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4. AgriProKnow

AgriProKnow - Information Management in Precision Dairy Farming

Short 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.

Project partners

Bundesministerium für Verkehr, Innovation und Technologie

Vetmeduni Vienna

Josephinum Research

SmartBow GmbH

Institut für Stochastik, JKU

Wasserbauer GmbH

Project team

Michael Schrefl - Project Leader (DKE)

Christoph Schütz - Senior Researcher (DKE)

Arjol Qeleshi - Junior Researcher (DKE)

Simon Schausberger - Junior Researcher (DKE)

Roman Sumereder - Junior Researcher (DKE)

Ilko Kovacic - Junior Researcher (DKE)

Publications

S. Schausberger: The Semantic Data Warehouse for the AgriProKnow Project: A First Prototype (Master Thesis, 2016)

M. Wischenbart, D. Tomic, M. Iwersen, M. Schrefl, V. Sturm: agriProKnow – Prozessbezogenes Informationsmanagement in Precision Dairy Farming In: Proceedings der 13. Tagung Bau, Technik und Umwelt in der landwirtschaftlichen Nutztierhaltung (BTU-Tagung 2017), 18.-20.09.2017, Stuttgart, Deutschland, 2017.

S. Schausberger: The Semantic Data Warehouse for the AgriProKnow Project In: Proceedings des TDWI Award im Rahmen der Europäischen TDWI Konferenz von 26.-28.6.2017 in München, Link: http://www.sigs.de/tdwi/Verein/TDWI_Award_2017.pdf, 2017.

M. Wischenbart, S. Schausberger, C. Schütz, D. Tomic: Data Integration and Analysis in Precision Dairy Farming: A Semantic Data Warehousing Approach In: Proceedings of the International Workshop Linked Open Data in Agriculture (Conference Book of Abstracts), organisiert vom Deutschen Bundesministerium für Ernährung und Landwirtschaft, in Verbindung mit MACS G-20 (Agricultural Chief Scientists of G20 States), 27.-28.09.2017, Berlin, Deutschland, 2017.

C. Schütz, S. Schausberger, I. Kovacic, M. Schrefl: Semantic OLAP Patterns: Elements of Reusable Business Analytics In: Proceedings of the Confederated International Conferences On-the-Move 2017 (OTM 2017), October 23-27, 2017, Rhodes, Greece, Springer International Publishing, Lecture Notes in Computer Science (LNCS Vol. 10574), Print ISBN 978-3-319-69458-0, Online ISBN 978-3-319-69459-7, peer reviewed, pp. 318-336, 2017.

C. Schütz, S. Schausberger, M. Schrefl: Building an Active Semantic Data Warehouse for Precision Dairy Farming In: Journal of Organizational Computing and Electronic Commerce (JOCEC), Issue on Business Intelligence and Analytics Case Studies, Vol. 28, No. 2, Taylor & Francis, ISSN 1091-9392, Online ISSN 1532-7744, DOI: http://doi.org/10.1080/10919392.2018.1444344, pp. 122-141, 2018.

I. Kovacic, C. Schütz, S. Schausberger, R. Sumereder, M. Schrefl: Guided Query Composition with Semantic OLAP Patterns In: Proceedings of the 2nd International Workshop on Data Analytics Solutions for Real-Life Applications (DARLI-AP 2018), EDBT/ICDT 2018 Joint Conference, Vienna, Austria, March 26, 2018, CEUR Workshop Proceedings (Vol. 2083), URN: urn:nbn:de:0074-2083-1, Download PDF: http://ceur-ws.org/Vol-2083/paper-11.pdf, pp. 67-74, 2018.

M. Iwersen, L. Lidauer, A. Berger, W. Auer, D. Tomic, M. Schrefl, D. Efrosinin, V. Sturm, E. Gusterer, M. Drillich, M. Wischenbart: Das "AgriProKnow"-Projekt: Prozessbezogenes Informationsmanagement in Precision Dairy Farming In: Proceedings der 39. GIL-Jahrestagung, Wien, Österreich, 18.-19. Februar 2019, Jahrestagung der Gesellschaft für Informatik in der Land-, Forst- und Ernährungswirtschaft e.V., 2019.