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2,348 results for “germany”
Surgical Treatment of Pelvis in Fragility Fracture in Germany: a Prospective, National, Multicenter, Observational, Comparative Cohort Study Comparing Isolated Posterior Versus Combined Anterior-poste
ClinicalTrials.gov study NCT06550934. IPD Sharing: NO. Countries: 0. Publications: 0.
The Effectiveness of Nivolumab Monotherapy as First-Line Therapy in Adults With Advanced Melanoma in Germany
ClinicalTrials.gov study NCT03205722. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Microsatellite genotypes of Aedes japonicus collected in Belgium and Germany
Open the record for dataset details and reuse information.
FIGURE 7 in On the distribution and ecology of Culiseta (Culicella) ochroptera (Peus) (Diptera: Culicidae) in Germany
FIGURE 7. Adult female of the blackish variant of the dark form of Culiseta ochroptera.
FIGURE 6 in On the distribution and ecology of Culiseta (Culicella) ochroptera (Peus) (Diptera: Culicidae) in Germany
FIGURE 6. Adult female of the normal form of Culiseta ochroptera.
Conspiracy Theories in Germany
<p>This dataset contains the results for Germany of the cross-national survey "Conspiracy Theories" commissioned by the Conspiracy and Democracy Project (CRASSH, University of Cambridge) to YouGov and fielded in nine countries: Britain, France, Germany, Hungary, Italy, Poland, Portugal, Sweden, US.</p>
Geo-locations and System Data of Renewable Energy Installations in Germany
<h2>Content</h2> <p>The <strong>dataset contains </strong>geolocation and system data on <strong>renewable energy installations in Germany</strong>. It is provided as <strong>GeoPackage (.gpkg) files </strong>with point geometries for onshore and offshore wind turbines, ground-mounted photovoltaic systems, bioenergy systems and their associated combined heat and power plants, hydropower plants, renewable gas production sites, and energy storage systems. In addition, it includes a file with polygon geometries for photovoltaic field systems and the same data in <strong>CSV format</strong>.</p> <p>The dataset is a <strong>site-verified extract</strong> from the <a href="https://www.marktstammdatenregister.de/MaStR/Datendownload" target="_blank" rel="noopener"><strong>Marktstammdatenregister</strong> </a>(Core Energy Market Data Register, <strong>MaStR</strong>) maintained by the Bundesnetzagentur (Federal Network Agency, BNetzA) as of <strong>January 1, 2025</strong>. System-relevant information was further checked for plausibility and, where necessary, corrected through individual research.</p> <p>The <strong>data processing steps</strong> are documented in the <strong>Git repository</strong>:<strong> <a href="https://git.ufz.de/manske/regeoloc" target="_blank" rel="noopener">https://git.ufz.de/manske/regeoloc</a></strong>.</p> <p>A <strong>detailed description</strong> of the processing <strong>workflow </strong>is provided in the related article: <strong><a href="https://doi.org/10.3390/data7090128" target="_blank" rel="noopener">https://doi.org/10.3390/data7090128</a></strong>.<strong> </strong>The article outlines the guiding principles, while the methodology is continuously being refined.</p> <h2>Metrics</h2> <p>The table presents a executive summary of the compiled dataset compared to the MaStR data extract at the specified cut-off date.</p> <table> <tbody> <tr> <td><strong>Dataset (V20250101)</strong></td> <td><strong>n records</strong></td> <td><strong>sum capacity</strong></td> <td><strong>n location corrected*</strong></td> <td><strong>Records not included from MaStR extract**</strong><br><strong>(n records / sum capacity)</strong></td> </tr> <tr> <td>Bioenergy</td> <td>23,012</td> <td>9144 MW</td> <td>11,377</td> <td>4 / 0.1</td> </tr> <tr> <td>Cogeneration_Units</td> <td>13,110</td> <td>29,992 MW</td> <td>not applicable</td> <td>not applicable</td> </tr> <tr> <td>Energy_Storage</td> <td>912</td> <td>11,864 MW</td> <td>134</td> <td>0 / 0</td> </tr> <tr> <td>Gas_Production</td> <td>274</td> <td>85,956 MWh / h</td> <td>22</td> <td>54 / not applicable</td> </tr> <tr> <td>Hydropower</td> <td>8686</td> <td>5405 MW</td> <td>2078</td> <td>4 / 0.3</td> </tr> <tr> <td>Solar_Energy_Polygons</td> <td>9770</td> <td>35,056 ha</td> <td>not applicable</td> <td>not applicable</td> </tr> <tr> <td>Solar_Energy</td> <td>12,237</td> <td>27,158 MW</td> <td>11,594</td> <td>54855 / 1067</td> </tr> <tr> <td>Wind_Energy</td> <td>32,317</td> <td>74,793 MW</td> <td>4132</td> <td>1054 / 55</td> </tr> </tbody> </table> <p>*Number of records whose location was adjusted by at least 10 meters.<br>**There are several reasons why certain records were not included. In most cases, they could not be assigned to a specific location due to incorrect or incomplete location information in MaStR.</p> <h2>Version History</h2> <table style="width: 100.059%; height: 141.067px;"> <tbody> <tr style="height: 17.6333px;"> <td style="width: 9.54374%; height: 17.6333px; text-align: left;"><strong>Version</strong></td> <td style="width: 11.4269%; text-align: left;"><strong>Cut-off Date</strong></td> <td style="width: 78.9876%; height: 17.6333px; text-align: left;"><strong>Documentation / Executive Summary </strong></td> </tr> <tr style="height: 35.2667px;"> <td style="width: 9.54374%; height: 35.2667px; text-align: left;"><a href="https://doi.org/10.5281/zenodo.16942382">V20250101</a></td> <td style="width: 11.4269%; text-align: left;">2025/01/01</td> <td style="width: 78.9876%; height: 35.2667px; text-align: left;">- Photovoltaic installations in MaStR previously classified as 'Building (Others)' have been reclassified as 'Ground-mounted' where applicable for solar energy systems.<br>- Category 'Big parking lot' has been introduced for solar energy systems.<br>- Additional locations for hydro power plants have been identified.<br>- All wind turbine locations were re-examined.</td> </tr> <tr style="height: 35.2667px;"> <td style="width: 9.54374%; height: 35.2667px; text-align: left;"><a href="https://doi.org/10.5281/zenodo.14627853">V20240204</a></td> <td style="width: 11.4269%; text-align: left;">2024/01/04</td> <td style="width: 78.9876%; height: 35.2667px; text-align: left;">- Category 'Agrivoltaics' has been introduced for solar energy systems.<br>- Related cogeneration units have been additionally added to bioenergy systems.<br>- Energy storage systems have been added to the dataset.<br>- Gas production sites have been added to the dataset.</td> </tr> <tr style="height: 35.2667px;"> <td style="width: 9.54374%; height: 35.2667px; text-align: left;"><a href="https://doi.org/10.5281/zenodo.8188601">V20230420</a></td> <td style="width: 11.4269%; text-align: left;">2023/04/20</td> <td style="width: 78.9876%; height: 35.2667px; text-align: left;">- Category 'Floating-mounted' has been introduced for solar energy systems.</td> </tr> <tr style="height: 17.6333px;"> <td style="width: 9.54374%; height: 17.6333px; text-align: left;"><a href="https://doi.org/10.5281/zenodo.6922043">V20210507</a></td> <td style="width: 11.4269%; text-align: left;">2021/05/07</td> <td style="width: 78.9876%; height: 17.6333px; text-align: left;">- Detailed documentation can be found in the related article: <a href="https://doi.org/10.3390/data7090128" target="_blank" rel="noopener">https://doi.org/10.3390/data7090128</a></td> </tr> </tbody> </table> <p> </p>
FIGURE 6 in Review of the rove beetles (Coleoptera: Staphylinidae) from the Pliocene of Willershausen, Germany
FIGURE 6. Tachinus sp. (GZG.W.18932 (30132)). Scale bar = 1 mm.
Wedding photos, near Frankfurt M., Germany (VIW_08_GE_170922)
<p>Husband I 1978* works as stockbroker with bitcoins</p> <p>Husband II 1960*(?) furniture salesman for high quality products</p> <p>wedding 2020 In Frankfurt/M</p> <p>No religious ceremony and no religious affiliation was mentioned</p> <p>Wedding album</p>
ELDIAdata: Interview data – Estonian in Germany
<p>This digital archive contains interview data with the Estonian minority speakers in Germany. The archive consists of audio files (available in .wav format) containing individual and focus group interviews with the speakers of four different age groups. All interview files were named using a special coding system. Each file name includes: a) a country where the research was conducted; b) the speech community studied; c) the form of an interview; d) the type of the target group; e) the age group and gender; f) the date of the interview (DDMMYEAR). For the full list of files, as well as code values please refer to the descriptions under “ELDIAdata: Metadata”.</p>
Quadrant plant diversity Germany 2021
<p>Plant records, list of plants, flowers and heterogeneity in 5-10 quadrants in plots from the Biodiversity Exploratories in Germany 2021</p>
Simulation files - Reconstructing relative transmission rates in Bayesian phylodynamics: Two-fold transmission advantage of Omicron in Berlin, Germany during December 2021
<p>Simulation XML files and log files for scenarios 1–10. </p> <p>Ariane Weber, Sanni Översti, Denise Kühnert</p> <p>"Reconstructing relative transmission rates in Bayesian phylodynamics: Two-fold transmission advantage of Omicron in Berlin, Germany during December 2021" </p> <p><em>Virus Evolution</em>, Volume 9, Issue 2, 2023, vead070, https://doi.org/10.1093/ve/vead070 </p>
Potential Wild Bee Habitat in the City of Frankfurt am Main (Germany)
<p>The raster dataset shows the spatial distribution of potential habitat of wild bees which is derived from land use and land cover data (CORINE land cover data). The methodological approach was adopted from Zulian et al. (2013) ( see section “related resources”) who estimated different CLC classes regarding their provision of potential nesting sites and floral resources via expert evaluation. Furthermore, the connectivity of the nesting and floral habitat is considered in the model assuming an average flight distance of</p> <p>200 m which represents small solitary wild bees (moving window approach).</p> <p> </p> <p>The approach of Zulian et al. (2013) was transferred to high resolution German database, which encompasses both the German land cover model 2015 (LBM-DE, version 1, release year 2018) and the official topographic-cartographic information system (AKTIS Basic-DLM) of the Federal Agency of Cartography and Geodesy of Germany (BKG).</p> <p> </p> <p><u>Content/structure of the dataset:</u></p> <p>The raster values include 2 decimal values from 0 to 1, while 0 refers to no available wild bee habitat and 1 equals the best habitat conditions for wild bees.</p> <p> </p> <p><u>Restrictions</u>: the approach has been developed for national scale analyses, for the purpose of local and regional analysis, higher resolution data should be included; inaccuracies in the distinction between intensive and extensive grassland; urban areas probably systematically underestimated due to insufficient information of urban vegetation in the basis data; the dataset has not been validated against wild bee sampling data</p> <p> </p> <p><u>Resolution:</u> 5 x 5 m</p> <p><u>Format</u>: TIFF</p> <p><u>Coordinate System</u>: EPSG: 3035 (ETRS89, LAEA)</p> <p><u>Reference year</u>: 2015</p> <p><u>Coverage</u>: Germany</p> <p>More details in literature listed under “related resources”</p> <p> </p> <p>Funding reference</p> <p>German Federal Agency of Nature Conservation (BfN), project number:</p> <p>FKZ 3518 81 0400</p> <p>___________________________________________________________________________________________________________________________________</p> <p> </p> <p>Der Rasterdatensatz zeigt die räumliche Bewertung von Landschaftsstrukturen (CORINE land cover-Klassen, CLC) hinsichtlich ihrer Eignung als potentielle Nist- und Nahrungshabitat für Wildbienen. Das potenzielle Wildbienenhabitat basiert auf dem Verfahren von Zulian et al. (2013) (siehe Abschnitt „related resources“), in dem CLC-Klassen potenzielle Vorkommen von Nist- und Blühhabitaten über eine Expertenschätzung zugewiesen wurden. Zusätzlich wurde die Konnektivität von Blüten- und Nisthabitaten über ein Moving-Window-Verfahren ermittelt, wobei von kleinen Solitärbienen mit einem durchschnittlichen Aktionsradius von 200 m ausgegangen wurde.</p> <p> Das Verfahren von Zulian et al. (2013) wurde auf hochaufgelöste deutschlandweiten Daten angewandt, bestehend aus dem Landbedeckungsmodell 2015 (LBM-DE, Version 1, Veröffentlichungsjahr: 2018) und dem amtliche topographisch-kartographische Informationssystem (ATKIS-Basis-DLM) vom Bundesamt für Kartographie und Geodäsie (BKG).</p> <p> </p> <p><u>Inhalt/Struktur des Datensatzes</u>: Im Rasterdatensatz sind 2-stellige Dezimalwerte von 0 bis 1 enthalten, wobei die 0 bedeutet, dass dort potenziell keine Wildbienenhabitate vorhanden sind, und die 1 die potentiell besten Habitatvoraussetzungen für Wildbienen wiederspiegelt.</p> <p> </p> <p><u>Einschränkungen</u>: der Datensatz und das Verfahren dient der Erfassung auf Bundesebene, für lokale oder regionale Aussagen müssten noch höher aufgelöste Daten mit hinzugezogen werden; zudem existieren Ungenauigkeiten bei der Unterscheidung von intensivem und extensivem Grünland; im Bereich der Städte werden die Werte vermutlich systematisch unterschätzt, da in den Ausgangsdaten das Stadtgrün nicht vollständig erfasst wurde; es wurde keine Validierung über Wildbienenerfassungen vorgenommen</p> <p> </p> <p><u>Auflösung</u>: 5 x 5 m</p> <p><u>Format</u>: TIFF</p> <p><u>Koordinatensystem</u>: EPSG: 3035 (ETRS89, LAEA)</p> <p><u>Referenzjahr</u>: 2015</p> <p><u>Räumliche Abdeckung</u>: Deutschland</p> <p>Weitere Information in der Literatur unter Abschnitt „related resources“.</p> <p> </p> <p>Förderung</p> <p>German Federal Agency of Nature Conservation (BfN), Projekt Nummer: FKZ 3518 81 0400</p> <p> </p>
Fig. 1 in The First Aleocharine Rove Beetle Fossil from Mid-Eocene Bitterfeld Amber of Germany (Coleoptera: Staphylinidae: Aleocharinae: Hypocyphtini)
Fig. 1. Cypha sp. in Bitterfeld amber. A) Dorsal habitus, B) Ventral habitus. Scale bars = 0.5 mm.
ERT data collected in the Kammstollen tunnel (Zugspitze, Germany) from 2007 to 2023. Raw and inverted values with relative scripts.
<p>This collection includes the raw and inverted ERT data collected in the Kamstollen Tunnel at the Zugspitze from 2007 to 2023.<br>It also includes the Matlab scripts for preparing the data and visualizing the results, as well as the CRTomo inversion code (Kemna, 2000).<br><br>Instructions are included in the file <em>how-to.docx</em>. Site and methods are presented in Krautblatter et al. (2010). Further analysis of this data is presented in Scandroglio et al. (in prep.).</p> <p>Data collectors:<br>- different students from 2007 to 2018 (refer to the Chair of Landslide Research, Technical University of Munich)<br>- Riccardo Scandroglio from 2018 to 2023.<br>Documentation and Matlab codes by Riccardo Scandroglio<br>Contact: <a href="mailto:johannes.leinauer@tum.de">r.scandroglio@tum.de</a></p> <p>This study was supported by the AlpSenseRely project, funded by the Bavarian State Ministry of the Environment and Consumer Protection (TUS01UFS-76976), and by the Hydro-PF project, funded by the TUM International Graduate School of Science and Technology IGSSE (Team 12.9). </p> <p>References: <br>- Kemna, A. (2000). <em>Tomographic inversion of complex resistivity: Theory and application</em>. Der Andere Verlag.<br>- Krautblatter, M., Verleysdonk, S., Flores‐Orozco, A., & Kemna, A. (2010). Temperature‐calibrated imaging of seasonal changes in permafrost rock walls by quantitative electrical resistivity tomography (Zugspitze, German/Austrian Alps). <em>Journal of Geophysical Research: Earth Surface</em>, <em>115</em>(F2).</p>
LoGov Germany Interview Report n°8
<p>The interviews have been realised in the framework of the H2020-MSCA-RISE-2018 project “LoGov - Local Government and the Changing Urban-Rural Interplay” as part of the implementation phase of the project. The interviews have been conducted with experts in the field of public administration, public law and political science, both researchers and practitioners, with the aim of widening the scope of the Country Report on Germany.</p> <p>To access the other interview reports on Germany, and to receive more information about the project, please visit: <a href="https://www.logov-rise.eu/">https://www.logov-rise.eu/</a>. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 823961.</p>
LoGov Germany Interview Report n°9
<p>The interviews have been realised in the framework of the H2020-MSCA-RISE-2018 project “LoGov - Local Government and the Changing Urban-Rural Interplay” as part of the implementation phase of the project. The interviews have been conducted with experts in the field of public administration, public law and political science, both researchers and practitioners, with the aim of widening the scope of the Country Report on Germany. To access the other interview reports on Germany, and to receive more information about the project, please visit: <a href="https://www.logov-rise.eu/">https://www.logov-rise.eu/</a>. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 823961.</p>
LoGov Germany Interview Report n°7
<p>The interviews have been realised in the framework of the H2020-MSCA-RISE-2018 project “LoGov - Local Government and the Changing Urban-Rural Interplay” as part of the implementation phase of the project. The interviews have been conducted with experts in the field of public administration, public law and political science, both researchers and practitioners, with the aim of widening the scope of the Country Report on Germany.</p> <p>To access the other interview reports on Germany, and to receive more information about the project, please visit: <a href="https://www.logov-rise.eu/">https://www.logov-rise.eu/</a>. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 823961.</p>
LoGov Germany Interview Report n°6
<p>The interviews have been realised in the framework of the H2020-MSCA-RISE-2018 project “LoGov - Local Government and the Changing Urban-Rural Interplay” as part of the implementation phase of the project. The interviews have been conducted with experts in the field of public administration, public law and political science, both researchers and practitioners, with the aim of widening the scope of the Country Report on Germany.</p> <p>To access the other interview reports on Germany, and to receive more information about the project, please visit: <a href="https://www.logov-rise.eu/">https://www.logov-rise.eu/</a>. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 823961.</p>
LoGov Germany Interview Report n°5
<p>The interviews have been realised in the framework of the H2020-MSCA-RISE-2018 project “LoGov - Local Government and the Changing Urban-Rural Interplay” as part of the implementation phase of the project. The interviews have been conducted with experts in the field of public administration, public law and political science, both researchers and practitioners, with the aim of widening the scope of the Country Report on Germany.</p> <p>To access the other interview reports on Germany, and to receive more information about the project, please visit: <a href="https://www.logov-rise.eu/">https://www.logov-rise.eu/</a>. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 823961.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.