Exploring sensor data for agricultural statistics: The fruit is not hanging as low as we thought

Article type: Research Article

Authors: Snijkers, Ger^{a; *} | Punt, Tim^b | De Broe, Sofie^c | Pérez, José Gómez^a

Affiliations: [a] Statistics Netherlands, Methodology Department, Heerlen, The Netherlands | [b] intern from Maastricht University at Statistics Netherlands; currently De Nederlandsche Bank (Dutch National Bank), Amsterdam, The Netherlands | [c] Statistics Netherlands, Methodology Department, Heerlen, Netherlands; currently Sciensano, Brussels, Belgium

Correspondence: [*] Corresponding author: Ger Snijkers, Statistics Netherlands, Methodology Department, P.O. Box 4481, 6401 CZ Heerlen, The Netherlands, Tel.: +31 45 570 6995, E-mail: [email protected]:TheviewsexpressedinthispaperarethoseoftheauthorsanddonotnecessarilyreflecttheofficialpolicyofStatisticsNetherlands.

Abstract: New business processes are increasingly data driven as sensors have become ubiquitous. Sensor data could be a valuable new data source for official statistics. To study this presumption Statistics Netherlands conducted a small-scale use case in the area of agricultural statistics in collaboration with an innovative farmer. A selection of his sensor data was explored for overlap with current data demands in surveys. The aim of the study was to obtain insights in the available agricultural data, their data structure and quality, and explore new methods of data collection for agricultural statistics. The conclusion is that these data are valuable for replacing or pre-filling (parts of) certain agricultural surveys. However, many more challenges surfaced than we expected, to which the title of this paper refers. These challenges will be discussed in this paper.

Keywords: Business data collection, official statistics, smart industry, precision farming, agriculture, data challenges

DOI: 10.3233/SJI-200728

Journal: Statistical Journal of the IAOS, vol. 37, no. 4, pp. 1301-1314, 2021