yingjie hu, phd student space and time knowledge organization lab department of geography, ucsb ...
TRANSCRIPT
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ARCGIS ONLINE AS LINKED DATA ?
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TEAM
Yingjie Hu, PhD student Space and Time Knowledge Organization Lab
Department of Geography, UCSBSummer intern, APL
Sathya PrasadLead and Mentor, APL
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UNDERSTANDING THE SEMANTIC WEB Web 3.0, Web of Data
W3C Standard
Sir Tim Berners-Lee
Currently, we are in Web 2.0
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WEB 2.0 V.S. WEB 3.0
Web 2.0 Web 3.0
Key elements Documents Data
Connections Hyperlinks among documents
Links among data
Data Consumers Humans Humans and machines
Data Organization
Customized ways RDF
Data Publication Customized ways Linked Data
Data Retrieval Customized APIs SPARQL queries
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UNDERSTANDING THE SEMANTIC WEB
Resource Description Framework
(RDF)
Ontologies
Data Organization Data Publishing
Linked Data principles:1. URI2. Http URI3. Self-descriptive4. External links
Data Retrieval
SPARQL query languageOriginal Data
A dataset on the Semantic Web
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UNDERSTANDING THE SEMANTIC WEB
Dataset A
Dataset B Dataset C
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EXISTING LINKED DATASETS
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PROJECT
Publish a sample of ArcGIS Online metadata following the principles of the Semantic Web.
Explore the new capabilities enabled by the semantically structured data.
Explore the functionalities enabled by GeoSPARQL, OGC’s standard for geospatial data on the Semantic Web.
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DATA IN ARCGIS ONLINE
ArcGIS Online is a GIS store A large number of items A variety of themes (tags) A rich amount of metadata for each item A lot of users from different backgrounds
Data access via REST API
REST APIData
consumerData
Request
Web app
Mobile app
Desktop app
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A LINKED DATA PORTAL FOR ARCGIS ONLINE
RDF Converter
SPARQLendpoint
REST APIData
consumerData
Request
SPARQLquery
data
Web app
Mobile app
Desktop app
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METHODOLOGY
1. Define ontologies (schema)
2. Mine items from ArcGIS Online (around 45,000 items)
3. Convert metadata of the items into RDF
4. Publish RDF data on a SPARQL endpoint
5. Use both SPARQL and GeoSPARQL to query
6. Build a prototype to consume the published data
Step 1, 2, 3 Step 4 Step 5
Prototype Data consumer
Step 6
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ONTOLOGIES
Class level perspective
arcgis: Item
arcgis:Item-Type arcgis: typearcgis: isTypeOf
arcgis: titlexsd:stringarcgis: User
arcgis: owner
arcgis: isOwnerOf
arcgis: created
xsd:dateTime arcgis: baseMap
xsd:…
arcg
is: …
arcgis: operationalLayer
arcgis: username xsd:string
arcgis: fullName xsd:string
xsd:dateTime
arcgis: created
arcgis: Group
arcg
is: h
asIte
m
arcg
is: i
sIte
mOf
arcgis:
groupUser
arcgis: isUserO
f
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ONTOLOGIES Entity level perspective
54ea730c3e3d4144b3ff45fc9512e3c5
arcgis:Web-Maparcgis: type
arcgis: titl
e
“Mountain Fire”
2013-07-18T06:23:06
arcg
is: cre
ated
arcgis: owner
arcgis: isOwnerOf
BSandigo
arc
gis
: base
Map
Topographic
arcgis:Map-Service
arcgis: type
arcgis: operationalLayer
Fire perimeter
arcgis: username “caldelmapas”
arcgis: fullName“Bosco Sandigo”
2012-06-24T06:18:12
arcgis: created
arcgis:Feature-Service
arcgis: type
arcgis:Web-App
arcgis: type
arcgis: owner
arcgis: isOw
nerOf
62487722f0104abe94859e5089c2a947
arcg
is: …
“…”
Esri Maps
arcg
is: h
asIte
m
arcg
is: i
sIte
mOf
arcgis:
groupUser
arcgis: isUserO
f
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DATA CONVERSION
REST API
Ontologies (schema)
RDFConverter
RDF data
JSON
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SPARQL ENDPOINT
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DEMO
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DEMO: BASIC SEARCH
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DEMO: VALIDATION
Result from REST API
Result from SPARQL endpoint
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DEMO: VALIDATION
Show <Web maps>
contains <“San Diego”>
AND <“County”>
NOT <“Agricultural”>
owned by <“onafetsid”>
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DEMO: NEW QUERIES
Summary queries:
Show <# of Web maps>
Created by <ArcGIS Online User>
Between <7-1-2013> and <7-15-2013>
Contains <at least 1 Feature Service>
<at least 1 Map service>
Order by <# of Web maps Desc>
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DEMO: NEW QUERIES
Link-tracking queries
DataNode 1
DataNode 2
DataNode 3
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DEMO: NEW QUERIES
Link-tracking queries
Web maps
avgRating > 3
Group
Web mapsHas no ratings
Num of view >10,000
Group Owner
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DEMO: KNOWLEDGE DISCOVERY Scenario 1: Basemap updating
Find out <users>
whose <web maps>
contains <World topology> as <BaseMap>
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DEMO: KNOWLEDGE DISCOVERY Scenario 2: Most popular baseMap
Find out <top 10 baseMap>
which have been used <Most frequently>
rank by <frequency>
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DEMO: KNOWLEDGE DISCOVERY Scenario 3: Analyze operational layers
Find out <Web maps>
which contains <Topology map> as <Basemap>
which contains <at least one “population” layer>
which contains <at least one “disaster” layer>
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DEMO: KNOWLEDGE DISCOVERY
Scenario 4: Find out inactive users
Find out <users>
who <haven’t made any action (create or modify) >
in <one month>
who do not have <a profile image>
who do not have <a self-description>
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USAGE SCENARIO: INTERNAL PORTAL
ArcGIS Linked Data portal
ArcGIS Online
Sales & Marketing
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USAGE SCENARIO: EXTERNAL PORTAL & API
ArcGIS Linked Data portal
ArcGIS Online Apps
Custom Web and Mobile apps
Desktop app
Users
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USAGE SCENARIO: FEDERATION
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USAGE SCENARIO: FEDERATION
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USAGE SCENARIO: FEDERATION
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USAGE SCENARIO: SEMANTIC WEB Linking Existing Datasets on the Semantic Web
U.S. Census
LinkedGeoData
GeoWordnet
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VISION
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FUTURE WORK
A friendly UI for customized SPARQL queries
Hierarchy and automatic reasoning
Language and translation
More process automation
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THANK YOU
http://esriurl.com/linkeddata