HackMD
    • Sharing Link copied
    • /edit
    • View mode
      • Edit mode
      • View mode
      • Book mode
      • Slide mode
      Edit mode View mode Book mode Slide mode
    • Note Permission
    • Read
      • Owners
      • Signed-in users
      • Everyone
      Owners Signed-in users Everyone
    • Write
      • Owners
      • Signed-in users
      • Everyone
      Owners Signed-in users Everyone
    • More (Comment, Invitee)
    • Publishing
    • Commenting Enable
      Disabled Forbidden Owners Signed-in users Everyone
    • Permission
      • Forbidden
      • Owners
      • Signed-in users
      • Everyone
    • Invitee
    • No invitee
    • Options
    • Versions
    • Transfer ownership
    • Delete this note
    • Template
    • Insert from template
    • Export
    • Google Drive Export to Google Drive
    • Gist
    • Import
    • Google Drive Import from Google Drive
    • Gist
    • Clipboard
    • Download
    • Markdown
    • HTML
    • Raw HTML
Menu Sharing Help
Menu
Options
Versions Transfer ownership Delete this note
Export
Google Drive Export to Google Drive Gist
Import
Google Drive Import from Google Drive Gist Clipboard
Download
Markdown HTML Raw HTML
Back
Sharing
Sharing Link copied
/edit
View mode
  • Edit mode
  • View mode
  • Book mode
  • Slide mode
Edit mode View mode Book mode Slide mode
Note Permission
Read
Owners
  • Owners
  • Signed-in users
  • Everyone
Owners Signed-in users Everyone
Write
Owners
  • Owners
  • Signed-in users
  • Everyone
Owners Signed-in users Everyone
More (Comment, Invitee)
Publishing
More (Comment, Invitee)
Commenting Enable
Disabled Forbidden Owners Signed-in users Everyone
Permission
Owners
  • Forbidden
  • Owners
  • Signed-in users
  • Everyone
Invitee
No invitee
   owned this note    owned this note      
Published Linked with
Like BookmarkBookmarked
Subscribed
  • Any changes
    Be notified of any changes
  • Mention me
    Be notified of mention me
  • Unsubscribe
Subscribe
# Data for social good: what’s the right formula? ## 對社會好的資料:什麼才是對的配方?【譯】 ###### tags: `summit2018` {%hackmd ry-5qaFFm %} > start here # 劉嘉凱 ,DSP 智庫驅動 DSP 在做的是透過資料,幫企業解決關鍵問題,後來發現公部門與 NPO 也有一樣的問題,所以開始了 [D4SG](https://d4sg.org/) (由開拓文教基金會、ITSA 社群運算與巨量資料跨校資源中心和 DSP 一起發起) 與其他資料英雄(資料分析師)以一期三個月的方式合作 專案挑選標準: - 成果能創造顯著社會影響力 - 已經掌握組織內部或外部資料 - 提供專人窗口,主管積極支持 - 成果能夠確實導入組織運作 - 成果能被複製到其他單位,例如火災預防可以跨縣市複製 媒合 => 概念測試 => 持續發展 持續法展可能是回頭檢討記有的資料收集流程,或是往下走,拿成果來調整政策方向。今天想要討論的是,往下走後,會碰到哪些問題,還有實際案例。 ## 案例:[高雄火災預防管理](http://d4sg.org/fire-risk-analysis-of-buildings/) 現在的預防管理,關鍵是作有效的居家訪視,找出房子裡有哪些需要改善的地方,但缺乏精準行銷,找到需要優先訪視的區域。 D4SG 就是要解決目前亂槍打鳥的問題,從原本的隨機命中率 26% 長到 8x% ,鳳山區的火災發生率明顯下降,其他行政區與縣市也開始想要複製。 2018.10.28 D4SG 成果發表 # 運用數據分析創造法律扶助資源與便民服務 林聰賢,法律扶助基金會副執行長 問題:目標客群是需要扶助的弱勢者,但不知道怎麼找到這些人扶助、宣導 前幾年的方式:和 NGO 合作找對象、宣導影片、舞台劇,但不知道有需要的人,是不是真的來了,比如新北市政府的中低收入戶,沒有很多來法扶申請。發現過去一直只有一直在做,但沒有問要用什麼東西檢驗、到底來申請的人是什麼面貌。 這次 D4SG 的案子,以行銷為目的,交叉比對內外不資料。外部的通常是開放資料,像是低收入戶人口、牽涉的法律案件是什麼。雖然外部資料通常不是即時的,但還是盡量使用。 中低收入戶有來申請法扶的,平均覆蓋率只有 2% ,也可以看到有哪些分會的覆蓋率是偏低的,這些分會做了哪些宣導、工作,有沒有需調整的。 另外也做了身心障礙、原住民、身障、法律意識等分佈圖。法律意識是看有多少原告來申請法扶。 從年長者覆蓋率,加上高齡人口分佈,發現台灣東北角有很多高齡人口,但卻沒有接什麼案件的。後來透過移動距離資訊比對,找出適合的駐點,看哪邊是老人可以方便到達的地方,配合政府的其他活動,一起到各地宣傳,結果每次活動都有接到案件。 法扶全國有三千多個律師,希望能整合資源 What is next? 心得是組織內需要有資料團隊,目前會找學術單位合作,把數據開放給他們,了解律師辦案品質 除了量化,質性田野調查也很重要,讓決策更貼近民眾需要 內部管理開始要設定目標,決定方向 The issue is about how to reach the people with real need. Therefore it's a marketing case this time. We try to collaborate with social worker to identfiy different type of mid-low income household people and their location. Most cases is civil ones, like property and marriage. A lot of people didn't know there are many things related to laws. We would say if you know you can sue someone for something, then you have "legal awareness." There are some areas, the cases from the low income and elder people are lower than other place. After study, we found out that it's a traffic and mobility issue. It's necessary to intergrate with other public service to let the people in need can access the legal assistance service. Quantity and quality study are both crucial to improve our service. So we try to do hire 2 ppl to work on this. # 蕭舒云,台北市社會局科長 ## 讓我們成為更好的資料英雄 主要會講當初為什麼會申請 D4SG ,以及心路歷程。 講者一直都在社服領域,主管年資 12 年,變成擅長出嘴巴而不是實際執行,數學也沒有很好,覺得原本自己應該跟 g0v summit 這樣的科技研討會很遠,直到... 參加 D4SG 的期末發表會,看到一個用數據作個案分析(紅黃燈),發現其實身邊有的數據,是可以拿來這樣用的。 ### 合作如何開啟? 1. 盤點問題與資料狀況 2. 約來談 3. 提案:脫貧潛客分析 - 脫貧方案其實已經辦了好幾年,但並沒有來分析哪些人是適合方案的潛在對象 4. 入選後才是辛苦的開始 ### 成果 1. 脫貧潛能預測模組雛形 2. 出國參加D4GX 3. 入選聯發科智在家鄉計畫 - 精簡低收 中低收入戶訪視流程 - 建置家庭脫貧潛力計算機 ### 推動關鍵 1. 找出工作的問題 2. 培力同仁 3. 開放的心交朋友 4. 拋開個資魔咒 - 公部門常見問題:拿個資問題作理由 - 但我覺得很多部分和法規其實並沒有那麼多衝突 ### 自己學到什麼 1. 讓系統不成為廢鐵 - 系統的資料要能夠被分析 2. 這是一舉數得的好事 3. 和不同專業合作,創造無限可能 4. 會上癮 ## EN transcript I will tell the story about why and how I involve D4SG and share the experience. It's amazing that I am on the stage since this activity seems belong to the tech people. However I am a social worker and a public servant with poor math and information skills. But it has been changed after a D4SG presenation where New Taipei City shared how they analyzed the data of dometic violence. This suprises me that the social work can also be fullfilled with data. As a manager I rise a meeting right the very next day and start to compose a proposal for D4SG. At beginning, we were lack of confidence, but CK said that once there is data, there is something we can do with. Our proposal is about poverty alleviation. It's a tough job since my colleagues have to work with D4SG after office hours. When the prediction model of poverty alleviation got the prototype, we also make it become a extend project in the buearu. We're lucky to start a partnership with Mediatek to keep the project growing. People doing with the real work never thought they would have a chance to go abroad because of this and doing their job in a totally different way. What I learn? If you can't learn things from the system, then it's junk. So we have to improve our system from time to time. It achieved a lot in a single project. It shows the huge potential if different professions work together. # 蔡志宏,行政院科技會報執行秘書 Data for social good Outline Government Open Data Milestones Ecosystem of Open Data Applications Stratigies for Open Data -Inter-agency efforts Strategies for Open Data Promotion -需求與供給端的媒合、開發環境的友善化 -以Bussiness Model 去思考才能長期發展 -與在地的結合是關鍵之一,重視國際合作與國際標準的一致性 Data for Social Good -(照片)國道公路邊的山坡崩塌造成很大傷亡,若有監控系統可避免,在事件後開始,介於公共利益與商業利益的案例。 -水、空氣、地震等政府資料已用API放在網路上提供大家運用 What's Next? -促成政府部門願意開放與願意與民間合作 -地方需要有ecosystem的發展 -有產業界的資源投注才能長期發展 -Open Data的國際標準 ### Q&A 1. Q:各國都在談開放資料的下一步是什麼?已看到各國將開放資料用於政策與公益目的,如何用資料與數據擬定進一步的政策制定,是否有現在進行中的例子可分享,過程中的阻礙、利用資料用於政策擬定的好處與壞處等? A: (蔡)資料本身是中性的,運用open data經過某種形式的整理使地方代表或組織可以一起看到資料,在社會溝通與社會共識建立上可帶來基礎,希望資料專家也一起加入,(之前的黑客松)過去的水資源投入公共建設分布是否經營,就把資料拿出來檢視。 (蕭)單純憑經驗判斷來做決策會有風險,如果將資料經過分析使社工員可用於判斷,能帶來很好的效果。 2. Q:關於社會福利政策與法扶,社會福利一定會畫一條線,例如有人可能會故意脫產來達到這條線的標準,所以中低收入戶的界定問題,是否能透過資訊反饋來檢視目前政策的制定是否正確。 A: (劉)脫產等都是個案,如何從機制上來防堵,這是社會福利上的漏洞,跟大數據比較沒有關係。數據分析應該是用於,這條線畫出來真的有助於現實,回應剛剛的提問,在人的服務上,現在的個資法在解釋或是用上繼模糊又嚴格,確實在法扶團體的服務上造成困難。 (蕭)以前沒有中低收入戶的線,但還是有需要幫助的群體,因此政府後來訂出,中央有建置相關系統可供使用者來檢視這條線的界定以及目前的制度是否合理。 ## EN transcript Taiwan had selected as No. 1 at Open Data by .... But the quality of data is still an issue, so we're trying to improve. It pops the chance fo application since the supply side and demand side meet together. Government funds the projects to encourage more open data to be used. It's also important to meet the intl. standand meahwhile meet the need of the locals. The hill-edge landslide issue shows it can be promote both public interest and commercial profit in a same time. The data of water, air and earthquake from government are already onlined with API. There should be resource from business, instead of government alone. ### Q&A Q: What's the next step of open data in Taiwan? How do we amend policy considering data, any challenge or experience to share?

Import from clipboard

Advanced permission required

Your current role can only read. Ask the system administrator to acquire write and comment permission.

This team is disabled

Sorry, this team is disabled. You can't edit this note.

This note is locked

Sorry, only owner can edit this note.

Reach the limit

Sorry, you've reached the max length this note can be.
Please reduce the content or divide it to more notes, thank you!

Import from Gist

Import from Snippet

or

Export to Snippet

Are you sure?

Do you really want to delete this note?
All users will lost their connection.

Create a note from template

Create a note from template

Oops...
This template has been removed or transferred.


Upgrade

All
  • All
  • Team
No template.

Create a template


Upgrade

Delete template

Do you really want to delete this template?

This page need refresh

You have an incompatible client version.
Refresh to update.
New version available!
See releases notes here
Refresh to enjoy new features.
Your user state has changed.
Refresh to load new user state.

Sign in

Forgot password

or

Sign in via GitHub

New to HackMD? Sign up

Help

  • English
  • 中文
  • 日本語

Documents

Tutorials

Book Mode Tutorial

Slide Example

YAML Metadata

Resources

Releases

Blog

Policy

Terms

Privacy

Cheatsheet

Syntax Example Reference
# Header Header 基本排版
- Unordered List
  • Unordered List
1. Ordered List
  1. Ordered List
- [ ] Todo List
  • Todo List
> Blockquote
Blockquote
**Bold font** Bold font
*Italics font* Italics font
~~Strikethrough~~ Strikethrough
19^th^ 19th
H~2~O H2O
++Inserted text++ Inserted text
==Marked text== Marked text
[link text](https:// "title") Link
![image alt](https:// "title") Image
`Code` Code 在筆記中貼入程式碼
```javascript
var i = 0;
```
var i = 0;
:smile: :smile: Emoji list
{%youtube youtube_id %} Externals
$L^aT_eX$ LaTeX
:::info
This is a alert area.
:::

This is a alert area.

Versions

Versions

Upgrade now

Version named by    

More Less
  • Edit
  • Delete

Note content is identical to the latest version.
Compare with
    Choose a version
    No search result
    Version not found

Feedback

Submission failed, please try again

Thanks for your support.

On a scale of 0-10, how likely is it that you would recommend HackMD to your friends, family or business associates?

Please give us some advice and help us improve HackMD.

 

Thanks for your feedback

Remove version name

Do you want to remove this version name and description?

Transfer ownership

Transfer to
    Warning: is a public team. If you transfer note to this team, everyone on the web can find and read this note.