Data service

The Research Data Management team (WG-RDM) supports you throughout the entire life cycle of (geo)data in agricultural landscape research, from project application, data generation and storage, initial use to long-term data archiving. In addition, we publish research data and make it not only citable, but also ensure that it meets modern FAIR principles for research data management. We support ZALF research through the internal provision of geospatial data.

If you are interested in RDM, please feel free to contact us. There are exciting opportunities to join our team.

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Title: Data Workshop at ZALF strengthens awareness for research data management
MehrLink: https://www.zalf.de/en/aktuelles/Pages/CDP/Datenworkshop-am-ZALF.aspx, More
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MyMeldungsdatum: 2025-11-05 10:00:00
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05.11.2025
Data Workshop at ZALF strengthens awareness for research data management
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Title: FAIRagro continues to grow. At the 2025 annual plenary, four new partners and successful interim results were presented.
MehrLink: https://www.zalf.de/en/aktuelles/Pages/Pressemitteilungen/FAIRagro-Jahrestreffen-2025.aspx, More
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MyMeldungsdatum: 2025-10-21 07:00:00
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21.10.2025
FAIRagro continues to grow. At the 2025 annual plenary, four new partners and successful interim results were presented.
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Data of the Month

Title: Maize Phenometrics
MehrLink: https://doi.org/10.4228/zalf-xmkx-3k66, View dataset
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MyTextfeld: <div class="ExternalClass5A6D49DA1D0242319444519ACFD06E1B"><p>Adjusted Vegetation Index) and retrieval methods (First-of-Slope, Median, Relative-Amplitude, and Seasonal-Amplitude), three maize phenometrics (SOS, POS, EOS) were derived from Sentinel-2 (S2) and Fused datasets (fusion of Sentinel-2 and PlanetScope data) for years 2021 and 2022. The pixel values refer to Day-of-Year (DOI) per phenological stage, clipped by fields and structured per test site and year. Note: This dataset consists of many rasterdata within a zipfile. Please start the download as csv and our server will compile a zip package.<br></p></div>
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Maize Phenometrics
Magdalena Main-Knorn, Claas Nendel, Laura Flores, Colja Krugmann, Leonardo Inforsato, Gohar Ghazaryan
Adjusted Vegetation Index) and retrieval methods (First-of-Slope, Median, Relative-Amplitude, and Seasonal-Amplitude), three maize phenometrics (SOS, POS, EOS) were derived from Sentinel-2 (S2) and Fused datasets (fusion of Sentinel-2 and PlanetScope data) for years 2021 and 2022. The pixel values refer to Day-of-Year (DOI) per phenological stage, clipped by fields and structured per test site and year. Note: This dataset consists of many rasterdata within a zipfile. Please start the download as csv and our server will compile a zip package.
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Multi-year crop yield data of silvoarable alley cropping ...

Multi-year crop yield data of silvoarable alley cropping (agroforesty) system in Brandenburg (DAKIS project)

This data collections contains yield data for different years and and the related coordinates for the project site DAKIS in Großmutz. Parallel to the agroforestry strips, the plot combine harvester drives a distance of around 5 m and then stops. The GNSS coordinates are determined using a GNSS device (the antenna of the GNSS device is marked with A in the figure) after stopping at the end position of the plot. The antenna is mounted above the cutting unit. The straw is collected on a straw scale and weighed, the grains are weighed, and the moisture content is determined. All data is stored in a continuous table. The plot length (marked C in the figure) is calculated from the distance to the previous point determined by GNSS. The plot width (marked B in the figure) corresponds to the working width of the harvester. After weighing, the straw is manually removed from the scale (recognizable in the picture as a haystack). For the next plot, the combine harvester now drives about 5m again and the process starts from the beginning. This table contains the index of all tables forming this data collection. Related datasets are listed in the metadata element 'Related Identifier'.

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silvoarable alley cropping (agroforesty)

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Data publication topics

All data in the repository are described with AGROVOC keywords. The Wordcloud shown here gives an overview of the subject areas for which you can find data (3064 keywords as a base).