SlideShare a Scribd company logo
1 of 27
Download to read offline
Transforming Your Data with
GraphDB: GraphDB Fundamentals
Live Webinar,
January 2018
Outline
o RDF and RDFS
o SPARQL Overview
o Ontology Overview
o GraphDB Overview
o GraphDB Workbench Demo
o Q&A
RDF
What? Resource Description Framework (RDF) is graph
data model that
o Formally describes the semantics, or meaning of information
o Represents metadata, I.e data about data
How? RDF data model consists of triples
o That represents links (or edges) on an RDF graph
o Where the structure of each triples is Subject, Predicate, Object
Example triples:
obr:fred br:hasSpouse br:Wilma.
obr:fred br:hasAge 25.
Where: br refers to the namespace <http://bedrock> so that br:Fred expands to
<http://bedrock/Fred> as a Universal Resource Identifier (URI)
RDF Use Cases
o Internal or public platform for data and meta-data publishing
o Use case: A big media or scientific publisher needs to expose all internal information assets classified
according multiple taxonomies;
o Content enrichment and retrieval based on deep data
o Use case: A big enterprise organization has tons of knowledge locked into textual documents
describing events and entities with complex contextual information
o Integration of deep and diverse data
o Use case: A big enterprise with a complex knowledge driven business needs to integrate information
from multiple data sources
Sample
RDF data
RDFS
o What? RDF schema (RDFS)
o Adds concepts such as Resource, Literal, Class and Datatype
o Represents metadata, i.e data about data. Adds relationships such as subClassOf, subPropertyOf,
domain and range
o Provides the means to Define
o Classes and properties
o Hierarchies of classes and properties
Includes rules to infer new statements
Apply RDFS to Infer New Triples
Outline
o RDF and RDFS
o SPARQL Overview
o Ontology Overview
o GraphDB Overview
o GraphDB Workbench Demo
o Q&A
o SPARQL is a SQL-like query language for
RDF graph data with the following query types:
o SELECT returns tabular results
o CONSTRUCT creates a new RDF graph based on query results
o ASK returns ‘yes’ if the query has a solution, otherwise ‘no’
o DESCRIBE returns RDF graph data about a resource; useful when the query client
does not know the structure of the RDF data in the data source
o INSERT inserts triples into a graph
o DELETE deletes triples from a graph.
What is SPARQL?
Using SPARQL to Insert Triples
o To create an RDF graph, perform these steps:
o Define prefixes to URIs with the PREFIX keyword
o Use INSERT DATA to signify you want to insert statements. Write the subject-predicate-object
statements (triples).
o Execute this query.
PREFIX br: <http://bedrock/>
INSERT DATA {
br:fred br:hasSpouse br:wilma .
br:fred br:hasChild br:pebbles .
br:wilma br:hasChild br:pebbles .
br:pebbles br:hasSpouse br:bamm-bamm ;
br:hasChild br:roxy, br:chip .
}
Using SPARQL to Select Triples
o To access the RDF graph you just created, perform these steps:
o Define prefixes to URIs with the PREFIX keyword.
o Use SELECT to signify you want to select certain information, and WHERE to signify your conditions,
restrictions and filters.
o Execute this query.
PREFIX br: <http://bedrock/>
SELECT ?subject ?predicate ?object
WHERE {?subject ?predicate ?object}
Subject Predicate Object
br:fred br:hasChild br:pebbles
br:pebbles br:hasChild br:roxy
br:pebbles br:hasChild br:chip
br:wilma br:hasChild br:pebbles
PREFIX br: <http://bedrock/>
SELECT ?subject ?predicate ?object
WHERE {?subject ?predicate ?object}
Subject Predicate Object
br:fred br:hasChild br:pebbles
br:pebbles br:hasChild br:roxy
br:pebbles br:hasChild br:chip
br:wilma br:hasChild br:pebbles
Using SPARQL to Find Fred’s Grandchildren
o To find Fred’s grandchildren, first find out if Fred has any grandchildren:
o Define prefixes to URIs with the PREFIX keyword
o Use ASK to discover whether Fred has a grandchild, and WHERE to signify your conditions.
YES
Using SPARQL to Find Fred’s Grandchildren
Now that we know he has at least one grandchild, perform these steps to
find the grandchild(ren):
oDefine prefixes to URIs with the PREFIX keyword
oUse SELECT to signify you want to select a grandchild, and WHERE to signify your conditions.
PREFIX br: <http://bedrock/>
SELECT ?grandChild
WHERE {
br:fred br:hasChild ?child .
?child br:hasChild ?grandChild .
}
grandChild
1. br:roxy
2. br:chip
PREFIX br: <http://bedrock/>
SELECT ?grandChild
WHERE {
br:fred br:hasChild ?child .
?child br:hasChild ?grandChild .
}
grandChild
1. br:roxy
2. br:chip
Outline
o RDF and RDFS
o SPARQL Overview
o Ontology Overview
o GraphDB Overview
o GraphDB Workbench Demo
o Q&A
What is Ontology
An ontology is a formal specification that provides sharable and
reusable knowledge representation.
Examples of formal specifications include:
oTaxonomies
oVocabularies
oThesauri
oTopic Maps
oLogical Models
What is in an Ontology?
An ontology specification includes descriptions of
oConcepts and properties in a domain
oRelationships between concepts
oConstraints on how the relationships can be used
oIndividuals as members of concepts
The Benefits of an Ontology
Ontologies provide:
oA common understanding of information
oExplicit domain assumptions
These provisions are valuable because ontologies:
oSupport data integration for analytics
oApply domain knowledge to data
oSupport interoperation of applications
oEnable model-driven applications
oReduce the time and cost of application development
oImprove data quality, i.e., metadata and provenance
Outline
o RDF and RDFS
o SPARQL Overview
o Ontology Overview
o GraphDB Overview
o GraphDB Workbench Demo
o Q&A
What is GraphDB?
Enterprise ready Semantic Graph Database,
compliant with W3C Standards
GraphDB™ Editions
o GraphDB™ Free
o GraphDB™ Standard
o GraphDB™ Cloud
o GraphDB™ Enterprise
#21
Outline
o RDF and RDFS
o SPARQL Overview
o Ontology Overview
o GraphDB Overview
o GraphDB Workbench Demo
o Q&A
DEMO
DEMO
Install GraphDB
Load Data
oUsing GraphDB Workbench import page
oUsing OntoRefine
Query Data
oSPARQL Ask
oSPARQL Select
oSPARQL Construct
Query Monitoring
DEMO
o Search DATA
o GraphDB Workbench Autocomplete
o GraphDB Connectors – Lucene, Solr,
o ElasticSearch
o Visualize DATA
o Visualize Class Hierarchy
o GraphDB Default Visual Graph
o GraphDB Custom Visual Graphs
Support and FAQ’s
graphDB-support@ontotext.com
Additional resources:
Ontotext:
Community Forum and Evaluation Support: http://stackoverflow.com/questions/tagged/graphdb
GraphDB Website and Documentation: http://graphdb.ontotext.com
Whitepapers, Fundamentals: http://ontotext.com/knowledge-hub/fundamentals/
SPARQL, OWL, and RDF:
RDF: http://www.w3.org/TR/rdf11-concepts/
RDFS: http://www.w3.org/TR/rdf-schema/
SPARQL Overview: http://www.w3.org/TR/sparql11-overview/
SPARQL Query: http://www.w3.org/TR/sparql11-query/
SPARQL Update: http://www.w3.org/TR/sparql11-update
Desislava Hristova, Senior Software Engineer
Get your GraphDB Today:
http://ontotext.com/products/graphdb/
FactForge: Hub for open data and news about People and Organizations
http://factforge.net/
Experience the technology with NOW: Semantic News Portal
http://now.ontotext.com
Thank you
for your attention!

More Related Content

What's hot

Building Knowledge Graphs in 10 steps
Building Knowledge Graphs in 10 stepsBuilding Knowledge Graphs in 10 steps
Building Knowledge Graphs in 10 stepsOntotext
 
First Steps in Semantic Data Modelling and Search & Analytics in the Cloud
First Steps in Semantic Data Modelling and Search & Analytics in the CloudFirst Steps in Semantic Data Modelling and Search & Analytics in the Cloud
First Steps in Semantic Data Modelling and Search & Analytics in the CloudOntotext
 
Diving in Panama Papers and Open Data to Discover Emerging News
Diving in Panama Papers and Open Data to Discover Emerging NewsDiving in Panama Papers and Open Data to Discover Emerging News
Diving in Panama Papers and Open Data to Discover Emerging NewsOntotext
 
Gain Super Powers in Data Science: Relationship Discovery Across Public Data
Gain Super Powers in Data Science: Relationship Discovery Across Public DataGain Super Powers in Data Science: Relationship Discovery Across Public Data
Gain Super Powers in Data Science: Relationship Discovery Across Public DataOntotext
 
Choosing the Right Graph Database to Succeed in Your Project
Choosing the Right Graph Database to Succeed in Your ProjectChoosing the Right Graph Database to Succeed in Your Project
Choosing the Right Graph Database to Succeed in Your ProjectOntotext
 
How to Reveal Hidden Relationships in Data and Risk Analytics
How to Reveal Hidden Relationships in Data and Risk AnalyticsHow to Reveal Hidden Relationships in Data and Risk Analytics
How to Reveal Hidden Relationships in Data and Risk AnalyticsOntotext
 
Enterprise knowledge graphs
Enterprise knowledge graphsEnterprise knowledge graphs
Enterprise knowledge graphsSören Auer
 
Linking Open, Big Data Using Semantic Web Technologies - An Introduction
Linking Open, Big Data Using Semantic Web Technologies - An IntroductionLinking Open, Big Data Using Semantic Web Technologies - An Introduction
Linking Open, Big Data Using Semantic Web Technologies - An IntroductionRonald Ashri
 
LDOW2015 Position Talk and Discussion
LDOW2015 Position Talk and DiscussionLDOW2015 Position Talk and Discussion
LDOW2015 Position Talk and DiscussionSören Auer
 
Linked Data Experiences at Springer Nature
Linked Data Experiences at Springer NatureLinked Data Experiences at Springer Nature
Linked Data Experiences at Springer NatureMichele Pasin
 
Using the Semantic Web Stack to Make Big Data Smarter
Using the Semantic Web Stack to Make  Big Data SmarterUsing the Semantic Web Stack to Make  Big Data Smarter
Using the Semantic Web Stack to Make Big Data SmarterMatheus Mota
 
ROI in Linking Content to CRM by Applying the Linked Data Stack
ROI in Linking Content to CRM by Applying the Linked Data StackROI in Linking Content to CRM by Applying the Linked Data Stack
ROI in Linking Content to CRM by Applying the Linked Data StackMartin Voigt
 
Supporting GDPR Compliance through effectively governing Data Lineage and Dat...
Supporting GDPR Compliance through effectively governing Data Lineage and Dat...Supporting GDPR Compliance through effectively governing Data Lineage and Dat...
Supporting GDPR Compliance through effectively governing Data Lineage and Dat...Connected Data World
 
Nicoletta Fornara and Fabio Marfia | Modeling and Enforcing Access Control Ob...
Nicoletta Fornara and Fabio Marfia | Modeling and Enforcing Access Control Ob...Nicoletta Fornara and Fabio Marfia | Modeling and Enforcing Access Control Ob...
Nicoletta Fornara and Fabio Marfia | Modeling and Enforcing Access Control Ob...semanticsconference
 
Explicit Semantics in Graph DBs Driving Digital Transformation With Neo4j
Explicit Semantics in Graph DBs Driving Digital Transformation With Neo4jExplicit Semantics in Graph DBs Driving Digital Transformation With Neo4j
Explicit Semantics in Graph DBs Driving Digital Transformation With Neo4jConnected Data World
 
Smart Data Applications powered by the Wikidata Knowledge Graph
Smart Data Applications powered by the Wikidata Knowledge GraphSmart Data Applications powered by the Wikidata Knowledge Graph
Smart Data Applications powered by the Wikidata Knowledge GraphPeter Haase
 
Analytics and Access to the UK web archive
Analytics and Access to the UK web archiveAnalytics and Access to the UK web archive
Analytics and Access to the UK web archiveLewis Crawford
 
Efficient Practices for Large Scale Text Mining Process
Efficient Practices for Large Scale Text Mining ProcessEfficient Practices for Large Scale Text Mining Process
Efficient Practices for Large Scale Text Mining ProcessOntotext
 

What's hot (20)

Building Knowledge Graphs in 10 steps
Building Knowledge Graphs in 10 stepsBuilding Knowledge Graphs in 10 steps
Building Knowledge Graphs in 10 steps
 
First Steps in Semantic Data Modelling and Search & Analytics in the Cloud
First Steps in Semantic Data Modelling and Search & Analytics in the CloudFirst Steps in Semantic Data Modelling and Search & Analytics in the Cloud
First Steps in Semantic Data Modelling and Search & Analytics in the Cloud
 
Diving in Panama Papers and Open Data to Discover Emerging News
Diving in Panama Papers and Open Data to Discover Emerging NewsDiving in Panama Papers and Open Data to Discover Emerging News
Diving in Panama Papers and Open Data to Discover Emerging News
 
Gain Super Powers in Data Science: Relationship Discovery Across Public Data
Gain Super Powers in Data Science: Relationship Discovery Across Public DataGain Super Powers in Data Science: Relationship Discovery Across Public Data
Gain Super Powers in Data Science: Relationship Discovery Across Public Data
 
Choosing the Right Graph Database to Succeed in Your Project
Choosing the Right Graph Database to Succeed in Your ProjectChoosing the Right Graph Database to Succeed in Your Project
Choosing the Right Graph Database to Succeed in Your Project
 
How to Reveal Hidden Relationships in Data and Risk Analytics
How to Reveal Hidden Relationships in Data and Risk AnalyticsHow to Reveal Hidden Relationships in Data and Risk Analytics
How to Reveal Hidden Relationships in Data and Risk Analytics
 
Enterprise knowledge graphs
Enterprise knowledge graphsEnterprise knowledge graphs
Enterprise knowledge graphs
 
Semantic web an overview and projects
Semantic web   an  overview and projectsSemantic web   an  overview and projects
Semantic web an overview and projects
 
Linking Open, Big Data Using Semantic Web Technologies - An Introduction
Linking Open, Big Data Using Semantic Web Technologies - An IntroductionLinking Open, Big Data Using Semantic Web Technologies - An Introduction
Linking Open, Big Data Using Semantic Web Technologies - An Introduction
 
LDOW2015 Position Talk and Discussion
LDOW2015 Position Talk and DiscussionLDOW2015 Position Talk and Discussion
LDOW2015 Position Talk and Discussion
 
Linked Data Experiences at Springer Nature
Linked Data Experiences at Springer NatureLinked Data Experiences at Springer Nature
Linked Data Experiences at Springer Nature
 
Using the Semantic Web Stack to Make Big Data Smarter
Using the Semantic Web Stack to Make  Big Data SmarterUsing the Semantic Web Stack to Make  Big Data Smarter
Using the Semantic Web Stack to Make Big Data Smarter
 
ROI in Linking Content to CRM by Applying the Linked Data Stack
ROI in Linking Content to CRM by Applying the Linked Data StackROI in Linking Content to CRM by Applying the Linked Data Stack
ROI in Linking Content to CRM by Applying the Linked Data Stack
 
Supporting GDPR Compliance through effectively governing Data Lineage and Dat...
Supporting GDPR Compliance through effectively governing Data Lineage and Dat...Supporting GDPR Compliance through effectively governing Data Lineage and Dat...
Supporting GDPR Compliance through effectively governing Data Lineage and Dat...
 
Nicoletta Fornara and Fabio Marfia | Modeling and Enforcing Access Control Ob...
Nicoletta Fornara and Fabio Marfia | Modeling and Enforcing Access Control Ob...Nicoletta Fornara and Fabio Marfia | Modeling and Enforcing Access Control Ob...
Nicoletta Fornara and Fabio Marfia | Modeling and Enforcing Access Control Ob...
 
Explicit Semantics in Graph DBs Driving Digital Transformation With Neo4j
Explicit Semantics in Graph DBs Driving Digital Transformation With Neo4jExplicit Semantics in Graph DBs Driving Digital Transformation With Neo4j
Explicit Semantics in Graph DBs Driving Digital Transformation With Neo4j
 
Smart Data Applications powered by the Wikidata Knowledge Graph
Smart Data Applications powered by the Wikidata Knowledge GraphSmart Data Applications powered by the Wikidata Knowledge Graph
Smart Data Applications powered by the Wikidata Knowledge Graph
 
Analytics and Access to the UK web archive
Analytics and Access to the UK web archiveAnalytics and Access to the UK web archive
Analytics and Access to the UK web archive
 
HyperGraphQL
HyperGraphQLHyperGraphQL
HyperGraphQL
 
Efficient Practices for Large Scale Text Mining Process
Efficient Practices for Large Scale Text Mining ProcessEfficient Practices for Large Scale Text Mining Process
Efficient Practices for Large Scale Text Mining Process
 

Similar to GraphDB Fundamentals Webinar: Transforming Data with GraphDB

Semantic web meetup – sparql tutorial
Semantic web meetup – sparql tutorialSemantic web meetup – sparql tutorial
Semantic web meetup – sparql tutorialAdonisDamian
 
Re-using Media on the Web: Media fragment re-mixing and playout
Re-using Media on the Web: Media fragment re-mixing and playoutRe-using Media on the Web: Media fragment re-mixing and playout
Re-using Media on the Web: Media fragment re-mixing and playoutMediaMixerCommunity
 
Introduction of semantic technology for SAS programmers
Introduction of semantic technology for SAS programmersIntroduction of semantic technology for SAS programmers
Introduction of semantic technology for SAS programmersKevin Lee
 
Graph databases & data integration v2
Graph databases & data integration v2Graph databases & data integration v2
Graph databases & data integration v2Dimitris Kontokostas
 
CSHALS 2010 W3C Semanic Web Tutorial
CSHALS 2010 W3C Semanic Web TutorialCSHALS 2010 W3C Semanic Web Tutorial
CSHALS 2010 W3C Semanic Web TutorialLeeFeigenbaum
 
2011 4IZ440 Semantic Web – RDF, SPARQL, and software APIs
2011 4IZ440 Semantic Web – RDF, SPARQL, and software APIs2011 4IZ440 Semantic Web – RDF, SPARQL, and software APIs
2011 4IZ440 Semantic Web – RDF, SPARQL, and software APIsJosef Petrák
 
Sparql a simple knowledge query
Sparql  a simple knowledge querySparql  a simple knowledge query
Sparql a simple knowledge queryStanley Wang
 
The Semantic Web #10 - SPARQL
The Semantic Web #10 - SPARQLThe Semantic Web #10 - SPARQL
The Semantic Web #10 - SPARQLMyungjin Lee
 
Querying the Web of Data
Querying the Web of DataQuerying the Web of Data
Querying the Web of DataRinke Hoekstra
 
Facet: Building Web Pages with SPARQL
Facet: Building Web Pages with SPARQLFacet: Building Web Pages with SPARQL
Facet: Building Web Pages with SPARQLLeigh Dodds
 
Graph databases & data integration - the case of RDF
Graph databases & data integration - the case of RDFGraph databases & data integration - the case of RDF
Graph databases & data integration - the case of RDFDimitris Kontokostas
 
C4l2008charper
C4l2008charperC4l2008charper
C4l2008charpercharper
 
SHACL: Shaping the Big Ball of Data Mud
SHACL: Shaping the Big Ball of Data MudSHACL: Shaping the Big Ball of Data Mud
SHACL: Shaping the Big Ball of Data MudRichard Cyganiak
 
State of the Semantic Web
State of the Semantic WebState of the Semantic Web
State of the Semantic WebIvan Herman
 
A Little SPARQL in your Analytics
A Little SPARQL in your AnalyticsA Little SPARQL in your Analytics
A Little SPARQL in your AnalyticsDr. Neil Brittliff
 

Similar to GraphDB Fundamentals Webinar: Transforming Data with GraphDB (20)

Semantic web meetup – sparql tutorial
Semantic web meetup – sparql tutorialSemantic web meetup – sparql tutorial
Semantic web meetup – sparql tutorial
 
Re-using Media on the Web: Media fragment re-mixing and playout
Re-using Media on the Web: Media fragment re-mixing and playoutRe-using Media on the Web: Media fragment re-mixing and playout
Re-using Media on the Web: Media fragment re-mixing and playout
 
Introduction of semantic technology for SAS programmers
Introduction of semantic technology for SAS programmersIntroduction of semantic technology for SAS programmers
Introduction of semantic technology for SAS programmers
 
Graph databases & data integration v2
Graph databases & data integration v2Graph databases & data integration v2
Graph databases & data integration v2
 
CSHALS 2010 W3C Semanic Web Tutorial
CSHALS 2010 W3C Semanic Web TutorialCSHALS 2010 W3C Semanic Web Tutorial
CSHALS 2010 W3C Semanic Web Tutorial
 
2011 4IZ440 Semantic Web – RDF, SPARQL, and software APIs
2011 4IZ440 Semantic Web – RDF, SPARQL, and software APIs2011 4IZ440 Semantic Web – RDF, SPARQL, and software APIs
2011 4IZ440 Semantic Web – RDF, SPARQL, and software APIs
 
Sparql a simple knowledge query
Sparql  a simple knowledge querySparql  a simple knowledge query
Sparql a simple knowledge query
 
The Semantic Web #10 - SPARQL
The Semantic Web #10 - SPARQLThe Semantic Web #10 - SPARQL
The Semantic Web #10 - SPARQL
 
Querying the Web of Data
Querying the Web of DataQuerying the Web of Data
Querying the Web of Data
 
Facet: Building Web Pages with SPARQL
Facet: Building Web Pages with SPARQLFacet: Building Web Pages with SPARQL
Facet: Building Web Pages with SPARQL
 
Introduction to RDF Data Model
Introduction to RDF Data ModelIntroduction to RDF Data Model
Introduction to RDF Data Model
 
Semantic Web talk TEMPLATE
Semantic Web talk TEMPLATESemantic Web talk TEMPLATE
Semantic Web talk TEMPLATE
 
Graph databases & data integration - the case of RDF
Graph databases & data integration - the case of RDFGraph databases & data integration - the case of RDF
Graph databases & data integration - the case of RDF
 
C4l2008charper
C4l2008charperC4l2008charper
C4l2008charper
 
RDF validation tutorial
RDF validation tutorialRDF validation tutorial
RDF validation tutorial
 
Sparql
SparqlSparql
Sparql
 
Danbri Drupalcon Export
Danbri Drupalcon ExportDanbri Drupalcon Export
Danbri Drupalcon Export
 
SHACL: Shaping the Big Ball of Data Mud
SHACL: Shaping the Big Ball of Data MudSHACL: Shaping the Big Ball of Data Mud
SHACL: Shaping the Big Ball of Data Mud
 
State of the Semantic Web
State of the Semantic WebState of the Semantic Web
State of the Semantic Web
 
A Little SPARQL in your Analytics
A Little SPARQL in your AnalyticsA Little SPARQL in your Analytics
A Little SPARQL in your Analytics
 

More from Ontotext

It Don’t Mean a Thing If It Ain’t Got Semantics
It Don’t Mean a Thing If It Ain’t Got SemanticsIt Don’t Mean a Thing If It Ain’t Got Semantics
It Don’t Mean a Thing If It Ain’t Got SemanticsOntotext
 
[Webinar] GraphDB Fundamentals: Adding Meaning to Your Data
[Webinar] GraphDB Fundamentals: Adding Meaning to Your Data[Webinar] GraphDB Fundamentals: Adding Meaning to Your Data
[Webinar] GraphDB Fundamentals: Adding Meaning to Your DataOntotext
 
Hercule: Journalist Platform to Find Breaking News and Fight Fake Ones
Hercule: Journalist Platform to Find Breaking News and Fight Fake OnesHercule: Journalist Platform to Find Breaking News and Fight Fake Ones
Hercule: Journalist Platform to Find Breaking News and Fight Fake OnesOntotext
 
How to migrate to GraphDB in 10 easy to follow steps
How to migrate to GraphDB in 10 easy to follow steps How to migrate to GraphDB in 10 easy to follow steps
How to migrate to GraphDB in 10 easy to follow steps Ontotext
 
GraphDB Cloud: Enterprise Ready RDF Database on Demand
GraphDB Cloud: Enterprise Ready RDF Database on DemandGraphDB Cloud: Enterprise Ready RDF Database on Demand
GraphDB Cloud: Enterprise Ready RDF Database on DemandOntotext
 
Smarter content with a Dynamic Semantic Publishing Platform
Smarter content with a Dynamic Semantic Publishing PlatformSmarter content with a Dynamic Semantic Publishing Platform
Smarter content with a Dynamic Semantic Publishing PlatformOntotext
 
How is smart data cooked?
How is smart data cooked?How is smart data cooked?
How is smart data cooked?Ontotext
 
The Knowledge Discovery Quest
The Knowledge Discovery Quest The Knowledge Discovery Quest
The Knowledge Discovery Quest Ontotext
 
Best Practices for Large Scale Text Mining Processing
Best Practices for Large Scale Text Mining ProcessingBest Practices for Large Scale Text Mining Processing
Best Practices for Large Scale Text Mining ProcessingOntotext
 
Build Narratives, Connect Artifacts: Linked Open Data for Cultural Heritage
Build Narratives, Connect Artifacts: Linked Open Data for Cultural HeritageBuild Narratives, Connect Artifacts: Linked Open Data for Cultural Heritage
Build Narratives, Connect Artifacts: Linked Open Data for Cultural HeritageOntotext
 
Semantic Data Normalization For Efficient Clinical Trial Research
Semantic Data Normalization For Efficient Clinical Trial ResearchSemantic Data Normalization For Efficient Clinical Trial Research
Semantic Data Normalization For Efficient Clinical Trial ResearchOntotext
 
Gaining Advantage in e-Learning with Semantic Adaptive Technology
Gaining Advantage in e-Learning with Semantic Adaptive TechnologyGaining Advantage in e-Learning with Semantic Adaptive Technology
Gaining Advantage in e-Learning with Semantic Adaptive TechnologyOntotext
 
Cooking up the Semantic Web
Cooking up the Semantic WebCooking up the Semantic Web
Cooking up the Semantic WebOntotext
 
Why Semantics Matter? Adding the semantic edge to your content, right from au...
Why Semantics Matter? Adding the semantic edge to your content,right from au...Why Semantics Matter? Adding the semantic edge to your content,right from au...
Why Semantics Matter? Adding the semantic edge to your content, right from au...Ontotext
 
Adding Semantic Edge to Your Content – From Authoring to Delivery
Adding Semantic Edge to Your Content – From Authoring to DeliveryAdding Semantic Edge to Your Content – From Authoring to Delivery
Adding Semantic Edge to Your Content – From Authoring to DeliveryOntotext
 
Open Data and News Analytics Demo
Open Data and News Analytics DemoOpen Data and News Analytics Demo
Open Data and News Analytics DemoOntotext
 
Boost your data analytics with open data and public news content
Boost your data analytics with open data and public news contentBoost your data analytics with open data and public news content
Boost your data analytics with open data and public news contentOntotext
 

More from Ontotext (17)

It Don’t Mean a Thing If It Ain’t Got Semantics
It Don’t Mean a Thing If It Ain’t Got SemanticsIt Don’t Mean a Thing If It Ain’t Got Semantics
It Don’t Mean a Thing If It Ain’t Got Semantics
 
[Webinar] GraphDB Fundamentals: Adding Meaning to Your Data
[Webinar] GraphDB Fundamentals: Adding Meaning to Your Data[Webinar] GraphDB Fundamentals: Adding Meaning to Your Data
[Webinar] GraphDB Fundamentals: Adding Meaning to Your Data
 
Hercule: Journalist Platform to Find Breaking News and Fight Fake Ones
Hercule: Journalist Platform to Find Breaking News and Fight Fake OnesHercule: Journalist Platform to Find Breaking News and Fight Fake Ones
Hercule: Journalist Platform to Find Breaking News and Fight Fake Ones
 
How to migrate to GraphDB in 10 easy to follow steps
How to migrate to GraphDB in 10 easy to follow steps How to migrate to GraphDB in 10 easy to follow steps
How to migrate to GraphDB in 10 easy to follow steps
 
GraphDB Cloud: Enterprise Ready RDF Database on Demand
GraphDB Cloud: Enterprise Ready RDF Database on DemandGraphDB Cloud: Enterprise Ready RDF Database on Demand
GraphDB Cloud: Enterprise Ready RDF Database on Demand
 
Smarter content with a Dynamic Semantic Publishing Platform
Smarter content with a Dynamic Semantic Publishing PlatformSmarter content with a Dynamic Semantic Publishing Platform
Smarter content with a Dynamic Semantic Publishing Platform
 
How is smart data cooked?
How is smart data cooked?How is smart data cooked?
How is smart data cooked?
 
The Knowledge Discovery Quest
The Knowledge Discovery Quest The Knowledge Discovery Quest
The Knowledge Discovery Quest
 
Best Practices for Large Scale Text Mining Processing
Best Practices for Large Scale Text Mining ProcessingBest Practices for Large Scale Text Mining Processing
Best Practices for Large Scale Text Mining Processing
 
Build Narratives, Connect Artifacts: Linked Open Data for Cultural Heritage
Build Narratives, Connect Artifacts: Linked Open Data for Cultural HeritageBuild Narratives, Connect Artifacts: Linked Open Data for Cultural Heritage
Build Narratives, Connect Artifacts: Linked Open Data for Cultural Heritage
 
Semantic Data Normalization For Efficient Clinical Trial Research
Semantic Data Normalization For Efficient Clinical Trial ResearchSemantic Data Normalization For Efficient Clinical Trial Research
Semantic Data Normalization For Efficient Clinical Trial Research
 
Gaining Advantage in e-Learning with Semantic Adaptive Technology
Gaining Advantage in e-Learning with Semantic Adaptive TechnologyGaining Advantage in e-Learning with Semantic Adaptive Technology
Gaining Advantage in e-Learning with Semantic Adaptive Technology
 
Cooking up the Semantic Web
Cooking up the Semantic WebCooking up the Semantic Web
Cooking up the Semantic Web
 
Why Semantics Matter? Adding the semantic edge to your content, right from au...
Why Semantics Matter? Adding the semantic edge to your content,right from au...Why Semantics Matter? Adding the semantic edge to your content,right from au...
Why Semantics Matter? Adding the semantic edge to your content, right from au...
 
Adding Semantic Edge to Your Content – From Authoring to Delivery
Adding Semantic Edge to Your Content – From Authoring to DeliveryAdding Semantic Edge to Your Content – From Authoring to Delivery
Adding Semantic Edge to Your Content – From Authoring to Delivery
 
Open Data and News Analytics Demo
Open Data and News Analytics DemoOpen Data and News Analytics Demo
Open Data and News Analytics Demo
 
Boost your data analytics with open data and public news content
Boost your data analytics with open data and public news contentBoost your data analytics with open data and public news content
Boost your data analytics with open data and public news content
 

Recently uploaded

Optimizing AI for immediate response in Smart CCTV
Optimizing AI for immediate response in Smart CCTVOptimizing AI for immediate response in Smart CCTV
Optimizing AI for immediate response in Smart CCTVshikhaohhpro
 
The Evolution of Karaoke From Analog to App.pdf
The Evolution of Karaoke From Analog to App.pdfThe Evolution of Karaoke From Analog to App.pdf
The Evolution of Karaoke From Analog to App.pdfPower Karaoke
 
Advancing Engineering with AI through the Next Generation of Strategic Projec...
Advancing Engineering with AI through the Next Generation of Strategic Projec...Advancing Engineering with AI through the Next Generation of Strategic Projec...
Advancing Engineering with AI through the Next Generation of Strategic Projec...OnePlan Solutions
 
What is Binary Language? Computer Number Systems
What is Binary Language?  Computer Number SystemsWhat is Binary Language?  Computer Number Systems
What is Binary Language? Computer Number SystemsJheuzeDellosa
 
Adobe Marketo Engage Deep Dives: Using Webhooks to Transfer Data
Adobe Marketo Engage Deep Dives: Using Webhooks to Transfer DataAdobe Marketo Engage Deep Dives: Using Webhooks to Transfer Data
Adobe Marketo Engage Deep Dives: Using Webhooks to Transfer DataBradBedford3
 
Call Girls in Naraina Delhi 💯Call Us 🔝8264348440🔝
Call Girls in Naraina Delhi 💯Call Us 🔝8264348440🔝Call Girls in Naraina Delhi 💯Call Us 🔝8264348440🔝
Call Girls in Naraina Delhi 💯Call Us 🔝8264348440🔝soniya singh
 
Cloud Management Software Platforms: OpenStack
Cloud Management Software Platforms: OpenStackCloud Management Software Platforms: OpenStack
Cloud Management Software Platforms: OpenStackVICTOR MAESTRE RAMIREZ
 
Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...
Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...
Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...kellynguyen01
 
why an Opensea Clone Script might be your perfect match.pdf
why an Opensea Clone Script might be your perfect match.pdfwhy an Opensea Clone Script might be your perfect match.pdf
why an Opensea Clone Script might be your perfect match.pdfjoe51371421
 
ODSC - Batch to Stream workshop - integration of Apache Spark, Cassandra, Pos...
ODSC - Batch to Stream workshop - integration of Apache Spark, Cassandra, Pos...ODSC - Batch to Stream workshop - integration of Apache Spark, Cassandra, Pos...
ODSC - Batch to Stream workshop - integration of Apache Spark, Cassandra, Pos...Christina Lin
 
5 Signs You Need a Fashion PLM Software.pdf
5 Signs You Need a Fashion PLM Software.pdf5 Signs You Need a Fashion PLM Software.pdf
5 Signs You Need a Fashion PLM Software.pdfWave PLM
 
Russian Call Girls in Karol Bagh Aasnvi ➡️ 8264348440 💋📞 Independent Escort S...
Russian Call Girls in Karol Bagh Aasnvi ➡️ 8264348440 💋📞 Independent Escort S...Russian Call Girls in Karol Bagh Aasnvi ➡️ 8264348440 💋📞 Independent Escort S...
Russian Call Girls in Karol Bagh Aasnvi ➡️ 8264348440 💋📞 Independent Escort S...soniya singh
 
DNT_Corporate presentation know about us
DNT_Corporate presentation know about usDNT_Corporate presentation know about us
DNT_Corporate presentation know about usDynamic Netsoft
 
Building Real-Time Data Pipelines: Stream & Batch Processing workshop Slide
Building Real-Time Data Pipelines: Stream & Batch Processing workshop SlideBuilding Real-Time Data Pipelines: Stream & Batch Processing workshop Slide
Building Real-Time Data Pipelines: Stream & Batch Processing workshop SlideChristina Lin
 
Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
Unveiling the Tech Salsa of LAMs with Janus in Real-Time ApplicationsUnveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
Unveiling the Tech Salsa of LAMs with Janus in Real-Time ApplicationsAlberto González Trastoy
 
The Essentials of Digital Experience Monitoring_ A Comprehensive Guide.pdf
The Essentials of Digital Experience Monitoring_ A Comprehensive Guide.pdfThe Essentials of Digital Experience Monitoring_ A Comprehensive Guide.pdf
The Essentials of Digital Experience Monitoring_ A Comprehensive Guide.pdfkalichargn70th171
 
XpertSolvers: Your Partner in Building Innovative Software Solutions
XpertSolvers: Your Partner in Building Innovative Software SolutionsXpertSolvers: Your Partner in Building Innovative Software Solutions
XpertSolvers: Your Partner in Building Innovative Software SolutionsMehedi Hasan Shohan
 
Building a General PDE Solving Framework with Symbolic-Numeric Scientific Mac...
Building a General PDE Solving Framework with Symbolic-Numeric Scientific Mac...Building a General PDE Solving Framework with Symbolic-Numeric Scientific Mac...
Building a General PDE Solving Framework with Symbolic-Numeric Scientific Mac...stazi3110
 
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...MyIntelliSource, Inc.
 
Salesforce Certified Field Service Consultant
Salesforce Certified Field Service ConsultantSalesforce Certified Field Service Consultant
Salesforce Certified Field Service ConsultantAxelRicardoTrocheRiq
 

Recently uploaded (20)

Optimizing AI for immediate response in Smart CCTV
Optimizing AI for immediate response in Smart CCTVOptimizing AI for immediate response in Smart CCTV
Optimizing AI for immediate response in Smart CCTV
 
The Evolution of Karaoke From Analog to App.pdf
The Evolution of Karaoke From Analog to App.pdfThe Evolution of Karaoke From Analog to App.pdf
The Evolution of Karaoke From Analog to App.pdf
 
Advancing Engineering with AI through the Next Generation of Strategic Projec...
Advancing Engineering with AI through the Next Generation of Strategic Projec...Advancing Engineering with AI through the Next Generation of Strategic Projec...
Advancing Engineering with AI through the Next Generation of Strategic Projec...
 
What is Binary Language? Computer Number Systems
What is Binary Language?  Computer Number SystemsWhat is Binary Language?  Computer Number Systems
What is Binary Language? Computer Number Systems
 
Adobe Marketo Engage Deep Dives: Using Webhooks to Transfer Data
Adobe Marketo Engage Deep Dives: Using Webhooks to Transfer DataAdobe Marketo Engage Deep Dives: Using Webhooks to Transfer Data
Adobe Marketo Engage Deep Dives: Using Webhooks to Transfer Data
 
Call Girls in Naraina Delhi 💯Call Us 🔝8264348440🔝
Call Girls in Naraina Delhi 💯Call Us 🔝8264348440🔝Call Girls in Naraina Delhi 💯Call Us 🔝8264348440🔝
Call Girls in Naraina Delhi 💯Call Us 🔝8264348440🔝
 
Cloud Management Software Platforms: OpenStack
Cloud Management Software Platforms: OpenStackCloud Management Software Platforms: OpenStack
Cloud Management Software Platforms: OpenStack
 
Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...
Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...
Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...
 
why an Opensea Clone Script might be your perfect match.pdf
why an Opensea Clone Script might be your perfect match.pdfwhy an Opensea Clone Script might be your perfect match.pdf
why an Opensea Clone Script might be your perfect match.pdf
 
ODSC - Batch to Stream workshop - integration of Apache Spark, Cassandra, Pos...
ODSC - Batch to Stream workshop - integration of Apache Spark, Cassandra, Pos...ODSC - Batch to Stream workshop - integration of Apache Spark, Cassandra, Pos...
ODSC - Batch to Stream workshop - integration of Apache Spark, Cassandra, Pos...
 
5 Signs You Need a Fashion PLM Software.pdf
5 Signs You Need a Fashion PLM Software.pdf5 Signs You Need a Fashion PLM Software.pdf
5 Signs You Need a Fashion PLM Software.pdf
 
Russian Call Girls in Karol Bagh Aasnvi ➡️ 8264348440 💋📞 Independent Escort S...
Russian Call Girls in Karol Bagh Aasnvi ➡️ 8264348440 💋📞 Independent Escort S...Russian Call Girls in Karol Bagh Aasnvi ➡️ 8264348440 💋📞 Independent Escort S...
Russian Call Girls in Karol Bagh Aasnvi ➡️ 8264348440 💋📞 Independent Escort S...
 
DNT_Corporate presentation know about us
DNT_Corporate presentation know about usDNT_Corporate presentation know about us
DNT_Corporate presentation know about us
 
Building Real-Time Data Pipelines: Stream & Batch Processing workshop Slide
Building Real-Time Data Pipelines: Stream & Batch Processing workshop SlideBuilding Real-Time Data Pipelines: Stream & Batch Processing workshop Slide
Building Real-Time Data Pipelines: Stream & Batch Processing workshop Slide
 
Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
Unveiling the Tech Salsa of LAMs with Janus in Real-Time ApplicationsUnveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
 
The Essentials of Digital Experience Monitoring_ A Comprehensive Guide.pdf
The Essentials of Digital Experience Monitoring_ A Comprehensive Guide.pdfThe Essentials of Digital Experience Monitoring_ A Comprehensive Guide.pdf
The Essentials of Digital Experience Monitoring_ A Comprehensive Guide.pdf
 
XpertSolvers: Your Partner in Building Innovative Software Solutions
XpertSolvers: Your Partner in Building Innovative Software SolutionsXpertSolvers: Your Partner in Building Innovative Software Solutions
XpertSolvers: Your Partner in Building Innovative Software Solutions
 
Building a General PDE Solving Framework with Symbolic-Numeric Scientific Mac...
Building a General PDE Solving Framework with Symbolic-Numeric Scientific Mac...Building a General PDE Solving Framework with Symbolic-Numeric Scientific Mac...
Building a General PDE Solving Framework with Symbolic-Numeric Scientific Mac...
 
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
 
Salesforce Certified Field Service Consultant
Salesforce Certified Field Service ConsultantSalesforce Certified Field Service Consultant
Salesforce Certified Field Service Consultant
 

GraphDB Fundamentals Webinar: Transforming Data with GraphDB

  • 1. Transforming Your Data with GraphDB: GraphDB Fundamentals Live Webinar, January 2018
  • 2.
  • 3. Outline o RDF and RDFS o SPARQL Overview o Ontology Overview o GraphDB Overview o GraphDB Workbench Demo o Q&A
  • 4. RDF What? Resource Description Framework (RDF) is graph data model that o Formally describes the semantics, or meaning of information o Represents metadata, I.e data about data How? RDF data model consists of triples o That represents links (or edges) on an RDF graph o Where the structure of each triples is Subject, Predicate, Object Example triples: obr:fred br:hasSpouse br:Wilma. obr:fred br:hasAge 25. Where: br refers to the namespace <http://bedrock> so that br:Fred expands to <http://bedrock/Fred> as a Universal Resource Identifier (URI)
  • 5. RDF Use Cases o Internal or public platform for data and meta-data publishing o Use case: A big media or scientific publisher needs to expose all internal information assets classified according multiple taxonomies; o Content enrichment and retrieval based on deep data o Use case: A big enterprise organization has tons of knowledge locked into textual documents describing events and entities with complex contextual information o Integration of deep and diverse data o Use case: A big enterprise with a complex knowledge driven business needs to integrate information from multiple data sources
  • 7. RDFS o What? RDF schema (RDFS) o Adds concepts such as Resource, Literal, Class and Datatype o Represents metadata, i.e data about data. Adds relationships such as subClassOf, subPropertyOf, domain and range o Provides the means to Define o Classes and properties o Hierarchies of classes and properties Includes rules to infer new statements
  • 8. Apply RDFS to Infer New Triples
  • 9. Outline o RDF and RDFS o SPARQL Overview o Ontology Overview o GraphDB Overview o GraphDB Workbench Demo o Q&A
  • 10. o SPARQL is a SQL-like query language for RDF graph data with the following query types: o SELECT returns tabular results o CONSTRUCT creates a new RDF graph based on query results o ASK returns ‘yes’ if the query has a solution, otherwise ‘no’ o DESCRIBE returns RDF graph data about a resource; useful when the query client does not know the structure of the RDF data in the data source o INSERT inserts triples into a graph o DELETE deletes triples from a graph. What is SPARQL?
  • 11. Using SPARQL to Insert Triples o To create an RDF graph, perform these steps: o Define prefixes to URIs with the PREFIX keyword o Use INSERT DATA to signify you want to insert statements. Write the subject-predicate-object statements (triples). o Execute this query. PREFIX br: <http://bedrock/> INSERT DATA { br:fred br:hasSpouse br:wilma . br:fred br:hasChild br:pebbles . br:wilma br:hasChild br:pebbles . br:pebbles br:hasSpouse br:bamm-bamm ; br:hasChild br:roxy, br:chip . }
  • 12. Using SPARQL to Select Triples o To access the RDF graph you just created, perform these steps: o Define prefixes to URIs with the PREFIX keyword. o Use SELECT to signify you want to select certain information, and WHERE to signify your conditions, restrictions and filters. o Execute this query. PREFIX br: <http://bedrock/> SELECT ?subject ?predicate ?object WHERE {?subject ?predicate ?object} Subject Predicate Object br:fred br:hasChild br:pebbles br:pebbles br:hasChild br:roxy br:pebbles br:hasChild br:chip br:wilma br:hasChild br:pebbles PREFIX br: <http://bedrock/> SELECT ?subject ?predicate ?object WHERE {?subject ?predicate ?object} Subject Predicate Object br:fred br:hasChild br:pebbles br:pebbles br:hasChild br:roxy br:pebbles br:hasChild br:chip br:wilma br:hasChild br:pebbles
  • 13. Using SPARQL to Find Fred’s Grandchildren o To find Fred’s grandchildren, first find out if Fred has any grandchildren: o Define prefixes to URIs with the PREFIX keyword o Use ASK to discover whether Fred has a grandchild, and WHERE to signify your conditions. YES
  • 14. Using SPARQL to Find Fred’s Grandchildren Now that we know he has at least one grandchild, perform these steps to find the grandchild(ren): oDefine prefixes to URIs with the PREFIX keyword oUse SELECT to signify you want to select a grandchild, and WHERE to signify your conditions. PREFIX br: <http://bedrock/> SELECT ?grandChild WHERE { br:fred br:hasChild ?child . ?child br:hasChild ?grandChild . } grandChild 1. br:roxy 2. br:chip PREFIX br: <http://bedrock/> SELECT ?grandChild WHERE { br:fred br:hasChild ?child . ?child br:hasChild ?grandChild . } grandChild 1. br:roxy 2. br:chip
  • 15. Outline o RDF and RDFS o SPARQL Overview o Ontology Overview o GraphDB Overview o GraphDB Workbench Demo o Q&A
  • 16. What is Ontology An ontology is a formal specification that provides sharable and reusable knowledge representation. Examples of formal specifications include: oTaxonomies oVocabularies oThesauri oTopic Maps oLogical Models
  • 17. What is in an Ontology? An ontology specification includes descriptions of oConcepts and properties in a domain oRelationships between concepts oConstraints on how the relationships can be used oIndividuals as members of concepts
  • 18. The Benefits of an Ontology Ontologies provide: oA common understanding of information oExplicit domain assumptions These provisions are valuable because ontologies: oSupport data integration for analytics oApply domain knowledge to data oSupport interoperation of applications oEnable model-driven applications oReduce the time and cost of application development oImprove data quality, i.e., metadata and provenance
  • 19. Outline o RDF and RDFS o SPARQL Overview o Ontology Overview o GraphDB Overview o GraphDB Workbench Demo o Q&A
  • 20. What is GraphDB? Enterprise ready Semantic Graph Database, compliant with W3C Standards
  • 21. GraphDB™ Editions o GraphDB™ Free o GraphDB™ Standard o GraphDB™ Cloud o GraphDB™ Enterprise #21
  • 22. Outline o RDF and RDFS o SPARQL Overview o Ontology Overview o GraphDB Overview o GraphDB Workbench Demo o Q&A
  • 23. DEMO
  • 24. DEMO Install GraphDB Load Data oUsing GraphDB Workbench import page oUsing OntoRefine Query Data oSPARQL Ask oSPARQL Select oSPARQL Construct Query Monitoring
  • 25. DEMO o Search DATA o GraphDB Workbench Autocomplete o GraphDB Connectors – Lucene, Solr, o ElasticSearch o Visualize DATA o Visualize Class Hierarchy o GraphDB Default Visual Graph o GraphDB Custom Visual Graphs
  • 26. Support and FAQ’s graphDB-support@ontotext.com Additional resources: Ontotext: Community Forum and Evaluation Support: http://stackoverflow.com/questions/tagged/graphdb GraphDB Website and Documentation: http://graphdb.ontotext.com Whitepapers, Fundamentals: http://ontotext.com/knowledge-hub/fundamentals/ SPARQL, OWL, and RDF: RDF: http://www.w3.org/TR/rdf11-concepts/ RDFS: http://www.w3.org/TR/rdf-schema/ SPARQL Overview: http://www.w3.org/TR/sparql11-overview/ SPARQL Query: http://www.w3.org/TR/sparql11-query/ SPARQL Update: http://www.w3.org/TR/sparql11-update
  • 27. Desislava Hristova, Senior Software Engineer Get your GraphDB Today: http://ontotext.com/products/graphdb/ FactForge: Hub for open data and news about People and Organizations http://factforge.net/ Experience the technology with NOW: Semantic News Portal http://now.ontotext.com Thank you for your attention!