Coursebooks

Foundations and tools for processing tree structured data

CS-525

Lecturer(s) :

Vanoirbeek Christine

Language:

English

Summary

The course is about the foundations and tools for processing tree structured data, a prevalent model for representing semi-structured data (SSD) over distributed information networks. It aims at presenting approaches, programming languages and tools for modeling and manipulating tree-structured info

Content

The theoretical part introduces underlying concepts sustaining the approach.
The practical part illustrates the application of the concepts in a concrete context: the development of Web applications that make use of an XML native database (one category of the NoSQL databases) and associated XML languages.
Theoretical foundations
¿ Tree grammars
¿ Finite tree automata
Type systems to describe and validate the structure of SSD
¿ Document Type Definition
¿ XML Schema
¿ RELAX NG and Schematron
Querying tree structured data and programming
¿ Navigation and extraction of information from tree structured data (XPath expressions)
¿ Tree data transformation (XSLT)
¿ Query and programmig language (XQuery) incl. Static Type Checking
Application scenario
¿ Use of a development framework in which all these languages fit

Keywords

Tree-shaped data representation and processing, Foundation of XML types, Tree grammars, XML core technologies, Web applications

Learning Outcomes

By the end of the course, the student must be able to:

Teaching methods

Ex cathedra lectures and group mini-projects.

Expected student activities

Attend the lectures

Work on mini-project

Assessment methods

Written exam and mini-project evaluation.

In the programs

  • Computer Science, 2019-2020, Master semester 1
    • Semester
      Fall
    • Exam form
      Written
    • Credits
      4
    • Subject examined
      Foundations and tools for processing tree structured data
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Project
      2 Hour(s) per week x 14 weeks
  • Computer Science, 2019-2020, Master semester 3
    • Semester
      Fall
    • Exam form
      Written
    • Credits
      4
    • Subject examined
      Foundations and tools for processing tree structured data
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Project
      2 Hour(s) per week x 14 weeks
  • Computer Science - Cybersecurity, 2019-2020, Master semester 1
    • Semester
      Fall
    • Exam form
      Written
    • Credits
      4
    • Subject examined
      Foundations and tools for processing tree structured data
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Project
      2 Hour(s) per week x 14 weeks
  • Computer Science - Cybersecurity, 2019-2020, Master semester 3
    • Semester
      Fall
    • Exam form
      Written
    • Credits
      4
    • Subject examined
      Foundations and tools for processing tree structured data
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Project
      2 Hour(s) per week x 14 weeks
  • Data Science, 2019-2020, Master semester 1
    • Semester
      Fall
    • Exam form
      Written
    • Credits
      4
    • Subject examined
      Foundations and tools for processing tree structured data
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Project
      2 Hour(s) per week x 14 weeks
  • Data Science, 2019-2020, Master semester 3
    • Semester
      Fall
    • Exam form
      Written
    • Credits
      4
    • Subject examined
      Foundations and tools for processing tree structured data
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Project
      2 Hour(s) per week x 14 weeks

Reference week

MoTuWeThFr
8-9
9-10
10-11
11-12
12-13
13-14 INM11
14-15
15-16 INM11
16-17
17-18
18-19
19-20
20-21
21-22
Lecture
Exercise, TP
Project, other

legend

  • Autumn semester
  • Winter sessions
  • Spring semester
  • Summer sessions
  • Lecture in French
  • Lecture in English
  • Lecture in German