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 Yingjie Hu, PhD student  Space and Time Knowledge Organization Lab  Department of Geography, UCSB  Summer intern, APL  Sathya Prasad  Lead and.

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Presentation on theme: " Yingjie Hu, PhD student  Space and Time Knowledge Organization Lab  Department of Geography, UCSB  Summer intern, APL  Sathya Prasad  Lead and."— Presentation transcript:

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2  Yingjie Hu, PhD student  Space and Time Knowledge Organization Lab  Department of Geography, UCSB  Summer intern, APL  Sathya Prasad  Lead and Mentor, APL

3  Web 3.0, Web of Data  W3C Standard  Sir Tim Berners-Lee  Currently, we are in Web 2.0

4 Web 2.0Web 3.0 Key elementsDocumentsData ConnectionsHyperlinks among documents Links among data Data ConsumersHumansHumans and machines Data OrganizationCustomized waysRDF Data PublicationCustomized waysLinked Data Data RetrievalCustomized APIsSPARQL queries

5 Resource Description Framework (RDF) Ontologies Data OrganizationData Publishing Linked Data principles: 1.URI 2.Http URI 3.Self-descriptive 4.External links Data Retrieval SPARQL query language Original Data A dataset on the Semantic Web

6 Dataset A Dataset BDataset C

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8  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.

9  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 API Data consumer Data Request Web app Mobile app Desktop app

10 RDF Converter SPARQL endpoint REST API Data consumer Data Request SPARQL query data Web app Mobile app Desktop app

11 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

12  Class level perspective arcgis: Item arcgis:Item-Type arcgis: type arcgis: isTypeOf arcgis: title xsd:string arcgis: User arcgis: owner arcgis: isOwnerOf arcgis: created xsd:dateTime arcgis: baseMap xsd:… arcgis: … arcgis: operationalLayer arcgis: username xsd:string arcgis: fullName xsd:string xsd:dateTime arcgis: created arcgis: Group arcgis: hasItem arcgis: isItemOf arcgis: groupUser arcgis: isUserOf

13  Entity level perspective 54ea730c3e3d4144b3ff45fc9512e3c5 arcgis:Web-Map arcgis: type arcgis: title “Mountain Fire” 2013-07-18T06:23:06 arcgis: created arcgis: owner arcgis: isOwnerOf BSandigo arcgis: baseMap 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: isOwnerOf 62487722f0104abe94859e5089c2a947 arcgis: … “…” Esri Maps arcgis: hasItem arcgis: isItemOf arcgis: groupUser arcgis: isUserOf

14 REST API Ontologies (schema) RDF Converter RDF data JSON

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18 Result from REST API Result from SPARQL endpoint

19 Show contains AND NOT owned by

20  Summary queries: Show Created by Between and Contains Order by

21  Link-tracking queries Data Node 1 Data Node 2 Data Node 3

22  Link-tracking queries Web maps avgRating > 3 Group Web maps Has no ratings Num of view >10,000 Group Owner

23  Scenario 1: Basemap updating  Find out whose contains as

24  Scenario 2: Most popular baseMap  Find out which have been used rank by

25  Scenario 3: Analyze operational layers  Find out which contains as which contains

26  Scenario 4: Find out inactive users  Find out who in who do not have

27 ArcGIS Linked Data portal ArcGIS Online Sales & Marketing

28 ArcGIS Linked Data portal ArcGIS Online Apps Custom Web and Mobile apps Desktop app Users

29 Portal

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32 Linking Existing Datasets on the Semantic Web U.S. Census Linked GeoData Geo Wordnet

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34  A friendly UI for customized SPARQL queries  Hierarchy and automatic reasoning  Language and translation  More process automation

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