Data Management
| Code | Completion | Credits | Range | Language |
|---|---|---|---|---|
| 126DATM | Z,ZK | 4 | 2P+1C | Czech |
- Course guarantor:
- Marek Suchánek
- Lecturer:
- Jana Martínková, Marek Suchánek
- Tutor:
- Jana Martínková, Marek Suchánek
- Supervisor:
- Department of Construction Management and Economics
- Synopsis:
-
The course „Data Management“ provides an overview of the basic principles and practices of data management in the context of construction projects. This course will equip students with the necessary knowledge and skills to effectively collect, organize, analyze, and interpret data related to structural analysis, geotechnical investigation, and other construction activities. The course covers various data management techniques, including data acquisition, storage, integration, quality assurance, and visualization, while emphasizing the importance of data governance, security, and ethical aspects. Students will gain valuable insights into using data to make informed decisions, increase project efficiency, and improve overall data management.
- Requirements:
-
No previous requirements beyond usual computer work.
- Syllabus of lectures:
-
1) Data management life cycle.
2) Data collection techniques and use of existing data sources.
3) Data formats, working with files and data flows.
4) Principles of data storage, selection of suitable storage and their options.
5) Ensuring data quality and integrity.
6) Design of data and metadata structure using standards and ontologies.
7) Technical modeling of data and metadata, creation of models using OntoUML.
8) Data integration and interoperability.
9) Data visualization and reporting.
10) Basics of big data analysis and use of ML/AI.
11) Security, confidentiality and ethics of data.
12) Data governance and data sharing.
13) Publishing, archiving and data reuse.
- Syllabus of tutorials:
-
1) Data management life cycle.
2) Data collection techniques and use of existing data sources.
3) Data formats, working with files and data flows.
4) Principles of data storage, selection of suitable storage and their options.
5) Ensuring data quality and integrity.
6) Design of data and metadata structure using standards and ontologies.
7) Technical modeling of data and metadata, creation of models using OntoUML.
8) Data integration and interoperability.
9) Data visualization and reporting.
10) Basics of big data analysis and use of ML/AI.
11) Security, confidentiality and ethics of data.
12) Data governance and data sharing.
13) Publishing, archiving and data reuse.
- Study Objective:
-
Upon completion of the course, students will be able to:
- Understand the principles and stages of the data management life cycle in construction projects.
- Collect, organize, and store data effectively using appropriate methods, formats, and tools.
- Design and model data and metadata structures following established standards and ontologies.
- Ensure data quality, integrity, and interoperability across various systems and sources.
- Apply techniques for data visualization, reporting, and analysis to support informed decision-making.
- Recognize and implement data governance, security, confidentiality, and ethical practices.
- Utilize modern technologies such as big data, machine learning, and AI for advanced data analysis.
- Promote efficient data sharing, publication, and long-term reuse within the construction domain.
- Study materials:
-
The primary source of information is the presentations and materials provided through Moodle.
Further reading:
Data Stewardship: An Actionable Guide to Effective Data Management and Data Governance, David Plotkin, 2020, Elsevier Science, 978-01-28221-67-9
https://aleph.cvut.cz/F?func=direct&doc_number=000823784&local_base=DUPL&format=999 (online)
Gils, Bas van. Data Management: A Gentle Introduction, Van Haren Publishing, 2020. ProQuest Ebook Central, https://ebookcentral.proquest.com/lib/cvut/detail.action?docID=6191450
Mahanti, Rupa. Data Governance and Data Management: Contextualizing Data Governance Drivers, Technologies, and Tools, Springer, 2021. ProQuest Ebook Central,
https://ebookcentral.proquest.com/lib/cvut/detail.action?docID=6723145
Big Data: Storage, Sharing, and Security. Editor Fei HU. Boca Raton: CRC Press, [2016]. ISBN 978-1-4987-3486-8. https://aleph.cvut.cz/F?func=direct&doc_number=000785926&local_base=DUPL&format=999
Domdouzis, Konstantinos. Concise Guide to Databases A Practical Introduction. Springer International Publishing AG. ISBN: 978-3-030-42223-3.
- Note:
- Time-table for winter semester 2025/2026:
-
06:00–08:0008:00–10:0010:00–12:0012:00–14:0014:00–16:0016:00–18:0018:00–20:0020:00–22:0022:00–24:00
Mon Tue Wed Thu Fri - Time-table for summer semester 2025/2026:
- Time-table is not available yet
- The course is a part of the following study plans:
-
- Digitalizace ve stavebnictví - prezenční forma studia (compulsory course in the program)