Readings: Difference between revisions

From info216
 
(243 intermediate revisions by 2 users not shown)
Line 1: Line 1:
=Text book=
''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.''
The text book in INFO216 is ''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.'' '''The whole book is obligatory reading.'''  
 
=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=
=Other materials=
In addition, '''the materials listed below for each lecture is either mandatory or suggested reading.''' Currently, the readings are not updated from 2017, so some of them may change. Make sure you download the papers and web sites in good time before the exam. That way you are safe if a site becomes unavailable or somehow damaged the last few days before the exam. Note that to download some of the papers, you need to be inside UiB's network. Either use a computer directly on the UiB network or connect to your UiB account with VPN if you are elsewhere.


Finally, '''the lectures and lectures notes are also part of the curriculum.'''
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.


=Lectures=
'''The lectures and lectures notes are also part of the curriculum.'''
Below are the mandatory and suggested readings for each lecture. All the text-book chapters are mandatory.


==Lecture 1: Introduction==
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:
Themes:
* Web of Data
* Introduction to Knowledge Graphs
* INFO216
* Organisation of the course
* Jena
* The programming project


Mandatory readings:
Mandatory readings:
* Chapters 1-2 in Allemang & Hendler. ''In text book.''
* 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]
* [http://jena.apache.org/about_jena/architecture.html Apache architecture overview] (mandatory)
* [[:File:S01-KnowledgeGraphs.pdf | Slides from the lecture]]
* [http://jena.apache.org/documentation/rdf/index.html The core RDF API] (mandatory)
* [http://jena.apache.org/tutorials/rdf_api.html An introduction to RDF and the Jena RDF API] (mandatory)
* [[:File:S01-Intro-WoD-Jena-7.pdf | Slides from the lecture]]


Useful materials:
Useful materials:
* [http://jena.apache.org/about_jena/ Welcome to Apache Jena] (useful starting page)
* Important knowledge graphs (''which we will look more at later''):
* [http://jena.apache.org/index.html Apache Jena] main page (useful starting page)
** Wikidata (https://www.wikidata.org/)
* [http://jena.apache.org/tutorials/ Jena tutorials] (useful starting page)
<!-- ** DBpedia (https://www.dbpedia.org, https://dbpedia.org/page/Bergen)
* [https://jena.apache.org/documentation/javadoc/jena/ Package org.apache.jena.rdf.model] (supplementary, but necessary for the labs and project - lab 1 and the lecture notes lists the classes and methods you should look at)
** 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 Jena
* Programming RDF in Python
* Finding datasets and vocabularies for your projects


Mandatory readings:
Mandatory readings:
* Chapter 3 in Allemang & Hendler. ''In text book.''
* 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)
* We also continue with the Jena RDF materials from lecture 1:
* [http://rdflib.readthedocs.io/ RDFlib 7.0.0 documentation], the following pages:
** [http://jena.apache.org/documentation/rdf/index.html The core RDF API] (mandatory)
** The main page
** [http://jena.apache.org/tutorials/rdf_api.html An introduction to RDF and the Jena RDF API] (mandatory)
** Getting started with RDFLib
* [[:File:S02-RDF-8.pdf | Slides from the lecture]]
** Loading and saving RDF
** Creating RDF triples
** Navigating Graphs
** Utilities and convenience functions
** RDF terms in rdflib
** Namespaces and Bindings
* [[:File:S02-RDF.pdf | Slides from the lecture]]


Useful materials:
Useful materials:
* [https://www.w3.org/TR/rdf11-concepts/ W3C's RDF 1.1 Concepts and Abstract Syntax] (cursory)
* [https://rdflib.readthedocs.io/en/stable/apidocs/modules.html RDFLib 7.0.0 packages] (reference for the labs)
** [https://jena.apache.org/documentation/javadoc/jena/ Package org.apache.jena.rdf.model] (supplementary, but necessary for the labs and project)
* [https://www.ldf.fi/service/rdf-grapher RDF Grapher] for drawing RDF graphs
* [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]
<!-- * 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: SPARQL==
==Lecture 3: Querying and updating KGs (SPARQL)==


Themes:
Themes:
* SPARQL
* SPARQL queries
* Programming SPARQL in Jena
* SPARQL Update
* SPARQL Update
* Programming SPARQL Update in Jena
* Programming SPARQL and SPARQL Update in Python


Mandatory readings:
Mandatory readings (tentative):
* Chapter 5 in Allemang & Hendler. ''In text book.''
* Chapter 6 in Allemang, Hendler & Gandon (3rd edition)
* [http://www.w3.org/TR/sparql11-update/ SPARQL 1.1 Update Language] (Sections 1-3 are obligatory)
* [http://www.w3.org/TR/sparql11-update/ SPARQL 1.1 Update Language] (Sections 1-3)
* [[:File:S03-SPARQL-12.pdf | Slides from the lecture]]
* [https://rdflib.readthedocs.io/ rdflib 7.0.0] materials:
** [https://rdflib.readthedocs.io/en/stable/intro_to_sparql.html Querying with SPARQL]
* [[: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]]
* [http://jena.apache.org/documentation/javadoc/arq/ Javadoc] for Apache Jena ARQ 3.2.0
* [https://en.wikibooks.org/wiki/SPARQL/Expressions_and_Functions SPARQL Expressions and Functions]
** Query, QueryFactory, QueryExecution, QueryExecutionFactory, ResultSet
* For example pages 54-55, 133 in Blumauer & Nagy (suggested)
** UpdateFactory, UpdateAction
* The [[:File:kg4news-dump-20230130.txt | Knowledge Graphs for the News]] example used in the lecture. (Remember to save with the correct ''.ttl'' extension.)
: (supplementary, but perhaps necessary for the labs and project)


==Lecture 4: Architecture==
==Lecture 4: Linked Open Data (LOD)==


Themes:
Themes:
* Application architecture
* Linked Open Data(LOD)
* Application components
* The LOD cloud
* Triple stores
* Data provisioning
* Visualisation


Mandatory readings:
Mandatory readings ''(both lecture 4 and 5)'':
* Chapter 4 in Allemang & Hendler. ''In text book.''
* Chapter 5 in Allemang, Hendler & Gandon (3rd edition)
* [http://jena.apache.org/about_jena/architecture.html Apache architecture overview] (mandatory, from lecture 1)
* [https://www.w3.org/DesignIssues/LinkedData.html Linked Data], Tim Berners-Lee, 2006-07-27.
* [https://jena.apache.org/documentation/tdb/index.html Apache's TDB] (mandatory)
* [[:File:S04-LOD.pdf | Slides from the lecture]]
* [https://jena.apache.org/documentation/tdb/java_api.html Apache's TDB Java API] (mandatory)
* [https://jena.apache.org/documentation/fuseki2/index.html Apache Jena Fuseki] (mandatory, we use Fuseki 2)
* [[:File:S04-architecture-5.pdf | Slides from the lecture]]


Useful materials:
Useful materials
* [https://jena.apache.org/documentation/javadoc/tdb/ Package org.apache.jena.tdb] Class TDBFactory (createDataset)
* [https://www.ontotext.com/knowledgehub/fundamentals/linked-data-linked-open-data/ What Are Linked Data and Linked Open Data?]
* [http://www.eswc2012.org/sites/default/files/eswc2012_submission_303.pdf Skjæveland 2012: Sgvizler.] ''Paper.''
* [[: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://mgskjaeveland.github.io/sgvizler/ Sgvizler 0.6]
* [[: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]
<!--
* [[:File:S07-Visualisation-4.pdf | Slides from the lecture]]
-->


==Lecture 5: RDFS==
==Lecture 5: Open Knowledge Graphs I==


Themes:
Themes:
* RDFS
* Important open KGs (LOD datasets)
* Axioms, rules and entailment
** Wikidata
* Programming RDFS in Jena
** DBpedia


Mandatory readings:
Mandatory readings:
* Chapters 6-7 in Allemang & Hendler. ''In text book.''
* Chapter 5 in Allemang, Hendler & Gandon (3rd edition)
* [http://www.w3.org/TR/rdf-schema/ W3C's RDF Schema 1.1] (mandatory)
* Important knowledge graphs - and what to read:
* [[:File:S05-RDFS-10.pdf | Slides from the lecture]]
** Wikidata (https://www.wikidata.org/):
*** [https://www.wikidata.org/wiki/Wikidata:Introduction Introduction to Wikidata]
*** [https://www.wikidata.org/wiki/Wikidata:SPARQL_query_service/Wikidata_Query_Help SPARQL query service/A gentle introduction to the Wikidata Query Service]
*** example: [https://www.wikidata.org/wiki/Q26793]
** DBpedia (https://www.dbpedia.org):
*** [http://wiki.dbpedia.org/about About Dbpedia]
*** example: [https://dbpedia.org/resource/Bergen]
* [[:File:S05-S06-OpenKGs.pdf | Slides from the lecture]]


Useful materials:
=Lecture 6: Open Knowledge Graphs II=
* [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)
* [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)
 
==Lecture 6: RDFS Plus==


Themes:
Themes:
* Basic OWL concepts
* Important open KGs (LOD datasets)
* Axioms, rules and entailments
** DBpedia ''(continued)''
* Programming basic OWL in Jena
** GeoNames
** the GDELT project
** WordNet
** BabelNet
** ConceptNet


Mandatory readings:
Mandatory readings:
* Chapter 8 in Allemang & Hendler. ''In text book.''
* Chapter 5 in Allemang, Hendler & Gandon (3rd edition)
* [[:File:S06-RDFSPlus-4.pdf | Slides from the lecture.]]
* 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:
Useful materials
* [https://jena.apache.org/documentation/javadoc/jena/ Javadoc] for
* Wikidata statistics
** OntModel (createOntologyModel)  
** [https://grafana.wikimedia.org/d/000000167/wikidata-datamodel?orgId=1&refresh=30m Entity statistics]
** 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)
** [https://grafana.wikimedia.org/d/000000175/wikidata-datamodel-statements?orgId=1&refresh=30m Statement statistics]
** OWL (defines built-in OWL resources)
* [https://www.dbpedia-spotlight.org/ DBpedia Spotlight]
** OntClass, Individual, ObjectProperty, DatatypeProperty
* GDELT documentation
: (supplementary, but perhaps necessary for the labs and project)
** [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: Vocabularies==
==Lecture 7: Enterprise Knowledge Graphs==


Themes:
Themes:  
* LOD vocabularies and ontologies
* Enterprise Knowledge Graphs (EKGs)
* Google’s Knowledge Graph
* Amazon’s Product Graph
* JSON-LD (video presentation)


Mandatory readings:
Mandatory readings:
* Chapters 9-10 and 13 in Allemang & Hendler. ''In text book.''
* [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.)''
* [http://lov.okfn.org/dataset/lov/ Linked Open Vocabularies (LOV)]
* [https://blog.google/products/search/about-knowledge-graph-and-knowledge-panels/ A reintroduction to our Knowledge Graph and knowledge panels], Danny Sullivan, Google (2020).
* [http://stats.lod2.eu/ LODstats]
* [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.)''
* [[:File:S07-Vocabularies-21.pdf | Slides from the lecture]]
* [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:
* Vocabularies:
* Parts 2 and 4 in Blumauer & Nagy's text book (''strongly suggested - this is where Blumauer & Nagy's book is good!'')
** [http://www.w3.org/2004/02/skos/ SKOS - Simple Knowledge Organization System Home Page]
* [[: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://schema.org/docs/full.html schema.org - Full Hierarchy]
* [[: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://dublincore.org/ Dublin Core (DC)]
** [http://xmlns.com/foaf/spec/ Friend of a Friend (FOAF)]
** [https://www.w3.org/2003/01/geo/wgs84_pos geo: World Geodetic Standard (WGS) 84] (and [https://www.w3.org/2003/01/geo/ few more general comments here])
** [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://vocab.deri.ie/void Vocabulary of Interlinked Datasets (VoID)]
** [http://www.w3.org/ns/prov# Provenance Interchange (PROV)]
** [http://motools.sourceforge.net/event/event.html Event Ontology (event)]
** [http://www.w3.org/TR/owl-time/ Time ontology in OWL (time, OWL-time)]
** [http://motools.sourceforge.net/timeline/timeline.html Timeline Ontology (tl)]
** [http://vocab.org/bio/ Biographical Information (BIO)]
** [http://rdfs.org/sioc/spec/ Semantic Interlinked Online Communities (SIOC)]
** [http://bibliontology.com/ Bibliographic Ontology (bibo)]
** [http://www.musicontology.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.


==Lecture 8 and 9: Linked Open Datasets==
==Lecture 8: Rules (SHACL and RDFS)==


Themes:
Themes:
* Important Linked Open Datasets
* SHACL and RDFS
** DBpedia
* Axioms, rules and entailment
** LinkedGeoData
* Programming SHACL and RDFS in Python
** GeoNames
** Wikidata
** and others


Mandatory readings:
Mandatory readings:
* [[: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.]]
* Chapters 7-8 in Allemang, Hendler & Gandon (3rd edition)
* [[: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.]]
* [https://book.validatingrdf.com/bookHtml011.html Chapter 5 ''SHACL''] in [https://book.validatingrdf.com/index.html Validating RDF] (available online)
* [http://lod-cloud.net The Linking Open Data (LOD) cloud diagram]
** Sections 5.1, 5.3-5.5, and 5.6,1-5.6.3
* [http://stats.lod2.eu/ LODstats]
* [http://www.w3.org/TR/rdf-schema/ W3C's RDF Schema 1.1], focus on sections 1-3 and 6
* [[:File:S08-LinkedOpenDatasets-23.pdf | Slides from the lecture]]
* [[:File:S07-SHACL-RDFS.pdf | Slides from the lecture]]  


Useful materials:
Useful materials:
* [http://wiki.dbpedia.org/about Dbpedia]
* Interactive, online [https://shacl.org/playground/ SHACL Playground]
* [https://www.wikidata.org/wiki/Wikidata:Introduction Wikidata]
* [https://docs.google.com/presentation/d/1weO9SzssxgYp3g_44X1LZsVtL0i6FurQ3KbIKZ8iriQ/ Lab presentation containing a short overview of SHACL and pySHACL]
* [http://www.geonames.org/about.html GeoNames]
* [https://pypi.org/project/pyshacl/ pySHACL - A Python validator for SHACL at PyPi.org] ''(after installation, go straight to "Python Module Use".)''
* [https://wordnet.princeton.edu/ WordNet - A lexical database for English]
* [https://w3c.github.io/data-shapes/shacl/ Shapes Constraint Language (SHACL) (Editor's Draft)]
* [http://live.babelnet.org/about BabelNet]
* [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://owl-rl.readthedocs.io/en/latest/owlrl.html OWL-RL documentation] (most likely more detailed than you will need - check the [[Python Examples]] first
* Pages 101-106 in Blumauer & Nagy (suggested)
 
==Old lectures (2003) - will be updated==


==Lecture 10: Services==
==Lecture 9: Ontologies (OWL)==


Themes:  
Themes:
* JSON, JSON-LD
* Basic OWL concepts
* Semantic web services
* Axioms, rules and entailments
* Semantic workflows
* Programming basic OWL in Python


Mandatory readings:
Mandatory readings:
* [http://json.org/ JSON Syntax] (mandatory)
* Chapter 9-10 in Allemang, Hendler & Gandon (3rd edition)
* Section 2 in W3C's [https://www.w3.org/TR/json-ld-api/ JSON-LD 1.0 Processing Algorithms and API] (mandatory)
* [http://www.w3.org/TR/owl-primer OWL2 Primer], sections 2-6
* [[:File:S10-Services-7.pdf | Slides from the lecture]]
* [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:
Useful materials (cursory):
* [http://json-ld.org/spec/latest/json-ld/ JSON-LD 1.1 - A JSON-based Serialization for Linked Data] (supplementary reference)
* [http://www.w3.org/TR/owl-overview OWL 2 Document Overview]
* [http://json-ld.org/ JSON for Linked Data] (supplementary)
* [https://www.w3.org/TR/owl2-quick-reference/ OWL 2 Quick Reference Guide]
** [http://www.youtube.com/watch?v=4x_xzT5eF5Q What is Linked Data?] Short video introduction to Linked Data by Manu Sporny
* [https://www.w3.org/TR/owl2-rdf-based-semantics/ OWL2 RDF-Based Semantics]
** [http://www.youtube.com/watch?v=vioCbTo3C-4 What is JSON-LD?] Short video introduction to JSON-LD by Manu Sporny
* The OWL-RL materials (from Lecture 5)
* [http://vowl.visualdataweb.org/v2 VOWL: Visual Notation for OWL Ontologies]
* [http://vowl.visualdataweb.org/webvowl/index.html#sioc WebVOWL]
* [[:File:LohmannEtAl2016-VisualizingOntologiesWithVOWL.pdf | Lohmann et al. (2019): Visualizing Ontologies with VOWL. ''Semantic Web Journal.'']]
* Pages 106-109 in Blumauer & Nagy (suggested)


==Lecture 11: OWL==
==Lecture 10: Vocabularies==


Themes:
Themes:
* Advanced OWL
* LOD vocabularies and ontologies
* Axioms, rules and entailments
* Programming advanced OWL in Jena


Mandatory readings:
Mandatory readings:
* Chapters 11-12 in Allemang & Hendler. ''In text book.''
* Chapters 10-11 in Allemang, Hendler & Gandon (3rd edition)
* [[:File:S11-OWL-15-utlagt.pdf | Slides from the lecture]]
* [http://lov.okfn.org/dataset/lov/ Linked Open Vocabularies (LOV)]
 
* Important vocabularies / ontologies:
Useful materials:
** [http://xmlns.com/foaf/spec/ Friend of a Friend (FOAF)] (if necessary follow the link to the 2004 version)
* [http://www.w3.org/TR/owl-overview OWL 2 Document Overview] (cursory)
** [http://motools.sourceforge.net/event/event.html Event Ontology (event)]
* [http://www.w3.org/TR/owl-primer OWL2 Primer] (cursory)
** [http://www.w3.org/TR/owl-time/ Time ontology in OWL (time, OWL-time)]
* [https://www.w3.org/TR/2012/REC-owl2-quick-reference-20121211/ OWL 2 Quick Reference Guide] (cursory)
** [https://www.w3.org/2003/01/geo/ geo: World Geodetic Standard (WGS) 84]
* [http://vowl.visualdataweb.org/v2 VOWL: Visual Notation for OWL Ontologies] (cursory)
** [http://dublincore.org/ Dublin Core (DC)]
* [http://vowl.visualdataweb.org/webvowl/index.html#sioc WebVOWL] (cursory)
** [http://www.w3.org/2004/02/skos/ SKOS - Simple Knowledge Organization System Home Page]
* [https://jena.apache.org/documentation/ontology/ Jena Ontology API] (we will most likely not go into this) (cursory)
** [http://rdfs.org/sioc/spec/ Semantic Interlinked Online Communities (SIOC)]
** [http://schema.org/docs/full.html schema.org - Full Hierarchy]
** [http://wikidata.dbpedia.org/services-resources/ontology DBpedia Ontology]
** [http://www.w3.org/ns/prov# Provenance Interchange (PROV)]
** [http://creativecommons.org/ns Creative Commons (CC) Vocabulary]
** ''What we expect you to know about each vocabulary is this:''
*** Its purpose and where and how it can be used.
*** 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.
* [[:File:S09-Vocabularies.pdf | Slides from the lecture]]


==Lecture 12: OWL DL==
==Lecture 11: Formal ontologies (description logic, OWL-DL)==


Themes:
Themes:
* OWL-DL
* Description logic
* Description logic
* Decision problems
* Decision problems
* OWL-DL
* Programming with OWL-DL reasoners in Jena


Mandatory readings:
Mandatory readings:
* [[:File:S12-OWL-DL-10.pdf | Slides from the lecture]]
* Chapters 12-13 in Allemang, Hendler & Gandon (3rd edition)
* [http://www.w3.org/TR/owl-primer OWL2 Primer], sections 2-6 (same as Lecture 8) and sections 9-10
* [[:File:S10-OWL-DL.pdf | Slides from the lecture]]


Useful materials:
Useful materials:
* [[:File:NardiBrachman-IntroductionToDescriptionLogic.pdf | Nardi & Brachman: Introduction to Description Logics. Chapter 1 in Description Logic Handbook.]] ''(cursory)''
* [http://www.w3.org/TR/owl-overview OWL 2 Document Overview] (same as Lecture 8)
* [https://www.w3.org/TR/2012/REC-owl2-quick-reference-20121211/ OWL 2 Quick Reference Guide] (same as Lecture 8)
* [[:File:NardiBrachman-IntroductionToDescriptionLogic.pdf | Nardi & Brachman: Introduction to Description Logics. Chapter 1 in Description Logic Handbook.]]
* [[:File:BaderNutt-BasicDescriptionLogics.pdf | Baader & Nutt: Basic Description Logics. Chapter 2 in Description Logic Handbook.]]
* [[: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.
** ''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 13: Ontology development==
==Lecture 12: KG embeddings==
 
Themes:
* KG embeddings
* Link prediction
* TorchKGE
 
Mandatory readings (preliminary):
* [https://towardsdatascience.com/introduction-to-machine-learning-for-beginners-eed6024fdb08 Introduction to Machine Learning for Beginners] ([[:file:IntroToMachineLearning.pdf | PDF]])
* [https://towardsdatascience.com/introduction-to-word-embedding-and-word2vec-652d0c2060fa Introduction to Word Embeddings and word2vec] ([[:file:IntroToWordEmbeddings.pdf | PDF]])
* [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]]
 
Supplementary readings (preliminary):
* [[:file:Mikolov_et_al._-_2013_-_Efficient_Estimation_of_Word_Representations_in_Ve.pdf | Mikolov et al’s original word2vec paper]]
* [[:file:Bordes_et_al._-_Translating_Embeddings_for_Modeling_Multi-relation.pdf | Bordes et al’s original TransE paper]]
* [https://torchkge.readthedocs.io/en/latest/ Welcome to TorchKGE’ s documentation!] (for the labs)
 
==Lecture 13: Wrapping up==


Themes:
Themes:
* Ontology Development 101 method
* Questions about the exam
* Quizzes


Mandatory readings:
Mandatory readings:
* Chapters 14-16 in Allemang & Hendler. ''In text book.''
* The rest of Allemang, Hendler & Gandon (3rd edition)
* [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:S14-method-and-quality-4.pdf | Slides from the lecture]]
-->


Useful materials:
Useful materials:
* [http://www.sciencedirect.com/science/article/pii/S095741741101640X Sicilia et al. (2012): Empirical findings on ontology metrics.] ''Paper.''  (cursory)
* The rest of Blumauer & Nagy (suggested)
 


&nbsp;
&nbsp;
<div class="credits" style="text-align: right; direction: ltr; margin-left: 1em;">''INFO216, UiB, Spring 2017-2018, 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)