SlideShare a Scribd company logo
1 of 17
Download to read offline
Semantika
Relational to RDF Mapping and Transparent Data
Access for SPARQL over SQL Databases
Facts about Semantika
• True transparent data access.
• Non-intrusive and utilizes fully over
existing database.

• Query language aligned with SPARQL.
• High priority on performance.
What is Semantika?
• Semantika is a robust, high-performance

RDB-to-RDF connector and data access
add-on API for Java and SQL. Semantika
provides interface for building semantic
query machine over your existing
database. The solution is non-intrusive
and risk-free for your valuable data.
What is Semantika?
• Semantika framework is based on

Ontology-based Database Access (OBDA)
paradigm that combines the best of
semantic discipline and relational database
technology.

• It offers API support and high processing
performance.
Semantika Core
Components
• RDB/RDF Mapping,
• Common Query Expression.
RDB/RDF Mapping
• Mapping domain entities and relational
data,

• Solution for the infamous object-relation
impedance mismatch,

• Finally application can focus on domain
specification.
Common Query
Expression
• Using one query to retrieve sets of data

without knowing what relational database
is the target.

• The query articulation is no longer tight
on a specific data schema; instead it is
bundled with terminology of your own
through SPARQL language.
Why use Semantika?
• Simple to implement,
• Isn’t intrusive, no migration is required.
• Instant added-value to your existing data
query system,

• Query mechanism closely resembles SQL
so learning curve is low,

• Useful for data publishing to public.
What makes up a
Semantika application?
• Domain Ontology,
• RDB/RDF Mapping Specification,
• Semantika Configuration
Domain Ontology
• A formal specification of the domain
application.

SubClassOf(TechnicalStaff, Employee)
SubClassOf(OperationalStaff, Employee)
SubClassOf(Manager, Employee)
DataPropertyDomain(firstName, Employee)
DataPropertyDomain(lastName, Employee)
DataPropertyDomain(hireDate, Employee)
ObjectPropertyDomain(memberOf, Employee)
ObjectPropertyRange(memberOf, Department)
RDB/RDF Mapping
• A formal specification about the relationship
between data in database and entities in
ontology.

<mapping tml:id="Mapping1">
<logical-table rr:tableName="EMPLOYEES"/>
<subject-map rr:template="Employee(EMP_NO)"/>
<predicate-object-map rr:predicate="firstName" rr:column="FIRST_NAME"/>
<predicate-object-map rr:predicate="lastName" rr:column="LAST_NAME"/>
<predicate-object-map rr:predicate="hireDate" rr:column="HIRE_DATE"/>
</mapping>

Ontology
entities

Database
columns
Semantika Configuration
• A collection of database settings and file
resources.

<semantika-configuration>
<application-factory name="empapp">
<data-source>
<property name="connection.url">jdbc:h2:tcp://localhost/empdb</property>
<property name="connection.driver_class">org.h2.Driver</property>
<property name="connection.username">sa</property>
<property name="connection.password"></property>
</data-source>
<ontology-source resource="model/empdb.owl" />
<mapping-source resource="model/empdb.tml.xml" />
</application-factory>
</semantika-configuration>
Semantika Classes
• ApplicationFactory - Consumer of

Semantika configuration file. System
initialization happens here. Creates
ApplicationManager.

• ApplicationManager - One instance per
app. Provides query engine for query
answering interface.
Semantika Classes
• SparqlQueryEngine - Default query engine
that takes input SPARQL and returns
QueryResult.

• RdfMaterializerEngine - RDB-to-RDF
export tool. Useful for open data
publishing.
Semantika Use Scenario
IT-experts

end-user

model

query

communicate

software agent

ontology

mappings

Semantika Core Framework
SQL Databases

(reproduced from Optique 1.0: Semantic Access to Big Data presentation)
Things to Take In
• Semantika is a robust, non-intrusive

platform for your semantic search need.

• Semantika offers you a new and intelligent
way for querying relational data through
semantic search.

• Semantika helps to extract your domain

information into standard documents that
is useful for knowledge sharing.
Visit our Site:
http://obidea.github.io/semantika-api/

Project Extras:
Command-line Tool:
https://github.com/obidea/semantika-cli
SPARQL endpoint with Sesame:
https://github.com/obidea/semantika-sesame

More Related Content

What's hot

Kasaysayan ng panitikan
Kasaysayan ng panitikanKasaysayan ng panitikan
Kasaysayan ng panitikan
SCPS
 
Pagtuturo ng filipino (1)
Pagtuturo ng filipino (1)Pagtuturo ng filipino (1)
Pagtuturo ng filipino (1)
Elvira Regidor
 
PAGSUSURI SA MGA AKDANG MAPANGHIMAGSIK SA PANITIKANG FILIPINO
PAGSUSURI SA MGA AKDANG MAPANGHIMAGSIK SA  PANITIKANG FILIPINOPAGSUSURI SA MGA AKDANG MAPANGHIMAGSIK SA  PANITIKANG FILIPINO
PAGSUSURI SA MGA AKDANG MAPANGHIMAGSIK SA PANITIKANG FILIPINO
Nimpha Gonzaga
 

What's hot (20)

Kasaysayan ng panitikan
Kasaysayan ng panitikanKasaysayan ng panitikan
Kasaysayan ng panitikan
 
Batutian
BatutianBatutian
Batutian
 
Baryasyon at Barayti ng WIka
Baryasyon at Barayti ng WIkaBaryasyon at Barayti ng WIka
Baryasyon at Barayti ng WIka
 
Fil 106: Ugnayan ng Wika, Kultura at Lipunan
Fil 106: Ugnayan ng Wika, Kultura at LipunanFil 106: Ugnayan ng Wika, Kultura at Lipunan
Fil 106: Ugnayan ng Wika, Kultura at Lipunan
 
Banghay aralin sa filipino 10 rose
Banghay aralin sa filipino 10   roseBanghay aralin sa filipino 10   rose
Banghay aralin sa filipino 10 rose
 
Pagtuturo ng filipino (1)
Pagtuturo ng filipino (1)Pagtuturo ng filipino (1)
Pagtuturo ng filipino (1)
 
KASAYSAYAN NG KURIKULUM SA PILIPINAS.pptx
KASAYSAYAN NG KURIKULUM SA PILIPINAS.pptxKASAYSAYAN NG KURIKULUM SA PILIPINAS.pptx
KASAYSAYAN NG KURIKULUM SA PILIPINAS.pptx
 
PANIMULANG LINGGWISTIKA : Ang Pagsasalita
PANIMULANG LINGGWISTIKA : Ang PagsasalitaPANIMULANG LINGGWISTIKA : Ang Pagsasalita
PANIMULANG LINGGWISTIKA : Ang Pagsasalita
 
Lexical at istruktura semantika.docx
Lexical at istruktura semantika.docxLexical at istruktura semantika.docx
Lexical at istruktura semantika.docx
 
PAGSUSURI SA MGA AKDANG MAPANGHIMAGSIK SA PANITIKANG FILIPINO
PAGSUSURI SA MGA AKDANG MAPANGHIMAGSIK SA  PANITIKANG FILIPINOPAGSUSURI SA MGA AKDANG MAPANGHIMAGSIK SA  PANITIKANG FILIPINO
PAGSUSURI SA MGA AKDANG MAPANGHIMAGSIK SA PANITIKANG FILIPINO
 
Mga estratehiya ginagamit sa pagtuturo ng wika
Mga estratehiya ginagamit sa pagtuturo ng wikaMga estratehiya ginagamit sa pagtuturo ng wika
Mga estratehiya ginagamit sa pagtuturo ng wika
 
Antas ng salita updated a
Antas ng salita updated aAntas ng salita updated a
Antas ng salita updated a
 
Kabanata v (mga salik sa matagumpay na pagkatuto ng wika)
Kabanata v (mga salik sa matagumpay na pagkatuto ng wika)Kabanata v (mga salik sa matagumpay na pagkatuto ng wika)
Kabanata v (mga salik sa matagumpay na pagkatuto ng wika)
 
Instruktura ng wika
Instruktura ng wikaInstruktura ng wika
Instruktura ng wika
 
Sintaksis
SintaksisSintaksis
Sintaksis
 
Mga teknik at mga estratehiya sa pagtuturo gamit ang pananaliksik
Mga teknik at mga estratehiya sa pagtuturo gamit ang pananaliksikMga teknik at mga estratehiya sa pagtuturo gamit ang pananaliksik
Mga teknik at mga estratehiya sa pagtuturo gamit ang pananaliksik
 
Asimilasyon
AsimilasyonAsimilasyon
Asimilasyon
 
Ang Kasaysayan ng Maikling Kuwento
Ang Kasaysayan ng Maikling KuwentoAng Kasaysayan ng Maikling Kuwento
Ang Kasaysayan ng Maikling Kuwento
 
Ponema
PonemaPonema
Ponema
 
Heograpikal,Morpolohikal at Ponolohikal na Varayti ng Wika
Heograpikal,Morpolohikal at Ponolohikal na Varayti ng WikaHeograpikal,Morpolohikal at Ponolohikal na Varayti ng Wika
Heograpikal,Morpolohikal at Ponolohikal na Varayti ng Wika
 

Viewers also liked

the scope of semantics
the scope of semanticsthe scope of semantics
the scope of semantics
Ayi Yulianty
 
9 kahulugan ng salita sa pamamagitan ng kasalungat
9   kahulugan ng salita sa pamamagitan ng kasalungat9   kahulugan ng salita sa pamamagitan ng kasalungat
9 kahulugan ng salita sa pamamagitan ng kasalungat
Flordeliza Betonio
 
Ikalawang pangkat sa filipino i
Ikalawang pangkat sa filipino iIkalawang pangkat sa filipino i
Ikalawang pangkat sa filipino i
Airez Mier
 
Pangungusap
PangungusapPangungusap
Pangungusap
Mckoi M
 

Viewers also liked (20)

Sintaksis
SintaksisSintaksis
Sintaksis
 
Morpolohiya
MorpolohiyaMorpolohiya
Morpolohiya
 
Semantika Story
Semantika StorySemantika Story
Semantika Story
 
Ponolohiya (FIL 101)
Ponolohiya (FIL 101)Ponolohiya (FIL 101)
Ponolohiya (FIL 101)
 
Mga Bahagi Ng Pananalita
Mga Bahagi Ng PananalitaMga Bahagi Ng Pananalita
Mga Bahagi Ng Pananalita
 
Gramatika at retorika
Gramatika at retorikaGramatika at retorika
Gramatika at retorika
 
Masining na pagpapahayag
Masining na pagpapahayagMasining na pagpapahayag
Masining na pagpapahayag
 
Istraktura ng wika
Istraktura ng wikaIstraktura ng wika
Istraktura ng wika
 
Badyet f ilipino gr. 4
Badyet f ilipino gr. 4Badyet f ilipino gr. 4
Badyet f ilipino gr. 4
 
the scope of semantics
the scope of semanticsthe scope of semantics
the scope of semantics
 
9 kahulugan ng salita sa pamamagitan ng kasalungat
9   kahulugan ng salita sa pamamagitan ng kasalungat9   kahulugan ng salita sa pamamagitan ng kasalungat
9 kahulugan ng salita sa pamamagitan ng kasalungat
 
the scope of semantic
the scope of semanticthe scope of semantic
the scope of semantic
 
Yunit 3 istruktura ng wika
Yunit 3  istruktura ng wikaYunit 3  istruktura ng wika
Yunit 3 istruktura ng wika
 
Filipino 3 Masining na Pagpapahayag
Filipino 3  Masining na PagpapahayagFilipino 3  Masining na Pagpapahayag
Filipino 3 Masining na Pagpapahayag
 
Ang masining na pagpapahayag
Ang masining na pagpapahayagAng masining na pagpapahayag
Ang masining na pagpapahayag
 
Ikalawang pangkat sa filipino i
Ikalawang pangkat sa filipino iIkalawang pangkat sa filipino i
Ikalawang pangkat sa filipino i
 
Retorika at Gramatika
Retorika at GramatikaRetorika at Gramatika
Retorika at Gramatika
 
Ponemang suprasegmental
Ponemang suprasegmentalPonemang suprasegmental
Ponemang suprasegmental
 
Pangungusap
PangungusapPangungusap
Pangungusap
 
BAHAGI NG PANANALITA
BAHAGI NG PANANALITABAHAGI NG PANANALITA
BAHAGI NG PANANALITA
 

Similar to Semantika Introduction

Similar to Semantika Introduction (20)

Applying large scale text analytics with graph databases
Applying large scale text analytics with graph databasesApplying large scale text analytics with graph databases
Applying large scale text analytics with graph databases
 
8th TUC Meeting - Zhe Wu (Oracle USA). Bridging RDF Graph and Property Graph...
8th TUC Meeting -  Zhe Wu (Oracle USA). Bridging RDF Graph and Property Graph...8th TUC Meeting -  Zhe Wu (Oracle USA). Bridging RDF Graph and Property Graph...
8th TUC Meeting - Zhe Wu (Oracle USA). Bridging RDF Graph and Property Graph...
 
Introduction to Property Graph Features (AskTOM Office Hours part 1)
Introduction to Property Graph Features (AskTOM Office Hours part 1) Introduction to Property Graph Features (AskTOM Office Hours part 1)
Introduction to Property Graph Features (AskTOM Office Hours part 1)
 
Ontologies & linked open data
Ontologies & linked open dataOntologies & linked open data
Ontologies & linked open data
 
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
 
Stream processing: The Matrix Revolutions
Stream processing: The Matrix RevolutionsStream processing: The Matrix Revolutions
Stream processing: The Matrix Revolutions
 
How To Model and Construct Graphs with Oracle Database (AskTOM Office Hours p...
How To Model and Construct Graphs with Oracle Database (AskTOM Office Hours p...How To Model and Construct Graphs with Oracle Database (AskTOM Office Hours p...
How To Model and Construct Graphs with Oracle Database (AskTOM Office Hours p...
 
Spark from the Surface
Spark from the SurfaceSpark from the Surface
Spark from the Surface
 
Etosha - Data Asset Manager : Status and road map
Etosha - Data Asset Manager : Status and road mapEtosha - Data Asset Manager : Status and road map
Etosha - Data Asset Manager : Status and road map
 
Evolution of the Graph Schema
Evolution of the Graph SchemaEvolution of the Graph Schema
Evolution of the Graph Schema
 
Navigating NoSQL in cloudy skies
Navigating NoSQL in cloudy skiesNavigating NoSQL in cloudy skies
Navigating NoSQL in cloudy skies
 
Change RelationalDB to GraphDB with OrientDB
Change RelationalDB to GraphDB with OrientDBChange RelationalDB to GraphDB with OrientDB
Change RelationalDB to GraphDB with OrientDB
 
TDWI Accelerate, Seattle, Oct 16, 2017: Distributed and In-Database Analytics...
TDWI Accelerate, Seattle, Oct 16, 2017: Distributed and In-Database Analytics...TDWI Accelerate, Seattle, Oct 16, 2017: Distributed and In-Database Analytics...
TDWI Accelerate, Seattle, Oct 16, 2017: Distributed and In-Database Analytics...
 
TWDI Accelerate Seattle, Oct 16, 2017: Distributed and In-Database Analytics ...
TWDI Accelerate Seattle, Oct 16, 2017: Distributed and In-Database Analytics ...TWDI Accelerate Seattle, Oct 16, 2017: Distributed and In-Database Analytics ...
TWDI Accelerate Seattle, Oct 16, 2017: Distributed and In-Database Analytics ...
 
Meetup Oracle Database BCN: 2.1 Data Management Trends
Meetup Oracle Database BCN: 2.1 Data Management TrendsMeetup Oracle Database BCN: 2.1 Data Management Trends
Meetup Oracle Database BCN: 2.1 Data Management Trends
 
Information Exploitation at BBN
Information Exploitation at BBNInformation Exploitation at BBN
Information Exploitation at BBN
 
Virtuoso -- The Prometheus of RDF
Virtuoso -- The Prometheus of RDFVirtuoso -- The Prometheus of RDF
Virtuoso -- The Prometheus of RDF
 
Database Cloud Services Office Hours : Oracle sharding hyperscale globally d...
Database Cloud Services Office Hours : Oracle sharding  hyperscale globally d...Database Cloud Services Office Hours : Oracle sharding  hyperscale globally d...
Database Cloud Services Office Hours : Oracle sharding hyperscale globally d...
 
Analytics Beyond RAM Capacity using R
Analytics Beyond RAM Capacity using RAnalytics Beyond RAM Capacity using R
Analytics Beyond RAM Capacity using R
 
ORM Methodology
ORM MethodologyORM Methodology
ORM Methodology
 

Recently uploaded

Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
panagenda
 

Recently uploaded (20)

From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
 
Manulife - Insurer Innovation Award 2024
Manulife - Insurer Innovation Award 2024Manulife - Insurer Innovation Award 2024
Manulife - Insurer Innovation Award 2024
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
 
Deploy with confidence: VMware Cloud Foundation 5.1 on next gen Dell PowerEdg...
Deploy with confidence: VMware Cloud Foundation 5.1 on next gen Dell PowerEdg...Deploy with confidence: VMware Cloud Foundation 5.1 on next gen Dell PowerEdg...
Deploy with confidence: VMware Cloud Foundation 5.1 on next gen Dell PowerEdg...
 
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
 
Strategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a FresherStrategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a Fresher
 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024
 
Top 5 Benefits OF Using Muvi Live Paywall For Live Streams
Top 5 Benefits OF Using Muvi Live Paywall For Live StreamsTop 5 Benefits OF Using Muvi Live Paywall For Live Streams
Top 5 Benefits OF Using Muvi Live Paywall For Live Streams
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘
 
Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
 
Top 10 Most Downloaded Games on Play Store in 2024
Top 10 Most Downloaded Games on Play Store in 2024Top 10 Most Downloaded Games on Play Store in 2024
Top 10 Most Downloaded Games on Play Store in 2024
 
Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...
 
Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyArtificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : Uncertainty
 
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
 
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
 

Semantika Introduction

  • 1. Semantika Relational to RDF Mapping and Transparent Data Access for SPARQL over SQL Databases
  • 2. Facts about Semantika • True transparent data access. • Non-intrusive and utilizes fully over existing database. • Query language aligned with SPARQL. • High priority on performance.
  • 3. What is Semantika? • Semantika is a robust, high-performance RDB-to-RDF connector and data access add-on API for Java and SQL. Semantika provides interface for building semantic query machine over your existing database. The solution is non-intrusive and risk-free for your valuable data.
  • 4. What is Semantika? • Semantika framework is based on Ontology-based Database Access (OBDA) paradigm that combines the best of semantic discipline and relational database technology. • It offers API support and high processing performance.
  • 5. Semantika Core Components • RDB/RDF Mapping, • Common Query Expression.
  • 6. RDB/RDF Mapping • Mapping domain entities and relational data, • Solution for the infamous object-relation impedance mismatch, • Finally application can focus on domain specification.
  • 7. Common Query Expression • Using one query to retrieve sets of data without knowing what relational database is the target. • The query articulation is no longer tight on a specific data schema; instead it is bundled with terminology of your own through SPARQL language.
  • 8. Why use Semantika? • Simple to implement, • Isn’t intrusive, no migration is required. • Instant added-value to your existing data query system, • Query mechanism closely resembles SQL so learning curve is low, • Useful for data publishing to public.
  • 9. What makes up a Semantika application? • Domain Ontology, • RDB/RDF Mapping Specification, • Semantika Configuration
  • 10. Domain Ontology • A formal specification of the domain application. SubClassOf(TechnicalStaff, Employee) SubClassOf(OperationalStaff, Employee) SubClassOf(Manager, Employee) DataPropertyDomain(firstName, Employee) DataPropertyDomain(lastName, Employee) DataPropertyDomain(hireDate, Employee) ObjectPropertyDomain(memberOf, Employee) ObjectPropertyRange(memberOf, Department)
  • 11. RDB/RDF Mapping • A formal specification about the relationship between data in database and entities in ontology. <mapping tml:id="Mapping1"> <logical-table rr:tableName="EMPLOYEES"/> <subject-map rr:template="Employee(EMP_NO)"/> <predicate-object-map rr:predicate="firstName" rr:column="FIRST_NAME"/> <predicate-object-map rr:predicate="lastName" rr:column="LAST_NAME"/> <predicate-object-map rr:predicate="hireDate" rr:column="HIRE_DATE"/> </mapping> Ontology entities Database columns
  • 12. Semantika Configuration • A collection of database settings and file resources. <semantika-configuration> <application-factory name="empapp"> <data-source> <property name="connection.url">jdbc:h2:tcp://localhost/empdb</property> <property name="connection.driver_class">org.h2.Driver</property> <property name="connection.username">sa</property> <property name="connection.password"></property> </data-source> <ontology-source resource="model/empdb.owl" /> <mapping-source resource="model/empdb.tml.xml" /> </application-factory> </semantika-configuration>
  • 13. Semantika Classes • ApplicationFactory - Consumer of Semantika configuration file. System initialization happens here. Creates ApplicationManager. • ApplicationManager - One instance per app. Provides query engine for query answering interface.
  • 14. Semantika Classes • SparqlQueryEngine - Default query engine that takes input SPARQL and returns QueryResult. • RdfMaterializerEngine - RDB-to-RDF export tool. Useful for open data publishing.
  • 15. Semantika Use Scenario IT-experts end-user model query communicate software agent ontology mappings Semantika Core Framework SQL Databases (reproduced from Optique 1.0: Semantic Access to Big Data presentation)
  • 16. Things to Take In • Semantika is a robust, non-intrusive platform for your semantic search need. • Semantika offers you a new and intelligent way for querying relational data through semantic search. • Semantika helps to extract your domain information into standard documents that is useful for knowledge sharing.
  • 17. Visit our Site: http://obidea.github.io/semantika-api/ Project Extras: Command-line Tool: https://github.com/obidea/semantika-cli SPARQL endpoint with Sesame: https://github.com/obidea/semantika-sesame