do you do with it once I have it? How do I know if it’s useful data? How do I turn it into something (visual) to support my research project? Who’s it for and why?

Data is not just numbers. There is hard data and soft data in the form of facts, figures, statistics, details, particulars, specifics and features. Learn some foundation concepts and processes to understanding and working with a variety of creative practice-based researchers.

INPUT (collect, survey & review)

Looking and finding
Your scope: ‘T’ shape = breadth & depth of knowledge (thanks Craig Cherrie & Lauren Deacon)

Provenance: Where does your data come from? 

  • ‘Scholarly’—how to read a scholarly, science research paper without your head exploding
  • Trusted sources (e.g., GraphsNZ, Google Scholar vs. Pinterest or Reddit)
  • Filters, log out of Google!
  • FindRelatedBooks.com

What form does it take? What does it look like?
Content:

  • Quality (qualitative) + Quantity (quantitative)
  • Visual, textual, numerical
  • Facts, opinions

Format:

  • Digital/Hardcopy
  • Graphs
  • Doodles
  • Photographs
  • Audio
  • Ideation
  • Documentation
  • Vox pop…

OUTPUT (Analyse & Synthesise)
Data visualization (www.processing.org)
What’s missing? Errors, gaps, and limitations in the data collection process

Analysis:

  • Correlations
  • Causation (Danger, Wil Robinson!)
  • Big, wicked problems: scale, distance and time

Biases:

  • Personal/political/public/generational/economic/cultural/world-view/community-based…
  • Confirmation bias
  • The “dot.com” bias with researching online

Theory — yes, relating to your topic area, but where is the space for design in this??  

2 Case studies: 

moodbank (plus video documentation here)
Graph Commons (data visualisation app) —”ways of seeing” (Paper)

We did an activity that Andre called ‘Game Show’ where we got given positions in the game. I was the contestant which meant my group all got to help me on my how might we statement. This activity really helped me in my project as it questioned my whole topic at an early stage. As a team we figured that there wasn’t actually many hard facts around my topic as I had already narrowed down my subject which didn’t allow for much further in depth research for the ‘discover’ phase.

Data Research:

  • NZ Prescription Data services
  • Ministry of Health
  • Statistics NZ
  • How might the NZ system for prescriptions be made more accessible &/or user-friendly?
  • If we can’t change the system, how do we help others understand the system?
  • How might we educate the work arounds and why the system is like that to begin with?
  • Where might design be helpful?
  • What is the core of that? Empowerment, health users, mangaging your own health, agility with health system, economic issues, wellbeing
  • Education, what are the different ways over 
  • find another niche in the step back
  • What are issues where people
  • Ask the doctor, why can’t I?
  • What systems in place, are working for you? 
  • Facilitating, educating, agility, 
  • 43.5% agreed or strongly agreed that they avoid healthcare – is this because of accessibility? economic?
  • Meeting the needs of people who think healthcare 
  • America’s healthcare system so much more

To continue with this topic I am going to need to add a bit more scope to the project and take a step back. Instead of focusing on prescriptions I need to maybe focus on healthcare in a more general sense or find a problem/pain point to start from.

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