Faculty of Technical Sciences

University of Novi Sad

Subject: Selected Topics in Data Management (17.IMDR36)

Native organizations units: Department of Industrial Engineering and Engineering Management
 
Type of studies Title
Doctoral Academic Studies Environmental Engineering (Year: 1, Semester: Winter)
Doctoral Academic Studies Disaster Risk Management and Fire Safety (Year: 1, Semester: Summer)
Doctoral Academic Studies Occupational Safety Engineering (Year: 1, Semester: Winter)
Doctoral Academic Studies Industrial Engineering / Engineering Management (Year: 2, Semester: Winter)
Doctoral Academic Studies Information Systems Engineering (Year: 2, Semester: Winter)
General information:
 
Category Scientific-professional
Scientific or art field
  • Inženjerstvo informacionih sistema
  • Information-Communication Systems
ECTS 10

Course covers a wide range of topics and technologies in selected field of data management. Its main goal is to prepare students for independent research work. Data management development perspectives are considered. Students are prepared to recognize the need and significance of an interdisciplinary approach within research in the field of data management. They will master actual approaches and methods in research work oriented towards improvement of methods, techniques and tolls in the field of data management.

Understanding the contemporary topics in data management and acquiring knowledge and skills required for the use of advanced techniques for data management. Enabling students to critically analyze the adequacy of the application of existing methods, techniques and tools, to find the directions and ways of possible improvement of existing ones, or to develop, independently or in the team, new methods, techniques and tools in the research field of data management. Researching the literature, students are introduced to the latest knowledge in research field, to methods for solving similar or new problems and with scientific approaches in their solving in the field of data management in different application domains.

Unstructured and semi-structured data. Imprecise data. Data management at scale. Transactions management – current issues and trends. Uncertainty in data management. Combining general knowledge stored in databases with individual knowledge obtained from the crowd, capturing people habits and preferences. Machine learning and data management. Parallel computation models. Data-centric business processes and workflows. Formal analysis, verification, and synthesis of workflows, workflow management system design, and process mining and inter-operation. Ethical issues in data management. Knowledge representation, ontologies, and semantic Web. Classical database questions on new kinds of data. Data heterogeneity and data integration. Model-driven software engineering and data management. Domain specific languages and data management. Computer architecture & operating systems and data management. Theory-practice gap in data management.

Teaching activity depends on the number of listeners, i.e. mentor or group approach. During the course, students are required to prepare a project and its defense. The students and the teachers meet on a regular basis with the goal of training the student to conduct research and publish in the chosen area.

Authors Title Year Publisher Language
Whang K. Y., Bernstein P.A., Jensen C.S. The VLDB Journal; The International Journal on Very Large Data Bases 2009 Springer English
Stark, J. Product lifecycle management: 21st century paradigm for product realisation 2005 Springer-Verlag, London English
Malinowski E., Zimányi E. Advanced Data Warehouse Design; From Conventional to Spatial and Temporal Applications 2008 Springer English
Rick Sherman Business Intelligence Guidebook - From Data Integration to Analytics 2014 Morgan Kaufmann English
Kutsche R-D., Milanovic N. Model-Based Software and Data Integration; First International WS, MBSDI 2008, Berlin, Germany, April 2008 2008 Springer English
Elmasri R., Navathe S. B., Fundamentals of Database Systems, 7th Edition 2015 Addison Wesley English
Brambilla M., Cabot J., Wimmer M. Model-Driven Software Engineering in Practice 2012 Morgan & Claypool Publishers English
Mernik M. Formal and Practical Aspects of Domain-Specific Languages: Recent Developments 2012 Information Science Reference English
Elmagarmid A.K., Sheth A.P. Distributed and Parallel Databases; An International Journal 2009 Springer US English
Borgman, C. L. Big Data, Little Data, No Data: Scholarship in the Networked World 2015 Cambridge MA: MIT Press. English
Fowler M. Domain-Specific Languages 2010 Addison-Wesley Professional English
Chaudhri B. A., Rashid A., Zicari R. XML Data Management: Native XML and XML-Enabled Database Systems 2003 Addison-Wesley English
Kashyap V., Bussler C., Moran M. The Semantic Web; Semantics for Data and Services on the Web 2008 Springer English
Witten, I., Frank, E., Hall, M.A., Pal, J.C. Data Mining Practical Machine Learning Tools and Techniques 2017 Morgan Kaufmann, Amsterdam English
Sharda, R., Delen, D., Turban, E. Business Intelligence, Analytics and Data Science - A Managed Perspective 2017 Pearson, New York English
Course activity Pre-examination Obligations Number of points
Oral part of the exam No Yes 50.00
Project Yes Yes 50.00
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Prof. Ristić Sonja

Full Professor

Lectures
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Prof. Sladojević Srđan

Full Professor

Lectures
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Assoc. Prof. Mandić Vladimir

Associate Professor

Lectures
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Prof. Ristić Sonja

Full Professor

Study research work
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Assoc. Prof. Mandić Vladimir

Associate Professor

Study research work
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Prof. Sladojević Srđan

Full Professor

Study research work

Faculty of Technical Sciences

University of Novi Sad
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© 2024. Faculty of Technical Sciences.