Digital Economy, Digital Tourism based on Open Data and Open Access Approach

Digital Economy, Digital Tourism based on Open Data and Open Access Approach

ดร. วิรัช ศรเลิศล้ำวาณิช ที่ปรึกษาสมาคมส่งเสริมเทคโนโลยี (ไทย-‐ ญี่ปุ่น) และ

กรรมการที่ปรึกษาสมาคมสมาพันธ์โอเพนซอร์สแห่งประเทศไทย [email protected]��30 กันยายน 2557

กระทรวงการท่องเที่ยวและกีฬา

Open Data, Open Access, 30 September 2014, [email protected]

ConnecIng the dots

•  “Crea%vity is just connecIng things. When you ask creaIve people how they did something, they feel a liPle guilty because they didn’t really do it, they just saw something. It seemed obvious to them aSer a while. That’s because they were able to connect experiences they’ve had and synthesize new things....” – Steve Jobs, Wired, February, 1995


Copy and ImitaIon

•  “Picasso had a saying -‐ 'good arIsts copy, great arIsts steal' -‐ and we have always been shameless about stealing great ideas.” ― Walter Isaacson, Steve Jobs

hPp://hbr.org/2010/04/defend-‐your-‐research-‐imitaIon-‐is-‐more-‐valuable-‐than-‐innovaIon/ar/1 Open Data, Open Access, 30 September 2014, [email protected]

Raw Data

•  “Raw data now!” – Tim Berners-‐Lee on the next Web, TED Talks At TED2009


OPEN DATA AND OPEN ACCESS


5 Great Apps Backed with Open Data •  Archimedes

–  Health and nutriIon data •  Trulia

–  Congressional district data –  Wildlife refuge data

•  HelloWallet –  Income and reIrement program data

•  SaferCar –  Five star raIng data

•  Red Cross Hurricane –  Weather data –  Climate data

hPp://opensource.com/government/14/9/5-‐apps-‐developed-‐you-‐open-‐data


Jeff Bezos's Amazon Re-‐architect hPp://ciIzentekk.com/2013/06/06/lessons-‐from-‐amazon/

•  All teams will henceforth expose their data and funcIonality through service interfaces.

•  Teams must communicate with each other through these interfaces.

•  There will be no other form of inter-‐process communicaIon allowed: no direct linking, no direct reads of another team’s data store, no shared-‐memory model, no back-‐doors whatsoever. The only communicaIon allowed is via service interface calls over the network.

•  It doesn’t maPer what technology they use.

•  All service interfaces, without excepIon, must be designed from the ground up to be externalizable. That is to say, the team must plan and design to be able to expose the interface to developers in the outside world. No excepIons.

•  The Mandate closed with: Anyone who doesn’t do this will be fired. Thank you; have a nice day!


Open Access

•  Gra%s open access => free online access

•  Libre open access => free online access plus some addiIonal usage rights, granted through CreaIve Commons licenses


CreaIve Commons Types of Licenses


CreaIve Commons Regularly Used Licenses


CLOUD COMPUTING AND BIG DATA


SaaS PaaS

Device VirtualizaIon

CommunicaIon Infrastructure

Cloud CompuIng

IaaS


Cloud Services

•  Provide soSware in a form of service SaaS

(SoSware as a Service)

•  Provide plaqorm in a form of service •  Execute applicaIons with no concern of the scale •  Include middleware (database, execuIon env., management tools, etc.)

•  Limit the programming language

PaaS

(Plaqorm as a Service)

•  Provide infrastructure (virtualizaIon, storage) in a form of service

•  Allow applicaIons on any installed OS or middleware •  Execute applicaIons with concern of the scale

IaaS

(Infrastructure as a Service)

Google (Gmail, …) Saleforce (CRM) MS (“Live”, “Online” service)

Google (Google App Engine) Saleforce (Force.com) MS (Azure Services Plaqorm)

IBM (Blue Cloud) Amazon (EC2/S3)


Internet of things

Audio / Video

Log Files

Text/Image

Social Sentiment

Data Market Feeds

eGov Feeds

Weather

Wikis / Blogs Click Stream

Sensors / RFID / Devices

Spatial & GPS Coordinates

WEB 2.0 Mobile

Advertising Collaboration eCommerce

Digital Marketing

Search Marketing

Web Logs

Recommendations

ERP / CRM

Sales Pipeline

Payables

Payroll

Inventory

Contacts

Deal Tracking

Terabytes (10E12)

Gigabytes (10E9)

Exabytes (10E18)

Petabytes (10E15)

Velocity - Variety - variability

Volu

me

1980 190,000$

2010 0.07$

1990 9,000$

2000 15$ Storage/GB

ERP / CRM WEB 2.0 Internet of things

What is Big Data?

Alexey Bokov ([email protected]) Open Data, Open Access, 30 September 2014, [email protected]

Big Data, Big Opportunity (hPp://www.cmo.com/arIcles/2012/3/20/big-‐data-‐big-‐opportunity-‐infographic.html) •  Big data comes from

“Billions of chats, blogs, e-‐mails, mobile phone calls, and social networks, consumers are talking about every business and organizaIon. Somewhere in this massive conversaIon are shouts, whispers, clicks, and purchases that will determine each company’s success or failure.”

•  Many organizaIons are data-‐rich and insight-‐poor •  Turning data into real-‐Ime insight, and insight into instant acIon

•  Turning Big Data into a Big Asset •  Finding a path from Big Data to Big Opportunity


CollecIve Intelligence and PredicIve analysis

How do I optimize my services based on patterns of weather, traffic. How do I build a recommendation engine?

What’s the social sentiment of my product?

How do I better predict future outcomes?

Alexey Bokov ([email protected]) Open Data, Open Access, 30 September 2014, [email protected]

Yahoo Japan! Big Data Insight hPp://www.idcf.jp/lp/bigdata/


LINKED DATA


•  Linked Data is a promising technology for closing the gap between SOA and unstructured information management

•  Wealth of knowledge available as LOD can be leveraged as background knowledge for Enterprise applications

•  The application of Linked Data in the enterprise is still largely unexplored (opportunity)

•  Linked Data will make Enterprise Information Integration more flexible, iterative, cost effective

Why Linked Data?

Auer, Frischmuth, Klímek, Tramp, Unbehauen, Holzweißig, Marquardt: Linked Data in Enterprise Informa%on Integra%on SubmiPed to SemanIc Web Journal.


The Linking Open Data cloud diagram -‐-‐datasets that have been published in Linked Data format-‐-‐

hPp://lod-‐cloud.net/ Open Data, Open Access, 30 September 2014, [email protected]

extract structured information from Wikipedia & make this information available on the Web as LOD:

•  ask sophisticated queries against Wikipedia (e.g. universities in brandenburg, mayors of elevated towns, soccer players),

•  link other data sets on the Web to Wikipedia data •  Represents a community consensus

Recently launched DBpedia Live transforms Wikipedia into a structured knowledge base

Transforming Wikipedia into an Knowledge Base

S. Auer et al.: DBpedia -‐ A CrystallizaIon Point for the Web of Data. Journal of Web SemanIcs, Elsevier 2009. Most Cited Ar%cle 2006-‐10 Award S. Auer et al.: DBpedia: A Nucleus for a Web of Open Data. 6th InternaIonal SemanIc Web Conference ISWC07. S. Auer et al.: What have Innsbruck and Leipzig in common? ExtracIng SemanIcs from Wiki Content. 4th European SemanIc Web Conf. ESWC07


Structure in Wikipedia

•  Title •  Abstract •  Infoboxes •  Geo-‐coordinates •  Categories •  Images •  Links

–  other language versions –  other Wikipedia pages –  To the Web –  Redirects – DisambiguaIons


Infobox templates {{Infobox Korean settlement | title = Busan Metropolitan City | img = Busan.jpg | imgcaption = A view of the [[Geumjeong]] district in Busan | hangul = 부산 광역시 ... | area_km2 = 763.46 | pop = 3635389 | popyear = 2006 | mayor = Hur Nam-sik | divs = 15 wards (Gu), 1 county (Gun) | region = [[Yeongnam]] | dialect = [[Gyeongsang]] }}

hPp://dbpedia.org/resource/Busan

dbp:Busan dbpp:title ″Busan Metropolitan City″ dbp:Busan dbpp:hangul ″부산 광역시″@Hang dbp:Busan dbpp:area_km2 ″763.46“^xsd:float dbp:Busan dbpp:pop ″3635389“^xsd:int dbp:Busan dbpp:region dbp:Yeongnam dbp:Busan dbpp:dialect dbp:Gyeongsang ...

Wikitext-‐Syntax

RDF representaIon


CULTURAL KNOWLEDGE SERVICE


Cultural Knowledge Portal hPp://www.m-‐culture.in.th/moc_new


SemanIc RelaIon ExtracIon

Infobox

Knowledge map


Document Similarity Creator

BaIk fabric

How to make BaIk art


Product AnnotaIon Cultural product

Cultural shop

Product annotaIon


What has been done so far?


SOCIAL MEDIA UNDERSTANDING


hPp://tulaneict4d.wordpress.com/2013/04/05/social-‐media-‐in-‐thailand/


Monthly AcIve Users on PC in 2013


million

Thailand Monthly AcIve Users on Social Network and Messenger App in 2013

hPp://www.chandlernguyen.com/2013/12/state-‐of-‐social-‐networks-‐in-‐southeast-‐asia.html


million

Data PreparaIon

•  Word segmentaIon •  Keyword extracted from topic related documents (training set)

•  Tweeter inquiry using the prepared topic related list of keywords

•  Text similarity using GETA algorithm


Tweeter Viewer

Pages\Words

“TwiSer”

“Tennis”

“Dollar”

“Google”

…

IT 2 0 1 4

Sport 0 2 1 0

Economics 0 0 2 0

…

Word

ArIcle

IT

Sport

Economics

Word ArIcle Matrix (WAM) Word segm

entaIo

n

Tweet q

uery by keyw

ord

Domain specific tweets

Social movement Imeline viewer


Tweet is a user generated document …

is a user generated document. Tweet …

a user generated document. Tweet is …

user generated document. Tweet is a …

Coup on May 22, 2014

•  ทหาร, คสช., ประเทศ, ประกาศ, สงบ, อำนาจ, รัฐบาล, รัฐประหาร, ชุมนุม, ตำรวจ, สถานการณ์, นายก, ควบคุม, ยึด, ประชุม, เศรษฐกิจ, กฎหมาย, ศึก, แกนนำ, รัฐมนตรี, เลือกตั้ง, ประชาธิปไตย, ปฏิวัติ. ยึดอำนาจ. เคอร์ฟิว. กฎอัยการศึก

•  military, NCPO, country, announce, peace, power, government, coup d’etat, gathering, police, situaIon, PM, control, seize, meeIng, economy, law, war, leader, minister, elecIon, democracy, revoluIon, seize the power, curfew, marIal law


Tweet Query

•  Search Tweets by using Resqul API – GET search/tweets. Set q = the keyword set – 100 tweets/search limited – Repeatedly fetch data unIl all tweets in the coup periods are discovered

•  Be able to search back to 7 days


May 22, 2014 Coup-‐related tweet : 339,148 tweets

Word Cloud Timeline


Coup D’etat hPp://sn.iisilab.org/

Links

•  hPp://sn.iisilab.org/ •  hPp://naIon.iisilab.org/ •  hPp://www.m-‐culture.in.th/

•  hPp://www.m-‐culture.in.th/moc_new/


Google Cultural InsItute hPps://www.google.com/culturalinsItute/home


Google is profiling us!

Google Uses the Data It Collects


Web of Data –the Big Picture-‐-‐

big data

internet of thing

device

ontology

sensor

web data

semi-‐structured unstructured

semanIc web

web of data rdf

owl

xml xml

linked data

structured


DigiIzed Thailand: The UlImate Goal

•  DT is a framework for collaboraIon in technology and content development

•  DT is a plaXorm for digital content sharing •  Toward digital economy, DT PaaS will be

established

Open API

API MarketPlace


Digital Economy, Digital Tourism based on Open Data and Open Access Approach

Technology

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