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Making Open Weather Data More Accessible: Extra...

Making Open Weather Data More Accessible: Extracting Seasonal Insights from Singapore Weather Station Data

Making Open Weather Data More Accessible: Extracting Seasonal Insights from Singapore Weather Station Data
讓天氣數據資料開源-洞悉新加坡天氣站的季節性資料

Event: Open UP Global Summit 2019
Date: 1 December 2019
Location: Taipei, Taiwan

Most of the world experience the four seasons, but how many seasons does a tropical country like Singapore have? We can get such insights from publicly-available weather data; however, we need to write scripts to make API requests to retrieve the data. In this talk, I will be sharing about a data-scraping tool that I have created to retrieve Singapore weather station data for a user-defined time period, and using a data-driven approach to gain a better understanding on the weather trends and seasons over the past few years.

Ong Chin Hwee

December 01, 2019
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  1. Making Open Weather Data More Accessible: Extracting Seasonal Insights from

    Singapore Weather Station Data Presented by: Ong Chin Hwee (@ongchinhwee) 1 December 2019
  2. About me Ong Chin Hwee 王敬惠 • Data Engineer @

    ST Engineering • Background in aerospace engineering + computational modelling • Loves (and contributes to) pandas • Mentor team at BigDataX, one of the Top 10 Data Communities in Singapore @ongchinhwee
  3. Are the “four seasons” just… 1. Hot 熱 2. Very

    Hot 很熱 3. Extremely Hot 超熱 4. Rain? 雨 @ongchinhwee
  4. Realtime Weather Readings across Singapore Real-time API (Application Programming Interface)

    on Data.gov.sg (Singapore’s open data portal) 即時應用程式介面 @ongchinhwee
  5. Realtime Weather Readings across Singapore Real-time API on Data.gov.sg (Singapore’s

    open data portal) Open government data available under the Singapore Open Data License 政府開放資料 @ongchinhwee
  6. Realtime Weather Readings across Singapore Real-time API on Data.gov.sg (Singapore’s

    open data portal) Open government data available under the Singapore Open Data License Minute-by-minute weather station readings @ongchinhwee
  7. “Let’s try to scrap weather data for a specific weather

    station!” “How about we scrap month-long data from the API?” @ongchinhwee
  8. “The data must be available as a whole and at

    no more than a reasonable reproduction cost...The data must also be available in a convenient and modifiable form.” - Open Knowledge Foundation @ongchinhwee
  9. Open Data - Available, Readable, Accessible Available: Open data is

    freely available for everyone to access and use without restrictions or exorbitant costs. @ongchinhwee
  10. Open Data - Available, Readable, Accessible Available: Open data is

    freely available for everyone to access and use without restrictions or exorbitant costs. Readable: Open data is more usable when it is shared in a machine-readable format such as JSON @ongchinhwee
  11. Open Data - Available, Readable, Accessible Available: Open data is

    freely available for everyone to access and use without restrictions or exorbitant costs. Readable: Open data is more usable when it is shared in a machine-readable format such as JSON Accessible: Open data is only useful if it’s shared in a way that everyone can easily discover and understand. @ongchinhwee
  12. If not everyone can understand how to use the available

    data, is the data really open? @ongchinhwee
  13. Data.gov.sg Weather Data API Scraping Scraping weather data from APIs

    via Python “Requests” library “Requests”: Python library for humans to send HTTP requests @ongchinhwee
  14. Data.gov.sg Weather Data API Scraping Scraping weather data from APIs

    via Python “Requests” library Currently supported Data.gov.sg APIs: 1. Air Temperature (in degree Celsius) -- 17 Weather Stations 2. Rainfall (in mm) -- 53 Weather Stations @ongchinhwee
  15. Data.gov.sg Weather Data API Scraping Scraping weather data from APIs

    via Python “Requests” library Currently supported Data.gov.sg APIs: 1. Air Temperature (in degree Celsius) 2. Rainfall (in mm) Scrap data for continuous time range + specific weather station @ongchinhwee
  16. Time Series Analysis of Singapore Weather Station Data Selected weather

    station: Changi Weather Station (ID: S24) Analysis timeframe: 2 Dec 2016 to 30 Nov 2019 (~3 years) Objective: - Extract trend and seasonality from minute-by-minute weather time series @ongchinhwee
  17. Key Takeaways 1. Open data needs to be accessible to

    anyone to be useful. ◦ Putting data out on the web with open data license is usually not enough - it’s not just developers using open data! @ongchinhwee
  18. Key Takeaways 1. Open data needs to be accessible to

    anyone to be useful. ◦ Putting data out on the web with open data license is usually not enough - it’s not just developers using open data! 2. If an open data source is not intuitive enough to use, build a tool to make the data more accessible for everyone! @ongchinhwee
  19. Reach out to me! : ongchinhwee : @ongchinhwee : hweecat

    https://ongchinhwee.me And check out my project on: hweecat/api-scraping-nea-datasets @ongchinhwee