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Curriculum

Modul CS4130-KP06, CS4130

Information Systems (InfoSys)

Duration:


1 Semester
Turnus of offer:


each summer semester
Credit points:


6
Course of studies, specific field and terms:
  • Master Computer Science 2019 (compulsory), Canonical Specialization Data Science and AI, Arbitrary semester
  • Master Entrepreneurship in Digital Technologies 2020 (basic module), technology field computer science, 1st or 2nd semester
  • Master Media Informatics 2020 (optional subject), computer science, Arbitrary semester
  • Master Computer Science 2019 (basic module), Applied computer science, 1st or 2nd semester
  • Master Medical Informatics 2019 (basic module), Applied computer science, 1st or 2nd semester
  • Master Robotics and Autonomous Systems 2019 (optional subject), Elective, 1st or 2nd semester
  • Master IT-Security 2019 (basic module), Applied computer science, 1st or 2nd semester
  • Master Medical Informatics 2014 (basic module), ehealth / infomatics, 1st or 2nd semester
  • Master Media Informatics 2014 (optional subject), computer science, Arbitrary semester
  • Master Entrepreneurship in Digital Technologies 2014 (basic module), technology field computer science, 1st or 2nd semester
  • Master Computer Science 2014 (optional subject), specialization field software systems engineering, 2nd or 3rd semester
  • Master Computer Science 2014 (basic module), Applied computer science, 1st or 2nd semester
Classes and lectures:
  • Information Systems (exercise, 2 SWS)
  • Information Systems (lecture, 2 SWS)
Workload:
  • 60 Hours in-classroom work
  • 20 Hours exam preparation
  • 100 Hours private studies
Contents of teaching:
  • Fundamentals of databases, conceptual modeling languages (ontologies), query languages, processes, and agents
  • Ontology based data access (OBDA)
  • Ontology evolution and ontology integration
  • Data exchange and data integration (schema mappings, duplicate detection, inconsistency handling, integration with relational and ontological constraints as well as with incomplete data)
  • Data stream processing (e.g., for sensor networks, robotics, web agents) with OBDA and complex event processing (CEP)
  • Non-symbolic data and their symbolic annotations (e.g., for applications in bioinformatics/computational biology and for media interpretation), syntax, semantics, hybrid decision and computation problems and their complexity, (analysis of) algorithms
  • Data- and ontology-oriented process analysis (e.g., for biological pathways) and process design (e.g., for non-trivial business processes)
Qualification-goals/Competencies:
  • Knowledge: The module aims at introducing the students to the formal basics of databases and ontologies, so that they get an overview of concepts, methods, and theories for understanding, analyzing, and designing information systems in open large contexts, such as the web.
  • Skills: The students get a basic understanding of logical and formal methods, which allows them to assess the possibilities and limitations of information systems, be it concrete ones or those that still have to be designed. Assessment parameters are correctness and completeness (Does the system produce what is expected? If so, does it produce all results?) as well as expressiveness (Is it possible to formulate all required queries? What are equivalent query languages?) and, last but not least, performance (How long does it take the system to come up with an answer? How much space does it need?). In addition to these analysis skills, students receive logical modeling skills using real application scenarios from industry (business processing, integration of data resources, processing of time-based and event data), and medicine (sensor networks, genomic ontologies, annotation). Based on these, the student not only acquires the ability to assess which logical model is suitable for which application scenario, but also the ability to construct their own logical models where necessary.
  • Social Competence und Independent Work: Students work in groups to solve small exercises and project problems and sketch their solutions in short presentations. Independent work is promoted by exercises with practical ontology and database systems.
Grading through:
  • Oral examination
Responsible for this module:
Teachers:
Literature:
  • S. Abiteboul, R. Hull, V. Vianu: Foundations of Databases - Addison-Wesley, 1995
  • M. Arenas, P. Barcelo, L. Libkin, and F. Murlak: Foundations of Data Exchange - Cambridge University Press, 2014
  • F. Baader, D. Calvanese, D.L. McGuinness, D. Nardi, and P.F. Patel-Schneider (Eds.): The Description Logic Handbook: Theory, Implementation, and Applications - Cambridge University Press, 2010
  • S. Chakravarthy, Q. Jiang: Stream Data Processing A Quality of Service Perspective - Springer, 2009
  • L. Libkin: Elements Of Finite Model Theory (Texts in Theoretical Computer Science. An Eatcs Series) - SpringerVerlag, 2004
Language:
  • German and English skills required
Notes:

Admission requirements for taking the module:
- None

Admission requirements for participation in module examination(s):
- Successful completion of exercises as specified at the beginning of the semester.

Module Exam(s):
- CS4130-L1: Information Systems, oral exam, 100% of module grade.

Previous name: Web Based Information Systems

Recommended previous modules:
- Algorithm and Data Structures (CS1001)
- Linear Algebra and Discrete Structures I+II (MA1000, MA1500)
- Databases (CS2700)
- Logic (CS1002)
- Bachelor Project Computer Science (CS3701), topic: logic programming
- Nonstandard Database Systems (CS3202)

Prerequisites for the exam:
- Successful completion of homework assignments during the semester.

Letzte Änderung:
1.2.2022