ICSI500 Knowledge Graph Engineering
Welcome to the homepage of the 2024 edition of Knowledge Graph Engineering course at the National Univeristy of Mongolia.

 

 

News

 

 

This class will start on Monday February 5th. See details at the Calendar section

February 1st, 2024

 

 

 

 

Last modification: February 1st, 2024

Instructions

The 2024 Spring edition of KGE is taught in presence. As for the last years, presence, even if not a formal requirement, is strongly suggested given that this is a hands-on lab course. Passing the exam amounts to developing a project, which ultimately will lead to the generation of a Knowledge Graph (and support documentation) starting from data provided by the lecturers. This course and project work will develop under the continuous supervision of the lecturers, in collaboration with a colleague. There are no easy or cost-effective ways to develop the project without a continuous presence in class.

The lectures will take place following the scheduling indicated in the section Calendar and Material. The course material includes slides, demo videos, support resources and links, all provided on the web sit. After each main phase of the project, there will be a Q&A lecture during which the students can ask questions about all their open problems and doubts.

At the end of the course students will be asked to fill an online questionnaire about the overall process and methodology they will have learned. This feedback is very important to us, as it is the basis for a continuous evolution and improvement of the course and methodology being taught. To this extent students are strongly encouraged to raise doubts, ask questions, discuss the doubts they have about the methodology itself during the Q&A lectures.

Syllabus

Course Objectives and Outcomes

The Knowledge Graph Engineering (KGE) course aims to teach what are Knowledge Graphs, which are their possible usages and features, and what it means to build a KG. During the curse the students will discover the different issues to be addressed when a KG is built, learning which are the activities to be executed to that end, as per the current state of the art on Knowledge Graph Engineering. The course will teach an innovative methodology for Knowledge Graph Engineering, called iTelos. The methodology, will be applied by the students over real-world use case. By applying iTelos, the students will learn how to execute together the several activities involved in the construction of Knowledge Graphs. Moreover, such a process will be supported, within the course, by the usage of specific tools and libraries that the students will learn in order to solve the issues encouterd.

 

This course is taught in English. The intended target are the graduate or undergraduate students of the Department of Information and Computer Science, School of Information Technology and Electornics (SITE) of the National University of Mongolia. This is a 14 week, 56 hours, three credit, advanced course on how to develop a Knowledge Graph (KG) starting from data – to be cleaned and adapted – which are already available. This is a hands-on course. After a few introductory classes, students are given a problem to solve and they will build a knowledge graph solving this problem. A limited set of teaching material is available, mainly in form of slides. The student will learn mainly by doing the actual work and by interacting with the teacher and tutors. The exam consists in: writing a project report, giving a demo and making a public presentation.

 

General Description

This course will cover the following topics:
  • What are Knowledge Graphs (KGs)
  • What Knowledge Graphs can be used for, and example of already used KGs
  • What does it means to build a KG
  • How to reduce the cost of data use and reuse, exploiting KG
  • How to solve the different problems involved in KG construction, using the iTelos KGE methodology
  • How to use new and existing tools and libraries to address the problems encounterd in KGs construction
  • How to develop an entire project of KGE on real-world case studies

 

Prerequisites

  • Data management: basic programming skills in python and/or java/javascript
  • Databases modeling: ER modeling, (Ontology modeling if possible, Ontology definition desirable)
  • Attitude to teamwork

 

Course modality

Theory:
  • Lectures about KGE and the iTelos methodology, which aims to be the approach to be used to achieve the course objectives. iTelos is divided into 4 main phases that will shape the theoretical body of the course.
Practice:
  • During the whole course the students (grouped in teams) will be asked to carry on a KGE project assigned by tutors, relative to real-world case studies. The student will apply the iTelos methodology to produce a KG suitable to satisfy the purpose of the projects assigned.
Modality:
  • Theory and practice will go on in parallel. The lectures will describe the problems and the solutions, proposed by the iTelos methodology, that will be then immediately applied in practice over the projects assigned.
  • The course requires the student's presence in the classroom for the theoretical lectures (difficult to be learnt by only reading the slides provided lecture by lecture). Moreover, a strong cooperation between the team members is required to carry on the project's development along the course.

Teachers

Amarsanaa Ganbold
Simone Bocca
Amarsanaa Ganbold
Simone Bocca
amarsanaag@num.edu.mn
simone.bocca@unitn.it

Calendar and Material

The course runs from Feb 5th, 2024 till May 6th, 2024 with the following schedule

     

  • Monday, 14:20-17:30, Room No. 207, NUM Building 8

 

You might want to read the Instructions to understand how to take the course.

 

Notice also the titles and structure of the lessons yet to be delivered might change slightly. The rule of the thumb is: if there are links with materials, things won’t change; if there are no links to the materials, titles and content are just suggestions.

 

Lesson Number Date                                  Time Material                              Content of Material Lecturer(s)                 External resources                         Phase documentation deadline                        
1-2 Mon 5 Feb, 2024 14:20 Slides-1
Slides-2 		Course Organization
The data reuse problem		 S. Bocca, A. Ganbold KGE projects catalog
- Mon 12 Feb, 2024 No class Lunar New Year Holiday!
3-4 Mon 19 Feb, 2024 14:20 Slides-1
Slides-2
Slides-3 		State of the art
OpenStreetMap		 S. Bocca, A. Ganbold, B. Lkhagvasuren (invited lecturer, Public Lab Mongolia)
5-6 Mon 26 Feb, 2024 14:20 Slides Resource Description Framework (RDF)
Ontology Web Language (OWL)		 A. Ganbold
7-8 Mon 4 Mar, 2024 14:20 Slides-1
Slides-2 		The solution EML, Process and Architecture S. Bocca, A. Ganbold
9-10 Mon 11 Mar, 2024 14:20 Slides
Project Proposals 		Data Producer
Projects		 S. Bocca, A. Ganbold Project Preference
11-12 Mon 18 Mar, 2024 14:20 Slides-1
Slides-2 		iTelos
Purpose Formalisation		 S. Bocca, A. Ganbold KGE teams
13-14 Mon 25 Mar, 2024 14:20 Slides_1 Information Gathering
Q&A		 S. Bocca, A. Ganbold Data Management
Protege
Protègè guidelines 		Purpose Formalization phase
15-16 Mon 1 Apr, 2024 14:20 Slides_1
Language resource template 		Language Definition
Q&A		 S. Bocca, A. Ganbold KGE teams Concept ID ranges
OSM reference concept ontology
17-18 Mon 8 Apr, 2024 14:20 Slides-1 Knowledge Definition
Theory + Practice		 S. Bocca, A. Ganbold Language Definition phase
19-20 Mon 15 Apr, 2024 14:20 Slides-1 Data Definition (Theory)
Q&A		 S. Bocca, A. Ganbold Karma
Karma example see video on lectures 13-14
21-22 Mon 22 Apr, 2024 14:20 Data Definition (Practice)
Q&A		 S. Bocca, A. Ganbold Knowledge Definition phase
23-24 Mon 29 Apr, 2024 14:20 Slides-1 KG Evaluation S. Bocca, A. Ganbold
25-26 Mon 6 May, 2024 14:20 Metadata & Data Distribution
SPARQL		 S. Bocca, A. Ganbold
27 Exams dates Registration sheet Registration sheet
28 Questionnaires Questionnaire
 Evaluation Questionnaires

Exam

After the completion of each iTelos methodology phase (both concerning theory and practice) the students will have to provide an intermediate report of the work done so far, which will be checked and evaluated by lecturers. This intermediate evaluation will allow the lecturers to lead the teams towards the right direction by correcting possible errors during the methodology implementation.

The final exam will consist of a presentation of the KGE projects developed along the course and finalized achieving the output required by the initial project's purpose. In addition some questions can be asked, at the end of the project presentation, to evaluate the students over the key aspect of the iTelos methodology.

Collaboration Opportunities

The general activities of the research groups are listed on the websites http://knowdive.disi.unitn.it/ and https://milab.num.edu.mn.

 

Anyone interested in these opportunities can send an email to amarsanaag@num.edu.mn, providing already information about preferences in terms of topics or activities (if known).