SlideShare a Scribd company logo
WOTS2E: A Search Engine for a
Semantic Web of Things
Unit for Reasoning, Querying and Stream Processing
Insight Centre for Data Analytics,
National University of Ireland, Galway
Andreas Kamilaris, Semih Yumusak, Ali Intizar
World Forum – IoT 2016
Reston, VA, USA- December 12-14, 2016
https://www.w3.org/WoT/images/iot.png
Web of Things
• Designed to connect
“things” to the Web
• A combination of
• Approaches
• Software Architectures
• Interfaces
https://www.w3.org/WoT/images/iot.png
• Increase Interoperability
among IoT platforms
• Mitigate Silo Architecture
• Avoid Multiple and Conflicting
Standards
• Global and Easy Discovery of
Devices
Why we need Web of Things?
• Few of the emerging WoT
platforms
• Sorcades
• ThingWorx
• SpitFire
• Evrythng
• Open.Sen.se
• WoTKit
• Auto WoT
• Xively
Web of Things Platforms
• Can we improve the discoverability of Web of Things?
• Can we use semantic technologies to improve device
discoverability?
• Are there any datasets produced by WoT devices available as
Open Data on the Web?
• Can we create a global and distributed index for search and
discovery of WoT devices?
Our Motivation
Discovery
• Machines needs to automatically discover devices/things and their
description
• Global repositories
• Indexing Things and their description
• Semantic Annotation to describe things
• SPARQL queries and data endpoints
• Discover devices on the fly (Late Binding)
Slide Source: ISWC 2016, Tutorial on Semantic Web Meets IoT/WoT (Soumya Kanti Datta)
Repository Based Discovery
Slide Source: ISWC 2016, Tutorial on Semantic Web Meets IoT/WoT (Soumya Kanti Datta)
Device Discovery Mechanisms
• Spatial Search
– BLE beacon based things
• Network Based Search
– mDNS, multicast CoAP
• Device Registration Directories
– CoRE resource directory, XMPP IoT directory, HyperCat
• Meta-Data Discovery
– CoRE Link Format
• Semantic Search and Discovery Techniqyes
– Offers high richness in search queries
• E.g. “search for all light bulbs in my house”
Slide Source: ISWC 2016, Tutorial on Semantic Web Meets IoT/WoT (Soumya Kanti Datta)
Semantic Search & Discovery: Key Challenges
• Optimal Data Source Discovery
• Streams are everywhere
• Multiple data streams can answer the same query
• Optimal data stream selection
• Catering for user-defined constraints and preferences
• On-Demand Stream Federation
• Automated composition of primitive data streams to
answer complex queries
• Adaptation
• Data source properties can change over time
• Make sure selected sources remain “optimal”
throughout life cycle of the query
Stream Discovery, Federation and Adaptation
• Stream Discovery
– Data interoperability:
• Semantic descriptions (ontologies and annotations)
– Interface interoperability:
• Streams as event services (service discovery)
• Stream Federation
– Efficient processing of complicated event logics
• Data Stream Management Systems
• Complex Event Processing
Semantic
Web
Service
Oriented
Architectures
DSMS and
CEP
Semantic Description
• A sensor service description is annotated as:
sdesc = (td, g, qd, Pd, FoId, fd)
type grounding QoS
Observed
Properties
Feature Of
Iterest
Pd → FoId
• Similarly, a sensor service request is annotated:
sr = (tr, Pr, FoIr, fr, pref, C)
type Requested
Properties
Feature of
Interest
Pd → FoId
no
grounding
NFP Constraint and
Preferences
Middle-ware for Stream Discovery and Federation
Semantic Annotation
ACEIS Core
Resource
Management
Application
Interface
Knowledge Base
QoI/QoS
Stream
Description
Data Mgmt,
Indexing,
Caching
User Input
Event Request
Data
Federation
Resource Discovery
Event Service Composer
Composition Plan
Subscription Manager
Query Transformer
Query Engine
Query
Results
Constraint
Validation
Constraint
Violation
Adaptation
Manager
Data Store
IoT Data
Stream
Social Data
Stream
Web of Things Discovery
• Optimal Data Source Discovery
• Web of Things Search Space is
Global
• Across the whole Web
• Indexing
• Geo-Spatial Mapping
• Movable Objects/Things
• Require Frequent Updates in
Indexes
Problem StatementLinked Open Data Cloud
WOTS2E: ArchitectureWOTS2E: Overview
• A Search engine to
discover semantic meta-
description of things
• Crawls the Web to
discover Linked Data
Sources
• Analyzes Linked Data
sources to identify
relevant WoT devices
WOTS2E: ArchitectureWOTS2E: Overview
• Maintain a registry of
devices for discovery
• Support application
request and provide
details to interact with
the devices.
WOTS2E: ArchitectureWOTS2E: Operations
• Discovery of Linked Data Endpoints
– Web crawlers that continuously scan the
web for discovery of Linked Data
endpoints, frequency of one scan per day
• Examination of Discovered Linked
Data Endpoints
– Query endpoints for IoT/WoT relevant
ontologies
– Explore popular dataset descriptions, such
as VoID, SPARQL-SD
• Analysis of Linked Data Endpoints
and WoT Device Discovery
– Through SPARQL queries, VoID/SPARQL-
SD files, use of open APIs
• Recording of WoT Devices and
Services Discovered
– Service type, location, time, features,
interaction types, restrictions etc.
WOTS2E: ArchitectureWOTS2E: Implementation/Analysis
Common Patterns
<meta name=”Keywords” content=”OpenLink Virtuoso Sparql”>
Virtuoso SPARQL Query Editor
OpenLink Software
<label for=”debug”>Strict checking of void variables</label>
<a href=”http://www.openlinksw.com/virtuoso” >
<a href=”/isparql”>iSPARQL</a>
<label for=”query”>Query text</label>
• SPARQL Endpoint Listed at Datahub.io
• Common Patterns Identification
• SPARQL endpoint discovery
WOTS2E: ArchitectureWOTS2E: Implementation/Analysis
• Discovered patterns are used
as an input to our web
crawlers, in order to search the
web for available SPARQL
endpoints.
• For web crawling, we used a
meta-crawling service called
SpEnD.
• SpEnD exploits the search
functionality available over
popular search engines to
accelerate the performance of
web crawling.
WOTS2E: ArchitectureWOTS2E: Implementation/Analysis
• To analyze the URLs retrieved, the Jena Framework was
used to send SPARQL queries to the candidate endpoints,
checking whether they are valid SPARQL endpoints or not.
• All valid SPARQL endpoints were examined whether they
contain information related to IoT/WoT, i.e. contained
relevant ontologies.
SELECT DISTINCT ?Concept WHERE {[] a ?Concept} LIMIT 100
SELECT * WHERE {{?s ?p ?o}
UNION {GRAPH ?g {?s ?p ?o}}
FILTER regex(?o, "/SSN"). FILTER isIRI(?o).
• After labeling some SPARQL endpoint as related to IoT/WoT, the next step was to
analyze it, discovering which devices/services are available through it:
VoID file adapted to
reveal information about
WoT devices and services
Extend SSN to include discovery and
description information through some
ontology that describes web services.
:ExampleDataset a void:Dataset;
void:subset :ExampleSensor .
:ExampleSensor a void:Dataset;
dcterms:title "WoT Example Sensor";
dcterms:description "http://../sens.wadl";
dcterms:contributor "Insight Centre";
dcterms:source "140.203.154.11"
WOTS2E: Implementation/Analysis
WOTS2E: ArchitectureWOTS2E: Implementation/Analysis
• Information about SPARQL endpoints, devices/services
discovered and sensor meta-data information was stored
as RDF triples on a Virtuoso RDF store, installed on
WOTS2E.
• Use of the IoT ontologyPrefix iot: <http://purl.org/IoT/iot#>
Prefix ssn: <http://purl.oclc.org/../ssn#>
SELECT ?sm ?device ?service
WHERE {
?sm a iot:smart_entity
?sm iot:has_part_device
?device ?device ssn:observes
?service ?service a iot:Temperature
}
WOTS2E: ArchitectureWOTS2E: Evaluation
• The SpEnD (meta-)crawling service ran for 24 hours
• Using the common patterns for SPARQL endpoints
• Relevant URLs from the Bing, Yahoo, Google, Baidu, and
Yandex search engines.
• Comparison of discovered endpoints with Datahub.
Active Inactive Total
WOTS2E 638 640 1278
Datahub 258 296 554
WOTS2E: ArchitectureWOTS2E: Evaluation
• From the discovered 638 active SPARQL endpoints, we
examined them one by one for relevance to IoT/WoT
Ontology Number of Endpoints
SSN 13
DBPedia 13
SmartBuilding 3
DogOnt 2
DUL 2
km4city 2
OpenEI 2
RDFS, SKOS 4
Fan Fpai, Fiemser, IoT,
PROV, SAREF
5 (once each ontology)
WOTS2E: ArchitectureWOTS2E: Evaluation
• IoT/WoT-specific triples from the endpoints
Ontology Number of Triples
SSN 1.433,248
DUL 182
km4city 56
Fiemser 50
OpenIoT 44
SmartBuilding 36
DogOnt 24
SAREF 4
Fan Fpai 2
Conclusion
• Semantic Search and Discovery is essential for Web of
Things
• Currently only a handful of available SPARQL endpoints
(46, 7.2%) seem to relate to IoT/WoT.
• Lack of meta data availability
• Need for standardization for discovery mechanisms
• Our method aims to suggest a solid proposal on how to
achieve discovery on SWoT seamlessly and with minimum
effort.
• WOTS2E can support applications looking for on the fly
discovery and integration of devices
Future Work
• Improve Search mechanism by designing good
vocabularies/ontologies and descriptions for IoT/WoT
devices, services and data.
• A user-friendly website of WOTS2E, to incrementally let
users to access the discovered lists of services in a well-
organized way.
• From meta-crawling to efficient (classical) web crawling.
• Contribute to the standardization efforts on the WoT (W3C
WoT IG, OGC Sensor Web Interface for IoT SWG),
promoting WOTS2E as a viable solution for a SWoT search
engine.

More Related Content

What's hot

Introduction to Elasticsearch with basics of Lucene
Introduction to Elasticsearch with basics of LuceneIntroduction to Elasticsearch with basics of Lucene
Introduction to Elasticsearch with basics of Lucene
Rahul Jain
 
ElasticSearch: Distributed Multitenant NoSQL Datastore and Search Engine
ElasticSearch: Distributed Multitenant NoSQL Datastore and Search EngineElasticSearch: Distributed Multitenant NoSQL Datastore and Search Engine
ElasticSearch: Distributed Multitenant NoSQL Datastore and Search Engine
Daniel N
 
RELIANCE ROHub hackathon
RELIANCE ROHub hackathonRELIANCE ROHub hackathon
RELIANCE ROHub hackathon
Raul Palma
 
Elasticsearch
ElasticsearchElasticsearch
Elasticsearch
Ricardo Peres
 
ElasticSearch in Production: lessons learned
ElasticSearch in Production: lessons learnedElasticSearch in Production: lessons learned
ElasticSearch in Production: lessons learned
BeyondTrees
 
Webinar: Search and Recommenders
Webinar: Search and RecommendersWebinar: Search and Recommenders
Webinar: Search and Recommenders
Lucidworks
 
The WorldCat Search API
The WorldCat Search APIThe WorldCat Search API
The WorldCat Search API
OCLC Research
 
Lucene And Solr Document Classification
Lucene And Solr Document ClassificationLucene And Solr Document Classification
Lucene And Solr Document Classification
Alessandro Benedetti
 
Roaring with elastic search sangam2018
Roaring with elastic search sangam2018Roaring with elastic search sangam2018
Roaring with elastic search sangam2018
Vinay Kumar
 
Wis2011_presentation_Realtime_Events_on_LOD
Wis2011_presentation_Realtime_Events_on_LODWis2011_presentation_Realtime_Events_on_LOD
Wis2011_presentation_Realtime_Events_on_LOD
Pramod Koneru
 
HRGRN: enabling graph search and integrative analysis of Arabidopsis signalin...
HRGRN: enabling graph search and integrative analysis of Arabidopsis signalin...HRGRN: enabling graph search and integrative analysis of Arabidopsis signalin...
HRGRN: enabling graph search and integrative analysis of Arabidopsis signalin...
Araport
 
Datasets and GATE Evaluation Framework for Benchmarking Wikipedia Based NER S...
Datasets and GATE Evaluation Framework for Benchmarking Wikipedia Based NER S...Datasets and GATE Evaluation Framework for Benchmarking Wikipedia Based NER S...
Datasets and GATE Evaluation Framework for Benchmarking Wikipedia Based NER S...
Milan Dojchinovski
 
Webinar: Fusion 2.3 Preview - Enhanced Features with Solr & Spark
Webinar: Fusion 2.3 Preview - Enhanced Features with Solr & SparkWebinar: Fusion 2.3 Preview - Enhanced Features with Solr & Spark
Webinar: Fusion 2.3 Preview - Enhanced Features with Solr & Spark
Lucidworks
 
Elasticsearch Introduction
Elasticsearch IntroductionElasticsearch Introduction
Elasticsearch Introduction
Roopendra Vishwakarma
 
Elasticsearch Basics
Elasticsearch BasicsElasticsearch Basics
Elasticsearch Basics
Shifa Khan
 
JBrowse within the Arabidopsis Information Portal - PAG XXIII
JBrowse within the Arabidopsis Information Portal - PAG XXIIIJBrowse within the Arabidopsis Information Portal - PAG XXIII
JBrowse within the Arabidopsis Information Portal - PAG XXIII
Vivek Krishnakumar
 
Search domain basics
Search domain basicsSearch domain basics
Search domain basicspmanvi
 
Building genomic data cyberinfrastructure with the online database software T...
Building genomic data cyberinfrastructure with the online database software T...Building genomic data cyberinfrastructure with the online database software T...
Building genomic data cyberinfrastructure with the online database software T...
mestato
 
Solr 6.0 Graph Query Overview
Solr 6.0 Graph Query OverviewSolr 6.0 Graph Query Overview
Solr 6.0 Graph Query Overview
Kevin Watters
 
Security Analytics using ELK stack
Security Analytics using ELK stack	Security Analytics using ELK stack
Security Analytics using ELK stack
Cysinfo Cyber Security Community
 

What's hot (20)

Introduction to Elasticsearch with basics of Lucene
Introduction to Elasticsearch with basics of LuceneIntroduction to Elasticsearch with basics of Lucene
Introduction to Elasticsearch with basics of Lucene
 
ElasticSearch: Distributed Multitenant NoSQL Datastore and Search Engine
ElasticSearch: Distributed Multitenant NoSQL Datastore and Search EngineElasticSearch: Distributed Multitenant NoSQL Datastore and Search Engine
ElasticSearch: Distributed Multitenant NoSQL Datastore and Search Engine
 
RELIANCE ROHub hackathon
RELIANCE ROHub hackathonRELIANCE ROHub hackathon
RELIANCE ROHub hackathon
 
Elasticsearch
ElasticsearchElasticsearch
Elasticsearch
 
ElasticSearch in Production: lessons learned
ElasticSearch in Production: lessons learnedElasticSearch in Production: lessons learned
ElasticSearch in Production: lessons learned
 
Webinar: Search and Recommenders
Webinar: Search and RecommendersWebinar: Search and Recommenders
Webinar: Search and Recommenders
 
The WorldCat Search API
The WorldCat Search APIThe WorldCat Search API
The WorldCat Search API
 
Lucene And Solr Document Classification
Lucene And Solr Document ClassificationLucene And Solr Document Classification
Lucene And Solr Document Classification
 
Roaring with elastic search sangam2018
Roaring with elastic search sangam2018Roaring with elastic search sangam2018
Roaring with elastic search sangam2018
 
Wis2011_presentation_Realtime_Events_on_LOD
Wis2011_presentation_Realtime_Events_on_LODWis2011_presentation_Realtime_Events_on_LOD
Wis2011_presentation_Realtime_Events_on_LOD
 
HRGRN: enabling graph search and integrative analysis of Arabidopsis signalin...
HRGRN: enabling graph search and integrative analysis of Arabidopsis signalin...HRGRN: enabling graph search and integrative analysis of Arabidopsis signalin...
HRGRN: enabling graph search and integrative analysis of Arabidopsis signalin...
 
Datasets and GATE Evaluation Framework for Benchmarking Wikipedia Based NER S...
Datasets and GATE Evaluation Framework for Benchmarking Wikipedia Based NER S...Datasets and GATE Evaluation Framework for Benchmarking Wikipedia Based NER S...
Datasets and GATE Evaluation Framework for Benchmarking Wikipedia Based NER S...
 
Webinar: Fusion 2.3 Preview - Enhanced Features with Solr & Spark
Webinar: Fusion 2.3 Preview - Enhanced Features with Solr & SparkWebinar: Fusion 2.3 Preview - Enhanced Features with Solr & Spark
Webinar: Fusion 2.3 Preview - Enhanced Features with Solr & Spark
 
Elasticsearch Introduction
Elasticsearch IntroductionElasticsearch Introduction
Elasticsearch Introduction
 
Elasticsearch Basics
Elasticsearch BasicsElasticsearch Basics
Elasticsearch Basics
 
JBrowse within the Arabidopsis Information Portal - PAG XXIII
JBrowse within the Arabidopsis Information Portal - PAG XXIIIJBrowse within the Arabidopsis Information Portal - PAG XXIII
JBrowse within the Arabidopsis Information Portal - PAG XXIII
 
Search domain basics
Search domain basicsSearch domain basics
Search domain basics
 
Building genomic data cyberinfrastructure with the online database software T...
Building genomic data cyberinfrastructure with the online database software T...Building genomic data cyberinfrastructure with the online database software T...
Building genomic data cyberinfrastructure with the online database software T...
 
Solr 6.0 Graph Query Overview
Solr 6.0 Graph Query OverviewSolr 6.0 Graph Query Overview
Solr 6.0 Graph Query Overview
 
Security Analytics using ELK stack
Security Analytics using ELK stack	Security Analytics using ELK stack
Security Analytics using ELK stack
 

Viewers also liked

Service Integration in the Web of Things
Service Integration in the Web of ThingsService Integration in the Web of Things
Service Integration in the Web of Things
Simon Mayer
 
WoT 2016 - Seventh International Workshop on the Web of Things
WoT 2016 - Seventh International Workshop on the Web of ThingsWoT 2016 - Seventh International Workshop on the Web of Things
WoT 2016 - Seventh International Workshop on the Web of Things
Simon Mayer
 
Towards the Web of Things: Web Mashups for the Real-World @ MEM 2009
Towards the Web of Things: Web Mashups for the Real-World @ MEM 2009Towards the Web of Things: Web Mashups for the Real-World @ MEM 2009
Towards the Web of Things: Web Mashups for the Real-World @ MEM 2009
Dominique Guinard
 
A Distributional Approach for Terminological Semantic Search on the Linked Da...
A Distributional Approach for Terminological Semantic Search on the Linked Da...A Distributional Approach for Terminological Semantic Search on the Linked Da...
A Distributional Approach for Terminological Semantic Search on the Linked Da...
Andre Freitas
 
Introduction to Swingly
Introduction to SwinglyIntroduction to Swingly
Introduction to Swingly
Andy Hickl
 
Michael Caulfield: Developing a Connected Health Economy
Michael Caulfield: Developing a Connected Health EconomyMichael Caulfield: Developing a Connected Health Economy
Michael Caulfield: Developing a Connected Health Economy3GDR
 
Demo: Profiling & Exploration of Linked Open Data
Demo: Profiling & Exploration of Linked Open DataDemo: Profiling & Exploration of Linked Open Data
Demo: Profiling & Exploration of Linked Open Data
Stefan Dietze
 
Search Engines After The Semanatic Web
Search Engines After The Semanatic WebSearch Engines After The Semanatic Web
Search Engines After The Semanatic Websamar_slideshare
 
A Survey of Entity Ranking over RDF Graphs
A Survey of Entity Ranking over RDF GraphsA Survey of Entity Ranking over RDF Graphs
Knowledge Patterns SSSW2016
Knowledge Patterns SSSW2016Knowledge Patterns SSSW2016
Knowledge Patterns SSSW2016
Aldo Gangemi
 
Service Integration - A Web of Things Perspective
Service Integration - A Web of Things PerspectiveService Integration - A Web of Things Perspective
Service Integration - A Web of Things PerspectiveSimon Mayer
 
SemTech 2011 Semantic Search tutorial
SemTech 2011 Semantic Search tutorialSemTech 2011 Semantic Search tutorial
SemTech 2011 Semantic Search tutorial
Peter Mika
 
Adaptive Go-To-Market Plan for a Business DNA Search Engine: VisionaryD Software
Adaptive Go-To-Market Plan for a Business DNA Search Engine: VisionaryD SoftwareAdaptive Go-To-Market Plan for a Business DNA Search Engine: VisionaryD Software
Adaptive Go-To-Market Plan for a Business DNA Search Engine: VisionaryD Software
Rod King, Ph.D.
 
VisionaryD's Business Model Canvas: Proposed Freemium, Multisided Business Mo...
VisionaryD's Business Model Canvas: Proposed Freemium, Multisided Business Mo...VisionaryD's Business Model Canvas: Proposed Freemium, Multisided Business Mo...
VisionaryD's Business Model Canvas: Proposed Freemium, Multisided Business Mo...
Rod King, Ph.D.
 
PhD Dissertation Supporting tools for automated generation and visual editing...
PhD Dissertation Supporting tools for automated generation and visual editing...PhD Dissertation Supporting tools for automated generation and visual editing...
PhD Dissertation Supporting tools for automated generation and visual editing...
Álvaro Sicilia
 
School intro
School introSchool intro
Towards an industrial Web of Things
Towards an industrial Web of ThingsTowards an industrial Web of Things
Towards an industrial Web of Things
Olivier Liechti
 
Tutorial Knowledge Discovery
Tutorial Knowledge DiscoveryTutorial Knowledge Discovery
Tutorial Knowledge Discovery
SSSW
 
A component based architecture for the Web of Things
A component based architecture for the Web of ThingsA component based architecture for the Web of Things
A component based architecture for the Web of Things
Andreas Ruppen
 
Web of Things presentation - Document Generation
Web of Things presentation - Document GenerationWeb of Things presentation - Document Generation
Web of Things presentation - Document Generation
KIT
 

Viewers also liked (20)

Service Integration in the Web of Things
Service Integration in the Web of ThingsService Integration in the Web of Things
Service Integration in the Web of Things
 
WoT 2016 - Seventh International Workshop on the Web of Things
WoT 2016 - Seventh International Workshop on the Web of ThingsWoT 2016 - Seventh International Workshop on the Web of Things
WoT 2016 - Seventh International Workshop on the Web of Things
 
Towards the Web of Things: Web Mashups for the Real-World @ MEM 2009
Towards the Web of Things: Web Mashups for the Real-World @ MEM 2009Towards the Web of Things: Web Mashups for the Real-World @ MEM 2009
Towards the Web of Things: Web Mashups for the Real-World @ MEM 2009
 
A Distributional Approach for Terminological Semantic Search on the Linked Da...
A Distributional Approach for Terminological Semantic Search on the Linked Da...A Distributional Approach for Terminological Semantic Search on the Linked Da...
A Distributional Approach for Terminological Semantic Search on the Linked Da...
 
Introduction to Swingly
Introduction to SwinglyIntroduction to Swingly
Introduction to Swingly
 
Michael Caulfield: Developing a Connected Health Economy
Michael Caulfield: Developing a Connected Health EconomyMichael Caulfield: Developing a Connected Health Economy
Michael Caulfield: Developing a Connected Health Economy
 
Demo: Profiling & Exploration of Linked Open Data
Demo: Profiling & Exploration of Linked Open DataDemo: Profiling & Exploration of Linked Open Data
Demo: Profiling & Exploration of Linked Open Data
 
Search Engines After The Semanatic Web
Search Engines After The Semanatic WebSearch Engines After The Semanatic Web
Search Engines After The Semanatic Web
 
A Survey of Entity Ranking over RDF Graphs
A Survey of Entity Ranking over RDF GraphsA Survey of Entity Ranking over RDF Graphs
A Survey of Entity Ranking over RDF Graphs
 
Knowledge Patterns SSSW2016
Knowledge Patterns SSSW2016Knowledge Patterns SSSW2016
Knowledge Patterns SSSW2016
 
Service Integration - A Web of Things Perspective
Service Integration - A Web of Things PerspectiveService Integration - A Web of Things Perspective
Service Integration - A Web of Things Perspective
 
SemTech 2011 Semantic Search tutorial
SemTech 2011 Semantic Search tutorialSemTech 2011 Semantic Search tutorial
SemTech 2011 Semantic Search tutorial
 
Adaptive Go-To-Market Plan for a Business DNA Search Engine: VisionaryD Software
Adaptive Go-To-Market Plan for a Business DNA Search Engine: VisionaryD SoftwareAdaptive Go-To-Market Plan for a Business DNA Search Engine: VisionaryD Software
Adaptive Go-To-Market Plan for a Business DNA Search Engine: VisionaryD Software
 
VisionaryD's Business Model Canvas: Proposed Freemium, Multisided Business Mo...
VisionaryD's Business Model Canvas: Proposed Freemium, Multisided Business Mo...VisionaryD's Business Model Canvas: Proposed Freemium, Multisided Business Mo...
VisionaryD's Business Model Canvas: Proposed Freemium, Multisided Business Mo...
 
PhD Dissertation Supporting tools for automated generation and visual editing...
PhD Dissertation Supporting tools for automated generation and visual editing...PhD Dissertation Supporting tools for automated generation and visual editing...
PhD Dissertation Supporting tools for automated generation and visual editing...
 
School intro
School introSchool intro
School intro
 
Towards an industrial Web of Things
Towards an industrial Web of ThingsTowards an industrial Web of Things
Towards an industrial Web of Things
 
Tutorial Knowledge Discovery
Tutorial Knowledge DiscoveryTutorial Knowledge Discovery
Tutorial Knowledge Discovery
 
A component based architecture for the Web of Things
A component based architecture for the Web of ThingsA component based architecture for the Web of Things
A component based architecture for the Web of Things
 
Web of Things presentation - Document Generation
Web of Things presentation - Document GenerationWeb of Things presentation - Document Generation
Web of Things presentation - Document Generation
 

Similar to WOTS2E: A Search Engine for a Semantic Web of Things

Do ”Web of Things Platforms” Truly Follow the Web of Things?
Do ”Web of Things Platforms” Truly Follow the Web of Things?Do ”Web of Things Platforms” Truly Follow the Web of Things?
Do ”Web of Things Platforms” Truly Follow the Web of Things?
Andreas Kamilaris
 
Standard Provenance Reporting and Scientific Software Management in Virtual L...
Standard Provenance Reporting and Scientific Software Management in Virtual L...Standard Provenance Reporting and Scientific Software Management in Virtual L...
Standard Provenance Reporting and Scientific Software Management in Virtual L...
njcar
 
Advanced Automated Analytics Using OSS Tools, GA Tech FDA Conference 2016
Advanced Automated Analytics Using OSS Tools, GA Tech FDA Conference 2016Advanced Automated Analytics Using OSS Tools, GA Tech FDA Conference 2016
Advanced Automated Analytics Using OSS Tools, GA Tech FDA Conference 2016
Grid Protection Alliance
 
Informix - The Ideal Database for IoT
Informix - The Ideal Database for IoTInformix - The Ideal Database for IoT
Informix - The Ideal Database for IoT
Pradeep Natarajan
 
Serverless SQL
Serverless SQLServerless SQL
Serverless SQL
Torsten Steinbach
 
Introduction to Apache Geode (Cork, Ireland)
Introduction to Apache Geode (Cork, Ireland)Introduction to Apache Geode (Cork, Ireland)
Introduction to Apache Geode (Cork, Ireland)
Anthony Baker
 
Hypermedia for Machine APIs
Hypermedia for Machine APIsHypermedia for Machine APIs
Hypermedia for Machine APIs
Michael Koster
 
Apache Geode Meetup, Cork, Ireland at CIT
Apache Geode Meetup, Cork, Ireland at CITApache Geode Meetup, Cork, Ireland at CIT
Apache Geode Meetup, Cork, Ireland at CIT
Apache Geode
 
FIWARE Global Summit - The Way Towards Interoperability between Web Of Things...
FIWARE Global Summit - The Way Towards Interoperability between Web Of Things...FIWARE Global Summit - The Way Towards Interoperability between Web Of Things...
FIWARE Global Summit - The Way Towards Interoperability between Web Of Things...
FIWARE
 
Ietf91 ad hoc-coap-lwm2m-ipso
Ietf91 ad hoc-coap-lwm2m-ipsoIetf91 ad hoc-coap-lwm2m-ipso
Ietf91 ad hoc-coap-lwm2m-ipso
Michael Koster
 
Data saturday malta - ADX Azure Data Explorer overview
Data saturday malta - ADX Azure Data Explorer overviewData saturday malta - ADX Azure Data Explorer overview
Data saturday malta - ADX Azure Data Explorer overview
Riccardo Zamana
 
Connecting to the internet of things (IoT)
Connecting to the internet of things (IoT)Connecting to the internet of things (IoT)
Connecting to the internet of things (IoT)
Fernando Lopez Aguilar
 
IoT Stream: A Lightweight Ontology for Internet of Things Data Streams (GIoTS...
IoT Stream: A Lightweight Ontology for Internet of Things Data Streams (GIoTS...IoT Stream: A Lightweight Ontology for Internet of Things Data Streams (GIoTS...
IoT Stream: A Lightweight Ontology for Internet of Things Data Streams (GIoTS...
Tarek Elsaleh
 
Building Fast Applications for Streaming Data
Building Fast Applications for Streaming DataBuilding Fast Applications for Streaming Data
Building Fast Applications for Streaming Data
freshdatabos
 
Data Science with the Help of Metadata
Data Science with the Help of MetadataData Science with the Help of Metadata
Data Science with the Help of Metadata
Jim Dowling
 
DataStax and Esri: Geotemporal IoT Search and Analytics
DataStax and Esri: Geotemporal IoT Search and AnalyticsDataStax and Esri: Geotemporal IoT Search and Analytics
DataStax and Esri: Geotemporal IoT Search and Analytics
DataStax Academy
 
A machine learning and data science pipeline for real companies
A machine learning and data science pipeline for real companiesA machine learning and data science pipeline for real companies
A machine learning and data science pipeline for real companies
DataWorks Summit
 
Using Data Lakes: Data Analytics Week SF
Using Data Lakes: Data Analytics Week SFUsing Data Lakes: Data Analytics Week SF
Using Data Lakes: Data Analytics Week SF
Amazon Web Services
 

Similar to WOTS2E: A Search Engine for a Semantic Web of Things (20)

Do ”Web of Things Platforms” Truly Follow the Web of Things?
Do ”Web of Things Platforms” Truly Follow the Web of Things?Do ”Web of Things Platforms” Truly Follow the Web of Things?
Do ”Web of Things Platforms” Truly Follow the Web of Things?
 
Standard Provenance Reporting and Scientific Software Management in Virtual L...
Standard Provenance Reporting and Scientific Software Management in Virtual L...Standard Provenance Reporting and Scientific Software Management in Virtual L...
Standard Provenance Reporting and Scientific Software Management in Virtual L...
 
Design patternsforiot
Design patternsforiotDesign patternsforiot
Design patternsforiot
 
Advanced Automated Analytics Using OSS Tools, GA Tech FDA Conference 2016
Advanced Automated Analytics Using OSS Tools, GA Tech FDA Conference 2016Advanced Automated Analytics Using OSS Tools, GA Tech FDA Conference 2016
Advanced Automated Analytics Using OSS Tools, GA Tech FDA Conference 2016
 
Informix - The Ideal Database for IoT
Informix - The Ideal Database for IoTInformix - The Ideal Database for IoT
Informix - The Ideal Database for IoT
 
Serverless SQL
Serverless SQLServerless SQL
Serverless SQL
 
Introduction to Apache Geode (Cork, Ireland)
Introduction to Apache Geode (Cork, Ireland)Introduction to Apache Geode (Cork, Ireland)
Introduction to Apache Geode (Cork, Ireland)
 
Hypermedia for Machine APIs
Hypermedia for Machine APIsHypermedia for Machine APIs
Hypermedia for Machine APIs
 
Apache Geode Meetup, Cork, Ireland at CIT
Apache Geode Meetup, Cork, Ireland at CITApache Geode Meetup, Cork, Ireland at CIT
Apache Geode Meetup, Cork, Ireland at CIT
 
FIWARE Global Summit - The Way Towards Interoperability between Web Of Things...
FIWARE Global Summit - The Way Towards Interoperability between Web Of Things...FIWARE Global Summit - The Way Towards Interoperability between Web Of Things...
FIWARE Global Summit - The Way Towards Interoperability between Web Of Things...
 
Ietf91 ad hoc-coap-lwm2m-ipso
Ietf91 ad hoc-coap-lwm2m-ipsoIetf91 ad hoc-coap-lwm2m-ipso
Ietf91 ad hoc-coap-lwm2m-ipso
 
Data saturday malta - ADX Azure Data Explorer overview
Data saturday malta - ADX Azure Data Explorer overviewData saturday malta - ADX Azure Data Explorer overview
Data saturday malta - ADX Azure Data Explorer overview
 
Connecting to the internet of things (IoT)
Connecting to the internet of things (IoT)Connecting to the internet of things (IoT)
Connecting to the internet of things (IoT)
 
IoT Stream: A Lightweight Ontology for Internet of Things Data Streams (GIoTS...
IoT Stream: A Lightweight Ontology for Internet of Things Data Streams (GIoTS...IoT Stream: A Lightweight Ontology for Internet of Things Data Streams (GIoTS...
IoT Stream: A Lightweight Ontology for Internet of Things Data Streams (GIoTS...
 
Bertenthal
BertenthalBertenthal
Bertenthal
 
Building Fast Applications for Streaming Data
Building Fast Applications for Streaming DataBuilding Fast Applications for Streaming Data
Building Fast Applications for Streaming Data
 
Data Science with the Help of Metadata
Data Science with the Help of MetadataData Science with the Help of Metadata
Data Science with the Help of Metadata
 
DataStax and Esri: Geotemporal IoT Search and Analytics
DataStax and Esri: Geotemporal IoT Search and AnalyticsDataStax and Esri: Geotemporal IoT Search and Analytics
DataStax and Esri: Geotemporal IoT Search and Analytics
 
A machine learning and data science pipeline for real companies
A machine learning and data science pipeline for real companiesA machine learning and data science pipeline for real companies
A machine learning and data science pipeline for real companies
 
Using Data Lakes: Data Analytics Week SF
Using Data Lakes: Data Analytics Week SFUsing Data Lakes: Data Analytics Week SF
Using Data Lakes: Data Analytics Week SF
 

More from Andreas Kamilaris

Experiences from the use of CovTracer: A contact tracing tool deployed in Cyp...
Experiences from the use of CovTracer: A contact tracing tool deployed in Cyp...Experiences from the use of CovTracer: A contact tracing tool deployed in Cyp...
Experiences from the use of CovTracer: A contact tracing tool deployed in Cyp...
Andreas Kamilaris
 
Transferring manure from livestock farms to be used as fertilizer in crop fields
Transferring manure from livestock farms to be used as fertilizer in crop fieldsTransferring manure from livestock farms to be used as fertilizer in crop fields
Transferring manure from livestock farms to be used as fertilizer in crop fields
Andreas Kamilaris
 
Training deep learning models to count using synthetic images
Training deep learning models to count using synthetic imagesTraining deep learning models to count using synthetic images
Training deep learning models to count using synthetic images
Andreas Kamilaris
 
Geospatial Analysis and Internet of Things in Environmental Informatics
Geospatial Analysis and Internet of Things in Environmental InformaticsGeospatial Analysis and Internet of Things in Environmental Informatics
Geospatial Analysis and Internet of Things in Environmental Informatics
Andreas Kamilaris
 
A Review on the Application of Natural Computing in Environmental Informatics
A Review on the Application of Natural Computing in Environmental InformaticsA Review on the Application of Natural Computing in Environmental Informatics
A Review on the Application of Natural Computing in Environmental Informatics
Andreas Kamilaris
 
The evolution of pervasive computing towards a Web of Things
The evolution of pervasive computing towards a Web of ThingsThe evolution of pervasive computing towards a Web of Things
The evolution of pervasive computing towards a Web of Things
Andreas Kamilaris
 
AgriBigCAT: An Online Platform for Estimating the Impact of Livestock Agricul...
AgriBigCAT: An Online Platform for Estimating the Impact of Livestock Agricul...AgriBigCAT: An Online Platform for Estimating the Impact of Livestock Agricul...
AgriBigCAT: An Online Platform for Estimating the Impact of Livestock Agricul...
Andreas Kamilaris
 
Estimating the Environmental Impact of Agriculture by means of Geospatial and...
Estimating the Environmental Impact of Agriculture by means of Geospatial and...Estimating the Environmental Impact of Agriculture by means of Geospatial and...
Estimating the Environmental Impact of Agriculture by means of Geospatial and...
Andreas Kamilaris
 
Disaster Monitoring using Unmanned Aerial Vehicles and Deep Learning
Disaster Monitoring using Unmanned Aerial Vehicles and Deep LearningDisaster Monitoring using Unmanned Aerial Vehicles and Deep Learning
Disaster Monitoring using Unmanned Aerial Vehicles and Deep Learning
Andreas Kamilaris
 
A Web of Things Based Eco-System for Urban Computing - Towards Smarter Cities
A Web of Things Based Eco-System for Urban Computing - Towards Smarter CitiesA Web of Things Based Eco-System for Urban Computing - Towards Smarter Cities
A Web of Things Based Eco-System for Urban Computing - Towards Smarter Cities
Andreas Kamilaris
 
Big data analysis and Integration of Geophysical information from the Catalan...
Big data analysis and Integration of Geophysical information from the Catalan...Big data analysis and Integration of Geophysical information from the Catalan...
Big data analysis and Integration of Geophysical information from the Catalan...
Andreas Kamilaris
 
Estimating the Impact of Agriculture on the Environment of Catalunya by means...
Estimating the Impact of Agriculture on the Environment of Catalunya by means...Estimating the Impact of Agriculture on the Environment of Catalunya by means...
Estimating the Impact of Agriculture on the Environment of Catalunya by means...
Andreas Kamilaris
 
Agri-IoT: A Semantic Framework for Internet of Things-enabled Smart Farming A...
Agri-IoT: A Semantic Framework for Internet of Things-enabled Smart Farming A...Agri-IoT: A Semantic Framework for Internet of Things-enabled Smart Farming A...
Agri-IoT: A Semantic Framework for Internet of Things-enabled Smart Farming A...
Andreas Kamilaris
 
Enabling the physical world to the Internet and potential benefits for agricu...
Enabling the physical world to the Internet and potential benefits for agricu...Enabling the physical world to the Internet and potential benefits for agricu...
Enabling the physical world to the Internet and potential benefits for agricu...
Andreas Kamilaris
 
Privacy Concerns in Sharing Personal Consumption Data through Online Applicat...
Privacy Concerns in Sharing Personal Consumption Data through Online Applicat...Privacy Concerns in Sharing Personal Consumption Data through Online Applicat...
Privacy Concerns in Sharing Personal Consumption Data through Online Applicat...
Andreas Kamilaris
 
Social Electricity User Manual
Social Electricity User ManualSocial Electricity User Manual
Social Electricity User Manual
Andreas Kamilaris
 
Social Electricity
Social ElectricitySocial Electricity
Social Electricity
Andreas Kamilaris
 
Social Electricity Online Platform (SEOP) EU Project Description
Social Electricity Online Platform (SEOP) EU Project DescriptionSocial Electricity Online Platform (SEOP) EU Project Description
Social Electricity Online Platform (SEOP) EU Project Description
Andreas Kamilaris
 
How the Internet can motivate you to switch off the lights
How the Internet can motivate you to switch off the lightsHow the Internet can motivate you to switch off the lights
How the Internet can motivate you to switch off the lights
Andreas Kamilaris
 
Good Practices in the Use of ICT Equipment for Electricity Savings at a Unive...
Good Practices in the Use of ICT Equipment for Electricity Savings at a Unive...Good Practices in the Use of ICT Equipment for Electricity Savings at a Unive...
Good Practices in the Use of ICT Equipment for Electricity Savings at a Unive...
Andreas Kamilaris
 

More from Andreas Kamilaris (20)

Experiences from the use of CovTracer: A contact tracing tool deployed in Cyp...
Experiences from the use of CovTracer: A contact tracing tool deployed in Cyp...Experiences from the use of CovTracer: A contact tracing tool deployed in Cyp...
Experiences from the use of CovTracer: A contact tracing tool deployed in Cyp...
 
Transferring manure from livestock farms to be used as fertilizer in crop fields
Transferring manure from livestock farms to be used as fertilizer in crop fieldsTransferring manure from livestock farms to be used as fertilizer in crop fields
Transferring manure from livestock farms to be used as fertilizer in crop fields
 
Training deep learning models to count using synthetic images
Training deep learning models to count using synthetic imagesTraining deep learning models to count using synthetic images
Training deep learning models to count using synthetic images
 
Geospatial Analysis and Internet of Things in Environmental Informatics
Geospatial Analysis and Internet of Things in Environmental InformaticsGeospatial Analysis and Internet of Things in Environmental Informatics
Geospatial Analysis and Internet of Things in Environmental Informatics
 
A Review on the Application of Natural Computing in Environmental Informatics
A Review on the Application of Natural Computing in Environmental InformaticsA Review on the Application of Natural Computing in Environmental Informatics
A Review on the Application of Natural Computing in Environmental Informatics
 
The evolution of pervasive computing towards a Web of Things
The evolution of pervasive computing towards a Web of ThingsThe evolution of pervasive computing towards a Web of Things
The evolution of pervasive computing towards a Web of Things
 
AgriBigCAT: An Online Platform for Estimating the Impact of Livestock Agricul...
AgriBigCAT: An Online Platform for Estimating the Impact of Livestock Agricul...AgriBigCAT: An Online Platform for Estimating the Impact of Livestock Agricul...
AgriBigCAT: An Online Platform for Estimating the Impact of Livestock Agricul...
 
Estimating the Environmental Impact of Agriculture by means of Geospatial and...
Estimating the Environmental Impact of Agriculture by means of Geospatial and...Estimating the Environmental Impact of Agriculture by means of Geospatial and...
Estimating the Environmental Impact of Agriculture by means of Geospatial and...
 
Disaster Monitoring using Unmanned Aerial Vehicles and Deep Learning
Disaster Monitoring using Unmanned Aerial Vehicles and Deep LearningDisaster Monitoring using Unmanned Aerial Vehicles and Deep Learning
Disaster Monitoring using Unmanned Aerial Vehicles and Deep Learning
 
A Web of Things Based Eco-System for Urban Computing - Towards Smarter Cities
A Web of Things Based Eco-System for Urban Computing - Towards Smarter CitiesA Web of Things Based Eco-System for Urban Computing - Towards Smarter Cities
A Web of Things Based Eco-System for Urban Computing - Towards Smarter Cities
 
Big data analysis and Integration of Geophysical information from the Catalan...
Big data analysis and Integration of Geophysical information from the Catalan...Big data analysis and Integration of Geophysical information from the Catalan...
Big data analysis and Integration of Geophysical information from the Catalan...
 
Estimating the Impact of Agriculture on the Environment of Catalunya by means...
Estimating the Impact of Agriculture on the Environment of Catalunya by means...Estimating the Impact of Agriculture on the Environment of Catalunya by means...
Estimating the Impact of Agriculture on the Environment of Catalunya by means...
 
Agri-IoT: A Semantic Framework for Internet of Things-enabled Smart Farming A...
Agri-IoT: A Semantic Framework for Internet of Things-enabled Smart Farming A...Agri-IoT: A Semantic Framework for Internet of Things-enabled Smart Farming A...
Agri-IoT: A Semantic Framework for Internet of Things-enabled Smart Farming A...
 
Enabling the physical world to the Internet and potential benefits for agricu...
Enabling the physical world to the Internet and potential benefits for agricu...Enabling the physical world to the Internet and potential benefits for agricu...
Enabling the physical world to the Internet and potential benefits for agricu...
 
Privacy Concerns in Sharing Personal Consumption Data through Online Applicat...
Privacy Concerns in Sharing Personal Consumption Data through Online Applicat...Privacy Concerns in Sharing Personal Consumption Data through Online Applicat...
Privacy Concerns in Sharing Personal Consumption Data through Online Applicat...
 
Social Electricity User Manual
Social Electricity User ManualSocial Electricity User Manual
Social Electricity User Manual
 
Social Electricity
Social ElectricitySocial Electricity
Social Electricity
 
Social Electricity Online Platform (SEOP) EU Project Description
Social Electricity Online Platform (SEOP) EU Project DescriptionSocial Electricity Online Platform (SEOP) EU Project Description
Social Electricity Online Platform (SEOP) EU Project Description
 
How the Internet can motivate you to switch off the lights
How the Internet can motivate you to switch off the lightsHow the Internet can motivate you to switch off the lights
How the Internet can motivate you to switch off the lights
 
Good Practices in the Use of ICT Equipment for Electricity Savings at a Unive...
Good Practices in the Use of ICT Equipment for Electricity Savings at a Unive...Good Practices in the Use of ICT Equipment for Electricity Savings at a Unive...
Good Practices in the Use of ICT Equipment for Electricity Savings at a Unive...
 

Recently uploaded

Building RAG with self-deployed Milvus vector database and Snowpark Container...
Building RAG with self-deployed Milvus vector database and Snowpark Container...Building RAG with self-deployed Milvus vector database and Snowpark Container...
Building RAG with self-deployed Milvus vector database and Snowpark Container...
Zilliz
 
GridMate - End to end testing is a critical piece to ensure quality and avoid...
GridMate - End to end testing is a critical piece to ensure quality and avoid...GridMate - End to end testing is a critical piece to ensure quality and avoid...
GridMate - End to end testing is a critical piece to ensure quality and avoid...
ThomasParaiso2
 
UiPath Test Automation using UiPath Test Suite series, part 5
UiPath Test Automation using UiPath Test Suite series, part 5UiPath Test Automation using UiPath Test Suite series, part 5
UiPath Test Automation using UiPath Test Suite series, part 5
DianaGray10
 
A tale of scale & speed: How the US Navy is enabling software delivery from l...
A tale of scale & speed: How the US Navy is enabling software delivery from l...A tale of scale & speed: How the US Navy is enabling software delivery from l...
A tale of scale & speed: How the US Navy is enabling software delivery from l...
sonjaschweigert1
 
Communications Mining Series - Zero to Hero - Session 1
Communications Mining Series - Zero to Hero - Session 1Communications Mining Series - Zero to Hero - Session 1
Communications Mining Series - Zero to Hero - Session 1
DianaGray10
 
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Albert Hoitingh
 
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
Neo4j
 
RESUME BUILDER APPLICATION Project for students
RESUME BUILDER APPLICATION Project for studentsRESUME BUILDER APPLICATION Project for students
RESUME BUILDER APPLICATION Project for students
KAMESHS29
 
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
SOFTTECHHUB
 
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex Proofs
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofszkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex Proofs
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex Proofs
Alex Pruden
 
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
James Anderson
 
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
DanBrown980551
 
Monitoring Java Application Security with JDK Tools and JFR Events
Monitoring Java Application Security with JDK Tools and JFR EventsMonitoring Java Application Security with JDK Tools and JFR Events
Monitoring Java Application Security with JDK Tools and JFR Events
Ana-Maria Mihalceanu
 
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
James Anderson
 
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
名前 です男
 
20240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 202420240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 2024
Matthew Sinclair
 
Large Language Model (LLM) and it’s Geospatial Applications
Large Language Model (LLM) and it’s Geospatial ApplicationsLarge Language Model (LLM) and it’s Geospatial Applications
Large Language Model (LLM) and it’s Geospatial Applications
Rohit Gautam
 
Securing your Kubernetes cluster_ a step-by-step guide to success !
Securing your Kubernetes cluster_ a step-by-step guide to success !Securing your Kubernetes cluster_ a step-by-step guide to success !
Securing your Kubernetes cluster_ a step-by-step guide to success !
KatiaHIMEUR1
 
How to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptxHow to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptx
danishmna97
 
Mind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AIMind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AI
Kumud Singh
 

Recently uploaded (20)

Building RAG with self-deployed Milvus vector database and Snowpark Container...
Building RAG with self-deployed Milvus vector database and Snowpark Container...Building RAG with self-deployed Milvus vector database and Snowpark Container...
Building RAG with self-deployed Milvus vector database and Snowpark Container...
 
GridMate - End to end testing is a critical piece to ensure quality and avoid...
GridMate - End to end testing is a critical piece to ensure quality and avoid...GridMate - End to end testing is a critical piece to ensure quality and avoid...
GridMate - End to end testing is a critical piece to ensure quality and avoid...
 
UiPath Test Automation using UiPath Test Suite series, part 5
UiPath Test Automation using UiPath Test Suite series, part 5UiPath Test Automation using UiPath Test Suite series, part 5
UiPath Test Automation using UiPath Test Suite series, part 5
 
A tale of scale & speed: How the US Navy is enabling software delivery from l...
A tale of scale & speed: How the US Navy is enabling software delivery from l...A tale of scale & speed: How the US Navy is enabling software delivery from l...
A tale of scale & speed: How the US Navy is enabling software delivery from l...
 
Communications Mining Series - Zero to Hero - Session 1
Communications Mining Series - Zero to Hero - Session 1Communications Mining Series - Zero to Hero - Session 1
Communications Mining Series - Zero to Hero - Session 1
 
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
 
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
 
RESUME BUILDER APPLICATION Project for students
RESUME BUILDER APPLICATION Project for studentsRESUME BUILDER APPLICATION Project for students
RESUME BUILDER APPLICATION Project for students
 
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
 
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex Proofs
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofszkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex Proofs
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex Proofs
 
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
 
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
 
Monitoring Java Application Security with JDK Tools and JFR Events
Monitoring Java Application Security with JDK Tools and JFR EventsMonitoring Java Application Security with JDK Tools and JFR Events
Monitoring Java Application Security with JDK Tools and JFR Events
 
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
 
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
 
20240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 202420240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 2024
 
Large Language Model (LLM) and it’s Geospatial Applications
Large Language Model (LLM) and it’s Geospatial ApplicationsLarge Language Model (LLM) and it’s Geospatial Applications
Large Language Model (LLM) and it’s Geospatial Applications
 
Securing your Kubernetes cluster_ a step-by-step guide to success !
Securing your Kubernetes cluster_ a step-by-step guide to success !Securing your Kubernetes cluster_ a step-by-step guide to success !
Securing your Kubernetes cluster_ a step-by-step guide to success !
 
How to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptxHow to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptx
 
Mind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AIMind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AI
 

WOTS2E: A Search Engine for a Semantic Web of Things

  • 1. WOTS2E: A Search Engine for a Semantic Web of Things Unit for Reasoning, Querying and Stream Processing Insight Centre for Data Analytics, National University of Ireland, Galway Andreas Kamilaris, Semih Yumusak, Ali Intizar World Forum – IoT 2016 Reston, VA, USA- December 12-14, 2016
  • 2. https://www.w3.org/WoT/images/iot.png Web of Things • Designed to connect “things” to the Web • A combination of • Approaches • Software Architectures • Interfaces
  • 3. https://www.w3.org/WoT/images/iot.png • Increase Interoperability among IoT platforms • Mitigate Silo Architecture • Avoid Multiple and Conflicting Standards • Global and Easy Discovery of Devices Why we need Web of Things?
  • 4. • Few of the emerging WoT platforms • Sorcades • ThingWorx • SpitFire • Evrythng • Open.Sen.se • WoTKit • Auto WoT • Xively Web of Things Platforms
  • 5. • Can we improve the discoverability of Web of Things? • Can we use semantic technologies to improve device discoverability? • Are there any datasets produced by WoT devices available as Open Data on the Web? • Can we create a global and distributed index for search and discovery of WoT devices? Our Motivation
  • 6. Discovery • Machines needs to automatically discover devices/things and their description • Global repositories • Indexing Things and their description • Semantic Annotation to describe things • SPARQL queries and data endpoints • Discover devices on the fly (Late Binding) Slide Source: ISWC 2016, Tutorial on Semantic Web Meets IoT/WoT (Soumya Kanti Datta)
  • 7. Repository Based Discovery Slide Source: ISWC 2016, Tutorial on Semantic Web Meets IoT/WoT (Soumya Kanti Datta)
  • 8. Device Discovery Mechanisms • Spatial Search – BLE beacon based things • Network Based Search – mDNS, multicast CoAP • Device Registration Directories – CoRE resource directory, XMPP IoT directory, HyperCat • Meta-Data Discovery – CoRE Link Format • Semantic Search and Discovery Techniqyes – Offers high richness in search queries • E.g. “search for all light bulbs in my house” Slide Source: ISWC 2016, Tutorial on Semantic Web Meets IoT/WoT (Soumya Kanti Datta)
  • 9. Semantic Search & Discovery: Key Challenges • Optimal Data Source Discovery • Streams are everywhere • Multiple data streams can answer the same query • Optimal data stream selection • Catering for user-defined constraints and preferences • On-Demand Stream Federation • Automated composition of primitive data streams to answer complex queries • Adaptation • Data source properties can change over time • Make sure selected sources remain “optimal” throughout life cycle of the query
  • 10. Stream Discovery, Federation and Adaptation • Stream Discovery – Data interoperability: • Semantic descriptions (ontologies and annotations) – Interface interoperability: • Streams as event services (service discovery) • Stream Federation – Efficient processing of complicated event logics • Data Stream Management Systems • Complex Event Processing Semantic Web Service Oriented Architectures DSMS and CEP
  • 11. Semantic Description • A sensor service description is annotated as: sdesc = (td, g, qd, Pd, FoId, fd) type grounding QoS Observed Properties Feature Of Iterest Pd → FoId • Similarly, a sensor service request is annotated: sr = (tr, Pr, FoIr, fr, pref, C) type Requested Properties Feature of Interest Pd → FoId no grounding NFP Constraint and Preferences
  • 12. Middle-ware for Stream Discovery and Federation Semantic Annotation ACEIS Core Resource Management Application Interface Knowledge Base QoI/QoS Stream Description Data Mgmt, Indexing, Caching User Input Event Request Data Federation Resource Discovery Event Service Composer Composition Plan Subscription Manager Query Transformer Query Engine Query Results Constraint Validation Constraint Violation Adaptation Manager Data Store IoT Data Stream Social Data Stream
  • 13. Web of Things Discovery • Optimal Data Source Discovery • Web of Things Search Space is Global • Across the whole Web • Indexing • Geo-Spatial Mapping • Movable Objects/Things • Require Frequent Updates in Indexes
  • 15. WOTS2E: ArchitectureWOTS2E: Overview • A Search engine to discover semantic meta- description of things • Crawls the Web to discover Linked Data Sources • Analyzes Linked Data sources to identify relevant WoT devices
  • 16. WOTS2E: ArchitectureWOTS2E: Overview • Maintain a registry of devices for discovery • Support application request and provide details to interact with the devices.
  • 17. WOTS2E: ArchitectureWOTS2E: Operations • Discovery of Linked Data Endpoints – Web crawlers that continuously scan the web for discovery of Linked Data endpoints, frequency of one scan per day • Examination of Discovered Linked Data Endpoints – Query endpoints for IoT/WoT relevant ontologies – Explore popular dataset descriptions, such as VoID, SPARQL-SD • Analysis of Linked Data Endpoints and WoT Device Discovery – Through SPARQL queries, VoID/SPARQL- SD files, use of open APIs • Recording of WoT Devices and Services Discovered – Service type, location, time, features, interaction types, restrictions etc.
  • 18. WOTS2E: ArchitectureWOTS2E: Implementation/Analysis Common Patterns <meta name=”Keywords” content=”OpenLink Virtuoso Sparql”> Virtuoso SPARQL Query Editor OpenLink Software <label for=”debug”>Strict checking of void variables</label> <a href=”http://www.openlinksw.com/virtuoso” > <a href=”/isparql”>iSPARQL</a> <label for=”query”>Query text</label> • SPARQL Endpoint Listed at Datahub.io • Common Patterns Identification • SPARQL endpoint discovery
  • 19. WOTS2E: ArchitectureWOTS2E: Implementation/Analysis • Discovered patterns are used as an input to our web crawlers, in order to search the web for available SPARQL endpoints. • For web crawling, we used a meta-crawling service called SpEnD. • SpEnD exploits the search functionality available over popular search engines to accelerate the performance of web crawling.
  • 20. WOTS2E: ArchitectureWOTS2E: Implementation/Analysis • To analyze the URLs retrieved, the Jena Framework was used to send SPARQL queries to the candidate endpoints, checking whether they are valid SPARQL endpoints or not. • All valid SPARQL endpoints were examined whether they contain information related to IoT/WoT, i.e. contained relevant ontologies. SELECT DISTINCT ?Concept WHERE {[] a ?Concept} LIMIT 100 SELECT * WHERE {{?s ?p ?o} UNION {GRAPH ?g {?s ?p ?o}} FILTER regex(?o, "/SSN"). FILTER isIRI(?o).
  • 21. • After labeling some SPARQL endpoint as related to IoT/WoT, the next step was to analyze it, discovering which devices/services are available through it: VoID file adapted to reveal information about WoT devices and services Extend SSN to include discovery and description information through some ontology that describes web services. :ExampleDataset a void:Dataset; void:subset :ExampleSensor . :ExampleSensor a void:Dataset; dcterms:title "WoT Example Sensor"; dcterms:description "http://../sens.wadl"; dcterms:contributor "Insight Centre"; dcterms:source "140.203.154.11" WOTS2E: Implementation/Analysis
  • 22. WOTS2E: ArchitectureWOTS2E: Implementation/Analysis • Information about SPARQL endpoints, devices/services discovered and sensor meta-data information was stored as RDF triples on a Virtuoso RDF store, installed on WOTS2E. • Use of the IoT ontologyPrefix iot: <http://purl.org/IoT/iot#> Prefix ssn: <http://purl.oclc.org/../ssn#> SELECT ?sm ?device ?service WHERE { ?sm a iot:smart_entity ?sm iot:has_part_device ?device ?device ssn:observes ?service ?service a iot:Temperature }
  • 23. WOTS2E: ArchitectureWOTS2E: Evaluation • The SpEnD (meta-)crawling service ran for 24 hours • Using the common patterns for SPARQL endpoints • Relevant URLs from the Bing, Yahoo, Google, Baidu, and Yandex search engines. • Comparison of discovered endpoints with Datahub. Active Inactive Total WOTS2E 638 640 1278 Datahub 258 296 554
  • 24. WOTS2E: ArchitectureWOTS2E: Evaluation • From the discovered 638 active SPARQL endpoints, we examined them one by one for relevance to IoT/WoT Ontology Number of Endpoints SSN 13 DBPedia 13 SmartBuilding 3 DogOnt 2 DUL 2 km4city 2 OpenEI 2 RDFS, SKOS 4 Fan Fpai, Fiemser, IoT, PROV, SAREF 5 (once each ontology)
  • 25. WOTS2E: ArchitectureWOTS2E: Evaluation • IoT/WoT-specific triples from the endpoints Ontology Number of Triples SSN 1.433,248 DUL 182 km4city 56 Fiemser 50 OpenIoT 44 SmartBuilding 36 DogOnt 24 SAREF 4 Fan Fpai 2
  • 26. Conclusion • Semantic Search and Discovery is essential for Web of Things • Currently only a handful of available SPARQL endpoints (46, 7.2%) seem to relate to IoT/WoT. • Lack of meta data availability • Need for standardization for discovery mechanisms • Our method aims to suggest a solid proposal on how to achieve discovery on SWoT seamlessly and with minimum effort. • WOTS2E can support applications looking for on the fly discovery and integration of devices
  • 27. Future Work • Improve Search mechanism by designing good vocabularies/ontologies and descriptions for IoT/WoT devices, services and data. • A user-friendly website of WOTS2E, to incrementally let users to access the discovered lists of services in a well- organized way. • From meta-crawling to efficient (classical) web crawling. • Contribute to the standardization efforts on the WoT (W3C WoT IG, OGC Sensor Web Interface for IoT SWG), promoting WOTS2E as a viable solution for a SWoT search engine.