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Repository dedicated to the webpage of the laboratory for the Knowledge Representation and Extraction course of the Master Degree in Digital Humanities and Digital Knowledge

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Knowledge Representation and Extraction Laboratory

Introduction

KRaE-Lab will be a practical take on the lessons of the Knowledge Representation and Extraction course of the Digital Humanities and Digital Knowledge Master Degree of the University of Bologna. It will be held by Bruno Sartini, PhD Student and Tutor of the DHDK course.

The aim of the laboratory is to make students familiarize with techniques of knowledge extraction and representation. It will include insights on SPARQL language, management of data and conversion of data from machine-readable formats such as json or csv to linked open data versions. Practical examples on how to construct, analyze and query graphs will be given along with an introduction on how to develop an Ontology.

The lessons will be held using the Microsoft Teams Software.

The whole content of the lab will be found in the website https://br0ast.github.io/KRaE-lab/

Required Knowledge

  • basic knowledge of what an RDF is
  • basic knowledge of the formats you can use to encode Linked open data
  • basic knowledge of python (libraries and platforms will be explained during the laboratory

Note: if you are not a student of the DHDK master degree and you plan to follow this course only you can acquire basic knowledge of the subjects above by looking at the materials/slides of the Computational Thinking and Programming course and Knowledge Organization and Cultural Heritage course.

Required Materials

  • The free software protégé will be used during the laboratory.
  • Microsoft Teams will be used to broadcast the lessons.
  • A browser will be used to access google colab and the various SPARQL endpoints that will be queried.

Timetable

Lesson Date Time Link
1 25/03/2021 14:30-17:30 Online Lesson
2 08/04/2021 14:30-17:30 Online Lesson
3 16/04/2021 14:30-17:30 Online Lesson
4 23/04/2021 14:30-17:30 Online Lesson
5 29/04/2021 14:30-17:30 Online Lesson

Lessons Content

Lesson 1: Wikipedia-based Ontology Induction

A frontal lesson on how to semi-automatically develop a domain-specific ontology by extracting, re-engineering the knowledge on DBpedia and Wikidata

Lesson 2: From Open Data to Linked Open Data: bottom-up approach to ontology development

A participative lesson on how to transform open data into linked open data and how to develop your ontology starting from data. Students will be divided into groups and at the end of the lesson will present their work.

Lesson 3: Theory-based ontology deduction

A participative lesson on how to develop an ontology starting from a specific theory of the interested domain. Students will be divided into groups and at the end of the lesson will present their work.

Lesson 4: Semantic virtual curation pt.1

A participative lesson in which students will be asked to develop a semantic virtual curation.

Lesson 5: Semantic virtual curation pt.2

Second part of the lesson based on a semantic virtual curation. At the end of the lesson students will present their work on their semantic virtual curation.

Output of the mini-projects

Available Soon

About the template

The website was generated using a Start Bootstrap template. Start Bootstrap is an open source library of free Bootstrap templates and themes. All of the free templates and themes on Start Bootstrap are released under the MIT license, which means you can use them for any purpose, even for commercial projects.

Start Bootstrap was created by and is maintained by David Miller.

Start Bootstrap is based on the Bootstrap framework created by Mark Otto and Jacob Thorton.

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