Kyung-Soo Kim, Jae-Song Lee, Seung Young Cho, Sang-Hoon Lee, Eunmi Chang National Geographic Information Institute Ziinconsulting Inc.

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*Introduction - Web portal search : Semantic web - Semantic web: Geospatial Semantic web *Previous cases for Geospatial Semantic web *Conversion tool development *Test and Result *Application Scenario of conversion tool *Conclusion

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1. Current web • Web material consists of natural language (atypical format), which is

understood by human not by computer 2. Semantic Web

• Computer can understand the contents of web materials 3. The Reason why we build web environment for Semantic web ?

Get More precise information Search Enhance Information building and Processing Next Generation web will not allow non-web standards, no exception

Current web: Only human understand

Semantic web : Information can be Understood, archived by computer By RDF standard and SPAQLE etc.

Web vise versa Semantic Web

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geospatial Query-> keyword’s coordinates are inferred… Busan Haewoondae -> nearest hotel lists are shown

1. Semantic Search To perform accurate search by querying not only about key word, but by inferring/using knowledge considering semantic (meaning)

Semantic Web Search

• Natural language

• Visual expression

• Information tagging

• Semantic net • Rules and

logics • Probability and

Statistics

Semantic Search Keyword Search

Public Data Services State data circulation/public by applying RDF format of standard sematnic web

• US (Data.gov), Australia (Data.gov.au): National data from the federal level GIS-based Semantic Web Services

• UK (Data.gov.uk): Spatial information and actively participation in national data fusion by semantic web services OS

• LOD (Linking Open Data): Wikipedia, private sector, such as public services data (semantic web building knowledge networks around the world - more than 4.2 billion

LOD Construction of the project data / connection status

Map-based Semantic Web Services in US(Data.gov) and UK(Data.gov)

Previous cases for Geospatial Semantic web

GeoSPARQL is a standard for representation and querying of geospatially linked data for the Semantic Web from the Open Geospatial Consortium (OGC).[1] The definition of a small ontology based on well-understood OGC standards is intended to provide a standardized interchange basis for geospatial RDF data which can support both quantitative and qualitative spatial reasoning and querying

Converter and Standards

Converter and Standards

CSV2RDF converter

SHP2RDF converter

NGI2RDF Converter

2011 basic ontology specification extended to the digital map layers

Schema structure analysis consisting of spatial information exchange standard language GML

3.2.1 Polygon, Line, Point

triple of Web standard language RDF (Subject, Predicate, Object) Schema analysis

Class schema modeling properties on GML using ontology modeling tool protégé

Extracted by parsing according to GML RDF Class schema modeling

Ontology model extends to the digital map based on standard ontology developed in 2011

Depending on spatial Information (Geometry) and (Purpose), feature schema (OWL, UML)

designed

Parsed GML

UML model, an ontology schema design

NGI2RDF Converter

Digital map spatial ontology model (RDF/OWL Schema, Protege)

NGI2RDF Converter

NGI2RDF Architecture configurations

NGI2RDF Digital Maps(GML) parsing designed through mapping RDF file conversion (open

source Open source libraries applied) according to ontology model RDF Schema

< Overall architecture configuration >

NGI2RDF o Conversion program

RDF Mashups Web GIS services

(NGI2RDF)

NGI2RDF Converter

Major conversion function

<Development environment >

• Operating system : Win32

• Memory : 4GB

• Development language : Java

1.7 SDK

• VM memory : 1.2GB applied

Conversion function, GML object in process tap 1)data extraction, 2) mapping between

extracted data and RDF schema, 3) Digital map RDF instantiation process performed

RDF files can be created by selecting one of the RDF files in GML multiple layers list

Even if particular features of Digital Maps are updated relevant RDF to select and update is

possible (RDF-based configuration of the object)

Function to see results - Hierarchy tree and the details of each property can seen through

result tab of converted digital map RDF file

NGI2RDF

NGI2RDF Converter

Seocho, Kangnam-member demonstration area.

Kangnam / Seocho main layers of the digital map RDF applied for verification of developed

converter format

1/5,000 digital map targeted on 22 sheets, digital topographic map 2.0 code system based

on digital map and classification applied

NGI2RDF Demonstration Application

NGI2RDF Converter

< Levee facilities (Line) RDF mash-up> < Oil Storage (Polygon) RDF mash-up>

NGI2RDF Demonstration Application

SPARQL query, features/geometry integrity comparison of converted RDF digital map through

mash-up service based on Open-API

NGI2RDF Converter

1: 1,000 topo Maps in Cities 1: 2,500 topo Map in rural areas

건물 RDF 시나리오 작성 : 건축물정보시스템 적법성 검토시스템 업무흐름도와 연계된 GIS시스템 분석

Facility Management

System

Building RDF scenario : architecture information compliance

system : Land Information System

Parking Lot Management

System

Urban Planning

Information System

Korean Land information

System

Law of Architecture (3)

regulations (11)

Articles (614)

Rules (32) Reference rules

Constraint rules

Structure standard

Local assembly rules

Construction Articles

Urban Planning Articles

Parking Lot Regulations

1. General

2. Construction, building

3. Maintenance

4. Parcels and Roads

5. Structure and Material

6. Districts Limit

7. Equipment

8. Special Districts

9. Auxiliary

Evacuation & fire

readiness

Equipment standard

Design standard

Maintenance Standard

Internet Search : I am looking for restaurant with sufficient parking lot near Yangjae station in the street Kangnam Street. -> location, direction, we are moving southward.

Just use portal 1. Key word -> key word overlap 2. Knowledge search ->need to wait until somebody answer to my question

Ontology RDF information Scenario 1. Road layer -> building layer->

parking lot layer Overlap 2. RDF format query-> several options for the restaurant

- Table between building ID and Road-based Address

- Buffer function works - Needs to define condition “parking

lot”

Building layer RDF Model (including ontology)

New Scenario

TO-BE AS_IS

Assumption

Case 1

Building RDF scenario

Genre de Vie: consumption space

Internet search: Toilet opened in the Yangjaecheon vicinity information about Seoul public toilet Designated as one of information that is frequently requested in the 120 Dasan Call Center 120

Case 2

While using current portal 1. Key word search -> semantic search (Nested keywords) 2. Knowledge search -> in case when not already asked by someone, wait until new answer is added and acquire information 3. Yangjae park search -> Obtain information by tracking the station through the park information

Ontology RDF information service scenarios 1. Content switch to RDF format will query directly to map DB and this search system can provide detailed information related to the search. 2. Yangjaecheon Street name DB + river DB +building DB (toilets) are joined and coordinate the place that meets the conditions 3. consider the main building and the user location etc.

TO-BE AS_IS

- Street name DB requires Layer - Join Model - Preposition words (context) requires

connection to map query (ex. Near, around, big, from, by, to)

Building layers and

Street name layer

RDF model formulation

(Ontology included)

New

Scenario

Creation Prerequisites

Create buildings RDF scenario Internet search

Internet search: Convenient hospital for the elderly The hospital is located in the 1st floor or has an elevator to ensure convenience Located close from home to ensure high usage frequency

Using current portals 1. Knowledge search -> Information is acquired when a reply is posted after some time 2. Usage of hospital’s homepage -> Information is acquired via each hospital’s homepage after searching for nearby hospitals

Ontology RDF information service scenarios 1. Building (hospital) DB + street name address DB 2. Using information on number of floors and elevators in Building DB contents

AIS Establishing AIS’s

RDF model (including ontology)

New Scenario Creation

TO-BE AS_IS

Preconditions

- Join Model - Elevators have to be

recognized as UFID in AIS.

Ministry of Health and Welfare enforced ‘Clinic Chronic Disease Management System’ from April 1 2012 for patients diagnosed with high blood pressure or diabetes

<Phase division of Seocho-gu’s elderly population>

If the elderly account for over 7% of the population, such region is designated as an aging society area; currently, the percentage of the elderly in Seocho-gu exceeds 8.8%.

- National Statistical Office data (2011)

Create buildings RDF scenario Internet search

Case 3

While the management system of country streams and small streams is dispersed between K-water and National Emergency Management Agency and there is no common system, a person wants to evaluate what kind of influence will installing special beams (after the Four Major Rivers development) have on nearby small streams

Using current portals 1. Using knowledge search: if one searches particular stream and beam, only the information on this stream and the beam will be suggested as text 2. While it is connected to the stream DB center, only information on country stream is provided with no information on small streams 3. In case of searching a stream’s name, the names do not appear on numerical maps of the National Geographic Information Institute and there is hardly any map service

Connecting to required information via numerical map RDF files will provide information of starting and ending points of nearby streams Providing extra information (e.g. cycle paths nearby Four Major Rivers) will allow connecting information on paths that lead to middle and small streams

RDF procedure of DB of middle/

small streams

New Scenario Creation

TO-BE

AS_IS

Preconditions

Creating RDF files of DB files of middle/small stream and country stream DB basing on Small River Maintenance Basic Plan

Create buildings RDF scenario Internet search

Case 1

A person wants to find information related to research of archaeological sites and wetlands located nearby Cheongju Musim River and small streams

Using current portals 1. Using knowledge search : when searching Musim River, the results provide irrelevant text and image information on Musim River 2. . In case of searching a stream’s name, the names do not appear on numerical maps of the National Geographic Information Institute and there is hardly any map service

Connecting to required information via numerical map RDF files will provide information of starting and ending points and center lines of nearby streams Other information can be mashed up (e.g. location info from the Ministry of Environment’s Musim River wetland info center line)

RDF procedure of DB of archaeological

sites and wetlands located nearby streams

New Scenario Creation

TO-BE AS_IS

Preconditions

Other wetland or archaeological DB can be searched via SHP2RDF conversion tool

Create buildings RDF scenario Internet search

Case 2

In policy dimension scenario, required layers are extracted after which connection method with other institutions or related organs is established.

SPACE OF INTEREST:

School building is extracted from national building DB and combined with local population and development materials; medium-and long-term plan materials for to-be-closed schools are made and active alternative means can be taken.

Analysis of closed schools

National schools’ list < receiving from the Ministry of Education and Science; Connecting with education GIS system -> List of schools closed until 2012 and analysis of school age materials-> Proceeding with methods such as analysis deduction of areas with schools likely to close (taking local environment in consideration) Areas with schools likely to close-> contribution to solving social problems by means such as securing land to establish an alternative school

It is difficult to establish a service plan due to the abstract definitions of superclasses and subclasses

based on ontology. Having considered sufficient scenarios, practical service model could be materialized

if required layer conversion and analysis system are done together

Superclass: building Class: building, school- attributes (closed school, operated school), current utilization status Subclass: wall

Things to consider

Ontology model

Semantic web search scenario classified by other layers

Institution Information system DB status Checking possibility of RDF conversion and assessing connection method

Ministry of Education and Science

Education GIS Information System

Every-year actualizations, oracle DB, GIS data based on schools’ locations

Joint securing of Shp file Conversion via GIS2RDF program

Semantic web search scenario classified by other layers CASE 1

Semantic web search scenario classified by other layers

CASE 2. “Bridge”

News words and related images and

explanations

Yangjae Bridge biking event Yangjae Stream walking event

Distinguished name

Location data Roads belonging to

Yangjae Bridge

Road UFID Search: Yangjae

Bridge

Yangjae Bridge

Unique identifier Distinguished name

Location data Various attributes

RDF-converted numerical map

Yangjae Bridge

Yangjae Bridge

Web words

Individual events related to incidents and accidents

Distinguished name Seocho-gu

Bridge management company

Bridge UFID

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Semantic web search scenario classified by other layers

CASE 2. “Bridge”

Bridge

HMS (highway management system) manager’s standpoint

Recognition: necessity of recognition as part of Seoul’s local roads: Checking who manages a road and to what road it belongs Recognition as part of statistics regarding recent construction management status Construction information demand: checking to what administrative area a bridge name belongs

Water resources and stream manager’s standpoint

Transport and logistics manager’s standpoint

Recognition: necessity of recognition of several bridges located at Yangjae Stream as one: Managing accessibility of water areas nearby Yangjae Stream When one wants to assess the possibility of locating water quality sensors in water quality management dimension during rainy season, Necessity of connecting with data such as water flow data to understand nearby environment

Recognition: Cars weighing how many tons are prohibited from entering Yangjae Bridge? if transport CCTV system is installed in the neighborhood of Yangjae Bridge, will the residents be aware of the location? We should reduce the gap of delivering information and status related to specific locations of Yangjae Bridge

Search scenario: searching only in respective systems

Search scenario: acquiring various information via semantic search in web search

TO-BE

AS_IS

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Semantic web search scenario classified by other layers

CASE 2. “Bridge”

Searching Seoul-> Seocho-> Yangjae 1-dong-> Yangjae Bridge on MOLIT’s portal does not offer results

Yangjae Bridge does not come up in search results. Searching for nearby Maehyeon Bridge displays it

Is there a need to connect all the systems? We should allow customers to find required information by themselves via web search

Semantic map’s concept means that if one types “bridge’s name” in a typical search engine, the map and related details as well as map data are displayed

Meanings of NGII2RDF

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V- world

Ministry of Construction and Transportation

Land Portal

NGII

Koreans prefer

Naver, Daum, Google and

T-map

Building information AIS enhancement

Real estate

enhancement

Ministry of Land, Transport and

Maritime Affairs

School facilities GIS

Ministry of

Education, Science and Technology

Ministry of Construction

and Transportation

River Management Information

System Ministry of

Construction and Transportation

National Geographic Information Institute should not create ONE OF sites, but introduce a system offering format conversion required for data search and including maps in searches

RIMGIS2RDF HMS2RDF AIS2RDF EDUGIS2RDF

VWORLD2RDF NGII2RDF Take the info. Develop more

service

Meaning of developing National Geographic Information Institute’s

NGII2RDF SHP2RDF

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Modelling results’

visualization

Added to V- WORLD platform

Disaster prevention

experts system

modelling

National Geographic Information Institute has to provide base and lattice data that could contribute to solving problems via analysis by creating standards of lattice systems that would offer more efficient and simple searches. RDF procedures of lattice data has to be expanded in phases.

VWORLD2RDF NGII2RDF

Meaning of developing National Geographic Information Institute’s

NGII2RDF SHP2RDF

GRID2RDF

SHP2RDF distribution

1st stage 2nd stage 3rd stage

Spatial data utilizing increased

by expanding spatial data

industry consulting utilization market

Enhancement of analysis base for private sector

Conclusions

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*NGII developed a conversion tool from NGII format to RDF format for 1: 5000 topographic maps

*We tested the conversion tools for two districts.

*We suggested the Application Scenario on buildings and rivers after the tools applied for the smart search on the internet

Conclusions