Contents

Course Introduction

TDT44 Semantic Web: a Specialization module complementary to TDT4175 Information Systems. Other IS modules can be found here.

TDT44 will be taught by Rune Sætre in the fall 2017. 

We will use the following book: https://link.springer.com/book/10.1007/978-3-319-45654-6 (free for NTNU students)

News

Readings in TDT44 Semantic Web (2017)

The book we will use is: Exploiting Linked Data and Knowledge Graphs in Large Organisations (amazon link).

Please order the book now, so you have it ready for the first class in September!

You can also download it for free on the NTNU-network from here: http://www.springer.com/br/book/9783662437957

You may also read two papers, on Logics and Turtle, and a student found this paper:

 The Unreasonable Effectiveness of Data.pdf is not really about the Semantic Web, but I post it here as a good read for those who like that.

Students 2017

From complete list on https: //www.idi/intra/teaching/theorymodule_participants.php? Code = TDT44

Expand
title Old News: Click here to expand...
Date Topic 2016.10.25 TDT44 Individual Essay Assignment 2016 released 2016.08.31 The welcome lecture will be on Friday, 9.30am, September 2nd, in room ITV-354 (IT building). See you there 2016.08.16 TDT44 will be taught in the autumn 2016. 2015.11.19 Vi er blitt bedt om å flytte oss fra 454 til 242 den siste onsdagen dette semesteret, nemlig 25/11-20215, så da gjør vi det. 2015.10.22 TDT44 Individual Essay Assignment 2015 released

OLD STUFF

Oral Exam (2016)

Write an essay on essay on a given topic. There will be a brief oral examination, presenting your essay.
Date: 30th November 2016, 20 minutes, between 0830 and 1700.
Place: ITV-114. Time: See student table below.

From https://innsida.ntnu.no/.../Specialization+Information+Systems (or in Norwegian https://innsida.ntnu.no/.../Fordypning+i+datateknologi).
Examination takes place as follows: Attendance schedule for students sent by email (username@stud) and posted on the bulletin board outside the reception at IDI.
First examination may start as early as 08:00.Each exam takes 5-20 minutes. If you fail or have valid reason for not showing up, a continuation exam will be held in August the following year.
Note especially the following matters regarding the theory modules: The Specialization project must be passed in order to be able to start the Master Thesis work.

Schedule (2017)

Schedule (2016)

Teachers (2011-2017)

Associate Professor Rune Sætre (teacher), satre at idi.ntnu.no, room  ITV-104
(Examiner: Professor Jon Atle Gulla, jag at idi.ntnu.no, room  ITV-114)

TDT44 Individual Essay Assignment 2016

External links

Part 1 and part 2 of this tutorial can be relevant for our class:

• Horrocks, Ian  (2010);  Semtech 2010  tutorial  part 1  and  part 2  on Description Logics and OWL

About the course

The students get an orientation of the theoretical, methodological and technological background and of the ongoing standardization work that support semantic Web.

You will gain:

• Background theoretical knowledge
• Insight to relevant problems within Web information resources and services
• Insight to how to use semantic web technology to solve problems in different domains
  
  

Mandatory activities: Presentations, project report, final presentation.

Final grade: Project report and final presentation.

Introduction for Fall 2021

Introductory presentation

Schedule

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Obligatory Individual Assignment 2021

To be announced.

Obligatory Individual Assignment 2020

You can choose one of the following obligatory assignments:

Option 1:

Write a report (max 10 pages) on a topic of your choice (to be agreed upon with the teacher).

You can choose a topic which will be close to your master thesis topic. You are not allowed to copy text from this report to your thesis or fall report, but you can re-use the ideas and insight you gain.

While deciding on the topic it is recommended to talk to your supervisor.

Option 2:

Develop an RDF(S) ontology (or a dictionary) on a chosen topic (to be agreed upon with the teacher) and write a short report (max 5 pages) explaining the details of your work.

Explain every aspect of your ontology. Explain the assumptions underlying your ontological choices.

The ontology should not exceed 30 classes and 30 instances. The modeling language should be Turtle or a similar syntax. You can use any modeling software.

If you choose this task, you may refer to the individual assignments in the previous years in this course.

Mandatory peer feedback:

Document to submit: (Deadline: 5 November 2020)

For this task please prepare a 1-2 page document where you explain your obligatory assignment in more detail.

Peer feedback: (Deadline: 10 November 2020)

After submitting your document to peergrade, you will be able to see the feedback form. There is an explanation of the task in the system.

More information has been sent by e-mail.

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PAST ASSIGNMENTS

Obligatory assignment from 2019.

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About the Exam (2019) 

Oral exam will take place on 28 November 2019. This will be the only exam in this course. The schedule for the exam will be announced through the official channels a few days before the exam, it won't be announced on this page.

For the sensors to read your reports before the oral exam, you need to send them a few days before the exam by e-mail to ozlem.ozgobek@ntnu.no.

The deadline for sending the reports is 25 November 2019, 07.00 AM.

Presentation Details

During the oral exam, each student will have 20 minutes. This includes the presentation of the individual assignment and questions from the sensors. For the presentation you don't need any slides, so don't prepare any slides. We will ask you to explain your assignment orally, you can use a white board if needed. Please bring a printed copy of your report with you. Questions from sensors will include details from your assignment and some basic knowledge from the book.

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Course Material

Books:

Semantic Web for the Working Ontologist, Second edition: Effective modeling in RDFS and OWL by Dean Allemang and James Hendler, Morgan Kaufmann, 384 pp. (Available online at NTNU Library)

Exploiting Linked Data and Knowledge Graphs in Large Organisations (Available for free on the NTNU-network: https://link.springer.com/book/10.1007/978-3-319-45654-6)

Presentations:

Presentations from 2019

Presentations from 2018

Presentations from 2017

Other Useful Material:

TDT44 Individual Assignment 2017

• To get more information about the last year's assignment please click here.
• Example solutions for the assignment of 2017.

Research Papers

You may also read two papers, on Logics and Turtle, and if you are interested:

• The Unreasonable Effectiveness of Data.pdf is not really about the Semantic Web, but I post it here as a good read for those who like that.
• https://www.w3.org/TR/owl2-primer/ might be useful when comparing RDF vs. Turtle etc.

External links

Part 1 and part 2 of this tutorial can be relevant for our class:

• Horrocks, Ian  (2010);  Semtech 2010  tutorial  part 1  and  part 2  on Description Logics and OWL

W3 : www.w3.org

OWL: https://www.w3.org/2001/sw/wiki/OWL

Schema.org

Friend of a friend ontology: https://en.wikipedia.org/wiki/FOAF_(ontology)

Blog post - knowledge graphs: https://medium.com/@sderymail/challenges-of-knowledge-graph-part-1-d9ffe9e35214

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Teachers

Özlem Özgöbek (Teacher), ozlem.ozgobek at ntnu.no, room  ITV-205)
(Professor Jon Atle Gulla (Examiner), jag at ntnu.no)

 1 Enterprise Knowledge Graph: An Introduction ................. 1 Jose Manuel Gomez-Perez, Jeff Z. Pan, Guido Vetere and Honghan Wu 1.1 A Brief History of Knowledge Graph....................... 2 1.1.1 The Arrival of Semantic Networks ................... 2 1.1.2 From Semantic Networks to Linked Data .............. 3 1.1.3 Knowledge Graphs: An Entity-Centric View of Linked Data .................................. 4 1.2 Knowledge Graph Technologies in a Nutshell ................ 5 1.3 Applications of Knowledge Graphs for Enterprise ............. 5 1.4 How to Read This Book................................. 10 1.4.1 Structure of This Book ............................ 10 1.4.2 Who This Book Is For ............................ 12 1.4.3 How to Use This Book ............................ 12 Part I Knowledge Graph Foundations & Architecture 2 Knowledge Graph Foundations .............................. 17 Boris Villazon-Terrazas, Nuria Garcia-Santa, Yuan Ren, Alessandro Faraotti, Honghan Wu, Yuting Zhao, Guido Vetere and Jeff Z. Pan 2.1 Knowledge Representation and Query Languages ............. 18 2.1.1 RDF and RDFS ................................. 18 2.1.2 OWL.......................................... 26 2.1.3 SPARQL....................................... 30 2.2 Ontologies and Vocabularies ............................. 33 2.2.1 Some Standard Vocabularies........................ 34 2.2.2 schema.org ..................................... 38 2.3 Data Lifting Standards .................................. 39 2.3.1 RDB2RDF ..................................... 39 2.3.2 GRDDL ....................................... 48 xi 2.4 Knowledge Graph Versus Linked Data ..................... 51 2.5 Knowledge Graph for Web Searching and Knowledge Graph for Enterprise .................................... 52 3 Knowledge Architecture for Organisations ..................... 57 Ronald Denaux, Yuan Ren, Boris Villazon-Terrazas, Panos Alexopoulos, Alessandro Faraotti and Honghan Wu 3.1 Architecture Overview .................................. 58 3.2 Acquisition and Integration Layer.......................... 60 3.2.1 Ontology Development ............................ 60 3.2.2 Ontologisation of Non-Ontological Resources........... 61 3.2.3 Text Integration via Named Entity and Thematic Scope Resolution ................................ 62 3.2.4 Ontology Learning ............................... 64 3.3 Knowledge Storing and Accessing Layer .................... 65 3.3.1 Ontology-Based Data Access ....................... 65 3.3.2 RDF Stores ..................................... 69 3.3.3 Property Graph-Based Stores ....................... 73 3.3.4 Conclusion: Storing Knowledge Graphs Versus Relational Databases .............................. 75 3.4 Knowledge Consumption Layer ........................... 77 3.4.1 Semantic Search ................................. 77 3.4.2 Summarisation................................... 78 3.4.3 Query Generation ................................ 80 3.4.4 Question Answering .............................. 81 3.4.5 Conclusion ..................................... 83 Part II Constructing, Understanding and Consuming Knowledge Graphs 4 Construction of Enterprise Knowledge Graphs (I) ............... 87 Boris Villazon-Terrazas, Nuria Garcia-Santa, Yuan Ren, Kavitha Srinivas, Mariano Rodriguez-Muro, Panos Alexopoulos and Jeff Z. Pan 4.1 Knowledge Construction and Maintenance Lifecycle ........... 88 4.2 Ontology Authoring: A Competency Question-Driven Approach ............................................ 93 4.2.1 Competency Questions ............................ 94 4.2.2 Formulation of Competency Questions ................ 96 4.2.3 Ontology Authoring Workflow ...................... 98 4.3 Semi-automated Linking of Enterprise Data for Virtual Knowledge Graphs..................................... 104 4.3.1 Virtual Knowledge Graph for Knowledge Discovery ..... 104 4.3.2 Semantic Tagging and Data Interlinking ............... 106 xii Contents 4.3.3 Usage Scenarios ................................. 109 4.3.4 Conclusion ..................................... 116 5 Construction of Enterprise Knowledge Graphs (II)* ............. 117 Panos Alexopoulos, Yuting Zhao, Jeff Z. Pan and Man Zhu 5.1 Scenario-Driven Named Entity and Thematic Scope Resolution of Unstructured Data*.......................... 117 5.1.1 Framework Description ............................ 118 5.1.2 Framework Application Evaluation ................... 123 5.2 Open-World Schema Learning for Knowledge Graphs* ......... 126 5.2.1 Motivation...................................... 126 5.2.2 BelNet þ ....................................... 128 5.2.3 TBox Learning as Inference ........................ 133 5.2.4 A Novel Evaluation Framework ..................... 133 5.2.5 Experiments .................................... 136 5.2.6 Experimental Results.............................. 139 5.2.7 Related Work and Summary ........................ 144 5.2.8 Conclusion ..................................... 145 6 Understanding Knowledge Graphs ........................... 147 Honghan Wu, Ronald Denaux, Panos Alexopoulos, Yuan Ren and Jeff Z. Pan 6.1 Understanding Things in KGs: The Summary of Individual Entities .............................................. 149 6.1.1 Entity Data Organisation ........................... 150 6.1.2 Summarisation of Entity Data ....................... 156 6.1.3 Conclusion ..................................... 157 6.2 Exploring KGs: The Summary of Entity Description Patterns .... 157 6.2.1 What Is the Entity Description Pattern? ............... 159 6.2.2 How Can the Entity Description Pattern Help in Knowledge Exploitations?.......................... 161 6.2.3 Conclusion ..................................... 163 6.3 Profiling KGs: A Goal-Driven Summarisation ................ 164 6.3.1 Motivating Scenario and Problem Definition............ 164 6.3.2 Framework Description ............................ 164 6.3.3 Implementation .................................. 166 6.3.4 Application Example.............................. 169 6.3.5 Conclusion ..................................... 171 6.4 Revealing Insights from KGs: A Query Generation Approach* ........................................... 171 6.4.1 Candidate Insightful Queries........................ 174 6.4.2 Query Generation Framework ....................... 177 6.4.3 Evaluation of the Query Generation Method............ 178 6.4.4 Conclusion and Future Work ....................... 180 Contents xiii 7 Question Answering and Knowledge Graphs ................... 181 Alessandro Moschitti, Kateryna Tymoshenko, Panos Alexopoulos, Andrew Walker, Massimo Nicosia, Guido Vetere, Alessandro Faraotti, Marco Monti, Jeff Z. Pan, Honghan Wu and Yuting Zhao 7.1 Question Answering over Text Documents................... 182 7.1.1 Realising a QA System: Approaches and Key Steps...... 182 7.2 Question Answering over Knowledge Graphs ................ 189 7.2.1 State-of-the-Art Approaches for Question Answering Over Knowledge Graphs........................... 190 7.2.2 Question Answering in the Enterprise ................. 193 7.3 Knowledge Graph and Watson DeepQA .................... 196 7.3.1 What Is Watson DeepQA? ......................... 196 7.3.2 What Are the Knowledge Graphs Used in Watson DeepQA? ...................................... 198 7.3.3 How Knowledge Graphs Are Used in Watson DeepQA? ...................................... 199 7.3.4 Lessons Learnt from Watson DeepQA ................ 201 7.4 Using Knowledge Graphs for Improving Textual Question Answering* .......................................... 202 7.4.1 A Flexible QA Pipeline............................ 202 7.4.2 Exploiting External Knowledge (Graphs) for Re-ranking................................... 204 7.4.3 Evaluation: Impact of Knowledge Graphs in Semantic Structures............................. 209 7.4.4 Conclusion ..................................... 212 Part III Industrial Applications and Successful Stories 8 Success Stories............................................ 215 Marco Monti, Fernanda Perego, Yuting Zhao, Guido Vetere, Jose Manuel Gomez-Perez, Panos Alexopoulos, Hai Nguyen, Gemma Webster, Boris Villazon-Terrazas, Nuria Garcia-Santa and Jeff Z. Pan 8.1 A Knowledge Graph for Innovation in the Media Industry ...... 216 8.1.1 The Business Problem............................. 216 8.1.2 The HAVAS 18 Knowledge Graph................... 217 8.1.3 Value Proposition ................................ 218 8.1.4 Challenges...................................... 219 8.2 Applying Knowledge Graphs in Cultural Heritage ............. 219 8.2.1 Digital Cultural Heritage and Linked Data ............. 219 8.2.2 The Challenges .................................. 220 8.2.3 The CURIOS Project ............................. 221 8.2.4 Constructing the Knowledge Graph .................. 223 xiv Contents 8.2.5 CURIOS—A Linked Data Adaptor for Content Management Systems ............................. 224 8.2.6 Presenting and Visualising Cultural Heritage Knowledge Graphs ............................... 225 8.2.7 Collaborative Construction and Maintenance of Cultural Heritage Knowledge Graphs ............... 228 8.3 Applying Knowledge Graphs in Healthcare .................. 228 8.3.1 The Problem in Clinical Practice Guidelines............ 229 8.3.2 Preparing the Data and Building the Knowledge Graphs ........................................ 230 8.3.3 Services Based on the Knowledge Graphs ............. 233 8.3.4 Contributions to Healthcare Practice .................. 235 9 Enterprise Knowledge Graph: Looking into the Future...