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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
H
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
H
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
H
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
H
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
H
*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