Introduction to semantic web. The first results in publication of library data into the semantic web at the National Széchényi Libary (National Library of Hungary)
This tutorial explains the Data Web vision, some preliminary standards and technologies as well as some tools and technological building blocks developed by AKSW research group from Universität Leipzig.
A Semantic Data Model for Web ApplicationsArmin Haller
This presentation gives a short overview of the Semantic Web, RDFa and Linked Data. The second part briefly discusses ActiveRaUL, our model and system for developing form-based Web applications using Semantic Web technologies.
This tutorial explains the Data Web vision, some preliminary standards and technologies as well as some tools and technological building blocks developed by AKSW research group from Universität Leipzig.
A Semantic Data Model for Web ApplicationsArmin Haller
This presentation gives a short overview of the Semantic Web, RDFa and Linked Data. The second part briefly discusses ActiveRaUL, our model and system for developing form-based Web applications using Semantic Web technologies.
Tutorial on RDFa, to be held at ISWC2010 in Shanghai, China. (I was supposed to hold the tutorial but last minute issues made it impossible for me to travel there...)
Overview of how data on the Web of Data can be consumed (first and foremost Linked Data) and implications for the development of usage mining approaches.
References:
Elbedweihy, K., Mazumdar, S., Cano, A. E., Wrigley, S. N., & Ciravegna, F. (2011). Identifying Information Needs by Modelling Collective Query Patterns. COLD, 782.
Elbedweihy, K., Wrigley, S. N., & Ciravegna, F. (2012). Improving Semantic Search Using Query Log Analysis. Interacting with Linked Data (ILD 2012), 61.
Raghuveer, A. (2012). Characterizing machine agent behavior through SPARQL query mining. In Proceedings of the International Workshop on Usage Analysis and the Web of Data, Lyon, France.
Arias, M., Fernández, J. D., Martínez-Prieto, M. A., & de la Fuente, P. (2011). An empirical study of real-world SPARQL queries. arXiv preprint arXiv:1103.5043.
Hartig, O., Bizer, C., & Freytag, J. C. (2009). Executing SPARQL queries over the web of linked data (pp. 293-309). Springer Berlin Heidelberg.
Verborgh, R., Hartig, O., De Meester, B., Haesendonck, G., De Vocht, L., Vander Sande, M., ... & Van de Walle, R. (2014). Querying datasets on the web with high availability. In The Semantic Web–ISWC 2014 (pp. 180-196). Springer International Publishing.
Verborgh, R., Vander Sande, M., Colpaert, P., Coppens, S., Mannens, E., & Van de Walle, R. (2014, April). Web-Scale Querying through Linked Data Fragments. In LDOW.
Luczak-Rösch, M., & Bischoff, M. (2011). Statistical analysis of web of data usage. In Joint Workshop on Knowledge Evolution and Ontology Dynamics (EvoDyn2011), CEUR WS.
Luczak-Rösch, M. (2014). Usage-dependent maintenance of structured Web data sets (Doctoral dissertation, Freie Universität Berlin, Germany), http://edocs.fu-berlin.de/diss/receive/FUDISS_thesis_000000096138.
Usage of Linked Data: Introduction and Application ScenariosEUCLID project
This presentation introduces the main principles of Linked Data, the underlying technologies and background standards. It provides basic knowledge for how data can be published over the Web, how it can be queried, and what are the possible use cases and benefits. As an example, we use the development of a music portal (based on the MusicBrainz dataset), which facilitates access to a wide range of information and multimedia resources relating to music.
The Bounties of Semantic Data Integration for the Enterprise Ontotext
If you are looking for solutions that allow you not only to manage all of your data (structured, semi-structured and unstructured) but to also make the most out of them, using a common language is critical.
Adding Semantic Technology to data integration is the glue that holds together all your enterprise data and their relationships in a meaningful way.
Learn how you can quickly design data processing jobs and integrate massive amounts of data and see what semantic integration can do for your data and your business.
www.ontotext.com
Lotus: Linked Open Text UnleaShed - ISWC COLD '15Filip Ilievski
Abstract:
It is difficult to find resources on the Semantic Web today, in particular if one wants to search for resources based on natural language keywords and across multiple datasets.
In this paper, we present \lotus: Linked Open Text UnleaShed, a full-text lookup index over a huge Linked Open Data collection.
We detail \lotus' approach, its implementation, its coverage, and demonstrate the ease with which it allows the LOD cloud to be queried in different domain-specific scenarios.
Create Linked Open Data (LOD) Microthesauri using Art & Architecture Thesaurus (AAT) LOD. View and manage options by a non-techy person. Everyone can use, create,
derive from, & map to AAT microthesauri and make the digital collection become LOD-ready dataset.
First Steps in Semantic Data Modelling and Search & Analytics in the CloudOntotext
This webinar will break the roadblocks that prevent many from reaping the benefits of heavyweight Semantic Technology in small scale projects. We will show you how to build Semantic Search & Analytics proof of concepts by using managed services in the Cloud.
Tutorial on RDFa, to be held at ISWC2010 in Shanghai, China. (I was supposed to hold the tutorial but last minute issues made it impossible for me to travel there...)
Overview of how data on the Web of Data can be consumed (first and foremost Linked Data) and implications for the development of usage mining approaches.
References:
Elbedweihy, K., Mazumdar, S., Cano, A. E., Wrigley, S. N., & Ciravegna, F. (2011). Identifying Information Needs by Modelling Collective Query Patterns. COLD, 782.
Elbedweihy, K., Wrigley, S. N., & Ciravegna, F. (2012). Improving Semantic Search Using Query Log Analysis. Interacting with Linked Data (ILD 2012), 61.
Raghuveer, A. (2012). Characterizing machine agent behavior through SPARQL query mining. In Proceedings of the International Workshop on Usage Analysis and the Web of Data, Lyon, France.
Arias, M., Fernández, J. D., Martínez-Prieto, M. A., & de la Fuente, P. (2011). An empirical study of real-world SPARQL queries. arXiv preprint arXiv:1103.5043.
Hartig, O., Bizer, C., & Freytag, J. C. (2009). Executing SPARQL queries over the web of linked data (pp. 293-309). Springer Berlin Heidelberg.
Verborgh, R., Hartig, O., De Meester, B., Haesendonck, G., De Vocht, L., Vander Sande, M., ... & Van de Walle, R. (2014). Querying datasets on the web with high availability. In The Semantic Web–ISWC 2014 (pp. 180-196). Springer International Publishing.
Verborgh, R., Vander Sande, M., Colpaert, P., Coppens, S., Mannens, E., & Van de Walle, R. (2014, April). Web-Scale Querying through Linked Data Fragments. In LDOW.
Luczak-Rösch, M., & Bischoff, M. (2011). Statistical analysis of web of data usage. In Joint Workshop on Knowledge Evolution and Ontology Dynamics (EvoDyn2011), CEUR WS.
Luczak-Rösch, M. (2014). Usage-dependent maintenance of structured Web data sets (Doctoral dissertation, Freie Universität Berlin, Germany), http://edocs.fu-berlin.de/diss/receive/FUDISS_thesis_000000096138.
Usage of Linked Data: Introduction and Application ScenariosEUCLID project
This presentation introduces the main principles of Linked Data, the underlying technologies and background standards. It provides basic knowledge for how data can be published over the Web, how it can be queried, and what are the possible use cases and benefits. As an example, we use the development of a music portal (based on the MusicBrainz dataset), which facilitates access to a wide range of information and multimedia resources relating to music.
The Bounties of Semantic Data Integration for the Enterprise Ontotext
If you are looking for solutions that allow you not only to manage all of your data (structured, semi-structured and unstructured) but to also make the most out of them, using a common language is critical.
Adding Semantic Technology to data integration is the glue that holds together all your enterprise data and their relationships in a meaningful way.
Learn how you can quickly design data processing jobs and integrate massive amounts of data and see what semantic integration can do for your data and your business.
www.ontotext.com
Lotus: Linked Open Text UnleaShed - ISWC COLD '15Filip Ilievski
Abstract:
It is difficult to find resources on the Semantic Web today, in particular if one wants to search for resources based on natural language keywords and across multiple datasets.
In this paper, we present \lotus: Linked Open Text UnleaShed, a full-text lookup index over a huge Linked Open Data collection.
We detail \lotus' approach, its implementation, its coverage, and demonstrate the ease with which it allows the LOD cloud to be queried in different domain-specific scenarios.
Create Linked Open Data (LOD) Microthesauri using Art & Architecture Thesaurus (AAT) LOD. View and manage options by a non-techy person. Everyone can use, create,
derive from, & map to AAT microthesauri and make the digital collection become LOD-ready dataset.
First Steps in Semantic Data Modelling and Search & Analytics in the CloudOntotext
This webinar will break the roadblocks that prevent many from reaping the benefits of heavyweight Semantic Technology in small scale projects. We will show you how to build Semantic Search & Analytics proof of concepts by using managed services in the Cloud.
Linked data for Enterprise Data IntegrationSören Auer
The Web evolves into a Web of Data. In parallel Intranets of large companies will evolve into Data Intranets based on the Linked Data principles. Linked Data has the potential to complement the SOA paradigm with a light-weight, adaptive data integration approach.
Nelson Piedra , Janneth Chicaiza
and Jorge López, Universidad Técnica Particular de Loja, Edmundo
Tovar, Universidad Politécnica de Madrid,
and Oscar Martínez, Universitas
Miguel Hernández
Explore the advantages of using linked data with OERs.
SKOS Thesaurus Editing which makes use of "Linked Data". A lot of facts from the Semantic Web (e.g. from DBpedia) can be used to augment local thesauri or knowledge bases. This video shows how PoolParty Thesaurus Management makes use of data from the Semantic Web.
morning session talk at the second Keystone Training School "Keyword search in Big Linked Data" held in Santiago de Compostela.
https://eventos.citius.usc.es/keystone.school/
It19 20140721 linked data personal perspectiveJanifer Gatenby
A presentation made for Standards Australia's seminar. Outlines the basic aspects of linked data from a personal perspective and where it fits with direct and subject searching.
Presentation at ELAG 2011, European Library Automation Group Conference, Prague, Czech Republic. 25th May 2011
http://elag2011.techlib.cz/en/815-lifting-the-lid-on-linked-data/
A szemantikus web és a könyvtárak, különös tekintettel a BIBFRAME formátumrahorvadam
A szemantikus web ismertetése. A szemantikus web jelenléte a könyvtárakban. A BIBFRAME formátum ismertetése. BIBFRAME a Magyar Nemzeti Múzeum Központi Könyvtárában. Másolásás katalogizálás jövője. A webnek fogunk közvetlenül katalogizálni.
First steps towards publishing library data on the semantic webhorvadam
First steps towards publishing library data on the semantic web. Implementing:
CoolUri
RDFDC
SKOS
RDF database and SPARQL interface
Content negotiation
Catalogue enrichment in LibriVision
Link service based on OpenUrl
Bookmark service
Permalink
Google Cover Page
Map integration
Cover pages produced by NSZL
Permalink is now a Cool URI
Linked Data at the National Széchényi Library : road to the publicationhorvadam
National Széchényi Library (National Library of Hungary) published its entire catalog and the thesaurus and the name authority file into the semantic web.ű
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
20240609 QFM020 Irresponsible AI Reading List May 2024
Semantic web: where are we now?
1. Semantic web: where are weSemantic web: where are we
now?now?
ADLUG Users Group MeetingADLUG Users Group Meeting
Bilbao, 16-18 September, 2009Bilbao, 16-18 September, 2009
ÁdámÁdám HorváthHorváth
NSZLNSZL
2. 2 Semantic web: where are we
ContentsContents
TutorialTutorial
Where are we now?Where are we now?
3. 3 Semantic web: where are we
Linked data on the webLinked data on the web
Use RDF data modelUse RDF data model
Use RDF linksUse RDF links
Web of Data or Semantic WebWeb of Data or Semantic Web
Linked Data browsersLinked Data browsers
Linked Data provides a single,Linked Data provides a single,
standardised access mechanismstandardised access mechanism
(compared to APIs)(compared to APIs)
4. 4 Semantic web: where are we
Advantage of Linked DataAdvantage of Linked Data
Linked Data provides a single,Linked Data provides a single,
standardised access mechanismstandardised access mechanism
– Easily crawlableEasily crawlable
– Accessible using generic data browserAccessible using generic data browserss
– Enables link between data from differentEnables link between data from different
data sourcesdata sources
5. 5 Semantic web: where are we
Web architecture : resourcesWeb architecture : resources
We have to identify the items of interestWe have to identify the items of interest
in our domainin our domain
All items of interest are calledAll items of interest are called
resourcesresources
– Information resources (everything in theInformation resources (everything in the
traditional web)traditional web)
– Non-information resources (real worldNon-information resources (real world
objects, things)objects, things)
6. 6 Semantic web: where are we
Web architecture : resourcesWeb architecture : resources
identifiersidentifiers
Uniform Resource Identifiers (URIs)Uniform Resource Identifiers (URIs)
HTTP URIHTTP URI
– Not URN, DOI and so onNot URN, DOI and so on
Why HTTP URIWhy HTTP URI
– Simple way of creating globally uniqueSimple way of creating globally unique
identifier without centralised managementidentifier without centralised management
– Can also be used for accessing humanCan also be used for accessing human
readable information (information on thereadable information (information on the
Web)Web)
7. 7 Semantic web: where are we
Web architecture : representationWeb architecture : representation
Information resources can haveInformation resources can have
representationsrepresentations
Representations are stream of bytesRepresentations are stream of bytes
A resource can have manyA resource can have many
representationsrepresentations
8. 8 Semantic web: where are we
Web architecture : dereferencingWeb architecture : dereferencing
HTTP URIHTTP URI
This is the process of looking up URI on theThis is the process of looking up URI on the
WEB to get information about the referencedWEB to get information about the referenced
resourceresource
Information resourcesInformation resources
– HTTP 200HTTP 200 „OK”„OK” response coderesponse code
Non-information resourcesNon-information resources
– HTTP 303HTTP 303 „„SeeSee OOtherther”” reference codereference code
– The client dereferences the new URI and getsThe client dereferences the new URI and gets
representation describing the original non-representation describing the original non-
information objectinformation object
9. 9 Semantic web: where are we
Web architecture : contentWeb architecture : content
negotiationnegotiation
For non-information resources it is aFor non-information resources it is a
good practice to create an HTMLgood practice to create an HTML
representation describing the thing forrepresentation describing the thing for
human being and an RDFhuman being and an RDF
representation for machinesrepresentation for machines
The different representations can beThe different representations can be
reached via the content negotiationreached via the content negotiation
12. 12 Semantic web: where are we
Web architecture : URI aliasesWeb architecture : URI aliases
Two data provider can assign differentTwo data provider can assign different
URI for the same resourceURI for the same resource
– http://dbpedia.org/resource/Berlinhttp://dbpedia.org/resource/Berlin
– http://sws.geonames.org/2950159/http://sws.geonames.org/2950159/
Information providers often setInformation providers often set
owl:sameAsowl:sameAs
link to URI aliases they know aboutlink to URI aliases they know about
13. 13 Semantic web: where are we
Web architecture : AssociatedWeb architecture : Associated
descriptionsdescriptions
RDF description of a non-informationRDF description of a non-information
object that a client obtains byobject that a client obtains by
dereferencing the URI of the non-dereferencing the URI of the non-
information objectinformation object
14. 14 Semantic web: where are we
The RDF data modelThe RDF data model
RDF (Resource Description Framework)RDF (Resource Description Framework)
is used to represent information aboutis used to represent information about
resourcesresources
A description of a resource isA description of a resource is
represented as a number of triplesrepresented as a number of triples
Triples contain subject, predicate,Triples contain subject, predicate,
objectobject
15. 15 Semantic web: where are we
The RDF data modelThe RDF data model
ExampleExample
– The bookThe book has the titlehas the title DekameronDekameron
– SubjectSubject PredicatePredicate ObjectObject
16. 16 Semantic web: where are we
The RDF data modelThe RDF data model
SubjectSubject
– URI identifying the described resourceURI identifying the described resource
ObjectObject
– Literal value (string, number, date, etc)Literal value (string, number, date, etc)
– URI that is related somehow to the subjectURI that is related somehow to the subject
PredicatePredicate
– Indicates the relationship between theIndicates the relationship between the
subject and objectsubject and object
– URI, and comes from vocabulariesURI, and comes from vocabularies
17. 17 Semantic web: where are we
The RDF data modelThe RDF data model
Two types of RDF triplesTwo types of RDF triples
– Literal RDFLiteral RDF
• Used to describe the properties of resourcesUsed to describe the properties of resources
– The title of a bookThe title of a book
– RDF linksRDF links
• Three URIThree URI
• Subject and Object identify the interlinkedSubject and Object identify the interlinked
resourcesresources
• Predicate tells the relationshipPredicate tells the relationship
18. 18 Semantic web: where are we
The RDF data modelThe RDF data model
ExampleExample 11
– The bookThe book has the titlehas the title DekameronDekameron
– SubjectSubject PredicatePredicate ObjectObject
Example 2Example 2
– SubjectSubject
• http://nektar.oszk.hu/resource/manifestation/2645471http://nektar.oszk.hu/resource/manifestation/2645471
– PredicatePredicate
• <dc:title><dc:title>
– ObjectObject
• DekameronDekameron
19.
20.
21.
22.
23. 23 Semantic web: where are we
The RDF data modelThe RDF data model
The most valuable RDF links are thoseThe most valuable RDF links are those
that connect the resource to externalthat connect the resource to external
data published by other data sourcesdata published by other data sources
24. 24 Semantic web: where are we
The RDF data modelThe RDF data model
Benefits of using the RDF data modelBenefits of using the RDF data model
– Clients can lookup every URI in the RDFClients can lookup every URI in the RDF
graph over the Web to retrieve additionalgraph over the Web to retrieve additional
informationinformation
– Information from different sources mergeInformation from different sources merge
naturallynaturally
– RDF links between data from differentRDF links between data from different
sources can be setsources can be set
– Information expressed in different schemaInformation expressed in different schema
can be represented in a single modelcan be represented in a single model
25. 25 Semantic web: where are we
Choosing URIsChoosing URIs
Good nameGood name
– ExpressiveExpressive
– Others can use confidentlyOthers can use confidently
Technical infrastructure to make themTechnical infrastructure to make them
dereferencabledereferencable
26. 26 Semantic web: where are we
Choosing URIsChoosing URIs
Good practice (Cool URIs)Good practice (Cool URIs)
– Use HTTP URIUse HTTP URI
• Not URN, DOINot URN, DOI
– Define URI in the namespace under yourDefine URI in the namespace under your
controlcontrol
27. 27 Semantic web: where are we
Choosing URIsChoosing URIs
Good practice (Cool URIs)Good practice (Cool URIs)
– Implementation specific things should notImplementation specific things should not
appearappear
– Compare:Compare:
http://link.oszk.hu/libriurl.php?http://link.oszk.hu/libriurl.php?
LN=hu&DB=OSZK&SRY=an&SRE=000002645471LN=hu&DB=OSZK&SRY=an&SRE=000002645471
http://nektar.oszk.hu/hu/manifestation/2645471http://nektar.oszk.hu/hu/manifestation/2645471
28. 28 Semantic web: where are we
Choosing URIsChoosing URIs
Good practice (Cool URIs)Good practice (Cool URIs)
– Try to keep stable and persistentTry to keep stable and persistent
29. 29 Semantic web: where are we
VocabulariesVocabularies
Well-known vocabulariesWell-known vocabularies
– Friend-of-a-Friend (FOAF), vocabulary for describing people.Friend-of-a-Friend (FOAF), vocabulary for describing people.
– Dublin Core (DC) defines general metadata attributes. See also theirDublin Core (DC) defines general metadata attributes. See also their
new domains and ranges draft.new domains and ranges draft.
– Semantically-Interlinked Online Communities (SIOC), vocabulary forSemantically-Interlinked Online Communities (SIOC), vocabulary for
representing online communities.representing online communities.
– Description of a Project (DOAP), vocabulary for describing projects.Description of a Project (DOAP), vocabulary for describing projects.
– Simple Knowledge Organization System (SKOS), vocabulary forSimple Knowledge Organization System (SKOS), vocabulary for
representing taxonomies and loosely structured knowledge.representing taxonomies and loosely structured knowledge.
– Music Ontology provides terms for describing artists, albums andMusic Ontology provides terms for describing artists, albums and
tracks.tracks.
– Review Vocabulary, vocabulary for representing reviews.Review Vocabulary, vocabulary for representing reviews.
– Creative Commons (CC), vocabulary for describing license terms.Creative Commons (CC), vocabulary for describing license terms.
30. 30 Semantic web: where are we
Serving information as Linked DataServing information as Linked Data
RequirementRequirement
– Things must be identified with dereferenceableThings must be identified with dereferenceable
HTTP URIsHTTP URIs
– Data source must return an RDF/XMLData source must return an RDF/XML
description of the identified resourcedescription of the identified resource
– Links to external resourcesLinks to external resources
– Links from external resources (ensure that thereLinks from external resources (ensure that there
are external RDF links pointing at URIs fromare external RDF links pointing at URIs from
your dataset)your dataset)
31. 31 Semantic web: where are we
Serving information as Linked DataServing information as Linked Data
How to create external links pointing to yourHow to create external links pointing to your
data?data?
– In your FOAF file point the central resources ofIn your FOAF file point the central resources of
your datasetyour dataset
• If one of your friends has a FOAF file and points toIf one of your friends has a FOAF file and points to
you your dataset is now part of the Web of Datayou your dataset is now part of the Web of Data
– Convince the owners of related data sets toConvince the owners of related data sets to
auto-generate links to your datasetauto-generate links to your dataset
32. 32 Semantic web: where are we
Serving information as Linked DataServing information as Linked Data
Serving the dataset as static RDF fileServing the dataset as static RDF file
– Which cases?Which cases?
• RDF files are created manuallyRDF files are created manually
• RDF files are created programs that produces fileRDF files are created programs that produces file
outputoutput
– HowHow
• Give .rdf filename extensionGive .rdf filename extension
• In httpd.conf add this lineIn httpd.conf add this line
– AddType application/rdf+xml .rdfAddType application/rdf+xml .rdf
– Problem: 303 redirect does not workProblem: 303 redirect does not work
33. 33 Semantic web: where are we
Serving information as Linked DataServing information as Linked Data
Serving relational databasesServing relational databases
– D2R serverD2R server
• Provides a SPARQL endpoint to the relationalProvides a SPARQL endpoint to the relational
database by the means of mapping filedatabase by the means of mapping file
34. 34 Semantic web: where are we
Serving information as Linked DataServing information as Linked Data
Wrappers around existing applications andWrappers around existing applications and
WEB APIWEB API
– RDF Book MashupRDF Book Mashup
• The RDF Book Mashup assigns a HTTP URI to eachThe RDF Book Mashup assigns a HTTP URI to each
book that has an ISBN numberbook that has an ISBN number
• Whenever the HTTP URI is dereferenceWhenever the HTTP URI is dereferencedd RDF BookRDF Book
Mashup requires data from Amazon API and GoogleMashup requires data from Amazon API and Google
Base APIBase API
35. 35 Semantic web: where are we
Serving information as Linked DataServing information as Linked Data
RDF databaseRDF database
– JenaJena
• SPARQL endpoint is JoSPARQL endpoint is Josekiseki
36. 36 Semantic web: where are we
Testing and debuggingTesting and debugging
RDF browsersRDF browsers
– TabulatorTabulator
– MarblesMarbles
– Open Link RDF BrowserOpen Link RDF Browser
– DiscoDisco
Testing dereferencingTesting dereferencing
– curlcurl
W3C RDF validation serviceW3C RDF validation service
37. 37 Semantic web: where are we
Discovering linked data on the webDiscovering linked data on the web
Ping the semantic webPing the semantic web
– Registry service for RDF documentsRegistry service for RDF documents
HTML link auto-discoveryHTML link auto-discovery
– Set links from existing web pages to RDF dataSet links from existing web pages to RDF data
– HTML <link> element in the <head> of yourHTML <link> element in the <head> of your
HTML pageHTML page
– <link rel="alternate" type="application/rdf+xml"<link rel="alternate" type="application/rdf+xml"
href="link_to_the_RDF_version"/>href="link_to_the_RDF_version"/>
38. 38 Semantic web: where are we
Discovering linked data on the webDiscovering linked data on the web
Semantic Web Crawling: a SitemapSemantic Web Crawling: a Sitemap
ExtensionExtension
– Data publishers can state where RDF is locatedData publishers can state where RDF is located
– Robot.txtRobot.txt
Dataset List on the ESW WikiDataset List on the ESW Wiki
39. 39 Semantic web: where are we
Web of data search enginesWeb of data search engines
FalconsFalcons developed by IWS Chinadeveloped by IWS China
SindiceSindice developed by DERI Irelanddeveloped by DERI Ireland
WatsonWatson developed by KMi, UKdeveloped by KMi, UK
Semantic Web Search Engine (SWSE)Semantic Web Search Engine (SWSE)
developed by DERI Irelanddeveloped by DERI Ireland
SwoogleSwoogle developed by ubiquity group atdeveloped by ubiquity group at
UMBC USAUMBC USA
40. 40 Semantic web: where are we
Semantic web: where are we now?Semantic web: where are we now?
41.
42. 42 Semantic web: where are we
The model in detailThe model in detail
The thing URIThe thing URI
http://nektar.oszk.hu/resource/manifestation/2645471http://nektar.oszk.hu/resource/manifestation/2645471
– The 303 redirection code indicates that this URI is for thingThe 303 redirection code indicates that this URI is for thing
The RDF document URIThe RDF document URI
http://nektar.oszk.hu/data/manifestation/2645471http://nektar.oszk.hu/data/manifestation/2645471
The WEB (LibriVision) document URIThe WEB (LibriVision) document URI
http://nektar.oszk.hu/http://nektar.oszk.hu/huhu/manifestation/2645471/manifestation/2645471
http://nektar.oszk.hu/http://nektar.oszk.hu/enen/manifestation/2645471/manifestation/2645471
43. 43 Semantic web: where are we
The model in detailThe model in detail
Content negotiation rulesContent negotiation rules
– If application/rdf+xml is accepted the xml is givenIf application/rdf+xml is accepted the xml is given
from this address via content negotiation and 303from this address via content negotiation and 303
redirect:redirect:
http://nektar.oszk.hu/data/manifestation/2645471http://nektar.oszk.hu/data/manifestation/2645471
– If text/html is acceptedIf text/html is accepted
• Depending on the language of the browser either theDepending on the language of the browser either the
Hungarian or the English interface of LibriVision is given.Hungarian or the English interface of LibriVision is given.
The default is Hungarian (again via content negotiation):The default is Hungarian (again via content negotiation):
http://nektar.oszk.hu/hu/manifestation/2645471http://nektar.oszk.hu/hu/manifestation/2645471
44. 44 Semantic web: where are we
The working modelThe working model
45. 45 Semantic web: where are we
The record in LibriVisionThe record in LibriVision
46. 46 Semantic web: where are we
The record in LibriVisionThe record in LibriVision
47. 47 Semantic web: where are we
The record in LibriVisionThe record in LibriVision
48. 48 Semantic web: where are we
The record in LibriVisionThe record in LibriVision
49. 49 Semantic web: where are we
The record in LibriVisionThe record in LibriVision
50. 50 Semantic web: where are we
The record in LibriVisionThe record in LibriVision
51. 51 Semantic web: where are we
The record in LibriVisionThe record in LibriVision
52. 52 Semantic web: where are we
The record in LibriVisionThe record in LibriVision
53. 53 Semantic web: where are we
The record in LibriVisionThe record in LibriVision
54. 54 Semantic web: where are we
SKOSSKOS
SKOS is now a W3C recommendationSKOS is now a W3C recommendation
– Last year it just was a proposedLast year it just was a proposed
recommendationrecommendation
NSZL is among the first implementersNSZL is among the first implementers
55. 55 Semantic web: where are we
Useful linksUseful links
How to Publish Linked Data on the WebHow to Publish Linked Data on the Web
– http://www4.wiwiss.fu-berlin.de/bizer/pub/LinkedDataTutorial/http://www4.wiwiss.fu-berlin.de/bizer/pub/LinkedDataTutorial/
Cool URIs for the Semantic WebCool URIs for the Semantic Web
– http://www.w3.org/TR/2008/NOTE-cooluris-20080331/http://www.w3.org/TR/2008/NOTE-cooluris-20080331/
SKOS Simple Knowledge Organization SystemSKOS Simple Knowledge Organization System
ReferenceReference
– http://www.w3.org/TR/skos-reference/http://www.w3.org/TR/skos-reference/
SKOS Simple Knowledge Organization System PrimerSKOS Simple Knowledge Organization System Primer
– http://www.w3.org/TR/skos-primer/http://www.w3.org/TR/skos-primer/
SKOS implementation reportSKOS implementation report
– http://www.w3.org/2006/07/SWD/SKOS/reference/20090315/implehttp://www.w3.org/2006/07/SWD/SKOS/reference/20090315/imple
mentation.htmlmentation.html