This document discusses how open data and open access approaches can be used to develop a digital economy and digital tourism. It provides examples of how open data has been used by various applications and organizations. It also discusses technologies like cloud computing, big data, linked data, and social media that can be used to analyze and understand open data for various purposes like developing cultural knowledge services.

1. Digital
Economy,
Digital
Tourism
based
on
Open
Data
and
Open
Access
Approach
ดร. วิรัช ศรเลิศล้ำวาณิช
ที่ปรึกษาสมาคมส่งเสริมเทคโนโลยี (ไทย-­‐
ญี่ปุ่น)
และ
กรรมการที่ปรึกษาสมาคมสมาพันธ์โอเพนซอร์สแห่งประเทศไทย
virach@gmail.com
30
กันยายน 2557
กระทรวงการท่องเที่ยวและกีฬา
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

2. 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
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

3. 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,
virach@gmail.com

4. Raw
Data
• “Raw
data
now!”
–
Tim
Berners-­‐Lee
on
the
next
Web,
TED
Talks
At
TED2009
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

5. OPEN
DATA
AND
OPEN
ACCESS
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

6. Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

7. 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
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

8. 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
Data,
Open
Access,
30
September
2014,
virach@gmail.com

9. 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
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

10. CreaIve
Commons
Types
of
Licenses
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

11. CreaIve
Commons
Regularly
Used
Licenses
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

12. CLOUD
COMPUTING
AND
BIG
DATA
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

13. Cloud
CompuIng
IaaS
SaaS
PaaS
Device
VirtualizaIon
CommunicaIon
Infrastructure
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

14. 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)
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

15. What
is
Big
Data?
Internet of things
Wikis / Blogs
Audio / Video
Log Files
Text/Image
Social Sentiment
Data Market Feeds
eGov Feeds
Weather
Click Stream
Sensors / RFID / Devices
Spatial GPS Coordinates
WEB 2.0 Mobile
Advertising eCommerce Collaboration
Digital Marketing
Search Marketing
Web Logs
Recommendations
ERP / CRM
Sales Pipeline
Payables
Payroll
Inventory
Contacts
Deal Tracking
Exabytes
(10E18)
Petabytes
(10E15)
Terabytes
(10E12)
Gigabytes
(10E9)
Velocity - Variety - variability
Volume
1980
190,000$
ERP / CRM WEB 2.0 Internet of things
2010
0.07$
1990
9,000$
2000
Storage/GB
15$
Alexey
Bokov
(abokov@microsoS.com)
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

16. 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
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

17. 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
(abokov@microsoS.com)
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

18. Yahoo
Japan!
Big
Data
Insight
hPp://www.idcf.jp/lp/bigdata/
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

19. LINKED
DATA
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

20. Why 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
Auer,
Frischmuth,
Klímek,
Tramp,
Unbehauen,
Holzweißig,
Marquardt:
Linked
Data
in
Enterprise
Informa%on
Integra%on
SubmiPed
to
SemanIc
Web
Journal.
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

21. 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,
virach@gmail.com

22. Transforming Wikipedia into an
Knowledge Base
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
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
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

23. Structure
in
Wikipedia
• Title
• Abstract
• Infoboxes
• Geo-­‐coordinates
• Categories
• Images
• Links
– other
language
versions
– other
Wikipedia
pages
– To
the
Web
– Redirects
– DisambiguaIons
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

24. Infobox
templates
Wikitext-­‐Syntax
{{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
RDF
representaIon
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
...
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

25. CULTURAL
KNOWLEDGE
SERVICE
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

26. Cultural
Knowledge
Portal
hPp://www.m-­‐culture.in.th/moc_new
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

27. SemanIc
RelaIon
ExtracIon
Infobox
Knowledge
map
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

28. Document
Similarity
Creator
BaIk
fabric
How
to
make
BaIk
art
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

29. Product
AnnotaIon
Cultural
product
Cultural
shop
Product
annotaIon
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

30. Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

31. What
has
been
done
so
far?
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

32. Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

33. SOCIAL
MEDIA
UNDERSTANDING
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

34. hPp://tulaneict4d.wordpress.com/2013/04/05/social-­‐media-­‐in-­‐thailand/
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

35. Monthly
AcIve
Users
on
PC
in
2013
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com
million

36. 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
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com
million

37. 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
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

38. Tweeter
Viewer
Pages
Words
“TwiSe
r”
“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
segmentaIon
Tweet
query
by
keyword
Domain
specific
tweets
Social
movement
Imeline
viewer
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com
Tweet
is
a
user
generated
document
…
is
a
user
generated
document.
Tweet
…
a
user
generated
document.
Tweet
is
…
user
generated
document.
Tweet
is
a
…

39. 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.
ยึด
อำนาจ.
เคอร์ฟิว.
กฎ
อัยการศึก
• 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
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

40. 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
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

41. Word
Cloud
Timeline
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com
Coup
D’etat
hPp://sn.iisilab.org/

42. Links
• hPp://sn.iisilab.org/
• hPp://naIon.iisilab.org/
• hPp://www.m-­‐culture.in.th/
• hPp://www.m-­‐culture.in.th/moc_new/
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

43. Google
Cultural
InsItute
hPps://www.google.com/culturalinsItute/home
Google
is
profiling
us!
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

44. Google
Uses
the
Data
It
Collects
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

45. Web
of
Data
–the
Big
Picture-­‐-­‐
big
data
ontology
internet
of
thing
device
sensor
web
data
semi-­‐structured
unstructured
semanIc
web
web
of
data
rdf
owl
xml
xml
linked
data
structured
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

46. Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com

47. 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
Open
Data,
Open
Access,
30
September
2014,
virach@gmail.com