This document proposes an 8-step framework for migrating Singapore government data to a linked data format. The framework includes steps for specification identification, data set analysis, object modeling, ontology modeling, URI naming, RDF creation, external linking, and dataset publication. It evaluates existing linked data implementations and tools to recommend approaches for each step. The goal is to standardize terms across agencies and make government data more conveniently reusable and joinable through linked data principles.

2. • Basics of Linked Data
• Purpose of this project
• Migrational Framework
• Eight Steps
• Conclusion

3. What is Linked Data?
• Linked Data is an alternative data representation
format.
• Actually, its just a repackaging of Semantic Web
elements
• It is different from relational database concepts
such as tables, rows, columns…

4. RDF
Subject-Predicate -Object
Jurong belongs to the West Zone
Linked Data Representation Format
http://data.gov.sg/resource/area/Jurong_West
http://data.gov.sg/ontology/property/has_zone
http://data.gov.sg/resource/zone/West
Subject
Predicate
Object
http://w3.org/2003/01/geo/wgs84_pos#/lat http://w3.org/2003/01/geo/wgs84_pos#/long
1°20'040.2"N
103°42'24.54"E
Traditional representation - Tables

5. Linked Data Components
• Data talks about itself. Humans and Machines
both understand data - How?
• URIs - lots of them
(http://data.gov.sg/PlanningArea/Kallang)
• RDF - Data model (Jurong Point is a location)
• Ontologies - Enforces a structure to data (Land
Hierarchy) – represented as RDFs
• SPARQL - Does the same job as SQL and a bit
more...

6. See the Difference?

7. Linked Data Cloud (Web of Data)
Linked Data becomes Linked Open Data(LOD) by
publishing it with “appropriate” license
Provides opportunity to link with other useful data
sets
Provides variety of information about the same
resource

8. Linked Data and Government Data - a
natural compatibility
• Why?
• Govt data is used by all
• Govt data needs to be transparent and easily
understandable
• Govt data is mainly factual – a direct fit!
• Standardized representation of Govt data across
the globe can facilitate comparison without
hassles.
• Best way to propagate a useful agenda to the
private arena...

9. Who have implemented Linked Data?
• UK, US, Brazil Governments
• Private Corporations? Yes
– BBC
– Nature
– World Bank
– New York Times
– FAO
– CIA Factbook
?Provide Links?

10. http://wheredoesmymoneygo.org/bubbletree-map.html#/~/grand-total--2010-
Sample Linked Data Usecase in UK

11. ABC Water Proj (R)
Agency Websites
Singstat
publicationsMINISTRIES
XLS
HTML
PDF
Accountant-General's Department
Accounting and Corporate Regulatory Authority
Agency For Science, Technology & Research
Attorney-General’s Chambers
Building & Construction Authority
Central Narcotics Bureau
Central Provident Fund Board
Civil Aviation Authority of Singapore
Department of Statistics
Economic Development Board
Energy Market Authority
Health Sciences Authority
Housing & Development Board
Immigration & Checkpoints Authority
Infocomm Development Authority of Singapore
Inland Revenue Authority of Singapore
Institute of Technical Education
Intellectual Property Office of Singapore
JTC Corporation
Judiciary, Subordinate Courts
Judiciary, Supreme Court
Land Transport Authority
Majlis Ugama Islam Singapura
Maritime & Port Authority of Singapore
Monetary Authority of Singapore
Nanyang Polytechnic
National Environment Agency
National Heritage Board
National Library Board
National Parks Board
Ngee Ann Polytechnic
People's Association
Public Service Division
Public Transport Council
Public Utilities Board
Republic Polytechnic
Sentosa Development Corporation
Singapore Civil Defence Force
Singapore Customs
Singapore Land Authority
Singapore Police Force
Singapore Polytechnic
Singapore Sports Council
Singapore Workforce Development Agency
Spring Singapore
Temasek Polytechnic
Urban Redevelopment Authority
Ministry of Community Development, Youth & Sports
Ministry of Education
Ministry of Foreign Affairs
Ministry of Health
Ministry of Law –Community Mediation Unit
Ministry of Manpower
Ministry of Transport
Media Development Authority
BFABuildings(C)
GreenBuilding(E)
C- Community
Cul - Culture
E- Environment
Emp- Employment
Edu - Education
H- Health
F- Family
R- Recreation
S- Sports
Breast Screen (H)
Cervical Screen (H)
Healthier Dining (H)
Quit Centers (H)
Infocomm Access (C)
Silver infocomm (C)
Wireless Hotspots (R)
Child care (F)
Disability (F)
Elder care (F)
Family (F)
Family Friendly Estab (F)
Student Care (F)
Comm Mediation Center (C)
After Death Facilities (E)
Funeral Palours (E)
Dengue Cluster (H)
Hawker Center (E)
NEA Offices (E)
Recycling Bins (E)
Waste Disposal Site (E)
Waste Treatment (E)
Heritage sites(Cul)
Monuments(Cul)
Museums(Cul)
Libraries (Cul)
Streets and Places(Cul)
CD Councils (C)
Community Clubs (C)
Constituency offices (C)
Other facilities (C)
Other Pan networks (C)
PA head quarters (C)
Residents Committee(C)
Water Venture (C)
National Parks (R)
Skyrise greenery (E)
Sports clubs (S)
CET Centers(Emp)
WDA Service points(Emp)
Kindergartens (Edu)
Get TokenAddress
SearchAgency Data
SearchStatic Map
Get Layer InfoMashup
Get Related Data
Get Directions
Public Transportation
Reverse Geocode
Map-related APIs from various agencies
Traffic-related APIs from Land Transport Authority
Tourism-related APIs from the Singapore Tourism Board
Environment-related APIs from the National Environment Agency
Library-related data feeds & web services from National Library Board
DGS Eco System
SG DATA
TEXTUAL
SPATIAL
API
THEMES OPERATIONSCATEGORIES
UNSTRUCTURED DATA
STRUCTURED DATA
STRUCTURED DATA
STATUTORY
BOARDS
SG Government Data Eco System

12. Different levels of
granularity
Multiple End points
Meta data only at
data set levels
Data already
cooked !!
Hierarchies not
captured
Vocabulary Conflict
in spatial and
textual data
Few design issues spotted through the Linked Data lens

13. Benefits of using Linked Data for iDA
Singapore
• An opportunity to standardize common terms
across agencies
• Re-use of resources (through URIs) ex:
http://data.gov.sg/zone/central
• Centralized control?
• Single endpoint for all govt data - Linked Data
API
• Very convenient for developers to join data
from different agencies. eg: combining data
from SLA and URA

14. URA Sites for Sales dataset(Urban Planning)
DOS Population and Household Characteristics dataset (Population Demographics)
Age Pyramid of Resident Population
Old Age Support Ratio
Datasets Used for Framework Evaluation

15. Framework Formulation Process
• Work was split into three phases – Analysis, Design
and Evaluation
• Based on study of Linked Data Migration Research
Papers and cookbooks published by the World Wide
Web Consortium(W3C)
• Analysis of Linked Data implementations in UK ,US
and Brazil
• Evaluation of Linked Data tools with Singapore data
sets for recommendation in each step of the
framework
• Contemplating on probable issues that could be
faced during implementation

16. Proposed Linked Data Migrational
Framework for DGS
Specification Identfication Analysis
Object Modeling
Ontology Modeling
URI Naming
RDF Creation
External Linking
Datasets Publication
Discovery & Exploitation
Re-use Create
S2R D2R A2R
Govt Agencies and IDA
Govt Agencies Domain
Matter Experts
Ontology Modelers
IDA and Web Architects
Developers
Developers and Domain
Experts
Developers
Web Architects
Objectives
Specifications
Project Duration
Dataset Prioritization
Dataset License Setting
Impln Mode Selection
Roadmap
Architecture
Overview
Relational Model
Dataset Overview
Drawing Objects in
Whiteboard
Conceptual View
Conceptual View
Public Vocabularies
Re-use of Existing
Vocabularies
Creation of New
Vocabularies
OWL, RDFS, RDF
Vocabulary files
Resources
Class and Properties
Visualization of URI
mining process
URI Administration
URI Lifecycle
ER Model
Spreadsheets,
DBMS, API
Conversion to RDF triples
using Mapping files
RDF Triples
Government and
external data sets
Linking based on
Similarity Algorithms
Outbound Links
RDF Triples
Ontologies
SPARQL, API
Data Insertion
VOID Modeling
Data Retrieval
API to SPARQL conversion
VOID Triples
JSON data
Actual Data
Existing Apps
Gamification
Crowdsourcing
Catalog Registration
External Reference
New Apps
INPUT
PROCESS
OUTPUT
INPUT
PROCESS
OUTPUT
INPUT
PROCESS
OUTPUT
INPUT
PROCESS
OUTPUT
INPUT
PROCESS
OUTPUT
INPUT
PROCESS
OUTPUT
INPUT
PROCESS
OUTPUT
INPUT
PROCESS
OUTPUT
Resource
Allocation
10
Resource
Allocation
15
Resource
Allocation
15
Resource
Allocation
5
Resource
Allocation
20
Resource
Allocation
5
Resource
Allocation
15
Resource
Allocation
15
1
2
3
4
5
6
7
8

17. Step 1 Step 2 Step 3 Step 4 Step 5 Step 6 Step 7 Step 8
Specification Home
1) Design the High Level Architecture
2) Set the “Migration Potential” for data sets
3) Decide the “Perspective” – Vertical vs Horizontal -> Agency vs Application (We recommend
Agency perspective)
Data set
Data set
URL Data Type Agency
Utility
Level
Interlinking
Possibility
Potential
Level
Annual Vehicle Population by Type of
Fuel Use URL
Textual
(PDF) LTA H L M
Administrative Data - Employment
Statistic URL
Textual
(HTML) MOM H M H

18. Step 1 Step 2 Step 3 Step 4 Step 5 Step 6 Step 7 Step 8
Specification Home
4) Setting up of License for data sets
5) Implementation Method – “Linked Data + RDF”
Other options - 1) Just URIs 2) URI for data sets only
Analysis of Data sets
 Study of System specifications, design & integration documents (including database) of
the selected data sets
• Understand Metadata, Schema design and Entity Relationship (ER) models
Data Set
Data Set
URL Data Type Agency License
Access
Rights Data Access Modes
Annual Vehicle Population by Type of Fuel
Use URL Textual (PDF) LTA PDDL R
API, SPARQL, RDF
Dump
Administrative Data - Employment
Statistic URL
Textual
(HTML) MOM PDDL R
API, SPARQL, RDF
Dump

19. Step 1 Step 2 Step 3 Step 4 Step 5 Step 6 Step 7 Step 8
Object Modeling
This is modeling without usage context.
*Requires normalization of database model in 3NF form
Issues
Possibility of applying high abstraction and
high granularity to objects
Key Learning
Ease in identifying the use of common
objects across data sets
Facilitates brainstorming of relationships
between objects
Home

20. Step 1 Step 2 Step 3 Step 4 Step 5 Step 6 Step 7 Step 8
Ontology Modeling
Takes the conceptual diagram from Object Modeling as input.
Design Ontologies
1. Identify classes and subclasses
2. Identify hierarchy structure
3. Connect classes through relationship
4. Create rules for inference (optional)
5. Output OWL vocabulary files
Ontology modelling is carried out in two ways:- 1) Using and extending public
ontologies 2) Designing a local ontology from scratch
Home

21. Step 1 Step 2 Step 3 Step 4 Step 5 Step 6 Step 7 Step 8
Ontology Modeling
Date fields, location fields and fields related to
measurements in DGS have scope for
vocabulary re-use
Vocabulary for the identified data sets
(developed using Protege) with screenshots
List of vocabularies required for LOGD
implementation
List of tools used for ontology modeling
OUTPUT?
ALLOCATION PERCENTAGE?
PERSONNEL INVOLVED
Home

22. Step 1 Step 2 Step 3 Step 4 Step 5 Step 6 Step 7 Step 8
URI Naming
ABOX TBOX
http://data.gov.sg/ontology/Ministry/ http://data.gov.sg/ministry/MOH
http://data.gov.sg/ontology/Agency/ http://data.gov.sg/agency/SLA
http://data.gov.sg/ontology/SiteLocation http://data.gov.sg/location/pioneer_road_north
http://data.gov.sg/ontology/Race http://data.gov.sg/race/chinese
Dataset ID URAstaticfile001
Dataset http://data.gov.sg/dataset/ URAstaticfile001/
Class http://data.gov.sg/terms/class/URAstaticfile001/sitesforsale
Property http://data.gov.sg/terms/property/URAstaticfile001/time
Row 1 http://data.gov.sg/dataset/URAstaticfile001/1
Row 1 - A generic column http://data.gov.sg/dataset/URAstaticfile001/1/columnName
Dataset URIs
Home
1) “URI Administration” Mode
Maintained centrally in the DGS platform (resultant URIs will start with http://data.gov.sg/)
-> RECOMMENDED
vs
Maintained by individual agencies (resultant URIs will start with http://ura.gov.sg or
http://sla.gov.sg).
vs
Maintained externally by third party platforms such as Kasabi (resultant URIs will start with
http://data.kasabi.org) – No longer valid as Kasabi service has been shut down
2) Setup of URI Taxonomy

23. Step 1 Step 2 Step 3 Step 4 Step 5 Step 6 Step 7 Step 8
RDF Creation Home
RDF triples are generated by converting data from source format with the necessary transformation
Type Nature Example of Singapore data sets Source format
S2R (Static Files) Static
URA Site for Sales, Singstat’s Population
Household Characteristics XLS, CSV, TXT files and other static files
D2R (RDBMS) Dynamic DGS tables RDBMS
A2R (APIs/Web
Services) Dynamc
OneMap API, myTransport API, NLB web
services
Application Programming Interface (API) and Web
Services(SOAP, REST)

24. Step 1 Step 2 Step 3 Step 4 Step 5 Step 6 Step 7 Step 8
RDF Creation Home
Evaluated 3 tools for each mode of conversion
Google Refine - S2R
RDF Views - D2R
RDF Sponger - A2R
Google Refine Demo for S2R!
 ER models from RDBMS are to be converted into corresponding
vocabularies/Ontologies for D2R process using STDTrip methodology
 For A2R, External Cartridges (mapping files) are to be created for mapping API
parameters to vocabularies. This can be done in RDF Sponger
“We feel that Linked Data is best suited for data from Static files and not for data that is
real-time and dynamic in nature unless conformity to structure can be trusted”

25. Step 1 Step 2 Step 3 Step 4 Step 5 Step 6 Step 7 Step 8
External Linking
External Linking is connecting with other data sets in the web of data
Data.gov.sg
WorldBank
CIA World
Factbook
DBpedia FAO Geonames
Supreme
Court
Flickr
<http://data.gov.sg/location/bugis> <owl:sameAs> <http://www.dbpedia.org/resource/Bugis>
<http://data.gov.sg/race/malay> <owl:sameAs> <http://www.dbpedia.org/resource/Malay_race>
Issues
•The outbound links made to data sets outside of IDA’s purview can be risky
•Dead links are a vivid possibility during the change of resource URIs or system
downtime
Home

26. Step 1 Step 2 Step 3 Step 4 Step 5 Step 6 Step 7 Step 8
Datasets Publication Home
 Triple Store or RDF Store is the data structure used to store Linked Data.
• We used Virtuoso Universal Server’s built-in triple store for evaluation
• It is visualized that the triple store will be centralized at iDA
 SPARQL (pronounced as SPARKLE) will be the main output terminal for Linked Data
• SPARQL can be used to SELECT, INSERT , DELETE, UPDATE data
• SPARQL is gateway to any operation on Linked Data. APIs and Applications are
built on top of it
Triple Store and SPARQL Demo!
We had some information about External Linked Data Hosting but we had to remove it
as the major provider Talis has closed its own hosting service Kasabi!

27. Step 1 Step 2 Step 3 Step 4 Step 5 Step 6 Step 7 Step 8
Datasets Publication Home
Linked Data API is the common API endpoint that will be used by developers and public
users to access government data.
- This solves the problem of maintaining multiple end points!
ex: http://gov.tso.co.uk/transport/api/transport/doc/bus-stop-point.xml

28. Step 1 Step 2 Step 3 Step 4 Step 5 Step 6 Step 7 Step 8
Discovery & Exploitation
Key Theme
1) Internal discovery within Singapore for local citizens – idea4apps (link)
2) External discovery for attracting usage of Singapore government data in
international economic & political research and global issues(water scarcity, Carbon
Footprint etc.)
• Entry in CKAN registry ->http://thedatahub.org/tag/registry
Home
Gamification? Promoted by LinkedGov.org

29. Original
data
provided
by URA
Possible because of
the re-use of the
common resource
URI Pasir Ris across
data sets
Similarly, location based
data from OneMap API is
retrieved for Pasir Ris
Interlinked Datasets Post-Migration

30. Other Interesting Use Cases
Definitely not Science Fiction!
Q & A Engine that works on top of government linked data. Inspired by www.trueknowledge.com

31. Sense-Making
Question: Which recent year had a growth rate close to 50% for majority of Singapore
based SME?
Step1: Spot the resources in this query
Dbpedia Spotlight does just that! – Semantic Information Extraction
Which recent year had a growth rate close to 50% for majority of Singapore based SME
Step2: Identify the relationship between the resources
SME is instance of the Organization class Organization class comes under Singapore country
Growth rate is a property of Sales class Year is a class by itself
Majority is subset of Group class
Step3: Use NLP technique – Syntactic Analysis (Stanford Parser) followed by Focus
Extraction for understanding the question
2010 is retuned as the result!
Step 4: Look for RDF triples that meet the criteria
Syntactic Parse tree is generated followed by Access Pattern

32. Key Challenges
• Dense data - lot of additional RDF triples will get created along with the
required RDF triples as a resource belongs to multiple ontologies
Demographics dataset stats:-
Rows:~300 Columns:16 in excel file
Resultant triples count in RDF/Triple store:13711
Reason: Majority of the generated triples are for machine understanding.
• URI administration could be an intense activity as dead URIs can cause
damage to applications eg: what will happen if
http://data.gov.sg/area/jurong doesn't work?
• Changes to structure of static files and RDMBS tables require changes in
RDF mapping files - might be a long process if not properly regulated
• Not readily suitable for real-time data

33. Summary
Four in-person
discussion sessions
with IDA, NIIT and SLA
Analysis of Five
data.gov.sg system
specifications
Evaluation of Four
existing Migration
Frameworks
Prototyping with Six
core Linked Data Tools
Dataset Publication
Virtuoso Universal Server Linked Data API
External Linking
SILK LIMES
RDF Creation
Google Refine RDF Views RDF Sponger
URI Naming
Pubby
Ontology Modeling
Protégé
Object Modeling
Concept Map

34. Summary
• Applicability of the framework to Singapore
Government Data
• Issues identified in existing Data Eco System
• Recommended tools and best practices for each step
• Launchpad for SG Linked Data implementation
Final Thoughts…
• ROI is not a key metric for Linked Data implementation
• Benefits of moving to Linked Data is intangible and may
not be immediately realizable
• Volume of work is huge compared to traditional
systems

35. We are thankful to Prof Chris Khoo
for his supervision and iDA staff Soy Boon Lim
for providing overview of data.gov.sg and also
for furnishing DGS design documents...

36. Why are we doing this project?
To prescribe a Linked Data migrational framework for
data.gov.sg (DGS) data sets
First hand view of the required migration activities
Issues anticipated at each step
Evaluation & Recommendation on Linked Data tools
To help IDA in realizing - What more can be done with existing
data ? A closer look at Government counterparts – UK and US !
In totality, iDA can use this report as a guide for the various
aspects related to Linked Data implementation

37. Basic Thought Process of Linked Data
Publishing
• Select data sets that appear apt for Linked
Data
• Identify the data sources for the data sets
• Find out what type of transformations are
needed
• Publish it!

38. iDA Singapore launched Data.gov.sg portal and mGov@SG public services during June 2011
Data.gov.sg provides 5000+ public data sets from 50 government agencies
Purpose: Building applications, research and for creating applications using the data
Data.Gov.Sg