Project Details
Description
The agriProKnow project develops a novel methodology for process related Information management, which aims at significantly improving the milk production efficiency in precision dairy farming. In a particularly complex cyber-physical production system that combines people, animals and technology, the focus is on animal health and welfare modelling, monitoring, and control, as they play the crucial roles in the production process. The focus of innovation is a procedure for process knowledge generation, which combines methods of stochastic analysis of sensor data, and semantic situation modeling and semantic datawarehousing. Furthermore, the use of semantic Web service technology enables creation of an open system that helps different actors in the value chain, to contribute to, and access the new process knowledge which is continuously created and integrated. The system and the procedure will be implemented and verified using real data from several experimental farms.
| Status | Finished |
|---|---|
| Effective start/end date | 01.11.2015 → 31.01.2018 |
Collaborative partners
- Johannes Kepler University Linz (lead)
- Josephinum Research (Project partner)
- Institut für Stochastik (Project partner)
- Veterinärmedizinische Universität Wien (Project partner)
- Wasserbauer GmbH (Project partner)
- Bundesministerium für Verkehr, Innovation und Technologie (Project partner)
- Smartbow GmbH (Project partner)
Fields of science
- 102028 Knowledge engineering
- 102016 IT security
- 102027 Web engineering
- 502050 Business informatics
- 503008 E-learning
- 102 Computer Sciences
- 102030 Semantic technologies
- 102010 Database systems
- 102015 Information systems
- 102025 Distributed systems
- 101019 Stochastics
- 101018 Statistics
- 101014 Numerical mathematics
- 102035 Data science
- 502058 Digital transformation
- 509026 Digitalisation research
- 102033 Data mining
- 101 Mathematics
- 101024 Probability theory
JKU Focus areas
- Digital Transformation
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Das "AgriProKnow"-Projekt: Prozessbezogenes Informationsmanagement in Precision Dairy Farming
Iwersen, M., Lidauer, L., Berger, A., Tomic, D., Schrefl, M., Efrosinin, D., Sturm, V., Gusterer, E., Drillich, M. & Wischenbart, M., Feb 2019, Proceedings der 39. GIL-Jahrestagung, Wien, Österreich, 18.-19. Februar 2019, Jahrestagung der Gesellschaft für Informatik in der Land-, Forst- und Ernährungswirtschaft e.V.. 6 p.Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review
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Building an Active Semantic Data Warehouse for Precision Dairy Farming
Schütz, C. G., Schausberger, S. & Schrefl, M., 03 Apr 2018, In: Journal of Organizational Computing and Electronic Commerce. 28, 2, p. 122-141 20 p.Research output: Contribution to journal › Article › peer-review
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Guided Query Composition with Semantic OLAP Patterns
Kovacic, I., Schütz, C. G., Schausberger, S., Sumereder, R. & Schrefl, M., 2018, Proceedings of the 2nd International Workshop on Data Analytics Solutions for Real-Life Applications (DARLI-AP 2018), EDBT/ICDT 2018 Joint Conference. http://ceur-ws.org/Vol-2083/paper-11.pdf: CEUR Digital, Vol. 2083. p. 67-74 8 p. (CEUR Workshop Proceedings).Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review
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Guided Query Composition with Semantic OLAP Patterns
Kovacic, I. (Speaker)
26 Mar 2018Activity: Talk or presentation › Contributed talk › science-to-science
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Exemplary analyses through use of a semantic data warehouse
Schausberger, S. (Speaker)
27 Nov 2017Activity: Talk or presentation › Other talk or presentation › science-to-public
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Semantic OLAP Patterns: Elements of Reusable Business Analytics
Kovacic, I. (Speaker) & Schausberger, S. (Speaker)
25 Oct 2017Activity: Talk or presentation › Contributed talk › science-to-science