建築與都市的黏著劑:開放資料 (淡江建築 2016.10.9)
TRANSCRIPT
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2016 10.9 10.16
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https://www.youtube.com/watch?v=_Nua3Cjdik0
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DSP OpenData
Tim HongE-mail: [email protected] https://tw.linkedin.com/in/hongtim
Geek MakerSeeker
App 3+yearsData RD 2 Startup1 NPO2 Apps 1st
2016 Intel pre-IoT Roadshow London
2015 Emirates Travel Hackathon SF
2015 AT&T Mobile App Hackathon - Bay Area (IoT)
2015 HackingEDU
2015 Integrate 2015 Hackathon
2014 Hackathon
2013 CfT Open data day Hackathon
2013 G0V Hackathon
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DATA / URBAN DATA
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WHAT IS DATA?
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WHAT IS DATA?
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WHAT IS DATA?
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WHAT IS DATA?
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http://upload.lsforum.net/users/public/q41674nba2k13%208-07p190.jpg
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Geneva
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http://youtu.be/ZSt9tm3RoUU
http://youtu.be/ZSt9tm3RoUU
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https://www.youtube.com/watch?v=dOlLm5V0HFo
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https://www.youtube.com/watch?v=tLqPEzpAR_4
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Words or Fact?
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DATA / URBAN DATA
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>>....world
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>>>....world
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Through the actual city data mapping urban graphic Population
lining
amount
>>>....world
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Through the actual city data mapping urban graphic Population
lining
amount
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Through the actual city data mapping urban graphic
Medical (main hospital)
hospital
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Through the actual city data mapping urban graphic
Education (kindergarten ~ University)
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Through the actual city data mapping urban graphic
Security (Police, fire stations, monitors, accident)
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Gotta Catch em All~~~
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HOW
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DATA ENGINEERING
Extract, transform, load(ETL) (ETL)
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DATA ENGINEERING
Extract, transform, load(ETL) (ETL)
80%
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DATA ENGINEERING
Extract, transform, load(ETL) (ETL)
80%
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http://data.gov.tw/
Gotta Catch em All~~~
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DATA ENGINEERING
Extract, transform, load(ETL) (ETL)
80%
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20,000
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THERE IS NO EASY WAY
PNGCSVXMLPDFXLS
1051005105/10/510510 NAnull
1051005
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vs
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DATA ENGINEERING
Extract, transform, load(ETL) (ETL)
80%
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DATA ENGINEERING
Extract, transform, load(ETL) (ETL)
80%
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vs
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Why
WhyWhy
WhyWhy
What
What
What
What
WhereHow
WhatAnswer
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DATA ENGINEERING
Extract, transform, load(ETL) (ETL)
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XMLCSVJSON
Extensible Markup LanguageXML
Comma-Separated ValuesCSV
JSONJavaScript Object Notation
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Application Programming InterfaceAPI
API
A: API ? B:A: JsonB OS: ...
()
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XMLCSV
Extensible Markup LanguageXML
Comma-Separated ValuesCSV
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SHOW TO OTHERS
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https://carto.com/
https://timdream.org/wordcloud/
https://carto.com/
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https://goo.gl/tsk4i
Geocode by Awesome Table
https://goo.gl/7NzfZX
https://goo.gl/tsk4i
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https://goo.gl/7NzfZX
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1 23
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https://carto.com/
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JSONJSONJavaScript Object Notation
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googlejson
Paul Gambill https://goo.gl/zb6OQPCode https://goo.gl/TaWGNN
https://goo.gl/zb6OQPhttps://goo.gl/TaWGNN
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API 1 2
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https://timdream.org/wordcloud/http://ckipsvr.iis.sinica.edu.tw/
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https://timdream.org/wordcloud/
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1691 531
1108 528
963 521
853 493
844 480
795 473
787 460
780 456
739 452
670 450
642 443
613 431
610 425
603 424
588 414
568 413
567 405
543 399
537 373
532 366
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2971 899
2811 860
2646 822
2560 815
1954 814
1834 813
1809 803
1706 797
1597 778
1514 777
1505 728
1503 694
1400 685
1372 654
1276 636
1275 629
1022 618
998 604
984 596
909 595
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1691 531
1108 528
963 521
853 493
844 480
795 473
787 460
780 456
739 452
670 450
642 443
613 431
610 425
603 424
588 414
568 413
567 405
543 399
537 373
532 366
2971 899
2811 860
2646 822
2560 815
1954 814
1834 813
1809 803
1706 797
1597 778
1514 777
1505 728
1503 694
1400 685
1372 654
1276 636
1275 629
1022 618
998 604
984 596
909 595
302 43
200 41
156 41
135 40
110 39
91 38
90 38
83 37
82 36
80 36
69 34
69 34
61 33
61 33
56 32 OS
55 32
51 32
49 32
47 31
44 30
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662 745
vs
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Team Work
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SQL 0~
Python
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https://goo.gl/T5CDw7
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https://goo.gl/T5CDw7
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https://goo.gl/T5CDw7
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https://goo.gl/T5CDw7
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https://goo.gl/T5CDw7
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https://goo.gl/T5CDw7
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20
http://bit.ly/2016scdc
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Statistics are like bikinis.
What they reveal is suggestive,
but what they conceal is vital. -Aaron Levenstein, Business Professor at Baruch Colleg
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