SlideShare uma empresa Scribd logo
1 de 30
Baixar para ler offline
KIT – The Research University in the Helmholtz Association www.kit.edu
Institute of Applied Informatics and Formal Description Methods (AIFB), Karlsruhe Service Research Institute (KSRI),
FZI Research Center for Information Technology
Semantic Technologies for Smart Services
Rudi Studer & Maria Maleshkova
Cognitive Systems Institute Speaker Series, 15 December 2016
Institute of Applied Informatics and Formal
Description Methods (AIFB)
2
“Semantic Karlsruhe”
Industrie 4.0
Medicine &
eHealth
Digital Shift
Big Data &
Data Analytics
SEMANTIC TECHNOLOGIES
Semantic
Data Management
Complex Event
Processing
Data / Text Mining
Smart
Services
Basic
Research
Applied
Research
Transfer
Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
Institute of Applied Informatics and Formal
Description Methods (AIFB)
3
WEB SCIENCE AND
KNOWLEDGE MANAGEMENT
Institute of Applied
Informatics and Formal
Description Methods
Institute of Applied Informatics and Formal
Description Methods (AIFB)
4
Karlsruhe Service Research Institute – an „industry-on-
campus“ model with focus on interdisciplinary research
  

 

Prof. Dr. Christof
Weinhardt
Information & Market
Engineering
Prof. Dr. Gerhard
Satzger
Digital Service
Innovation
Prof. Dr. Stefan Nickel
Discrete Optimization
& Logistics
Prof. Dr. Wolf Fichtner
Energy Economics
Prof. Dr. Alexander
Mädche
Information Systems &
Service Design
Prof. Dr. Rudi Studer
Knowledge Management
Prof. Dr. York Sure-
Vetter
Prof. Dr. Kai Furmans
Value Stream Services
Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
Dr. Markus Bauer
Institute of Applied Informatics and Formal
Description Methods (AIFB)
5
Service Research investigates complex service systems where
economic value is created jointly by multiple independent parties, acting
together efficiently through the systematic use of information and
communication technologies…
…from different perspectives and in different domains
... and others
Healthcare
Services
Crowd and
Participation
Services
(e)-Mobility
Smart
Services,
Industry 4.0
and IoT
Research Focus:
Intelligent Services for Real-world Networks
Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
Institute of Applied Informatics and Formal
Description Methods (AIFB)
6
• Motivation
• Why Smart Services via Semantic Technologies?
• Use Case 1 - Building Agile Systems
• Use Case 2 – Smart Services for Predictive
Maintenance
• Summary and Conclusions
Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
Institute of Applied Informatics and Formal
Description Methods (AIFB)
7
Market
Influence
Technology
Development
Today’s Driving Forces
Shorter innovation cycles
Need for continuous adaptation
Near real-time analyses
Involvement of the customer not only with
the finished product/service but during the
complete development cycle
Ubiquitous access
Social and community Web
Heterogeneous big data
Distributed component-based
solutions
Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
Institute of Applied Informatics and Formal
Description Methods (AIFB)
8
Internet of Things (IoT) Challenges
We expect one hundred billion IoT devices to be deployed
within the next ten years
BUT the IoT is currently facing a lot of problems
Product silos that do not interoperate with each other
Many approaches and incompatible platforms
No network effect
Heterogeneity in terms of
Data
Devices and interfaces
Data volumes and number of sources explode
Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
We expect one hundred billion IoT devices to be deployed
within the next ten years
BUT the IoT is currently facing a lot of problems
Product silos that do not interoperate with each other
Many approaches and incompatible platforms
No network effect
Heterogeneity in terms of
Data
Devices and interfaces
Data volumes and number of sources explode
see: http://www.w3.org/2015/05/wot-framework.pdf
Institute of Applied Informatics and Formal
Description Methods (AIFB)
9
The Web as the Solution
Source: http://www.w3.org/2015/05/wot-framework.pdf
Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
Institute of Applied Informatics and Formal
Description Methods (AIFB)
10
Semantic Technologies for Smart Services
Data Integration – combining data from multiple sources enables
new applications and insights
More and more data available on the Web is published conforming to
Semantic Web standards
Linking Open Data (LOD) initiative
Semantic Web technologies are beneficial for data exchange, integration
and search
Decentralised Architectures – no central controller or repository
Overcoming device heterogeneity – common model for devices
(functional and non-functional properties)
Overcoming interface heterogeneity – standard Web Technologies +
Linked Data
Adaptation – adjusting services, products, things according to context
and current needs
Intelligent Programmable Interfaces
Embedding intelligence into the service interface (e.g. rules)
Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
Institute of Applied Informatics and Formal
Description Methods (AIFB)
11
Semantic Technologies
Semantic Web technologies,
standardised by the W3C, are
mature:
RDF recommendation in 1999,
update in 2004
RDFa (RDF in HTML) note in 2008
RDFS recommendation in 2004
SPARQL recommendation in 2008
OWL recommendation in 2004,
update in 2009
Linked Data is a subset of the
Semantic Web stack
Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
Institute of Applied Informatics and Formal
Description Methods (AIFB)
12
Use Cases
1. Building Agile Systems
Fast integration of data and programmable interfaces based on semantic
technologies
2. Smart Services for Predictive Maintenance
Semantics for integrating sensor data, background knowledge and
decision rules
Recognizing maintenance
needs before they occur
Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
Semantic
description
Semantic
description
Semantic
description
Institute of Applied Informatics and Formal
Description Methods (AIFB)
13
BUILDING AGILE SYSTEMS
Semantics for integrating data and programmable interfaces
Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
Institute of Applied Informatics and Formal
Description Methods (AIFB)
14
Today‘s Web is about Dynamic Data
Data is often dynamically created as a result of some calculation
carried out over input data (e.g., weather information)
Data can change frequently (e.g., moving objects)
APIs are used to trigger functionalities in the Web and the real world
and provide access to dynamic and static data sources
An important role plays
Representational State Transfer
(REST)
Architectural style for client–
server interaction
Compatible with Web architecture
http://programmableweb.com
8816 APIs
Over 16,400 APIs and 7,800 mashups
Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
Institute of Applied Informatics and Formal
Description Methods (AIFB)
15
Linked Data Principles
1. Use URIs to name things; not only documents, but also people, locations,
concepts, etc.
http://dbpedia.org/resource/Johannes_Gutenberg
2. To enable agents (human users and machine agents alike) to look up those
names, use HTTP URIs
http://dbpedia.org/page/Printing_press
3. When someone looks up a URI we provide useful information; with 'useful' in
the strict sense we usually mean structured data in RDF
http://dbpedia.org/page/Printing_press
dct:subject dbc:Johannes_Gutenberg.
4. Include links to other URIs allowing agents (machines and humans) to
discover more things
<http://dbpedia.org/page/Printing_press> rdfs:seeAlso
<http://dbpedia.org/page/Letterpress_printing> .
http://www.w3.org/DesignIssues/LinkedData
Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
Institute of Applied Informatics and Formal
Description Methods (AIFB)
16
Linking Open Data Cloud
Linking Open Data cloud diagram 2014, by Max Schmachtenberg, Christian Bizer, Anja Jentzsch and Richard Cyganiak. http://lod-cloud.net/
Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
Institute of Applied Informatics and Formal
Description Methods (AIFB)
17
Motivation for Combining Semantics and
Services
Increased value comes from combinations of services and
APIs
But a lot of manual effort is required for this compositions (glue code)
Structured service/API descriptions ease the composition process considerably
Semantic descriptions allow for execution of several tasks automatically
(e.g., data matching, discovery, ranking)
Manually drafted
glue code
Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
Semantic
description
Semantic
description
Semantic
description
Institute of Applied Informatics and Formal
Description Methods (AIFB)
18
Motivation for Combining Semantics and
Services
Increased value comes from combinations of services and
APIs
But a lot of manual effort is required for this compositions (glue code)
Structured service/API descriptions ease the composition process considerably
Semantic descriptions allow for execution of several tasks automatically
(e.g., data matching, discovery, ranking)
Manually drafted
glue code
Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
Semantic
description
Semantic
description
Semantic
description
Institute of Applied Informatics and Formal
Description Methods (AIFB)
19
Creating Linked Services
Functionality attainable via the Web by combining:
RESTful services (respecting Web architecture)
resource-oriented
manipulated with HTTP verbs
GET, PUT (, PATCH), POST, DELETE
Negotiate representations
Linked data
Uniform use of URIs
Use of RDF and SPARQL
= Linked Services
Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
Institute of Applied Informatics and Formal
Description Methods (AIFB)
20
Facilitate Data Integration
Linked Service
Combines data (MashUp)
build on top
Application
that consumes one
Linked Service
Bad solution
Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
Institute of Applied Informatics and Formal
Description Methods (AIFB)
21
Facilitate Data Integration
Linked Service
Combines data (MashUp)
build on top
Application
that consumes one
Linked Service
Bad solution
Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
Institute of Applied Informatics and Formal
Description Methods (AIFB)
22
Facilitate Data Integration
Linked
Service
Application
(integrates data and
functionalities from several
Linked Services, e.g. via Linked
Data-Fu)
Good solution
Linked
Service
Linked
Service
Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
http://linked-data-fu.github.io/
Institute of Applied Informatics and Formal
Description Methods (AIFB)
23
SMART SERVICES FOR
PREDICTIVE MAINTENANCE
Semantics for integrating sensor data, background knowledge and
decision rules
Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
Institute of Applied Informatics and Formal
Description Methods (AIFB)
24
Cognition Framework
Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
Perception Reaction
Background
Knowledge
Interpretation and
Analysis
Institute of Applied Informatics and Formal
Description Methods (AIFB)
25
The Cognition Framework for Predictive
Maintenance
Input data in terms of
- Sensor data
- Personal observations
- Alarms and errors
Background knowledge
- Log files
- Previous similar problems
and solutions
- Guidelines
- Manuals
- Detail about the machines
Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
Interpretation and Analysis
- Data integration to enable
analysis
- Similarity analysis with
previous problems
- Heuristics encoded as rules
Reaction
- Automated solution
recommendation vs.
- Providing solution support
Institute of Applied Informatics and Formal
Description Methods (AIFB)
26
Problem Breakdown
1. Smart Services for Problem Recognition
Recognizing what the current problem is based on previous problems
Combination with heuristics
2. Smart Services for preparing Solution Containers
Providing summary of the problem, difficulty, time estimate
Links to relevant manuals, links to required parts
Required expertise, contacts of people with relevant qualifications
Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
?
http://www.aifb.kit.edu/web/STEP/en
Institute of Applied Informatics and Formal
Description Methods (AIFB)
27
Problem Breakdown
2. Smart Services for preparing Solution Containers (continued)
Dealing with multilingual and multimodal sources
Identifying related articles across different languages and media types
Possible use – the solution might be available in another language;
images and videos can be used to identify the problem, support the solution
3. Smart Services for Interactive
Problem Solving
Guiding the user towards the solution
Recommending the next possible step
Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
http://xlime.eu/
Institute of Applied Informatics and Formal
Description Methods (AIFB)
28
Problem Breakdown
4. Smart Services for Route Planning for the technician
Supporting the dispatcher in planning the routes
Supporting the technician during the trips
Solution based on Use Case 1: Building Agile Systems
Creating Linked Services for the interfaces
Rules for defining the composition and interaction
Automated execution with Linked DataFu
Prototype system for data / service integration and execution
Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
Proximity service
Street View
Maintenance route-planning
Institute of Applied Informatics and Formal
Description Methods (AIFB)
29
Summary and Outlook
Market trends and technology developments pave the way for
developing new products and services, which are more flexible and
adapted to the customer needs
We need technology solutions to achieve more automation and
adaptability –– putting the ‘Smartness’ into services
Providing means for agile system development
Providing means for self-adaptivity
We can use Semantic Technologies for Smart Services to support:
The rapid development of mashups and applications
To realize Industry 4.0 / IoT solutions
Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
Institute of Applied Informatics and Formal
Description Methods (AIFB)
30
Relevant Publications
S. Stadtmüller, S. Speiser, A. Harth, R. Studer
Data-Fu: A Language and an Interpreter for Interaction with Read/Write Linked Data.
Proceedings of the 22nd International Conference on World Wide Web, pp. 1225-1236, Rio
de Janeiro, 2013.
A. Harth, C. Knoblock, S. Stadtmüller, R. Studer, und P. Szekely. On-the-fly Integration of
Static and Dynamic Sources. Proceedings of the ISWC Workshop
on Consuming Linked Data. 2013: CEUR-WS.
M. Maleshkova, P. Philipp, Y. Sure-Vetter, R. Studer. Smart Web Services (SmartWS) –
The Future of Services on the Web. IPSI BgD Transactions on Advanced Research
(TAR), 12 (1), pp. 15-26, January, 2016.
T. Weller, M. Maleshkova, K. März, L. Maier-Hein. A RESTful Approach for Developing
Medical Decision Support Systems. The Semantic Web: ESWC 2015 Satellite
Events, pp. 376-384, Springer, 9341.
T. Weller, M. Maleshkova. Cognitive Process - An Open-Source Tool to Capture
Processes according to the Linked Data Principles. The Semantic Web: ESWC 2016
Satellite Events, Springer.
L. Zhang, A. Rettinger, J. Zhang. A Knowledge Base Approach to Cross-Lingual
Keyword Query Interpretation. The 15th International Semantic Web Conference
(ISWC'16), Springer, Oktober, 2016
Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series

Mais conteúdo relacionado

Mais procurados

GeeCon Prague 2018 - A Practical-ish Introduction to Data Science
GeeCon Prague 2018 - A Practical-ish Introduction to Data ScienceGeeCon Prague 2018 - A Practical-ish Introduction to Data Science
GeeCon Prague 2018 - A Practical-ish Introduction to Data ScienceMark West
 
Data+Science : A First Course
Data+Science : A First CourseData+Science : A First Course
Data+Science : A First CourseArnab Majumdar
 
Data science vs. Data scientist by Jothi Periasamy
Data science vs. Data scientist by Jothi PeriasamyData science vs. Data scientist by Jothi Periasamy
Data science vs. Data scientist by Jothi PeriasamyPeter Kua
 
Introduction to Data Science
Introduction to Data ScienceIntroduction to Data Science
Introduction to Data ScienceANOOP V S
 
JavaZone 2018 - A Practical(ish) Introduction to Data Science
JavaZone 2018 - A Practical(ish) Introduction to Data ScienceJavaZone 2018 - A Practical(ish) Introduction to Data Science
JavaZone 2018 - A Practical(ish) Introduction to Data ScienceMark West
 
What Is Data Science? Data Science Course - Data Science Tutorial For Beginne...
What Is Data Science? Data Science Course - Data Science Tutorial For Beginne...What Is Data Science? Data Science Course - Data Science Tutorial For Beginne...
What Is Data Science? Data Science Course - Data Science Tutorial For Beginne...Edureka!
 
A Practical-ish Introduction to Data Science
A Practical-ish Introduction to Data ScienceA Practical-ish Introduction to Data Science
A Practical-ish Introduction to Data ScienceMark West
 
Intro to Data Science for Non-Data Scientists
Intro to Data Science for Non-Data ScientistsIntro to Data Science for Non-Data Scientists
Intro to Data Science for Non-Data ScientistsSri Ambati
 
Introduction to Data Science (Data Summit, 2017)
Introduction to Data Science (Data Summit, 2017)Introduction to Data Science (Data Summit, 2017)
Introduction to Data Science (Data Summit, 2017)Caserta
 
Pistoia Alliance Demystifying AI & ML part 2
Pistoia Alliance Demystifying AI & ML part 2Pistoia Alliance Demystifying AI & ML part 2
Pistoia Alliance Demystifying AI & ML part 2Pistoia Alliance
 
NDC Oslo : A Practical Introduction to Data Science
NDC Oslo : A Practical Introduction to Data ScienceNDC Oslo : A Practical Introduction to Data Science
NDC Oslo : A Practical Introduction to Data ScienceMark West
 
Smart Data Slides: Data Science and Business Analysis - A Look at Best Practi...
Smart Data Slides: Data Science and Business Analysis - A Look at Best Practi...Smart Data Slides: Data Science and Business Analysis - A Look at Best Practi...
Smart Data Slides: Data Science and Business Analysis - A Look at Best Practi...DATAVERSITY
 
8 minute intro to data science
8 minute intro to data science 8 minute intro to data science
8 minute intro to data science Mahesh Kumar CV
 
1. introduction to data science —
1. introduction to data science —1. introduction to data science —
1. introduction to data science —swethaT16
 
Analysis of ‘Unstructured’ Data
Analysis of ‘Unstructured’ DataAnalysis of ‘Unstructured’ Data
Analysis of ‘Unstructured’ DataSeth Grimes
 
Smart datamining semtechbiz 2013 report
Smart datamining semtechbiz 2013 reportSmart datamining semtechbiz 2013 report
Smart datamining semtechbiz 2013 reportJesse Wang
 
Data sci sd-11.6.17
Data sci sd-11.6.17Data sci sd-11.6.17
Data sci sd-11.6.17Thinkful
 
SMART Seminar - The Future of Business Intelligence: Information 2020
SMART Seminar - The Future of Business Intelligence: Information 2020SMART Seminar - The Future of Business Intelligence: Information 2020
SMART Seminar - The Future of Business Intelligence: Information 2020SMART Infrastructure Facility
 

Mais procurados (20)

GeeCon Prague 2018 - A Practical-ish Introduction to Data Science
GeeCon Prague 2018 - A Practical-ish Introduction to Data ScienceGeeCon Prague 2018 - A Practical-ish Introduction to Data Science
GeeCon Prague 2018 - A Practical-ish Introduction to Data Science
 
Data+Science : A First Course
Data+Science : A First CourseData+Science : A First Course
Data+Science : A First Course
 
Data science vs. Data scientist by Jothi Periasamy
Data science vs. Data scientist by Jothi PeriasamyData science vs. Data scientist by Jothi Periasamy
Data science vs. Data scientist by Jothi Periasamy
 
Introduction to Data Science
Introduction to Data ScienceIntroduction to Data Science
Introduction to Data Science
 
JavaZone 2018 - A Practical(ish) Introduction to Data Science
JavaZone 2018 - A Practical(ish) Introduction to Data ScienceJavaZone 2018 - A Practical(ish) Introduction to Data Science
JavaZone 2018 - A Practical(ish) Introduction to Data Science
 
What Is Data Science? Data Science Course - Data Science Tutorial For Beginne...
What Is Data Science? Data Science Course - Data Science Tutorial For Beginne...What Is Data Science? Data Science Course - Data Science Tutorial For Beginne...
What Is Data Science? Data Science Course - Data Science Tutorial For Beginne...
 
A Practical-ish Introduction to Data Science
A Practical-ish Introduction to Data ScienceA Practical-ish Introduction to Data Science
A Practical-ish Introduction to Data Science
 
Intro to Data Science for Non-Data Scientists
Intro to Data Science for Non-Data ScientistsIntro to Data Science for Non-Data Scientists
Intro to Data Science for Non-Data Scientists
 
Introduction to Data Science (Data Summit, 2017)
Introduction to Data Science (Data Summit, 2017)Introduction to Data Science (Data Summit, 2017)
Introduction to Data Science (Data Summit, 2017)
 
Pistoia Alliance Demystifying AI & ML part 2
Pistoia Alliance Demystifying AI & ML part 2Pistoia Alliance Demystifying AI & ML part 2
Pistoia Alliance Demystifying AI & ML part 2
 
Intro to Data Science by DatalentTeam at Data Science Clinic#11
Intro to Data Science by DatalentTeam at Data Science Clinic#11Intro to Data Science by DatalentTeam at Data Science Clinic#11
Intro to Data Science by DatalentTeam at Data Science Clinic#11
 
NDC Oslo : A Practical Introduction to Data Science
NDC Oslo : A Practical Introduction to Data ScienceNDC Oslo : A Practical Introduction to Data Science
NDC Oslo : A Practical Introduction to Data Science
 
Smart Data Slides: Data Science and Business Analysis - A Look at Best Practi...
Smart Data Slides: Data Science and Business Analysis - A Look at Best Practi...Smart Data Slides: Data Science and Business Analysis - A Look at Best Practi...
Smart Data Slides: Data Science and Business Analysis - A Look at Best Practi...
 
8 minute intro to data science
8 minute intro to data science 8 minute intro to data science
8 minute intro to data science
 
Data analytics
Data analyticsData analytics
Data analytics
 
1. introduction to data science —
1. introduction to data science —1. introduction to data science —
1. introduction to data science —
 
Analysis of ‘Unstructured’ Data
Analysis of ‘Unstructured’ DataAnalysis of ‘Unstructured’ Data
Analysis of ‘Unstructured’ Data
 
Smart datamining semtechbiz 2013 report
Smart datamining semtechbiz 2013 reportSmart datamining semtechbiz 2013 report
Smart datamining semtechbiz 2013 report
 
Data sci sd-11.6.17
Data sci sd-11.6.17Data sci sd-11.6.17
Data sci sd-11.6.17
 
SMART Seminar - The Future of Business Intelligence: Information 2020
SMART Seminar - The Future of Business Intelligence: Information 2020SMART Seminar - The Future of Business Intelligence: Information 2020
SMART Seminar - The Future of Business Intelligence: Information 2020
 

Destaque

Semantic technologies for the Internet of Things
Semantic technologies for the Internet of Things Semantic technologies for the Internet of Things
Semantic technologies for the Internet of Things PayamBarnaghi
 
Declarative Multilingual Information Extraction with SystemT
Declarative Multilingual Information Extraction with SystemTDeclarative Multilingual Information Extraction with SystemT
Declarative Multilingual Information Extraction with SystemTdiannepatricia
 
Embodied Cognition - Booch HICSS50
Embodied Cognition - Booch HICSS50Embodied Cognition - Booch HICSS50
Embodied Cognition - Booch HICSS50diannepatricia
 
An Ontology for Learning Services on the Shop Floor
An Ontology for Learning Services on the Shop FloorAn Ontology for Learning Services on the Shop Floor
An Ontology for Learning Services on the Shop FloorCarsten Ullrich
 
from text and ontology : methodologies and tools - Text2Onto
from text and ontology : methodologies and tools - Text2Ontofrom text and ontology : methodologies and tools - Text2Onto
from text and ontology : methodologies and tools - Text2OntoRadhoueneRouached
 
Semantic Web and Machine Learning Tutorial
Semantic Web and Machine Learning TutorialSemantic Web and Machine Learning Tutorial
Semantic Web and Machine Learning Tutorialbutest
 
Semantic Technologies for the Internet of Things: Challenges and Opportunities
Semantic Technologies for the Internet of Things: Challenges and Opportunities Semantic Technologies for the Internet of Things: Challenges and Opportunities
Semantic Technologies for the Internet of Things: Challenges and Opportunities PayamBarnaghi
 
Ekaw ontology learning for cost effective large-scale semantic annotation
Ekaw ontology learning for cost effective large-scale semantic annotationEkaw ontology learning for cost effective large-scale semantic annotation
Ekaw ontology learning for cost effective large-scale semantic annotationShahab Mokarizadeh
 

Destaque (11)

Semantic technologies for the Internet of Things
Semantic technologies for the Internet of Things Semantic technologies for the Internet of Things
Semantic technologies for the Internet of Things
 
Declarative Multilingual Information Extraction with SystemT
Declarative Multilingual Information Extraction with SystemTDeclarative Multilingual Information Extraction with SystemT
Declarative Multilingual Information Extraction with SystemT
 
Embodied Cognition - Booch HICSS50
Embodied Cognition - Booch HICSS50Embodied Cognition - Booch HICSS50
Embodied Cognition - Booch HICSS50
 
ppt
pptppt
ppt
 
Steps towards on Ontology based Learning Environment
Steps towards on Ontology based Learning EnvironmentSteps towards on Ontology based Learning Environment
Steps towards on Ontology based Learning Environment
 
An Ontology for Learning Services on the Shop Floor
An Ontology for Learning Services on the Shop FloorAn Ontology for Learning Services on the Shop Floor
An Ontology for Learning Services on the Shop Floor
 
from text and ontology : methodologies and tools - Text2Onto
from text and ontology : methodologies and tools - Text2Ontofrom text and ontology : methodologies and tools - Text2Onto
from text and ontology : methodologies and tools - Text2Onto
 
Ontology Learning
Ontology LearningOntology Learning
Ontology Learning
 
Semantic Web and Machine Learning Tutorial
Semantic Web and Machine Learning TutorialSemantic Web and Machine Learning Tutorial
Semantic Web and Machine Learning Tutorial
 
Semantic Technologies for the Internet of Things: Challenges and Opportunities
Semantic Technologies for the Internet of Things: Challenges and Opportunities Semantic Technologies for the Internet of Things: Challenges and Opportunities
Semantic Technologies for the Internet of Things: Challenges and Opportunities
 
Ekaw ontology learning for cost effective large-scale semantic annotation
Ekaw ontology learning for cost effective large-scale semantic annotationEkaw ontology learning for cost effective large-scale semantic annotation
Ekaw ontology learning for cost effective large-scale semantic annotation
 

Semelhante a “Semantic Technologies for Smart Services”

TFF2016, Rudi Studer, Smarte Dienstleistungen mit semantischen Technologien
TFF2016, Rudi Studer, Smarte Dienstleistungen mit semantischen TechnologienTFF2016, Rudi Studer, Smarte Dienstleistungen mit semantischen Technologien
TFF2016, Rudi Studer, Smarte Dienstleistungen mit semantischen TechnologienTourismFastForward
 
Information Technology in Industry(ITII) - November Issue 2018
Information Technology in Industry(ITII) - November Issue 2018Information Technology in Industry(ITII) - November Issue 2018
Information Technology in Industry(ITII) - November Issue 2018ITIIIndustries
 
Dublinked tech workshop_15_dec2011
Dublinked tech workshop_15_dec2011Dublinked tech workshop_15_dec2011
Dublinked tech workshop_15_dec2011Dublinked .
 
Big Data Expo 2015 - Cisco Connected Analytics
Big Data Expo 2015 - Cisco Connected AnalyticsBig Data Expo 2015 - Cisco Connected Analytics
Big Data Expo 2015 - Cisco Connected AnalyticsBigDataExpo
 
Enabling the digital thread using open OSLC standards
Enabling the digital thread using open OSLC standardsEnabling the digital thread using open OSLC standards
Enabling the digital thread using open OSLC standardsAxel Reichwein
 
Tag.bio: Self Service Data Mesh Platform
Tag.bio: Self Service Data Mesh PlatformTag.bio: Self Service Data Mesh Platform
Tag.bio: Self Service Data Mesh PlatformSanjay Padhi, Ph.D
 
TUW-ASE Summer 2015: IoT Cloud Systems
TUW-ASE Summer 2015:  IoT Cloud SystemsTUW-ASE Summer 2015:  IoT Cloud Systems
TUW-ASE Summer 2015: IoT Cloud SystemsHong-Linh Truong
 
Linked Services for the Web of Data
Linked Services for the Web of DataLinked Services for the Web of Data
Linked Services for the Web of DataCarlos Pedrinaci
 
IoT Architecture - Are Traditional Architectures Good Enough or do we Need Ne...
IoT Architecture - Are Traditional Architectures Good Enough or do we Need Ne...IoT Architecture - Are Traditional Architectures Good Enough or do we Need Ne...
IoT Architecture - Are Traditional Architectures Good Enough or do we Need Ne...Guido Schmutz
 
Phoenix Data Conference - Big Data Analytics for IoT 11/4/17
Phoenix Data Conference - Big Data Analytics for IoT 11/4/17Phoenix Data Conference - Big Data Analytics for IoT 11/4/17
Phoenix Data Conference - Big Data Analytics for IoT 11/4/17Mark Goldstein
 
Putting the L in front: from Open Data to Linked Open Data
Putting the L in front: from Open Data to Linked Open DataPutting the L in front: from Open Data to Linked Open Data
Putting the L in front: from Open Data to Linked Open DataMartin Kaltenböck
 
Building Reference Architectures for the Industrial IoT
Building Reference Architectures for the Industrial IoTBuilding Reference Architectures for the Industrial IoT
Building Reference Architectures for the Industrial IoTCapgemini
 
A Framework for Geospatial Web Services for Public Health by Dr. Leslie Lenert
A Framework for Geospatial Web Services for Public Health by Dr. Leslie LenertA Framework for Geospatial Web Services for Public Health by Dr. Leslie Lenert
A Framework for Geospatial Web Services for Public Health by Dr. Leslie LenertWansoo Im
 
RioInfo 2010: Seminário de Tecnologia - Mesa 1 - Integração e Convergência Ma...
RioInfo 2010: Seminário de Tecnologia - Mesa 1 - Integração e Convergência Ma...RioInfo 2010: Seminário de Tecnologia - Mesa 1 - Integração e Convergência Ma...
RioInfo 2010: Seminário de Tecnologia - Mesa 1 - Integração e Convergência Ma...Rio Info
 
General introduction to IoTCrawler
General introduction to IoTCrawlerGeneral introduction to IoTCrawler
General introduction to IoTCrawlerIoTCrawler
 
Emerging Dynamic TUW-ASE Summer 2015 - Distributed Systems and Challenges for...
Emerging Dynamic TUW-ASE Summer 2015 - Distributed Systems and Challenges for...Emerging Dynamic TUW-ASE Summer 2015 - Distributed Systems and Challenges for...
Emerging Dynamic TUW-ASE Summer 2015 - Distributed Systems and Challenges for...Hong-Linh Truong
 
Alitora Innovation Networks
Alitora Innovation NetworksAlitora Innovation Networks
Alitora Innovation Networksalitora
 
BrownResearch_CV
BrownResearch_CVBrownResearch_CV
BrownResearch_CVAbby Brown
 

Semelhante a “Semantic Technologies for Smart Services” (20)

TFF2016, Rudi Studer, Smarte Dienstleistungen mit semantischen Technologien
TFF2016, Rudi Studer, Smarte Dienstleistungen mit semantischen TechnologienTFF2016, Rudi Studer, Smarte Dienstleistungen mit semantischen Technologien
TFF2016, Rudi Studer, Smarte Dienstleistungen mit semantischen Technologien
 
Information Technology in Industry(ITII) - November Issue 2018
Information Technology in Industry(ITII) - November Issue 2018Information Technology in Industry(ITII) - November Issue 2018
Information Technology in Industry(ITII) - November Issue 2018
 
Dublinked tech workshop_15_dec2011
Dublinked tech workshop_15_dec2011Dublinked tech workshop_15_dec2011
Dublinked tech workshop_15_dec2011
 
Big Data Expo 2015 - Cisco Connected Analytics
Big Data Expo 2015 - Cisco Connected AnalyticsBig Data Expo 2015 - Cisco Connected Analytics
Big Data Expo 2015 - Cisco Connected Analytics
 
Enabling the digital thread using open OSLC standards
Enabling the digital thread using open OSLC standardsEnabling the digital thread using open OSLC standards
Enabling the digital thread using open OSLC standards
 
Tag.bio: Self Service Data Mesh Platform
Tag.bio: Self Service Data Mesh PlatformTag.bio: Self Service Data Mesh Platform
Tag.bio: Self Service Data Mesh Platform
 
TUW-ASE Summer 2015: IoT Cloud Systems
TUW-ASE Summer 2015:  IoT Cloud SystemsTUW-ASE Summer 2015:  IoT Cloud Systems
TUW-ASE Summer 2015: IoT Cloud Systems
 
Linked Services for the Web of Data
Linked Services for the Web of DataLinked Services for the Web of Data
Linked Services for the Web of Data
 
IoT Architecture - Are Traditional Architectures Good Enough or do we Need Ne...
IoT Architecture - Are Traditional Architectures Good Enough or do we Need Ne...IoT Architecture - Are Traditional Architectures Good Enough or do we Need Ne...
IoT Architecture - Are Traditional Architectures Good Enough or do we Need Ne...
 
Phoenix Data Conference - Big Data Analytics for IoT 11/4/17
Phoenix Data Conference - Big Data Analytics for IoT 11/4/17Phoenix Data Conference - Big Data Analytics for IoT 11/4/17
Phoenix Data Conference - Big Data Analytics for IoT 11/4/17
 
Putting the L in front: from Open Data to Linked Open Data
Putting the L in front: from Open Data to Linked Open DataPutting the L in front: from Open Data to Linked Open Data
Putting the L in front: from Open Data to Linked Open Data
 
Building Reference Architectures for the Industrial IoT
Building Reference Architectures for the Industrial IoTBuilding Reference Architectures for the Industrial IoT
Building Reference Architectures for the Industrial IoT
 
Software Architecture in an Agile World
Software Architecture in an Agile WorldSoftware Architecture in an Agile World
Software Architecture in an Agile World
 
A Framework for Geospatial Web Services for Public Health by Dr. Leslie Lenert
A Framework for Geospatial Web Services for Public Health by Dr. Leslie LenertA Framework for Geospatial Web Services for Public Health by Dr. Leslie Lenert
A Framework for Geospatial Web Services for Public Health by Dr. Leslie Lenert
 
RioInfo 2010: Seminário de Tecnologia - Mesa 1 - Integração e Convergência Ma...
RioInfo 2010: Seminário de Tecnologia - Mesa 1 - Integração e Convergência Ma...RioInfo 2010: Seminário de Tecnologia - Mesa 1 - Integração e Convergência Ma...
RioInfo 2010: Seminário de Tecnologia - Mesa 1 - Integração e Convergência Ma...
 
General introduction to IoTCrawler
General introduction to IoTCrawlerGeneral introduction to IoTCrawler
General introduction to IoTCrawler
 
Emerging Dynamic TUW-ASE Summer 2015 - Distributed Systems and Challenges for...
Emerging Dynamic TUW-ASE Summer 2015 - Distributed Systems and Challenges for...Emerging Dynamic TUW-ASE Summer 2015 - Distributed Systems and Challenges for...
Emerging Dynamic TUW-ASE Summer 2015 - Distributed Systems and Challenges for...
 
Alitora Innovation Networks
Alitora Innovation NetworksAlitora Innovation Networks
Alitora Innovation Networks
 
BrownResearch_CV
BrownResearch_CVBrownResearch_CV
BrownResearch_CV
 
SomeSlides
SomeSlidesSomeSlides
SomeSlides
 

Mais de diannepatricia

Teaching cognitive computing with ibm watson
Teaching cognitive computing with ibm watsonTeaching cognitive computing with ibm watson
Teaching cognitive computing with ibm watsondiannepatricia
 
Cognitive systems institute talk 8 june 2017 - v.1.0
Cognitive systems institute talk   8 june 2017 - v.1.0Cognitive systems institute talk   8 june 2017 - v.1.0
Cognitive systems institute talk 8 june 2017 - v.1.0diannepatricia
 
Building Compassionate Conversational Systems
Building Compassionate Conversational SystemsBuilding Compassionate Conversational Systems
Building Compassionate Conversational Systemsdiannepatricia
 
“Artificial Intelligence, Cognitive Computing and Innovating in Practice”
“Artificial Intelligence, Cognitive Computing and Innovating in Practice”“Artificial Intelligence, Cognitive Computing and Innovating in Practice”
“Artificial Intelligence, Cognitive Computing and Innovating in Practice”diannepatricia
 
Cognitive Insights drive self-driving Accessibility
Cognitive Insights drive self-driving AccessibilityCognitive Insights drive self-driving Accessibility
Cognitive Insights drive self-driving Accessibilitydiannepatricia
 
Artificial Intellingence in the Car
Artificial Intellingence in the CarArtificial Intellingence in the Car
Artificial Intellingence in the Cardiannepatricia
 
“Semantic PDF Processing & Document Representation”
“Semantic PDF Processing & Document Representation”“Semantic PDF Processing & Document Representation”
“Semantic PDF Processing & Document Representation”diannepatricia
 
Joining Industry and Students for Cognitive Solutions at Karlsruhe Services R...
Joining Industry and Students for Cognitive Solutions at Karlsruhe Services R...Joining Industry and Students for Cognitive Solutions at Karlsruhe Services R...
Joining Industry and Students for Cognitive Solutions at Karlsruhe Services R...diannepatricia
 
170330 cognitive systems institute speaker series mark sherman - watson pr...
170330 cognitive systems institute speaker series    mark sherman - watson pr...170330 cognitive systems institute speaker series    mark sherman - watson pr...
170330 cognitive systems institute speaker series mark sherman - watson pr...diannepatricia
 
“Fairness Cases as an Accelerant and Enabler for Cognitive Assistance Adoption”
“Fairness Cases as an Accelerant and Enabler for Cognitive Assistance Adoption”“Fairness Cases as an Accelerant and Enabler for Cognitive Assistance Adoption”
“Fairness Cases as an Accelerant and Enabler for Cognitive Assistance Adoption”diannepatricia
 
Cognitive Assistance for the Aging
Cognitive Assistance for the AgingCognitive Assistance for the Aging
Cognitive Assistance for the Agingdiannepatricia
 
From complex Systems to Networks: Discovering and Modeling the Correct Network"
From complex Systems to Networks: Discovering and Modeling the Correct Network"From complex Systems to Networks: Discovering and Modeling the Correct Network"
From complex Systems to Networks: Discovering and Modeling the Correct Network"diannepatricia
 
The Role of Dialog in Augmented Intelligence
The Role of Dialog in Augmented IntelligenceThe Role of Dialog in Augmented Intelligence
The Role of Dialog in Augmented Intelligencediannepatricia
 
Developing Cognitive Systems to Support Team Cognition
Developing Cognitive Systems to Support Team CognitionDeveloping Cognitive Systems to Support Team Cognition
Developing Cognitive Systems to Support Team Cognitiondiannepatricia
 
Cyber-Social Learning Systems
Cyber-Social Learning SystemsCyber-Social Learning Systems
Cyber-Social Learning Systemsdiannepatricia
 
“IT Technology Trends in 2017… and Beyond”
“IT Technology Trends in 2017… and Beyond”“IT Technology Trends in 2017… and Beyond”
“IT Technology Trends in 2017… and Beyond”diannepatricia
 
"Curious Learning: using a mobile platform for early literacy education as a ...
"Curious Learning: using a mobile platform for early literacy education as a ..."Curious Learning: using a mobile platform for early literacy education as a ...
"Curious Learning: using a mobile platform for early literacy education as a ...diannepatricia
 
KATE - a Platform for Machine Learning
KATE - a Platform for Machine LearningKATE - a Platform for Machine Learning
KATE - a Platform for Machine Learningdiannepatricia
 
Cognitive Computing for Aging Society
Cognitive Computing for Aging SocietyCognitive Computing for Aging Society
Cognitive Computing for Aging Societydiannepatricia
 

Mais de diannepatricia (20)

Teaching cognitive computing with ibm watson
Teaching cognitive computing with ibm watsonTeaching cognitive computing with ibm watson
Teaching cognitive computing with ibm watson
 
Cognitive systems institute talk 8 june 2017 - v.1.0
Cognitive systems institute talk   8 june 2017 - v.1.0Cognitive systems institute talk   8 june 2017 - v.1.0
Cognitive systems institute talk 8 june 2017 - v.1.0
 
Building Compassionate Conversational Systems
Building Compassionate Conversational SystemsBuilding Compassionate Conversational Systems
Building Compassionate Conversational Systems
 
“Artificial Intelligence, Cognitive Computing and Innovating in Practice”
“Artificial Intelligence, Cognitive Computing and Innovating in Practice”“Artificial Intelligence, Cognitive Computing and Innovating in Practice”
“Artificial Intelligence, Cognitive Computing and Innovating in Practice”
 
Cognitive Insights drive self-driving Accessibility
Cognitive Insights drive self-driving AccessibilityCognitive Insights drive self-driving Accessibility
Cognitive Insights drive self-driving Accessibility
 
Artificial Intellingence in the Car
Artificial Intellingence in the CarArtificial Intellingence in the Car
Artificial Intellingence in the Car
 
“Semantic PDF Processing & Document Representation”
“Semantic PDF Processing & Document Representation”“Semantic PDF Processing & Document Representation”
“Semantic PDF Processing & Document Representation”
 
Joining Industry and Students for Cognitive Solutions at Karlsruhe Services R...
Joining Industry and Students for Cognitive Solutions at Karlsruhe Services R...Joining Industry and Students for Cognitive Solutions at Karlsruhe Services R...
Joining Industry and Students for Cognitive Solutions at Karlsruhe Services R...
 
170330 cognitive systems institute speaker series mark sherman - watson pr...
170330 cognitive systems institute speaker series    mark sherman - watson pr...170330 cognitive systems institute speaker series    mark sherman - watson pr...
170330 cognitive systems institute speaker series mark sherman - watson pr...
 
“Fairness Cases as an Accelerant and Enabler for Cognitive Assistance Adoption”
“Fairness Cases as an Accelerant and Enabler for Cognitive Assistance Adoption”“Fairness Cases as an Accelerant and Enabler for Cognitive Assistance Adoption”
“Fairness Cases as an Accelerant and Enabler for Cognitive Assistance Adoption”
 
Cognitive Assistance for the Aging
Cognitive Assistance for the AgingCognitive Assistance for the Aging
Cognitive Assistance for the Aging
 
From complex Systems to Networks: Discovering and Modeling the Correct Network"
From complex Systems to Networks: Discovering and Modeling the Correct Network"From complex Systems to Networks: Discovering and Modeling the Correct Network"
From complex Systems to Networks: Discovering and Modeling the Correct Network"
 
The Role of Dialog in Augmented Intelligence
The Role of Dialog in Augmented IntelligenceThe Role of Dialog in Augmented Intelligence
The Role of Dialog in Augmented Intelligence
 
Developing Cognitive Systems to Support Team Cognition
Developing Cognitive Systems to Support Team CognitionDeveloping Cognitive Systems to Support Team Cognition
Developing Cognitive Systems to Support Team Cognition
 
Cyber-Social Learning Systems
Cyber-Social Learning SystemsCyber-Social Learning Systems
Cyber-Social Learning Systems
 
“IT Technology Trends in 2017… and Beyond”
“IT Technology Trends in 2017… and Beyond”“IT Technology Trends in 2017… and Beyond”
“IT Technology Trends in 2017… and Beyond”
 
"Curious Learning: using a mobile platform for early literacy education as a ...
"Curious Learning: using a mobile platform for early literacy education as a ..."Curious Learning: using a mobile platform for early literacy education as a ...
"Curious Learning: using a mobile platform for early literacy education as a ...
 
KATE - a Platform for Machine Learning
KATE - a Platform for Machine LearningKATE - a Platform for Machine Learning
KATE - a Platform for Machine Learning
 
Cognitive Computing for Aging Society
Cognitive Computing for Aging SocietyCognitive Computing for Aging Society
Cognitive Computing for Aging Society
 
Hicss17 asakawa
Hicss17 asakawaHicss17 asakawa
Hicss17 asakawa
 

Último

9 Steps For Building Winning Founding Team
9 Steps For Building Winning Founding Team9 Steps For Building Winning Founding Team
9 Steps For Building Winning Founding TeamAdam Moalla
 
UiPath Community: AI for UiPath Automation Developers
UiPath Community: AI for UiPath Automation DevelopersUiPath Community: AI for UiPath Automation Developers
UiPath Community: AI for UiPath Automation DevelopersUiPathCommunity
 
UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6DianaGray10
 
COMPUTER 10 Lesson 8 - Building a Website
COMPUTER 10 Lesson 8 - Building a WebsiteCOMPUTER 10 Lesson 8 - Building a Website
COMPUTER 10 Lesson 8 - Building a Websitedgelyza
 
Secure your environment with UiPath and CyberArk technologies - Session 1
Secure your environment with UiPath and CyberArk technologies - Session 1Secure your environment with UiPath and CyberArk technologies - Session 1
Secure your environment with UiPath and CyberArk technologies - Session 1DianaGray10
 
VoIP Service and Marketing using Odoo and Asterisk PBX
VoIP Service and Marketing using Odoo and Asterisk PBXVoIP Service and Marketing using Odoo and Asterisk PBX
VoIP Service and Marketing using Odoo and Asterisk PBXTarek Kalaji
 
AI You Can Trust - Ensuring Success with Data Integrity Webinar
AI You Can Trust - Ensuring Success with Data Integrity WebinarAI You Can Trust - Ensuring Success with Data Integrity Webinar
AI You Can Trust - Ensuring Success with Data Integrity WebinarPrecisely
 
Using IESVE for Loads, Sizing and Heat Pump Modeling to Achieve Decarbonization
Using IESVE for Loads, Sizing and Heat Pump Modeling to Achieve DecarbonizationUsing IESVE for Loads, Sizing and Heat Pump Modeling to Achieve Decarbonization
Using IESVE for Loads, Sizing and Heat Pump Modeling to Achieve DecarbonizationIES VE
 
activity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdf
activity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdf
activity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdfJamie (Taka) Wang
 
The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...
The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...
The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...Aggregage
 
Nanopower In Semiconductor Industry.pdf
Nanopower  In Semiconductor Industry.pdfNanopower  In Semiconductor Industry.pdf
Nanopower In Semiconductor Industry.pdfPedro Manuel
 
Basic Building Blocks of Internet of Things.
Basic Building Blocks of Internet of Things.Basic Building Blocks of Internet of Things.
Basic Building Blocks of Internet of Things.YounusS2
 
Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...
Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...
Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...DianaGray10
 
UiPath Solutions Management Preview - Northern CA Chapter - March 22.pdf
UiPath Solutions Management Preview - Northern CA Chapter - March 22.pdfUiPath Solutions Management Preview - Northern CA Chapter - March 22.pdf
UiPath Solutions Management Preview - Northern CA Chapter - March 22.pdfDianaGray10
 
Artificial Intelligence & SEO Trends for 2024
Artificial Intelligence & SEO Trends for 2024Artificial Intelligence & SEO Trends for 2024
Artificial Intelligence & SEO Trends for 2024D Cloud Solutions
 
ADOPTING WEB 3 FOR YOUR BUSINESS: A STEP-BY-STEP GUIDE
ADOPTING WEB 3 FOR YOUR BUSINESS: A STEP-BY-STEP GUIDEADOPTING WEB 3 FOR YOUR BUSINESS: A STEP-BY-STEP GUIDE
ADOPTING WEB 3 FOR YOUR BUSINESS: A STEP-BY-STEP GUIDELiveplex
 
Bird eye's view on Camunda open source ecosystem
Bird eye's view on Camunda open source ecosystemBird eye's view on Camunda open source ecosystem
Bird eye's view on Camunda open source ecosystemAsko Soukka
 
Empowering Africa's Next Generation: The AI Leadership Blueprint
Empowering Africa's Next Generation: The AI Leadership BlueprintEmpowering Africa's Next Generation: The AI Leadership Blueprint
Empowering Africa's Next Generation: The AI Leadership BlueprintMahmoud Rabie
 
Anypoint Code Builder , Google Pub sub connector and MuleSoft RPA
Anypoint Code Builder , Google Pub sub connector and MuleSoft RPAAnypoint Code Builder , Google Pub sub connector and MuleSoft RPA
Anypoint Code Builder , Google Pub sub connector and MuleSoft RPAshyamraj55
 
20230202 - Introduction to tis-py
20230202 - Introduction to tis-py20230202 - Introduction to tis-py
20230202 - Introduction to tis-pyJamie (Taka) Wang
 

Último (20)

9 Steps For Building Winning Founding Team
9 Steps For Building Winning Founding Team9 Steps For Building Winning Founding Team
9 Steps For Building Winning Founding Team
 
UiPath Community: AI for UiPath Automation Developers
UiPath Community: AI for UiPath Automation DevelopersUiPath Community: AI for UiPath Automation Developers
UiPath Community: AI for UiPath Automation Developers
 
UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6
 
COMPUTER 10 Lesson 8 - Building a Website
COMPUTER 10 Lesson 8 - Building a WebsiteCOMPUTER 10 Lesson 8 - Building a Website
COMPUTER 10 Lesson 8 - Building a Website
 
Secure your environment with UiPath and CyberArk technologies - Session 1
Secure your environment with UiPath and CyberArk technologies - Session 1Secure your environment with UiPath and CyberArk technologies - Session 1
Secure your environment with UiPath and CyberArk technologies - Session 1
 
VoIP Service and Marketing using Odoo and Asterisk PBX
VoIP Service and Marketing using Odoo and Asterisk PBXVoIP Service and Marketing using Odoo and Asterisk PBX
VoIP Service and Marketing using Odoo and Asterisk PBX
 
AI You Can Trust - Ensuring Success with Data Integrity Webinar
AI You Can Trust - Ensuring Success with Data Integrity WebinarAI You Can Trust - Ensuring Success with Data Integrity Webinar
AI You Can Trust - Ensuring Success with Data Integrity Webinar
 
Using IESVE for Loads, Sizing and Heat Pump Modeling to Achieve Decarbonization
Using IESVE for Loads, Sizing and Heat Pump Modeling to Achieve DecarbonizationUsing IESVE for Loads, Sizing and Heat Pump Modeling to Achieve Decarbonization
Using IESVE for Loads, Sizing and Heat Pump Modeling to Achieve Decarbonization
 
activity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdf
activity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdf
activity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdf
 
The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...
The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...
The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data a...
 
Nanopower In Semiconductor Industry.pdf
Nanopower  In Semiconductor Industry.pdfNanopower  In Semiconductor Industry.pdf
Nanopower In Semiconductor Industry.pdf
 
Basic Building Blocks of Internet of Things.
Basic Building Blocks of Internet of Things.Basic Building Blocks of Internet of Things.
Basic Building Blocks of Internet of Things.
 
Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...
Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...
Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...
 
UiPath Solutions Management Preview - Northern CA Chapter - March 22.pdf
UiPath Solutions Management Preview - Northern CA Chapter - March 22.pdfUiPath Solutions Management Preview - Northern CA Chapter - March 22.pdf
UiPath Solutions Management Preview - Northern CA Chapter - March 22.pdf
 
Artificial Intelligence & SEO Trends for 2024
Artificial Intelligence & SEO Trends for 2024Artificial Intelligence & SEO Trends for 2024
Artificial Intelligence & SEO Trends for 2024
 
ADOPTING WEB 3 FOR YOUR BUSINESS: A STEP-BY-STEP GUIDE
ADOPTING WEB 3 FOR YOUR BUSINESS: A STEP-BY-STEP GUIDEADOPTING WEB 3 FOR YOUR BUSINESS: A STEP-BY-STEP GUIDE
ADOPTING WEB 3 FOR YOUR BUSINESS: A STEP-BY-STEP GUIDE
 
Bird eye's view on Camunda open source ecosystem
Bird eye's view on Camunda open source ecosystemBird eye's view on Camunda open source ecosystem
Bird eye's view on Camunda open source ecosystem
 
Empowering Africa's Next Generation: The AI Leadership Blueprint
Empowering Africa's Next Generation: The AI Leadership BlueprintEmpowering Africa's Next Generation: The AI Leadership Blueprint
Empowering Africa's Next Generation: The AI Leadership Blueprint
 
Anypoint Code Builder , Google Pub sub connector and MuleSoft RPA
Anypoint Code Builder , Google Pub sub connector and MuleSoft RPAAnypoint Code Builder , Google Pub sub connector and MuleSoft RPA
Anypoint Code Builder , Google Pub sub connector and MuleSoft RPA
 
20230202 - Introduction to tis-py
20230202 - Introduction to tis-py20230202 - Introduction to tis-py
20230202 - Introduction to tis-py
 

“Semantic Technologies for Smart Services”

  • 1. KIT – The Research University in the Helmholtz Association www.kit.edu Institute of Applied Informatics and Formal Description Methods (AIFB), Karlsruhe Service Research Institute (KSRI), FZI Research Center for Information Technology Semantic Technologies for Smart Services Rudi Studer & Maria Maleshkova Cognitive Systems Institute Speaker Series, 15 December 2016
  • 2. Institute of Applied Informatics and Formal Description Methods (AIFB) 2 “Semantic Karlsruhe” Industrie 4.0 Medicine & eHealth Digital Shift Big Data & Data Analytics SEMANTIC TECHNOLOGIES Semantic Data Management Complex Event Processing Data / Text Mining Smart Services Basic Research Applied Research Transfer Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
  • 3. Institute of Applied Informatics and Formal Description Methods (AIFB) 3 WEB SCIENCE AND KNOWLEDGE MANAGEMENT Institute of Applied Informatics and Formal Description Methods
  • 4. Institute of Applied Informatics and Formal Description Methods (AIFB) 4 Karlsruhe Service Research Institute – an „industry-on- campus“ model with focus on interdisciplinary research        Prof. Dr. Christof Weinhardt Information & Market Engineering Prof. Dr. Gerhard Satzger Digital Service Innovation Prof. Dr. Stefan Nickel Discrete Optimization & Logistics Prof. Dr. Wolf Fichtner Energy Economics Prof. Dr. Alexander Mädche Information Systems & Service Design Prof. Dr. Rudi Studer Knowledge Management Prof. Dr. York Sure- Vetter Prof. Dr. Kai Furmans Value Stream Services Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series Dr. Markus Bauer
  • 5. Institute of Applied Informatics and Formal Description Methods (AIFB) 5 Service Research investigates complex service systems where economic value is created jointly by multiple independent parties, acting together efficiently through the systematic use of information and communication technologies… …from different perspectives and in different domains ... and others Healthcare Services Crowd and Participation Services (e)-Mobility Smart Services, Industry 4.0 and IoT Research Focus: Intelligent Services for Real-world Networks Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
  • 6. Institute of Applied Informatics and Formal Description Methods (AIFB) 6 • Motivation • Why Smart Services via Semantic Technologies? • Use Case 1 - Building Agile Systems • Use Case 2 – Smart Services for Predictive Maintenance • Summary and Conclusions Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
  • 7. Institute of Applied Informatics and Formal Description Methods (AIFB) 7 Market Influence Technology Development Today’s Driving Forces Shorter innovation cycles Need for continuous adaptation Near real-time analyses Involvement of the customer not only with the finished product/service but during the complete development cycle Ubiquitous access Social and community Web Heterogeneous big data Distributed component-based solutions Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
  • 8. Institute of Applied Informatics and Formal Description Methods (AIFB) 8 Internet of Things (IoT) Challenges We expect one hundred billion IoT devices to be deployed within the next ten years BUT the IoT is currently facing a lot of problems Product silos that do not interoperate with each other Many approaches and incompatible platforms No network effect Heterogeneity in terms of Data Devices and interfaces Data volumes and number of sources explode Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series We expect one hundred billion IoT devices to be deployed within the next ten years BUT the IoT is currently facing a lot of problems Product silos that do not interoperate with each other Many approaches and incompatible platforms No network effect Heterogeneity in terms of Data Devices and interfaces Data volumes and number of sources explode see: http://www.w3.org/2015/05/wot-framework.pdf
  • 9. Institute of Applied Informatics and Formal Description Methods (AIFB) 9 The Web as the Solution Source: http://www.w3.org/2015/05/wot-framework.pdf Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
  • 10. Institute of Applied Informatics and Formal Description Methods (AIFB) 10 Semantic Technologies for Smart Services Data Integration – combining data from multiple sources enables new applications and insights More and more data available on the Web is published conforming to Semantic Web standards Linking Open Data (LOD) initiative Semantic Web technologies are beneficial for data exchange, integration and search Decentralised Architectures – no central controller or repository Overcoming device heterogeneity – common model for devices (functional and non-functional properties) Overcoming interface heterogeneity – standard Web Technologies + Linked Data Adaptation – adjusting services, products, things according to context and current needs Intelligent Programmable Interfaces Embedding intelligence into the service interface (e.g. rules) Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
  • 11. Institute of Applied Informatics and Formal Description Methods (AIFB) 11 Semantic Technologies Semantic Web technologies, standardised by the W3C, are mature: RDF recommendation in 1999, update in 2004 RDFa (RDF in HTML) note in 2008 RDFS recommendation in 2004 SPARQL recommendation in 2008 OWL recommendation in 2004, update in 2009 Linked Data is a subset of the Semantic Web stack Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
  • 12. Institute of Applied Informatics and Formal Description Methods (AIFB) 12 Use Cases 1. Building Agile Systems Fast integration of data and programmable interfaces based on semantic technologies 2. Smart Services for Predictive Maintenance Semantics for integrating sensor data, background knowledge and decision rules Recognizing maintenance needs before they occur Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series Semantic description Semantic description Semantic description
  • 13. Institute of Applied Informatics and Formal Description Methods (AIFB) 13 BUILDING AGILE SYSTEMS Semantics for integrating data and programmable interfaces Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
  • 14. Institute of Applied Informatics and Formal Description Methods (AIFB) 14 Today‘s Web is about Dynamic Data Data is often dynamically created as a result of some calculation carried out over input data (e.g., weather information) Data can change frequently (e.g., moving objects) APIs are used to trigger functionalities in the Web and the real world and provide access to dynamic and static data sources An important role plays Representational State Transfer (REST) Architectural style for client– server interaction Compatible with Web architecture http://programmableweb.com 8816 APIs Over 16,400 APIs and 7,800 mashups Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
  • 15. Institute of Applied Informatics and Formal Description Methods (AIFB) 15 Linked Data Principles 1. Use URIs to name things; not only documents, but also people, locations, concepts, etc. http://dbpedia.org/resource/Johannes_Gutenberg 2. To enable agents (human users and machine agents alike) to look up those names, use HTTP URIs http://dbpedia.org/page/Printing_press 3. When someone looks up a URI we provide useful information; with 'useful' in the strict sense we usually mean structured data in RDF http://dbpedia.org/page/Printing_press dct:subject dbc:Johannes_Gutenberg. 4. Include links to other URIs allowing agents (machines and humans) to discover more things <http://dbpedia.org/page/Printing_press> rdfs:seeAlso <http://dbpedia.org/page/Letterpress_printing> . http://www.w3.org/DesignIssues/LinkedData Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
  • 16. Institute of Applied Informatics and Formal Description Methods (AIFB) 16 Linking Open Data Cloud Linking Open Data cloud diagram 2014, by Max Schmachtenberg, Christian Bizer, Anja Jentzsch and Richard Cyganiak. http://lod-cloud.net/ Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
  • 17. Institute of Applied Informatics and Formal Description Methods (AIFB) 17 Motivation for Combining Semantics and Services Increased value comes from combinations of services and APIs But a lot of manual effort is required for this compositions (glue code) Structured service/API descriptions ease the composition process considerably Semantic descriptions allow for execution of several tasks automatically (e.g., data matching, discovery, ranking) Manually drafted glue code Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series Semantic description Semantic description Semantic description
  • 18. Institute of Applied Informatics and Formal Description Methods (AIFB) 18 Motivation for Combining Semantics and Services Increased value comes from combinations of services and APIs But a lot of manual effort is required for this compositions (glue code) Structured service/API descriptions ease the composition process considerably Semantic descriptions allow for execution of several tasks automatically (e.g., data matching, discovery, ranking) Manually drafted glue code Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series Semantic description Semantic description Semantic description
  • 19. Institute of Applied Informatics and Formal Description Methods (AIFB) 19 Creating Linked Services Functionality attainable via the Web by combining: RESTful services (respecting Web architecture) resource-oriented manipulated with HTTP verbs GET, PUT (, PATCH), POST, DELETE Negotiate representations Linked data Uniform use of URIs Use of RDF and SPARQL = Linked Services Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
  • 20. Institute of Applied Informatics and Formal Description Methods (AIFB) 20 Facilitate Data Integration Linked Service Combines data (MashUp) build on top Application that consumes one Linked Service Bad solution Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
  • 21. Institute of Applied Informatics and Formal Description Methods (AIFB) 21 Facilitate Data Integration Linked Service Combines data (MashUp) build on top Application that consumes one Linked Service Bad solution Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
  • 22. Institute of Applied Informatics and Formal Description Methods (AIFB) 22 Facilitate Data Integration Linked Service Application (integrates data and functionalities from several Linked Services, e.g. via Linked Data-Fu) Good solution Linked Service Linked Service Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series http://linked-data-fu.github.io/
  • 23. Institute of Applied Informatics and Formal Description Methods (AIFB) 23 SMART SERVICES FOR PREDICTIVE MAINTENANCE Semantics for integrating sensor data, background knowledge and decision rules Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
  • 24. Institute of Applied Informatics and Formal Description Methods (AIFB) 24 Cognition Framework Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series Perception Reaction Background Knowledge Interpretation and Analysis
  • 25. Institute of Applied Informatics and Formal Description Methods (AIFB) 25 The Cognition Framework for Predictive Maintenance Input data in terms of - Sensor data - Personal observations - Alarms and errors Background knowledge - Log files - Previous similar problems and solutions - Guidelines - Manuals - Detail about the machines Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series Interpretation and Analysis - Data integration to enable analysis - Similarity analysis with previous problems - Heuristics encoded as rules Reaction - Automated solution recommendation vs. - Providing solution support
  • 26. Institute of Applied Informatics and Formal Description Methods (AIFB) 26 Problem Breakdown 1. Smart Services for Problem Recognition Recognizing what the current problem is based on previous problems Combination with heuristics 2. Smart Services for preparing Solution Containers Providing summary of the problem, difficulty, time estimate Links to relevant manuals, links to required parts Required expertise, contacts of people with relevant qualifications Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series ? http://www.aifb.kit.edu/web/STEP/en
  • 27. Institute of Applied Informatics and Formal Description Methods (AIFB) 27 Problem Breakdown 2. Smart Services for preparing Solution Containers (continued) Dealing with multilingual and multimodal sources Identifying related articles across different languages and media types Possible use – the solution might be available in another language; images and videos can be used to identify the problem, support the solution 3. Smart Services for Interactive Problem Solving Guiding the user towards the solution Recommending the next possible step Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series http://xlime.eu/
  • 28. Institute of Applied Informatics and Formal Description Methods (AIFB) 28 Problem Breakdown 4. Smart Services for Route Planning for the technician Supporting the dispatcher in planning the routes Supporting the technician during the trips Solution based on Use Case 1: Building Agile Systems Creating Linked Services for the interfaces Rules for defining the composition and interaction Automated execution with Linked DataFu Prototype system for data / service integration and execution Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series Proximity service Street View Maintenance route-planning
  • 29. Institute of Applied Informatics and Formal Description Methods (AIFB) 29 Summary and Outlook Market trends and technology developments pave the way for developing new products and services, which are more flexible and adapted to the customer needs We need technology solutions to achieve more automation and adaptability –– putting the ‘Smartness’ into services Providing means for agile system development Providing means for self-adaptivity We can use Semantic Technologies for Smart Services to support: The rapid development of mashups and applications To realize Industry 4.0 / IoT solutions Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series
  • 30. Institute of Applied Informatics and Formal Description Methods (AIFB) 30 Relevant Publications S. Stadtmüller, S. Speiser, A. Harth, R. Studer Data-Fu: A Language and an Interpreter for Interaction with Read/Write Linked Data. Proceedings of the 22nd International Conference on World Wide Web, pp. 1225-1236, Rio de Janeiro, 2013. A. Harth, C. Knoblock, S. Stadtmüller, R. Studer, und P. Szekely. On-the-fly Integration of Static and Dynamic Sources. Proceedings of the ISWC Workshop on Consuming Linked Data. 2013: CEUR-WS. M. Maleshkova, P. Philipp, Y. Sure-Vetter, R. Studer. Smart Web Services (SmartWS) – The Future of Services on the Web. IPSI BgD Transactions on Advanced Research (TAR), 12 (1), pp. 15-26, January, 2016. T. Weller, M. Maleshkova, K. März, L. Maier-Hein. A RESTful Approach for Developing Medical Decision Support Systems. The Semantic Web: ESWC 2015 Satellite Events, pp. 376-384, Springer, 9341. T. Weller, M. Maleshkova. Cognitive Process - An Open-Source Tool to Capture Processes according to the Linked Data Principles. The Semantic Web: ESWC 2016 Satellite Events, Springer. L. Zhang, A. Rettinger, J. Zhang. A Knowledge Base Approach to Cross-Lingual Keyword Query Interpretation. The 15th International Semantic Web Conference (ISWC'16), Springer, Oktober, 2016 Prof. Dr. Rudi Studer | Cognitive Systems Institute Speaker Series