101 to 110 of 24,494 Results
Markdown Text - 751 B - SHA-256: c85b6e8b54470bfe1be4612a133571641fbfcec4612efac5952679667a84bc2b
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Loup, Ulrich; Küpper, Werner; Lorenz, Christof; Gasche, Rainer; Kunkel, Ralf; Gründling, Ralf; Groh, Jannis; Brinckmann, Nils; Buberger, Jan; Hanisch, Marc; Kuhnert, Tobias; Moorthy, Rubankumar; Obersteiner, Florian; Schäfer, David; Schnicke, Thomas, 2026, "Evolving Scientific Software in Long-Running Observatories: Lessons from the TERENO Sensor Management Migration", https://doi.org/10.26165/JUELICH-DATA/GRXBJX, Jülich DATA, V1
Scientific software in the geosciences often evolves organically, growing from small, purpose-built tools into long-lived infrastructure. Using the example of the TERENO observatories and their integration into the Earth & Environment DataHub, this contribution reflects on the ch... |
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May 2, 2026 -
Evolving Scientific Software in Long-Running Observatories: Lessons from the TERENO Sensor Management Migration
Adobe PDF - 820.3 KB - SHA-256: 26afc9e762c03e5bc384bb0c698dedeb1dc8dce686ff9814414b025b794499e5
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Apr 28, 2026 - Institute of Bio- and Geosciences – Plant Sciences (IBG-2)
Kerstin A. Nagel; Laura V. Junker-Frohn; Shivan Jia; Fabio Fiorani, 2026, "Root and shoot dataset of 23 parental lines of a DRR barley population and Barke as reference phenotyped using the high throughput phenotyping platform GrowScreen-Rhizo 3", https://doi.org/10.26165/JUELICH-DATA/BPSWGG, Jülich DATA, V1
The dataset contains phenotypic data of 24 barley (Hordeum vulgare L.) genotypes, 23 parents of a nested association mapping population plus Barke as reference genotype. The plants were phenotyped over the course of three weeks under greenhouse conditions using the automated high... |
MS Excel Spreadsheet - 1.6 MB - SHA-256: 61c8f27d72a37c32b77a0ab1bb24608a81300c980964290f1582a172b157cea4
The files includes the phenotypic data, environmental data and metadata. |
Apr 27, 2026 - Institute of Climate and Energy Systems – Troposphere (ICE-3)
Gkatzelis, Georgios; Wu, Yizhen; Tillmann, Ralf; Pfannerstill, Eva; Khare, Peeyush; Marcillo, Andrea; Grasse, Achim; Rohrer, Franz; Depp, Clémence; Roska, Milan; Adam, Max; Albertin, Sarah; Asgher, Rabbia; Bannan, Thomas; Barua, Shawon; Bates, Kelvin; Bell, David; Bohn, Birger; Buchholz, Angela; Chen, Yanfang; Coe, Hugh; Coggon, Matthew; Färber, Michelle; Farhoudian, Sana; Fry, Juliane; Fuchs, Hendrik; Graus, Martin; El Haddad, Imad; He, Quanfu; Hohaus, Thorsten; Iyer, Siddharth; Kumar, Avinash; Leiminger, Markus; Liu, Lu; Matthews, Emily; McFiggans, Gordon; Middlebrook, Ann; Müller, Markus; Nissinen, Aki; Novelli, Anna; Nursanto, Farhan; Perrier, Sebastien; Prévôt, André; Pullinen, Iida; Pusfitasari, Eka Dian; Reinecke, Tobias; Rissanen, Matti; Riva, Matthieu; Schobesberger, Siegfried; Stockwell, Chelsea; Top, Jens; Vinkvist, Netta; Voliotis, Aristeidis; Wahner, Andreas; Wang, Yuantao; Wang, Yuwei; Wegener, Robert; Yang, Boxing; Nölscher, Anke, 2026, "SAPHIR CHANEL 2024 Campaign", https://doi.org/10.26165/JUELICH-DATA/SYIRWS, Jülich DATA, V1
This dataset contains gas-phase and aerosol measurements collected during the CHANEL (Household Chemicals Amplifying Urban Aerosol Pollution) campaign, conducted at the SAPHIR (Simulation of Atmospheric PHotochemistry In a large Reaction Chamber) outdoor atmospheric simulation ch... |
Apr 27, 2026 -
SAPHIR CHANEL 2024 Campaign
Network Common Data Form - 66.0 KB - SHA-256: bd42a1bfcc2ad162b421f66486ee3d5a83cd9bbd4f0ebf3568f19b722af3f7d3
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Apr 27, 2026 -
SAPHIR CHANEL 2024 Campaign
Network Common Data Form - 160.7 KB - SHA-256: 1c9847845185b504b1ce1b1804fefb282327d03ee3d3f59f32b44d8f14d977a2
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Apr 27, 2026 -
SAPHIR CHANEL 2024 Campaign
Network Common Data Form - 70.8 KB - SHA-256: 9b9ee916dcd31e4b1d5f3653b902b2d38138395d98fa16c548388e778d556b3f
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Apr 27, 2026 -
SAPHIR CHANEL 2024 Campaign
Network Common Data Form - 50.7 KB - SHA-256: abd9fc28f4bf66beea9c2573960455ca61fbe43b44227514b2cacce8c7f4dde2
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