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Regular version of the site

Scientific Seminar "Theory and Practice of Knowledge Management"

2022/2023
Academic Year
ENG
Instruction in English
5
ECTS credits
Delivered at:
Department of Information Systems and Technologies (Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod))
Course type:
Elective course
When:
2 year, 3 module

Course Syllabus

Abstract

The discipline follows the course "Conceptual Modeling", which allows students to consider the theory and practice of building conceptual models and knowledge issues in relation to each other. In the process of mastering the educational material, students get acquainted with the theory of knowledge representation using relational logic. Practical exercises are based on the use of the MIT Alloy Analyzer software toolkit. Using this tool, students perform the formalization of knowledge in several subject areas, analyze the consistency of the constructed models, apply the results of the analysis to make decisions and verify the properties of information systems. Particular attention in the course of training is paid to the dynamic aspect of knowledge, orientation to use in the process of analyzing a problem situation and making decisions. At the final stage of training, students master the skills of joint use of conceptual modeling tools and formal logical analysis using the examples of UFO ontology and relational logic. The course is intended for Masters of Business Informatics of the second year of study, for studying the course it is desirable to successfully master the course "Conceptual Modeling: Ontological Theories".
Learning Objectives

Learning Objectives

  • Целью освоения дисциплины «Теория и практика управления знаниями» является овладение навыками описания и анализа знаний о предметной области в форме формальных логических теорий.
Expected Learning Outcomes

Expected Learning Outcomes

  • Understand various definitions of knowledge relevant for modelling domain problems and enterprise processes.
  • Explain principal steps in the process of formal verification of complex artificial systems.
  • Explain critical problems in formal knowledge representation and verification using formal logic.
  • Explain main characteristics of satisfiability problem, and its solution methods and tools.
  • Explain principal elements of syntax and semantics of relational logic using MIT Alloy Analyzer as an example.
  • Describe and explain critical characteristics of solving SAT problem in the bounded context, using MIT alloy Analyzer as a example.
  • Demonstrate correspondence between relational logic, relational algebra and relational databases in the process of domain knowledge modelling.
  • Explain principal elements of syntax and semantics of Alloy domain specific language for knowledge representation.
  • Explain principal reusable methods of knowledge analysis using Alloy domain specific language.
  • Demonstrate ability to model and analyse domain problems in terms of Alloy DSL.
  • Demostrate skills of professional using software tools for knowledge representation and analysis, using MIT Alloy Analyzer and OntoUML tools as examples.
  • Explain correspondence between languages and tools for conceptual modelling and tools for logical formal analysis, using OntoUML tools and MIT Alloy Analyzer as examples.
  • Demonstrate good understanding of principal trends of further scientific and technological advances in the domain of knowledge representation and analysis, using MIT Alloy analyser as an example.
Course Contents

Course Contents

  • Introduction to knowledge representation
  • Lightweight logical analysis of knowledge
  • Formal Relational Logics of Alloy
  • Domain-specific language of Alloy for knowledge representation and verification
  • Methods of knowledge representation and analysis using Alloy DSL
  • Domain modelling techniques using Alloy DSL
  • Alloy Analyzer meets conceptual modelling
Assessment Elements

Assessment Elements

  • non-blocking Накопленная оценка
  • non-blocking Экзамен
Interim Assessment

Interim Assessment

  • 2022/2023 3rd module
    0.2 * Экзамен + 0.8 * Накопленная оценка
Bibliography

Bibliography

Recommended Core Bibliography

  • Nipkow, T., Grumberg, O., Hauptmann, B. (ed.). Software Safety and Security: Tools for Analysis and Verification. – IOS Press, 2012. – 400 pp.
  • Извлечение и структурирование знаний для экспертных систем, Гаврилова, Т. А., 1992
  • Инженерия знаний : модели и методы: учебник, Гаврилова, Т. А., 2016
  • Интеллектуальные технологии в менеджменте : Учеб. пособие, Гаврилова, Т.А., 2008
  • Логическое проектирование и верификация систем на SystemVerilog, Томас, Д., 2019

Recommended Additional Bibliography

  • Calvanese, D., Ghilardi, S., Gianola, A., Montali, M., & Rivkin, A. (2019). Formal Modeling and SMT-Based Parameterized Verification of Data-Aware BPMN (Extended Version). Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsarx&AN=edsarx.1906.07811
  • Verification of Sequential and Concurrent Programs. (2009). Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsnar&AN=edsnar.oai.cwi.nl.14569