Universität Passau
6210V Lecture: Semantic Data Integration - Details
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General information

Subtitle
Course number 6210V
Semester SoSe 24
Current number of participants 261
expected number of participants 150
Home institute Lehrstuhl für Informatik mit Schwerpunkt Data and Knowledge Engineering
Courses type Lecture in category Lehre (mit Prüfung)
Next date Wed., 25.09.2024 10:00 - 12:00 Uhr, Room: (PHIL) HS 1
Type/Form
Participants
Master Informatik: Modulgruppe „Informations- und Kommunikationssysteme“
Master AI Engineering: Modulgruppe “AI Applications”
Master Computational Mathematics: Modulgruppe „Data Analysis and Data Management and Programming“
Pre-requisites
Datenbanken und Informationssysteme
Algorithmen und Datenstrukturen
Web und Data Engineering

Databases and information systems
Algorithms and data structures
Web and data engineering
Performance record
90 min Klausur
SWS
2V+2UE
Literatur
– AnHai Doan, Alon Halevy, Zachary Ives: Principles of Data Integration. Morgan Kaufmann, 2012.
– Barbella, Marcello, and Genoveffa Tortora. "A Semi-automatic Data Integration Process of heterogeneous databases." Pattern Recognition Letters (2023).
– Ulf Leser, Felix Naumann: Informationsintegration. Dpunkt Verlag, 2007.
– Luna Dong, Divesh Srivastava: Big Data Integration. Morgan & Claypool, 2015.
– Serge Abiteboul, et al: Web Data Management. Cambridge University Press, 2012.
– Mountantonakis, Michalis, and Yannis Tzitzikas. "Large-scale semantic integration of linked data: A survey." ACM Computing Surveys (CSUR) 52.5 (2019): 1-40.
– Jérôme Euzenat, Pavel Shvaiko: Ontology Matching. Springer, 2007.
– Felix Naumann: An Introduction to Duplicate Detection. Morgan & Claypool, 2012.
Hinweise zur Anrechenbarkeit
Ab 1. Semester Master
Workload
60 Std. Präsenz + 60 Std. Übungen + 60 Std. Nachbereitung der Vorlesung und Prüfungsvorbereitung
60 contact hours + 60 hrs exercises + 60 hrs independent study
and exam preparation
Miscellanea
The course will be in English.
ECTS points
6

Course location / Course dates

(PHIL) HS 1 Tue.. 10:30 - 12:00 (13x)
Wednesday. 25.09.24 10:00 - 12:00
(SP) Tuesday. 30.07.24 10:00 - 11:40
(HK 30) R 214a Tuesday. 30.07.24 12:00 - 18:00

Fields of study

This information on acceptance for credit of modules for individual degree programmes is not binding; please check the module catalogue at the Faculty of Computer Science and Mathematics to confirm that this module can be counted towards your degree.

Module assignments

Comment/Description

This module focuses on the principles of data integration describing the importance of data integration in different applications and use cases. Different schemes of integration such virtual and physical data integration will be covered and then focusing on virtual and web data integration. Various aspect of data integration, such as data and semantic heterogeneities, schema and ontology matching, and the role of semantic and ontologies in improving data integration and data interoperability. The students will acquire a systematic understanding of combining and integrating different data sources using a broad range and techniques of data integration. During the integration process, the students will know basic and advanced models and formats for representing data, how to identify and discover data and semantic heterogeneities across different data sources, the principles for achieving data interoperability through ontologies, and advanced technologies for querying the data