Subject: Selected Topics in Data Management (17.IMDR36 )
Native organizations units: Department of Industrial Engineering and Engineering Management
Study programmes of the course:
| Type of studies | Title |
|---|---|
| Doctoral Academic Studies | Information Systems Engineering (Godina: 2, Winter) |
| Doctoral Academic Studies | Disaster Risk Management and Fire Safety (Godina: 1, Summer) |
| Doctoral Academic Studies | Environmental Engineering (Godina: 1, Winter) |
| Doctoral Academic Studies | Industrial Engineering / Engineering Management (Godina: 2, Winter) |
| Doctoral Academic Studies | Disaster Risk Management and Fire Safety (Godina: 1, Summer) |
| Doctoral Academic Studies | Occupational Safety Engineering (Godina: 1, Winter) |
| Doctoral Academic Studies | Industrial Engineering / Engineering Management (Godina: 2, Winter) |
| Doctoral Academic Studies | Information Systems Engineering (Godina: 2, Winter) |
Educational goal:
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.
Educational outcome:
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.
Course content:
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 methods:
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.
Literature:
| Authors | Title | Year | Publisher | Language |
|---|---|---|---|---|
| 2003 | English | |||
| 2008 | English | |||
| 2015 | English | |||
| 2014 | English | |||
| 2008 | English | |||
| 2005 | English | |||
| 2008 | English | |||
| 2009 | English | |||
| 2012 | English | |||
| 2009 | English | |||
| 2012 | English | |||
| 2015 | English | |||
| 2017 | English | |||
| 2017 | English | |||
| 2010 | English |
Knowledge evaluation:
| Course activity | Pre-examination | Obligations | Number of points |
|---|---|---|---|
| Oral part of the exam | No | Yes | 50.00 |
| Project | Yes | Yes | 50.00 |
Lecturers:
prof. dr Sladojević Srđan
Full Professor
Study research work
vanr. prof. dr Mandić Vladimir
Associate Professor
Lectures
vanr. prof. dr Mandić Vladimir
Associate Professor
Study research work
prof. dr Ristić Sonja
Full Professor
Lectures
prof. dr Sladojević Srđan
Full Professor
Lectures
prof. dr Ristić Sonja
Full Professor
Study research work
Faculty of Technical Sciences
© 2024. Faculty of Technical Sciences.
Contact:
Address: Trg Dositeja Obradovića 6, 21102 Novi Sad
© 2024. Faculty of Technical Sciences.