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=Textbook=
''This page currently shows some of the lectures and readings from the Spring of 2023. It will be updated with materials for 2024 as the course progresses.''


* New textbook in the Spring semester 2021 is ''The Knowledge Graph Cookbook - Recipes that Work, by Andreas Blumauer and Helmut Nagy (April 16, 2020). mono/monochrom.'' '''The whole book is mandatory reading.'''
=Textbooks=


* The old textbook in INFO216 was ''Semantic Web for the Working Ontologist, Second Edition: Effective Modeling in RDFS and OWL by Dean Allemang and James Hendler (Jun 3, 2011). Morgan Kaufmann.'' It is still recommended reading, but not mandatory.
Main course book (''the whole book is mandatory reading''):
* Dean Allemang, James Hendler & Fabien Gandon (2020). '''Semantic Web for the Working Ontologist, Effective Modeling for Linked Data, RDFS and OWL (Third Edition).''' ISBN: 9781450376143, PDF ISBN: 9781450376150, Hardcover ISBN: 9781450376174, DOI: 10.1145/3382097.  


Supplementary reading book (''not'' mandatory):
* Andreas Blumauer and Helmut Nagy (2020). '''The Knowledge Graph Cookbook - Recipes that Work.''' mono/monochrom. ISBN-10: ‎3902796707, ISBN-13: 978-3902796707.


=Other materials=
=Other materials=


In addition, '''the materials listed below for each lecture are either mandatory or suggested reading.''' More materials will be added to each lecture in the coming weeks.
In addition, '''the materials listed below for each lecture are either mandatory or suggested reading'''. More materials will be added to each lecture in the coming weeks.


'''The lectures and lectures notes are also part of the curriculum.'''
'''The lectures and lectures notes are also part of the curriculum.'''


Make sure you download the electronic resources to your own computer in good time before the exam. This is your own responsibility. That way you are safe if a site becomes unavailable or somehow damaged the last few days before the exam.  
Make sure you download the electronic resources to your own computer in good time before the exam. This is your own responsibility. That way you are safe if a site becomes unavailable or somehow damaged the last few days before the exam.


''Note:'' to download some of the papers, you may need to be inside UiB's network. Either use a computer directly on the UiB network or connect to your UiB account through VPN.
''Note:'' to download some of the papers, you may need to be inside UiB's network. Either use a computer directly on the UiB network or connect to your UiB account through VPN.


=Lectures (in progress)=


=Lectures=
Below are the mandatory and suggested readings for each lecture. All the textbook chapters in Allemang, Hendler & Gandon are mandatory, whereas the chapters in Blumauer & Nagy are suggested.


Below are the mandatory and suggested readings for each lecture. All the textbook chapters in Blumauer & Nagy are mandatory, whereas the chapters in Allemang & Hendler are suggested. [[Java-based readings]] are also available as an alternative to the Python-based materials.
==Lecture 1: Introduction to KGs==
 
 
==Lecture 1: Knowledge Graphs==


Themes:
Themes:
* Introduction to Knowledge Graphs
* Introduction to Knowledge Graphs
* Organisation of INFO216
* Organisation of the course


Mandatory readings:
Mandatory readings:
* Pages 27-55 and 105-122 in Blumauer & Nagy (mandatory)
* Chapters 1-2 in Allemang, Hendler & Gandon (3rd edition)
* [http://www.youtube.com/watch?v=HeUrEh-nqtU Tim Berners-Lee talks about the semantic web] (mandatory)
* [http://www.youtube.com/watch?v=HeUrEh-nqtU Tim Berners-Lee talks about the semantic web]
* [[:File:S01-KnowledgeGraphs.pdf | Slides from the lecture]]
* [[:File:S01-KnowledgeGraphs.pdf | Slides from the lecture]]


Useful materials:
Useful materials:
* Chapters 1-2 in Allemang & Hendler (suggested)
* Important knowledge graphs (''which we will look more at later''):
 
** Wikidata (https://www.wikidata.org/)
<!-- ** DBpedia (https://www.dbpedia.org, https://dbpedia.org/page/Bergen)
** GeoNames (https://www.geonames.org/)
** BabelNet (https://babelnet.org/)
** Linking Open Data (LOD) (http://lod-cloud.net)
** Linked Open Vocabularies (LOV, https://lov.linkeddata.es/dataset/lov/)
-->
* Pages 27-55 and 105-122 in Blumauer & Nagy (suggested)


==Lecture 2: RDF==
==Lecture 2: Representing KGs (RDF)==


Themes:  
Themes:  
* RDF
* Resource Description Framework (RDF)
* Programming RDF in Python
* Programming RDF in Python
* The group project


Mandatory readings:
Mandatory readings:
* Pages 25-28, 92-100, 125-128, and 164-167 in Blumauer & Nagy (mandatory)
* Chapter 3 in Allemang, Hendler & Gandon (3rd edition)
* [https://www.w3.org/TR/rdf11-primer/ W3C's RDF 1.1 Primer] (mandatory)
* [https://www.w3.org/TR/rdf11-primer/ W3C's RDF 1.1 Primer] until and including 5.1.2 Turtle (but not the rest for now)
* [http://rdflib.readthedocs.io/ rdflib 5.0.0] materials:
* [http://rdflib.readthedocs.io/ RDFlib 7.0.0 documentation], the following pages:
** Main page
** The main page
** Getting started with RDFLib
** Getting started with RDFLib
** Loading and saving RDF
** Loading and saving RDF
Line 54: Line 61:
** Navigating Graphs
** Navigating Graphs
** Utilities and convenience functions
** Utilities and convenience functions
** RDF terms in rdflib
** Namespaces and Bindings
* [[:File:S02-RDF.pdf | Slides from the lecture]]
* [[:File:S02-RDF.pdf | Slides from the lecture]]


Useful materials:
Useful materials:
* Chapter 3 in Allemang & Hendler (suggested)
* [https://rdflib.readthedocs.io/en/stable/apidocs/modules.html RDFLib 7.0.0 packages] (reference for the labs)
* [https://rdflib.readthedocs.io/en/stable/apidocs/modules.html RDFLib API documentation] (useful for the labs and group project)
* [https://www.ldf.fi/service/rdf-grapher RDF Grapher] for drawing RDF graphs
* [https://github.com/RDFLib/rdflib RDFLib's GitHub page]
* [https://issemantic.net/rdf-visualizer RDF Visualizer] for drawing RDF graphs
* [https://www.w3.org/TR/rdf11-concepts/ W3C's RDF 1.1 Concepts and Abstract Syntax] (cursory)
* [https://www.w3.org/TR/rdf11-concepts/ W3C's RDF 1.1 Concepts and Abstract Syntax]
* [https://www.w3.org/2018/09/rdf-data-viz/ RDF Data Visualization tools]
<!-- * An overview page of some other [https://www.w3.org/2018/09/rdf-data-viz/ RDF Data Visualization tools] -->
* Pages 25-28, 92-100, 125-128, and 164-167 in Blumauer & Nagy (suggested)


 
==Lecture 3: Querying and updating KGs (SPARQL)==
==Lecture 3: SPARQL==


Themes:
Themes:
Line 71: Line 80:
* Programming SPARQL and SPARQL Update in Python
* Programming SPARQL and SPARQL Update in Python


Mandatory readings:
Mandatory readings (tentative):
* For example pages 54-55, 133 in Blumauer & Nagy (mandatory)
* Chapter 6 in Allemang, Hendler & Gandon (3rd edition)
* Chapter 5 in Allemang & Hendler (suggested)
* [http://www.w3.org/TR/sparql11-update/ SPARQL 1.1 Update Language] (Sections 1-3)
* [[:File:sparql-1_1-cheat-sheet.pdf | SPARQL 1.1 Cheat Sheet]]
* [https://rdflib.readthedocs.io/ rdflib 7.0.0] materials:
* [http://www.w3.org/TR/sparql11-update/ SPARQL 1.1 Update Language] (Sections 1-3 are obligatory)
** [https://rdflib.readthedocs.io/en/stable/intro_to_sparql.html Querying with SPARQL]
<!-- * [[:File:S03-SPARQL-13.pdf | Slides from the lecture]] -->
* [https://rdflib.readthedocs.io/ rdflib 5.0.0] materials:
** Querying with SPARQL
* [[:File:S03-SPARQL.pdf | Slides from the lecture]]
* [[:File:S03-SPARQL.pdf | Slides from the lecture]]


Useful materials:
Useful materials:
<!-- * [https://medium.com/wallscope/constructing-sparql-queries-ca63b8b9ac02 Constructing SPARQL Queries] -->
* [http://www.w3.org/TR/sparql11-query/ SPARQL 1.1 Query Language]
* [http://www.w3.org/TR/sparql11-query/ SPARQL 1.1 Query Language]
* [http://www.w3.org/TR/sparql11-update/ SPARQL 1.1 Update Language] (the rest of it)
* [http://www.w3.org/TR/sparql11-update/ SPARQL 1.1 Update Language] (the rest of it)
* [https://www.w3.org/TR/sparql11-overview/ SPARQL 1.1 Overview]
* [[:File:sparql-1_1-cheat-sheet.pdf | SPARQL 1.1 Cheat Sheet]]
* [https://rdflib.readthedocs.io/en/stable/apidocs/modules.html RDFLib API documentation] (same as Lecture 1)
* [https://en.wikibooks.org/wiki/SPARQL/Expressions_and_Functions SPARQL Expressions and Functions]
* For example pages 54-55, 133 in Blumauer & Nagy (suggested)
* The [[:File:kg4news-dump-20230130.txt | Knowledge Graphs for the News]] example used in the lecture. (Remember to save with the correct ''.ttl'' extension.)


==Lecture 4: Tools and services==
==Lecture 4: Linked Open Data (LOD)==


Themes:
Themes:
* Application architecture
* Linked Open Data(LOD)
* Triple stores and Blazegraph
* The LOD cloud
* Endpoints and Wikidata Query Service (WDQS)
* Data provisioning
* Web APIs and JSON-LD
 
* Serialisation formats
Mandatory readings ''(both lecture 4 and 5)'':
* Chapter 5 in Allemang, Hendler & Gandon (3rd edition)
* [https://www.w3.org/DesignIssues/LinkedData.html Linked Data], Tim Berners-Lee, 2006-07-27.
* [[:File:S04-LOD.pdf | Slides from the lecture]]
 
Useful materials
* [https://www.ontotext.com/knowledgehub/fundamentals/linked-data-linked-open-data/ What Are Linked Data and Linked Open Data?]
* [[:File:BizerHeathBernersLee-LinkedData2009-TheStorySoFar.pdf | Bizer, C., Heath, T., & Berners-Lee, T. (2009). Linked data-the story so far. Semantic services, interoperability and web applications: emerging concepts, 205-227.]]
 
==Lecture 5: Open Knowledge Graphs I==
 
Themes:
* Important open KGs (LOD datasets)
** Wikidata
** DBpedia


Mandatory readings:
Mandatory readings:
* Part 4 (System Architecture and Technologies) in Blumauer & Nagy (mandatory)
* Chapter 5 in Allemang, Hendler & Gandon (3rd edition)
* Chapter 4 in Allemang & Hendler (suggested)
* Important knowledge graphs - and what to read:
* [http://lov.okfn.org/dataset/lov/ Linked Open Vocabularies (LOV)]
** Wikidata (https://www.wikidata.org/):
* [https://wiki.blazegraph.com/wiki/index.php/Main_Page Blazegraph]:
*** [https://www.wikidata.org/wiki/Wikidata:Introduction Introduction to Wikidata]
** Introduction - About Blazegraph
*** [https://www.wikidata.org/wiki/Wikidata:SPARQL_query_service/Wikidata_Query_Help SPARQL query service/A gentle introduction to the Wikidata Query Service]
** Getting started
*** example: [https://www.wikidata.org/wiki/Q26793]
** SPARQL Extensions - Full Text Search, GeoSpatial Search, Refication Done Right
** DBpedia (https://www.dbpedia.org):
* [[:File:S04-Architecture-6.pdf | Slides from the lecture]]
*** [http://wiki.dbpedia.org/about About Dbpedia]
* [https://www.wikidata.org/wiki/Wikidata:Introduction Wikidata]
*** example: [https://dbpedia.org/resource/Bergen]
* [https://www.JSON.org/json-en.html JSON Syntax] (mandatory)
*  [[:File:S05-S06-OpenKGs.pdf | Slides from the lecture]]
* Section 2 in W3C's [https://www.w3.org/TR/json-ld-api/ JSON-LD 1.1 Processing Algorithms and API] (mandatory)
 
* [[:File:S04-ToolsAndServices.pdf | Slides from the lecture]]
=Lecture 6: Open Knowledge Graphs II=
 
Themes:
* Important open KGs (LOD datasets)
** DBpedia ''(continued)''
** GeoNames
** the GDELT project
** WordNet
** BabelNet
** ConceptNet
 
Mandatory readings:
* Chapter 5 in Allemang, Hendler & Gandon (3rd edition)
* Important knowledge graphs - and what to read:
** GeoNames (https://www.geonames.org/):
*** [http://www.geonames.org/about.html About GeoNames]
*** example: [https://www.geonames.org/3161732/bergen.html]
** GDELT (https://www.gdeltproject.org/)
*** [https://www.gdeltproject.org/ The GDELT Project] - see also the About and Data pages
** WordNet (https://wordnet.princeton.edu/)
*** [https://wordnet.princeton.edu/ WordNet - A lexical database for English]
** BabelNet (https://babelnet.org/):
*** [http://live.babelnet.org/about About BabelNet]
*** [https://babelnet.org/how-to-use How to use]
*** example: [https://babelnet.org/synset?id=bn%3A00010008n&orig=Bergen&lang=EN]
** ConceptNet (http://conceptnet.io)
*** [http://conceptnet.io ConceptNet - An open, multilingual knowledge graph]
* [[:File:S05-S06-OpenKGs.pdf | Slides from the lecture]]
 
Useful materials
* Wikidata statistics
** [https://grafana.wikimedia.org/d/000000167/wikidata-datamodel?orgId=1&refresh=30m Entity statistics]
** [https://grafana.wikimedia.org/d/000000175/wikidata-datamodel-statements?orgId=1&refresh=30m Statement statistics]
* [https://www.dbpedia-spotlight.org/ DBpedia Spotlight]
* GDELT documentation
** [http://data.gdeltproject.org/documentation/GDELT-Event_Codebook-V2.0.pdf Event Codebook (and covers mentions)]
** [http://data.gdeltproject.org/documentation/CAMEO.Manual.1.1b3.pdf CAMEO event codes and other codes]
** [http://data.gdeltproject.org/documentation/GDELT-Global_Knowledge_Graph_Codebook-V2.1.pdf Global Knowledge Graph Codebook]
* Parts 1 and 3 in Blumauer & Nagy's text book (not tightly related to the lecture, but time to finish them by now :-))
 
==Lecture 7: Enterprise Knowledge Graphs==
 
Themes:
* Enterprise Knowledge Graphs (EKGs)
* Google’s Knowledge Graph
* Amazon’s Product Graph
* JSON-LD (video presentation)
 
Mandatory readings:
* [https://www.blog.google/products/search/introducing-knowledge-graph-things-not/ Introducing the Knowledge Graph: Things not Strings], Amit Singhal, Google (2012). ''(The blog post that introduced Google's knowledge graph to the world.)''
* [https://blog.google/products/search/about-knowledge-graph-and-knowledge-panels/ A reintroduction to our Knowledge Graph and knowledge panels], Danny Sullivan, Google (2020).
* [https://www.aboutamazon.com/news/innovation-at-amazon/making-search-easier How Amazon’s Product Graph is helping customers find products more easily], Arun Krishnan, Amazon (2018). ''(Short blog post that reviews some central ideas from the AutoKnow research paper listed below.)''
* [https://www.amazon.science/blog/building-product-graphs-automatically Building product graphs automatically], Xin Luna Dong, Amazon (2020).
* [https://json-ld.org/ JSON for Linking Data]
* [[:File:S07-EnterpriseKGs.pdf | Slides from the lecture]]


Useful materials:
Supplementary readings:
* [https://wiki.blazegraph.com/wiki/index.php/Main_Page Blazegraph]
* Parts 2 and 4 in Blumauer & Nagy's text book (''strongly suggested - this is where Blumauer & Nagy's book is good!'')
** The rest of it...
* [[:File:Bosch-LIS.pdf | LIS: A knowledge graph-based line information system]] by Grangel-González, I., Rickart, M., Rudolph, O., & Shah, F. (2023, May). In Proceedings of the European Semantic Web Conference (pp. 591-608). Cham: Springer Nature Switzerland.
* [http://json-ld.org/ JSON for Linked Data] (supplementary)
* [[:File:2006.13473.pdf | AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types]] by Dong, X. L., He, X., Kan, A., Li, X., Liang, Y., Ma, J., ... & Han, J. (2020, August). In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (pp. 2724-2734). ''Research paper from Amazon about AutoKnow - this is a bit heavy for Bachelor level, but you can have a look :-)''
** [http://www.youtube.com/watch?v=4x_xzT5eF5Q What is Linked Data?] Short video introduction to Linked Data by Manu Sporny
** [http://www.youtube.com/watch?v=vioCbTo3C-4 What is JSON-LD?] Short video introduction to JSON-LD by Manu Sporny


==Lecture 5: RDFS==
==Lecture 8: Rules (SHACL and RDFS)==


Themes:
Themes:
* RDFS
* SHACL and RDFS
* Axioms, rules and entailment
* Axioms, rules and entailment
* Programming RDFS in Python
* Programming SHACL and RDFS in Python


Mandatory readings:
Mandatory readings:
* Pages 101-106 in Blumauer & Nagy (mandatory)
* Chapters 7-8 in Allemang, Hendler & Gandon (3rd edition)
* Chapters 6-7 in Allemang & Hendler (suggested)
* [https://book.validatingrdf.com/bookHtml011.html Chapter 5 ''SHACL''] in [https://book.validatingrdf.com/index.html Validating RDF] (available online)
* [http://www.w3.org/TR/rdf-schema/ W3C's RDF Schema 1.1], focus on sections 1-3 and 6 (mandatory)
** Sections 5.1, 5.3-5.5, and 5.6,1-5.6.3
* [[:File:S05-RDFS.pdf | Slides from the lecture]]  
* [http://www.w3.org/TR/rdf-schema/ W3C's RDF Schema 1.1], focus on sections 1-3 and 6
* [[:File:S07-SHACL-RDFS.pdf | Slides from the lecture]]  


Useful materials:
Useful materials:
* [https://www.w3.org/TR/rdf11-mt/ W3C's RDF 1.1 Semantics] (cursory, except the axioms and entailments in sections 8 and 9, which we will review in the lecture)
* Interactive, online [https://shacl.org/playground/ SHACL Playground]
* [https://docs.google.com/presentation/d/1weO9SzssxgYp3g_44X1LZsVtL0i6FurQ3KbIKZ8iriQ/ Lab presentation containing a short overview of SHACL and pySHACL]
* [https://pypi.org/project/pyshacl/ pySHACL - A Python validator for SHACL at PyPi.org] ''(after installation, go straight to "Python Module Use".)''
* [https://w3c.github.io/data-shapes/shacl/ Shapes Constraint Language (SHACL) (Editor's Draft)]
* [https://www.w3.org/TR/rdf11-mt/ W3C's RDF 1.1 Semantics] (''the axioms and entailments in sections 8 and 9, are most important, and we will review them in the lecture'')
* [https://github.com/blazegraph/database/wiki/InferenceAndTruthMaintenance Inference and Thruth Maintenance in Blazegraph]
* [https://github.com/RDFLib/OWL-RL OWL-RL] adds inference capability on top of RDFLib. To use it, copy the ''owlrl'' folder into your project folder, next to your Python files, and import it with ''import owlrl''.
* [https://github.com/RDFLib/OWL-RL OWL-RL] adds inference capability on top of RDFLib. To use it, copy the ''owlrl'' folder into your project folder, next to your Python files, and import it with ''import owlrl''.
* [https://owl-rl.readthedocs.io/en/latest/owlrl.html OWL-RL documentation] (most likely more detailed than you will need - check the [[Python Examples]] first
* [https://owl-rl.readthedocs.io/en/latest/owlrl.html OWL-RL documentation] (most likely more detailed than you will need - check the [[Python Examples]] first
* [https://github.com/blazegraph/database/wiki/InferenceAndTruthMaintenance Inference and Thruth Maintenance in Blazegraph]
* Pages 101-106 in Blumauer & Nagy (suggested)
<!--
* [https://jena.apache.org/documentation/inference/index.html Reasoners and rules engines: Jena inference support] (cursory; sections 1 and 3 are relevant, but quite hard)
* [https://jena.apache.org/documentation/javadoc/jena/ Javadoc] for
** Model (createRDFSModel)
** InfModel (getRawModel, remove + the same methods as Model)
** RDFS (label, comment, subClassOf, subPropertyOf, domain, range...)
** Reasoner (but we will not use it directly)
: (supplementary, but perhaps necessary for the labs and project)


Case-based examples:
==Old lectures (2003) - will be updated==
* [[:File:S5_RDFS_Example.pdf | RDFS Eating vegetables case]]
-- >


==Lecture 6: OWL 1==
==Lecture 9: Ontologies (OWL)==


Themes:
Themes:
Line 156: Line 227:


Mandatory readings:
Mandatory readings:
* Pages 106-109 in Blumauer & Nagy (mandatory)
* Chapter 9-10 in Allemang, Hendler & Gandon (3rd edition)
* Chapter 8 in Allemang & Hendler (suggested)
* [http://www.w3.org/TR/owl-primer OWL2 Primer], sections 2-6
* [[:File:S06-RDFSPlus-5.pdf | Slides from the lecture.]]
 
 
* [[:File:LohmannEtAl2016-VisualizingOntologiesWithVOWL.pdf | Lohmann et al. (2019): Visualizing Ontologies with VOWL. ''Semantic Web Journal.'']] ''Paper.''
* [http://vowl.visualdataweb.org/ VOWL: Visual Notation for OWL Ontologies]
* [http://vowl.visualdataweb.org/ VOWL: Visual Notation for OWL Ontologies]
 
* [https://protegeproject.github.io/protege/getting-started/ Protégé-OWL Getting Started]
* [[:File:S08-OWL.pdf | Slides from the lecture]]


Useful materials (cursory):
Useful materials (cursory):
* [http://www.w3.org/TR/owl-overview OWL 2 Document Overview]
* [http://www.w3.org/TR/owl-overview OWL 2 Document Overview]
* [http://www.w3.org/TR/owl-primer OWL2 Primer]
* [https://www.w3.org/TR/owl2-quick-reference/ OWL 2 Quick Reference Guide]
* [https://www.w3.org/TR/2012/REC-owl2-quick-reference-20121211/ OWL 2 Quick Reference Guide]
* [https://www.w3.org/TR/owl2-rdf-based-semantics/ OWL2 RDF-Based Semantics]
* [https://www.w3.org/TR/owl2-rdf-based-semantics/ OWL2 RDF-Based Semantics]
* The OWL-RL materials from Lecture 5
* The OWL-RL materials (from Lecture 5)
< !--
* [http://vowl.visualdataweb.org/v2 VOWL: Visual Notation for OWL Ontologies]
* [https://jena.apache.org/documentation/javadoc/jena/ Javadoc] for
* [http://vowl.visualdataweb.org/webvowl/index.html#sioc WebVOWL]
** OntModel (createOntologyModel)
* [[:File:LohmannEtAl2016-VisualizingOntologiesWithVOWL.pdf | Lohmann et al. (2019): Visualizing Ontologies with VOWL. ''Semantic Web Journal.'']]
** OntModelSpec (the different reasoners are outlined [https://jena.apache.org/documentation/inference/index.html here (very long)], OWL_MEM_RULE_INF is a good starting point)
* Pages 106-109 in Blumauer & Nagy (suggested)
** OWL (defines built-in OWL resources)
** OntClass, Individual, ObjectProperty, DatatypeProperty
: (supplementary, but perhaps necessary for the labs and project)
 
Case-based examples:
* [[:File:S6_RDFS_Plus_Example.pdf | RDFS Plus People and Person case]]
 
OWL helpful clarifications:
* [[:File:OWL-example_I.pdf | owl:InverseFuctionalProperty vs owl:propertyDisjointWith]]
-- >


==Lecture 7 and 8: Vocabularies==
==Lecture 10: Vocabularies==


Themes:
Themes:
Line 192: Line 249:


Mandatory readings:
Mandatory readings:
* Pages ... in Blumauer & Nagy (mandatory)
* Chapters 10-11 in Allemang, Hendler & Gandon (3rd edition)
* Chapters 9-10 and 13 in Allemang & Hendler (suggested)
* [http://lov.okfn.org/dataset/lov/ Linked Open Vocabularies (LOV)]
* [http://lov.okfn.org/dataset/lov/ Linked Open Vocabularies (LOV)]
* [http://lodstats.aksw.org/ LODstats]
* Important vocabularies / ontologies:
* [[:File:S07-S08-Vocabularies-23.pdf | Slides from the lecture]]
** [http://xmlns.com/foaf/spec/ Friend of a Friend (FOAF)] (if necessary follow the link to the 2004 version)
* [[:File:S08-extra-NA-ontologies-1.pdf | Additional slides about the News Angler project]]
** [http://motools.sourceforge.net/event/event.html Event Ontology (event)]
 
** [http://www.w3.org/TR/owl-time/ Time ontology in OWL (time, OWL-time)]
Useful materials:
** [https://www.w3.org/2003/01/geo/ geo: World Geodetic Standard (WGS) 84]
* Vocabularies:
** [http://dublincore.org/ Dublin Core (DC)]
** [http://www.w3.org/2004/02/skos/ SKOS - Simple Knowledge Organization System Home Page]
** [http://www.w3.org/2004/02/skos/ SKOS - Simple Knowledge Organization System Home Page]
** [http://rdfs.org/sioc/spec/ Semantic Interlinked Online Communities (SIOC)]
** [http://schema.org/docs/full.html schema.org - Full Hierarchy]
** [http://schema.org/docs/full.html schema.org - Full Hierarchy]
** [http://dublincore.org/ Dublin Core (DC)]
** [http://wikidata.dbpedia.org/services-resources/ontology DBpedia Ontology]
** [http://xmlns.com/foaf/spec/ Friend of a Friend (FOAF)]
** [http://www.w3.org/ns/prov# Provenance Interchange (PROV)]
** [https://www.w3.org/2003/01/geo/ geo: World Geodetic Standard (WGS) 84]
** [https://www.w3.org/TR/vocab-data-cube/ The RDF Data Cube Vocabulary]
** [http://purl.org/vocab/vann/ Annotating vocabulary descriptions (VANN)]
** [https://www.w3.org/2003/06/sw-vocab-status/note Vocabulary Status (VS)]
** [http://creativecommons.org/ns Creative Commons (CC) Vocabulary]
** [http://creativecommons.org/ns Creative Commons (CC) Vocabulary]
** [http://vocab.deri.ie/void Vocabulary of Interlinked Datasets (VoID)]
** ''What we expect you to know about each vocabulary is this:''  
** [http://www.w3.org/ns/prov# Provenance Interchange (PROV)]
*** Its purpose and where and how it can be used.
** [http://motools.sourceforge.net/event/event.html Event Ontology (event)]
*** Its most central 3-6 classes and properties be able to explain its basic structure.  
** [http://www.w3.org/TR/owl-time/ Time ontology in OWL (time, OWL-time)]
*** It is less important to get all the names and prefixes 100% right: we do not expect you to learn every little detail by heart.  
** [http://motools.sourceforge.net/timeline/timeline.html Timeline Ontology (tl)]
* [[:File:S09-Vocabularies.pdf | Slides from the lecture]]
** [http://vocab.org/bio/ Biographical Information (BIO)]
** [http://rdfs.org/sioc/spec/ Semantic Interlinked Online Communities (SIOC)]
** [http://bibliontology.com/ Bibliographic Ontology (bibo)]
** [http://musiconMandatory readings:
* [https://www.wikidata.org/wiki/Wikidata:Introduction Wikidata]
* [https://www.JSON.org/json-en.html JSON Syntax] (mandatory)
* Section 2 in W3C's [https://www.w3.org/TR/json-ld-api/ JSON-LD 1.1 Processing Algorithms and API] (mandatory)
* [[:File:S11-S12-Web-APIs-8.pdf | Slides from the lecture]]
Useful materials:
* [http://json-ld.org/ JSON for Linked Data] (supplementary)
** [http://www.youtube.com/watch?v=4x_xzT5eF5Q What is Linked Data?] Short video introduction to Linked Data by Manu Sporny
** [http://www.youtube.com/watch?v=vioCbTo3C-4 What is JSON-LD?] Short video introduction to JSON-LD by Manu Sporny
tology.com/ Music Ontology (mo)]
: '''This is what we expect you to know about each vocabulary:''' Its purpose and where and how it can be used. You should know its most central 3-6 classes and properties be able to explain its basic structure. It is less important to get all the names and prefixes 100% right: we do not expect you to learn every little detail by heart. ''schema.org'' is less important because you have already had about it in INFO116.
* [https://wiki.uib.no/info216/images/4/42/Slr-kg4news-dataset.txt The SLR-KG4News dataset from the News Angler project]


==Lecture 9 and 10: Linked Data Resources==
==Lecture 11: Formal ontologies (description logic, OWL-DL)==


Themes:
Themes:
* Important Linked Open Datasets
* OWL-DL
** DBpedia
* Description logic
** LinkedGeoData
* Decision problems
** GeoNames
** Wikidata
** and others


Mandatory readings:
Mandatory readings:
* Pages 101-116 in Blumauer & Nagy.
* Chapters 12-13 in Allemang, Hendler & Gandon (3rd edition)
* [[:File:BizerHeathBernersLee-LinkedData2009-TheStorySoFar.pdf | Bizer, C., Heath, T., & Berners-Lee, T. (2009). Linked data-the story so far. Semantic services, interoperability and web applications: emerging concepts, 205-227.]]
* [http://www.w3.org/TR/owl-primer OWL2 Primer], sections 2-6 (same as Lecture 8) and sections 9-10
* [[:File:FarberEtAl-ComparativeSurvey-SWJ2015.pdf | Färber, M., Ell, B., Menne, C., & Rettinger, A. (2015). A Comparative Survey of DBpedia, Freebase, OpenCyc, Wikidata, and YAGO. Semantic Web Journal, July.]]
* [[:File:S10-OWL-DL.pdf | Slides from the lecture]]
* [http://lod-cloud.net The Linking Open Data (LOD) cloud diagram]
* [[:File:S09-S10-LinkedOpenDatasets-25.pdf | Slides from the lecture]]


Useful materials:
Useful materials:
* [http://lodstats.aksw.org/ LODstats]
* [http://www.w3.org/TR/owl-overview OWL 2 Document Overview] (same as Lecture 8)
* [http://wiki.dbpedia.org/about Dbpedia]
* [https://www.w3.org/TR/2012/REC-owl2-quick-reference-20121211/ OWL 2 Quick Reference Guide] (same as Lecture 8)
* [https://www.wikidata.org/wiki/Wikidata:Introduction Wikidata]
* [[:File:NardiBrachman-IntroductionToDescriptionLogic.pdf | Nardi & Brachman: Introduction to Description Logics. Chapter 1 in Description Logic Handbook.]]
* [http://www.geonames.org/about.html GeoNames]
* [[:File:BaderNutt-BasicDescriptionLogics.pdf | Baader & Nutt: Basic Description Logics. Chapter 2 in Description Logic Handbook.]]
* [https://wordnet.princeton.edu/ WordNet - A lexical database for English]
** ''Cursory'', quickly gets mathematical after the introduction. In particular, sections 2.2.2.3-4 about fixpoint semantics apply to TBoxes with cyclic definitions, which we do not consider in this course. We also do not consider the stuff about rules, epistemics, and reasoning from section 2.2.5 on.
* [http://live.babelnet.org/about BabelNet]
 
==Lecture 11 and 12: Web APIs==


Themes:
==Lecture 12: KG embeddings==
* JSON, JSON-LD
* Semantic web services
* Semantic workflows
 
 
==Lecture 13: OWL==


Themes:
Themes:
* Advanced OWL
* KG embeddings
* Axioms, rules and entailments
* Link prediction
* Programming advanced OWL in Python
* TorchKGE


Mandatory readings:
Mandatory readings (preliminary):
* Pages ... in Blumauer & Nagy (mandatory)
* [https://towardsdatascience.com/introduction-to-machine-learning-for-beginners-eed6024fdb08 Introduction to Machine Learning for Beginners] ([[:file:IntroToMachineLearning.pdf | PDF]])
* Chapters 11-12 in Allemang & Hendler. ''In the text book.''
* [https://towardsdatascience.com/introduction-to-word-embedding-and-word2vec-652d0c2060fa Introduction to Word Embeddings and word2vec] ([[:file:IntroToWordEmbeddings.pdf | PDF]])
* [[:File:S13-OWL-16.pdf | Slides from the lecture]]
* [https://towardsdatascience.com/introduction-to-knowledge-graph-embedding-with-dgl-ke-77ace6fb60ef Introduction to Knowledge Graph Embeddings] ([[:file:IntroToKGEmbeddings.pdf | PDF]])
* [[:file:S11-GraphEmbeddings.pdf | Slides from the lecture]]


Useful materials:
Supplementary readings (preliminary):
* [http://www.w3.org/TR/owl-overview OWL 2 Document Overview] (cursory)
* [[:file:Mikolov_et_al._-_2013_-_Efficient_Estimation_of_Word_Representations_in_Ve.pdf | Mikolov et al’s original word2vec paper]]
* [http://www.w3.org/TR/owl-primer OWL2 Primer] (cursory)
* [[:file:Bordes_et_al._-_Translating_Embeddings_for_Modeling_Multi-relation.pdf | Bordes et al’s original TransE paper]]
* [https://www.w3.org/TR/2012/REC-owl2-quick-reference-20121211/ OWL 2 Quick Reference Guide] (cursory)
* [https://torchkge.readthedocs.io/en/latest/ Welcome to TorchKGE’ s documentation!] (for the labs)
* [http://vowl.visualdataweb.org/v2 VOWL: Visual Notation for OWL Ontologies] (cursory)
* [http://vowl.visualdataweb.org/webvowl/index.html#sioc WebVOWL] (cursory)
< !--
* [https://jena.apache.org/documentation/ontology/ Jena Ontology API] (we will most likely not go into this) (cursory)
-- >


==Lecture 14: OWL DL==
==Lecture 13: Wrapping up==


Themes:
Themes:
* Description logic
* Questions about the exam
* Decision problems
* Quizzes
* OWL-DL
* Programming with OWL-DL reasoners in Python


Mandatory readings:
Mandatory readings:
* [[:File:S14-OWL-DL-11.pdf | Slides from the lecture]]
* The rest of Allemang, Hendler & Gandon (3rd edition)


Useful materials:
Useful materials:
* [[:File:NardiBrachman-IntroductionToDescriptionLogic.pdf | Nardi & Brachman: Introduction to Description Logics. Chapter 1 in Description Logic Handbook.]] ''(cursory)''
* The rest of Blumauer & Nagy (suggested)
* [[:File:BaderNutt-BasicDescriptionLogics.pdf | Baader & Nutt: Basic Description Logics. Chapter 2 in Description Logic Handbook.]]
** ''Cursory'', quickly gets mathematical after the introduction. In particular, sections 2.2.2.3-4 about fixpoint semantics apply to TBoxes with cyclic definitions, which we do not consider in this course. We also do not consider the stuff about rules, epistemics, and reasoning from section 2.2.5 on.
* [http://www.cs.man.ac.uk/~ezolin/dl/ Complexity of Reasoning in Description Logics. Powered by Evgeny Zolin.] (informative)
 
 
==Lecture 15: Ontology Development==
 
Themes:
* Ontology Development 101 method


Mandatory readings:
* Pages ... in Blumauer & Nagy (mandatory)
* Chapters 14-16 in Allemang & Hendler (suggested)
* [http://liris.cnrs.fr/alain.mille/enseignements/Ecole_Centrale/What%20is%20an%20ontology%20and%20why%20we%20need%20it.htm Noy & McGuinness (2001): Ontology Development 101: A Guide to Creating Your First Ontology.] ''Paper.''
* [[:File:S15-OntologyDevelopment-5.pdf | Slides from the lecture]]
Useful materials:
* [http://www.sciencedirect.com/science/article/pii/S095741741101640X Sicilia et al. (2012): Empirical findings on ontology metrics.] ''(very cursory paper)''
-->


&nbsp;
&nbsp;
<div class="credits" style="text-align: right; direction: ltr; margin-left: 1em;">''INFO216, UiB, 2017-2021, Andreas L. Opdahl (c)''</div>
<div class="credits" style="text-align: right; direction: ltr; margin-left: 1em;">''INFO216, UiB, 2017-2024, Andreas L. Opdahl (c)''</div>

Latest revision as of 21:54, 20 March 2024

This page currently shows some of the lectures and readings from the Spring of 2023. It will be updated with materials for 2024 as the course progresses.

Textbooks

Main course book (the whole book is mandatory reading):

  • Dean Allemang, James Hendler & Fabien Gandon (2020). Semantic Web for the Working Ontologist, Effective Modeling for Linked Data, RDFS and OWL (Third Edition). ISBN: 9781450376143, PDF ISBN: 9781450376150, Hardcover ISBN: 9781450376174, DOI: 10.1145/3382097.

Supplementary reading book (not mandatory):

  • Andreas Blumauer and Helmut Nagy (2020). The Knowledge Graph Cookbook - Recipes that Work. mono/monochrom. ISBN-10: ‎3902796707, ISBN-13: 978-3902796707.

Other materials

In addition, the materials listed below for each lecture are either mandatory or suggested reading. More materials will be added to each lecture in the coming weeks.

The lectures and lectures notes are also part of the curriculum.

Make sure you download the electronic resources to your own computer in good time before the exam. This is your own responsibility. That way you are safe if a site becomes unavailable or somehow damaged the last few days before the exam.

Note: to download some of the papers, you may need to be inside UiB's network. Either use a computer directly on the UiB network or connect to your UiB account through VPN.

Lectures (in progress)

Below are the mandatory and suggested readings for each lecture. All the textbook chapters in Allemang, Hendler & Gandon are mandatory, whereas the chapters in Blumauer & Nagy are suggested.

Lecture 1: Introduction to KGs

Themes:

  • Introduction to Knowledge Graphs
  • Organisation of the course

Mandatory readings:

Useful materials:

  • Important knowledge graphs (which we will look more at later):
  • Pages 27-55 and 105-122 in Blumauer & Nagy (suggested)

Lecture 2: Representing KGs (RDF)

Themes:

  • Resource Description Framework (RDF)
  • Programming RDF in Python

Mandatory readings:

  • Chapter 3 in Allemang, Hendler & Gandon (3rd edition)
  • W3C's RDF 1.1 Primer until and including 5.1.2 Turtle (but not the rest for now)
  • RDFlib 7.0.0 documentation, the following pages:
    • The main page
    • Getting started with RDFLib
    • Loading and saving RDF
    • Creating RDF triples
    • Navigating Graphs
    • Utilities and convenience functions
    • RDF terms in rdflib
    • Namespaces and Bindings
  • Slides from the lecture

Useful materials:

Lecture 3: Querying and updating KGs (SPARQL)

Themes:

  • SPARQL queries
  • SPARQL Update
  • Programming SPARQL and SPARQL Update in Python

Mandatory readings (tentative):

Useful materials:

Lecture 4: Linked Open Data (LOD)

Themes:

  • Linked Open Data(LOD)
  • The LOD cloud
  • Data provisioning

Mandatory readings (both lecture 4 and 5):

Useful materials

Lecture 5: Open Knowledge Graphs I

Themes:

  • Important open KGs (LOD datasets)
    • Wikidata
    • DBpedia

Mandatory readings:

Lecture 6: Open Knowledge Graphs II

Themes:

  • Important open KGs (LOD datasets)
    • DBpedia (continued)
    • GeoNames
    • the GDELT project
    • WordNet
    • BabelNet
    • ConceptNet

Mandatory readings:

Useful materials

Lecture 7: Enterprise Knowledge Graphs

Themes:

  • Enterprise Knowledge Graphs (EKGs)
  • Google’s Knowledge Graph
  • Amazon’s Product Graph
  • JSON-LD (video presentation)

Mandatory readings:

Supplementary readings:

  • Parts 2 and 4 in Blumauer & Nagy's text book (strongly suggested - this is where Blumauer & Nagy's book is good!)
  • LIS: A knowledge graph-based line information system by Grangel-González, I., Rickart, M., Rudolph, O., & Shah, F. (2023, May). In Proceedings of the European Semantic Web Conference (pp. 591-608). Cham: Springer Nature Switzerland.
  • AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types by Dong, X. L., He, X., Kan, A., Li, X., Liang, Y., Ma, J., ... & Han, J. (2020, August). In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (pp. 2724-2734). Research paper from Amazon about AutoKnow - this is a bit heavy for Bachelor level, but you can have a look :-)

Lecture 8: Rules (SHACL and RDFS)

Themes:

  • SHACL and RDFS
  • Axioms, rules and entailment
  • Programming SHACL and RDFS in Python

Mandatory readings:

Useful materials:

Old lectures (2003) - will be updated

Lecture 9: Ontologies (OWL)

Themes:

  • Basic OWL concepts
  • Axioms, rules and entailments
  • Programming basic OWL in Python

Mandatory readings:

Useful materials (cursory):

Lecture 10: Vocabularies

Themes:

  • LOD vocabularies and ontologies

Mandatory readings:

Lecture 11: Formal ontologies (description logic, OWL-DL)

Themes:

  • OWL-DL
  • Description logic
  • Decision problems

Mandatory readings:

Useful materials:

Lecture 12: KG embeddings

Themes:

  • KG embeddings
  • Link prediction
  • TorchKGE

Mandatory readings (preliminary):

Supplementary readings (preliminary):

Lecture 13: Wrapping up

Themes:

  • Questions about the exam
  • Quizzes

Mandatory readings:

  • The rest of Allemang, Hendler & Gandon (3rd edition)

Useful materials:

  • The rest of Blumauer & Nagy (suggested)


 

INFO216, UiB, 2017-2024, Andreas L. Opdahl (c)