Abstract
The multidimensional data models are most often used for decision support in Business Intelligence field. This paper presents innovative approach for support of knowledge analysis in precision agriculture, where such analytical approach offers great potential for the future. Corner stone of our approach is the creation of knowledge rules based on open data and information available from inside a particular agricultural company. In the next step such explicit knowledge is transformed into multidimensional database and an analytical model for decision support of the farm’s managers is designed. Our approach is demonstrated on example concerning knowledge analysis of one of the agricultural problems – infestation of farm plants by aphids.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Sauter, V.L.: Decision Support Systems for business intelligence. Wiley, New York (2014)
Fisher, D., Drucker, S., Czerwinski, M.: Business intelligence analytics. Comput. Graph. Appl. 34(5), 22–24 (2014)
Tyrychtr, J., Ulman, M., Vostrovský, V.: Evaluation of the state of the business intelligence among small czech farms. Agric. Econ. 61(2), 63–71 (2015)
Feigenbaum, E.A.: The art of artificial intelligence. 1. Themes and case studies of knowledge engineering, Stanford Univ CA Dept of Computer Science (1977)
Feigenbaum, E., Mccorduck, P.: The Fifth Generation: Artificial Intelligence and Japan’s Challenge to the World (1983)
Charvat, K., Esbri, M.A., Mayer, W., Campos, A., Palma, R., Krivanek, Z.: FOODIE—Open data for agriculture, In: IST-Africa Conference Proceedings (2014)
Lausch, A., Schmidt, A., Tischndorf, L.: Data mining and linked open data – New perspectives for data analysis in environmental research. Ecol. Model. 295, 5–17 (2015)
Piedra, N., Tovar, E., Colomo-Palacios, R., Lopez-Vargas, J., Chicaiza, J.A.: Consuming and producing linked open data: the case of OpenCourseWare. Program: Electron. Libr. Inf. Syst. 48(1), 16–40 (2014)
Rysová, H., Kubata, K., Tyrychtr, J., Ulman, M., Šmejkalová, M., Vostrovský, V.: Evaluation of electronic public services in agriculture in the Czech Republic. Acta Univ. Agriculturae et Silviculturae Mendelianae Brunensis 61(2), 437–479 (2013)
Fonkam, M.: On a Composite Formal-ism and Approach to Presenting the Knowledge Content of a Relational Database. In: Advances in Artificial Intelligence, pp. 274–284 (1995)
Hawryszkiewycz, I.: Knowledge Management: Organizing Knowledge Based Enter-prises, Palgrave Macmillan P (2009)
Vaníček, J., Vostrovský, V.: Knowledge acquisition from agricultural data-bases. Sci. Agriculturae Bohemica 39, 82–85 (2008)
Pankowski, T.: Using Da-ta-to-Knowledge exchange for transforming relational databases to knowledge bases. Rules on the Web Res. Appl. 7438, 256–263 (2012)
Abelló A., Romero, O.: On-Line Analytical Processing. In: Liu, L., Özsu, M.T. (eds.), pp. 1949–1954. Springer (2009)
Pedersen, T.: Cube. In: Liu, L., Özsu, M.T. (eds.) Dictionary of Gems and Gemology, pp. 538–539. Springer, US (2009a)
Vassiliadis, P., Sellis, T.: A survey of logical models for OLAP databases. ACM SIGMOD Rec. 28, 64–69 (1999)
Pedersen, T., Dimension, L.L., Özsu, M.T. (eds.) p. 836. Springer US (2009b)
Mendoza, M., Alegría, E., Maca, M., Cobos, C., León, E.: Multidimensional analysis model for a document warehouse that includes textual measures. Decis. Support Syst. 72, 44–59 (2015)
Datta, A., Thomas, H.: The cube data model: a conceptual model and algebra for on-line analytical processing in data warehouses. Decis. Support Syst. 27(3), 298–301 (1999)
Khan, A.: SAP and BW Data Warehousing: How to Plan and Implement, Khan Consulting and Publishing, LLC (2005)
Tyrychtr, J.: Provozní a analytické databáze, Praha: ČSVIZ (2015). http://www.csviz.cz/kniha-provozni-a-analyticke-databaze/
Pedersen, T.: Multidimensional Modeling. In: Liu, L., Özsu, M.T. (eds.) pp. 1777–1784. Springer US (2009)
Wu, M., Buchmann, A.: Research Issues in Data Warehousing, Ulm, Germany (1997)
Chaudhuri, S., Dayal, U.: An Overview of Data Warehousing and OLAP Technology, vol. 26, pp. 65–74 (1997)
Ballard, C., Herreman, D., Schauer, D., Bell, R., Kim, E., Valencic, A.: Data Modeling Techniques for Data Warehousing, l, IBM International Technical Support Organization (1998)
McGuff, F.: Designing the Perfect Data Warehouse (1998). http://members.aol.com/fmcguff/dwmodel/index.htm
Boehnlein, M., Ende, A.: Deriving initial data warehouse structures from the conceptual data models of the underlying operational information systems, Kansas City, USA (1999)
Abdelhédi, F., Zurfluh, G.: User Support System for Designing Decisional Database, Nice, France: IARIA (2013)
Levene, M., Loizou, G.: Why is the snowflake schema a good data warehouse design? Inf. Systems 28, 225–240 (2003)
Edwards, M.: Best practices in data warehousing award winners, Bus. Intell. J. 6(4) (2001)
Elbashir, M.Z., Collier, P.A., Davern, M.J.: Measuring the effects of business intelligence systems: the relationship between business process and organizational performance. Int. J. Account. Inf. Syst. 9(3), 135–153 (2008)
Popovič, A., Hackney, R., Coelho, P.S., Jaklič, J.: Towards business intelligence systems success: Effects of maturity and culture on. Decis. Support Syst. 54, 729–739 (2012)
Vostrovský, V., Tyrychtr, J., Ulman, M.: Knowledge support of information and communication technology in agricultural enterprises in the Czech Republic. Acta Univ. Agric. Silvic. Mendel. Brun. 63(1), 327–336 (2015)
Acknowledgments
The results and knowledge included herein have been obtained owing to support from the IGA of the Faculty of Economics and Management, Czech University of Life Sciences in Prague, grant No. 20141040, “New methods for support of managers in agriculture”.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Tyrychtr, J., Brožek, J., Vostrovský, V. (2015). Multidimensional Modelling from Open Data for Precision Agriculture. In: Barjis, J., Pergl, R., Babkin, E. (eds) Enterprise and Organizational Modeling and Simulation. EOMAS 2015. Lecture Notes in Business Information Processing, vol 231. Springer, Cham. https://doi.org/10.1007/978-3-319-24626-0_11
Download citation
DOI: https://doi.org/10.1007/978-3-319-24626-0_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-24625-3
Online ISBN: 978-3-319-24626-0
eBook Packages: Computer ScienceComputer Science (R0)