Tag: Civic Tech


【轉載注】特朗普自從上臺以來,一直是媒體和學者關注的焦點。這位「推特治國」的總統,不僅極具話題性,也伴隨着豐富的數據集。這無疑是政治新聞報道中,非常適合數據驅動報道的議題。這篇文章來自兩位港大的同學,初稿形成于 Open Data Day Hong Kong 2017 的黑客松,由 Initium Lab 編輯和發表。轉載此文有兩個契機。一是 Open Data Day Hong Kong 2018 將于3月3日在港大舉行,屆時全港的開放數據行動者、公民科技愛好者、記者、學者、市民將匯聚一堂,發起專案,並在一天的時間內做出原型。部分項目組會在活動之後繼續研發,形成出色的數據應用或者數據報道。這篇文章是一個經典的案例,無論從選題、數據搜集/分析/可視化,還是項目執行,都極具代表性。黑客松讓不同背景的參與者,在高壓下腦力激盪、通力合作,可以很高效地找到有趣的選題,並做出原型。而將原型轉化爲最終作品,往往會花上數倍于黑客松現場的時間,並且需要專業技能的介入。希望通過這篇文章,讓正在努力學習 Python、R、Javascript 的傳播同學看到一種可能性——獨行者最速,衆行者最遠。轉載的第二個契機是,最近NBC發出了有關俄羅斯在Twitter上虛假帳號的數據集和報道。特朗普的崛起讓大量精英階層感覺到是一記耳光,他們慌了,不斷苛責媒體和社交網絡。究竟俄羅斯有沒有從中作祟?作用有多大?爲什麼特朗普的支持者如此之多,但民調竟沒發現?是隨機誤差還是系統誤差?這些疑問會在很長一段時間內不斷閃現,而人們熱衷於各種蛛絲馬跡。可以說,盯住特朗普、盯住Twitter總會有用不完的數據,寫不完的故事。這篇文章是很典型的文本分析于可視化,用R完成,可借鑑處頗多。


美國新晉總統唐納德·特朗普(Donald Trump)以其極端言論在一眾政客裡獨領風騷。端Lab曾於2016年撰文分析特朗普與其競選對手希拉里·柯林頓(Hillary Clinton)面對媒體採訪時不同的言論風格,發現特朗普發言多用簡單句型,且善於用第二人稱敘事獲取觀眾共鳴。

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Workshop recap: Use Arduino to Collect Water Quality Data

1. What is the workshop about?

The Computer Science department and Data & News Society have invited Shan He, a Guangzhou-based civic scientist as well as the project director of Chinese NGO Greenovation Hub, to hold a workshop on harvesting water quality data through simple chemical test kits and DIY water monitoring device for environmental investigation on the 18th of January, 2018. A dozen of mixed students from computer science and journalism background and some interested citizens attended and worked in groups.

Ms. Shan He
Shan He, a Guangzhou-based data scientist, as well as the project director of Chinese NGO Greenovation Hub and science community Public Lab, held the workshop on DIY water monitoring.

Continue reading “Workshop recap: Use Arduino to Collect Water Quality Data”

Workshop | Harvest water quality data for environmental investigation — DIY monitor with Arduino

Data is the key for environmental investigation and monitoring. However it is very hard for ordinary citizens to get access to. Let water quality be example, which is associated closely with our daily life. When serious environmental disasters break out, with limited information disclosure from government, general public can hardly know the truth in time. The motivates us to organise this workshop that enables you to make DIY monitoring devices with open technology.

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Data News of the Week | e-waste in Hong Kong

Cover photo credit: Monitour Project

We have a special edition for DNW this week dedicated to e-waste in Hong Kong. The notes are derived from a seminar plus brainstorm session with researchers from CUHK, HKBU, PolyU, Lingnan U, activists from Land Justice, Open Data Hong Kong, CODE4HK. This is a quick note from memory, so evidence/ statistics/ figures quoted in this note need further verification before you use them. There are enough pointers for the reader to go back the source and find direct contacts.

The news points to follow

E-waste refers to the abandoned Electric and Electronic Equipments (EEE). With the booming of ICT industry, we are witnessing more and more e-waste these days. Why should you care? Let’s cut through the news points first:

  • 75% e-waste is disappeared, as Green Peace estimates. It collects data of EEE production and calculates expected e-waste according to the lifespans of devices. Comparing this with the e-waste collection data from formal government bodies, we can see a 75% gap, meaning those are lost track
  • 97.7% e-waste in Hong Kong goes to unknown channels (figure in 2009; may change due to new recycling plant; government is trying to increase supervised channels). This may signal a large number of illegal operation, but not necessary all illegal.
  • Hong Kong used to import a large volume of e-wastes given the loophole in the legislations. Those e-wastes went to mainland China for processing. The export to China was disrupted at 2015.
  • Yards/ factories/ workshops that collect, process and dump e-wastes exist in many remote locations in Hong Kong, especially New Territory. Those locations are not easily accessible, protected by “private lands” and “gangs”, as put by Land Justice investigators.
  • Many workers in those yards are illegal immigrants, for example from mainland and South East Asia. They usually work without proper protective measures.

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