Data and Knowledge Engineering

Johann Mitloehner, 2020-25

• Relational Database Systems
  • Basic database concepts ||| NB 15.10.
    • Video: Basic Concepts
    • Video: JupyterHub, Birding example
  • Functional Dependencies and Keys ||| NB 15.10.
    • Video: Functional dependencies and keys
    • Video: Exercise chess club
  • SQL by examples: products, customers and orders ||| NB 22.10.
    • Video: SQL by Examples: Join and Group by
    • Solutions to exercises
  • Good table design: Normal Forms ||| NB
    • Video: Normal Forms 1,2,3
    • Video: BCNF and Algorithms
    • Video: 1NF movie example
    • Exercises for Normal Forms
    • Solutions for Exercises
  • DB Applications ||| NB 05.11.
    • Video: DB Apps Part 1: CSV Import
    • Video: DB Apps Part 2: CSV Export, Reports
    • Video: Another Import/Export Example: Auto MPG
• Knowledge Graphs
  • RDF and N3 ||| NB 12.11. MC1
    • Video: Populating the Knowledge Graph
    • Video: Defining a simple Ontology
    • Example: NBA notebook and file teams.csv
  • Sparql ||| NB 12.11.
    • Video: Sparql
  • Reasoning ||| NB 03.12.
    • Video: Reasoning
  • Sparql Endpoints ||| NB 03.12.
    • Video: Querying Endpoints
• Applications
  • Combining relational DB and RDF sources ||| NB 10.12. MC2
    • Video: Combine SQL and Sparql
    • Video: DBpedia
    • Video: Sun Spots and Pirates

NB = Jupyter notebook zum download

In der LV wird nur open source software verwendet, die Sie auf Ihrem Computer installieren koennen:

• python.org
• jupyter.org

Alternativ dazu: JupyterHub server jupyter.wu.ac.at

Misc

• Ev. notwendig (error bei select, je nach Version jupyter/sqlite extension):
  %config SqlMagic.style = '_DEPRECATED_DEFAULT'
• Normalization Tool at griffith.edu.au with lots of examples
• Some sources of CSV data files:
  • R datasets
  • UCI Machine Learning Repository
  • Hugging Face datasets
• RDF sources:
  • DBPedia sparql query editor
  • WikiData query service
  • OpenStreetMap Sophox service
• Comments: # for Python, -- for SQL
• PostgresQL connector am JupyterHub server des Departments (ueber Learn-Seite zur LV/Lernaktivitaeten):
  %sql postgresql://h12345678:h12345678@postgresql.student-db.svc.cluster.local/h12345678
• A very basic LLM implementation for the Tale of Peter Rabbit ||| NB
• N3 examples for Chess and Peter Rabbit; generate N3 from CSV

References

• Chris Date, An Introduction to Database Systems, various editions

  This one stands out from the large crowd of DB books as it is not tied to a particular software product and approaches relational DB systems and SQL critically; Date covers relational theory in great detail and points out weaknesses and bad design decisions in existing DBMS and SQL, at least from his point of view. Lots of exercises, very interesting read. Highly recommended, but not at all needed for this lecture; for those who wish to further explore the relational approach. New copies of the latest edition are very expensive, but older editions are fine as well (e.g. paperback 1999); cheap used copies can be found at various online retailers, often for a few $.