Data Management in Agriculture
- Faculty
Faculty of Engineering and Computer Science
- Version
Version 1 of 26.02.2026.
- Module identifier
11B2148
- Module level
Bachelor
- Language of instruction
German
- ECTS credit points and grading
5.0
- Module frequency
only summer term
- Duration
1 semester
- Brief description
Within the agricultural domain, extensive data is collected, processed, and linked in highly distributed systems. Students of this module learn the theoretical foundations necessary to understand the management of this data and to be able to manage and utilize their own (operational) data. Practical exercises enable students to work with the underlying technologies.
- Teaching and learning outcomes
- Data and information
- Database management systems (relational, NOSQL)
- General data formats (temporal, geo-data, ... )
- Special data formats (e.g. ISOXML, ...)
- Data procurement/data sources
- Data sinks and documentation (agronomic reporting systems and interfaces)
- Networking of data: Producer/consumer (MQTT, “agrirouter”, ...), distributed data management, polyglot persistence
- Data description: metadata management, vocabularies (e.g. AgroVoc)
- Research data/open data
- Application examples
Translated with DeepL.com (free version)
- Overall workload
The total workload for the module is 150 hours (see also "ECTS credit points and grading").
- Teaching and learning methods
Lecturer based learning Workload hours Type of teaching Media implementation Concretization 30 Lecture Presence or online - 30 Laboratory activity Presence or online - 1 Examination Presence - Lecturer independent learning Workload hours Type of teaching Media implementation Concretization 29 Creation of examinations - 30 seminar paper - 30 Preparation/follow-up for course work -
- Graded examination
- Homework / Assignment
- Ungraded exam
- Field work / Experimental work and Regular participation
- Exam duration and scope
Graded examination:
Term paper: approx. 15 pages, accompanying presentation approx. 10 minutes
Ungraded examination:
Experimental work: Experiment: approx. 5 experiments in total
Regular attendance: Attendance of at least 80% of the course
- Recommended prior knowledge
The module requires solid programming knowledge, such as that taught in the Programming I (I) module. Students who have not taken this module can prepare themselves using suitable MOOCs or by studying literature with accompanying tasks. The teacher will provide support with appropriate material and advice.
- Knowledge Broadening
Students can name the main sub-areas of data management in agriculture and have a good overview of selected areas).
- Knowledge deepening
Students are able to propose adequate technical solutions for data management. They are able to carry out simple CRUD operations.
- Application and Transfer
Students of the module are able to transfer simple concepts to upstream and downstream processes (e.g. seed production, food processing, etc.) as appropriate to the situation.
- Communication and Cooperation
Students can critically reflect on, discuss and help shape data management plans in teams, with clients and IT service providers.
- Literature
Die Veranstaltung stützt sich diverse Literatur (insb. wiss. Veröffentlichungen). Um die Aktualität der Lehrveranstaltung zu gewährleisten, wird eine Literaturliste zu Beginn der jeweiligen Lehrveranstaltung ausgegeben.
BLE: Positionspapier "Datenmanagement in der Landwirtschaft" der Arbeitsgruppe "Datenmanagement" im Kompetenznetzwerk Digitalisierung in der Landwirtschaft, 2022
BLE: Gutachten zu Leitlinien und Regeln für Agrardaten in der EU, 2022
- Applicability in study programs
- Agricultural Technologies
- Agricultural Technologies B.Sc. (01.09.2025)
- Person responsible for the module
- Tapken, Heiko
- Teachers
- Tapken, Heiko