Project #10 Translation Device / Spiral Code

Description

The main goal was to explore air pollution around the world along with the weather changes. A lot of real data is not available, some cities report the amount of pollution for their benefit. 

I used https://openweathermap.org to create a comparison between weather data, pollution data, and area maps between defined cities. The main problem is loading the actual JSON data from the server. I had a lot of trouble and difficulties because through time p5js gives me an error loading data while the actual link with my API key worked in the browser. I do not know if this is a problem with the server, my computer, my internet provider, or p5js. Sometimes it is working, sometimes it shows an error. I spend the majority of time solving the issue with the API connection since this API is not the only server I have trouble with. Every API website I request data from did not load into p5js, even though it loaded in the browser. After visiting a large number of forums with similar issues I found only one solution that partly worked with my sketch. I used 'const proxyurl = "https://cors-anywhere.herokuapp.com/";' to give access to API data from the proxy. The resource I found the solution: https://stackoverflow.com/questions/43871637/no-access-control-allow-origin-header-is-present-on-the-requested-resource-whe It is working from time to time, but sometimes the server or proxy is not working and the issue solves only with time. It gives me “Script error.” in Safari or “Uncaught TypeError: Cannot read property 'split' of undefined” in Chrome. 



That is why I also visualize my sketches with illustrator because I couldn’t fully work with p5js with loading issues. In the future, hopefully, I will connect these sketches. I wanted to create a “visual map” of the interested area.

Design Process

I tried to explore 2. Collect, Analyze, Imagine, Teach feminist data principle. Although I am not completely sure I could explore it fully, I will continue the investigation. First, the https://openweathermap.org uses 371 cities for evaluation. This list consists of national capitals and many other major cities. This amount is not enough to compare. 

My current p5js design more represents an abstract comparison between “current data” and pollution in the city or by latitude and longitude. I generally wanted to collect it and reimagine the way we percept information. How is it for us to have only abstract shapes or movements? Will it be better to have explanatory text next to each parameter representation? Computers can easily tell what circle and movement represents what variables, but can humans interpret it in their way? I was imagining a world where machines and humans can use visual language to connect the perception between our worlds. 





There are some problems with the API itself. The website says the data API is free but generally, it is not if you want to dig out more data. The only free data is “current weather”. Not very responsive API sometimes it is hard to find the information or request the data. 

To provide weather data through the API, they use their numerical weather prediction (NWP) model, which uses several data sources:
* Global NWP models:

* NOAA GFS 0.25 and 0.5 grid sizes

* NOAA CFS

* ECMWF ERA

* Weather stations:

* METAR stations

* Users’ stations

* Companies’ stations

* Weather radar data

* Satellite data


Current weather is also a type of prediction because global NWP models and weather stations cannot provide a regular one-minute time step, and not all sites have stations. This type of prediction is known as nowcasting.

Reflection

I received some beneficial comments from my peers such as “A comparison of air pollution in crowded cities compared to less crowded suburban areas would be remarkable.” I would like to consider it If I get to work on the link between data pollution and weather. Also, there are a couple of troubles with loading pollution data, the resource only represents the data by latitude and longitude and not by city or area names. That means I either have to create a path from two links resources (weather data to pollution data) or manually type latitude and longitude to show the data. I did not figure out how to link them correctly yet. 

Overall, our path through feminist data principles gives me a lot of thoughts to reconsider and rethink in my work and projects. If not right away, but gradually I will work towards these principles more thoughtfully.