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1,648 results for “farm”
Connectivity performance metrics Grain Automate GRDC Southern region farm 2024-08
<p>A collection of connectivity performance metrics including data usage, location mapping, uptime/downtime, wan quality, captured on a device-basis at each of 3 farms participating in the Grain Automate Project 1 - peer to peer learning through the development of autonomous working farms, for the month of August 2024</p>
Connectivity performance metrics Grain Automate GRDC Western Region farm 2024-09
<p>A collection of connectivity performance metrics including data usage, location mapping, uptime/downtime, wan quality captured on a device-basis at each of 3 farms participating in the Grain Automate Project 1 - peer-to-peer learning through the development of autonomous working farms, for the September 2024.</p>
Connectivity performance metrics Grain Automate GRDC Northern Region Farm 2024-09
<p>A collection of connectivity performance metrics including data usage, location mapping, uptime/downtime, wan quality, captured on a device-basis at each of 3 farms participating in the Grain Automate Project 1 - peer-to-peer learning through the development of autonomous working farms for the month of September 2024.</p>
Connectivity performance metrics Grain Automate GRDC Southern Region farm 2024-09
<p>A collection of connectivity performance metrics including data usage, location mapping, uptime/downtime, wan quality captured on a device-basis at each of 3 farms participating in the Grain Automate Project 1 - peer-to-peer learning through the development of autonomous working farms, for the month of September 2024.</p>
Weight of fauna collected in farmed and wild kelp in Norway April 2019
<p>This is the dataset used to analyse biomass of fauna collected in farmed and wild kelp at the West coast of Norway (Søre Sunnmøre) in April 2019. Coordinates are given in the fil. </p>
Determination of natural radioactivity levels in soil samples from irrigated vegetable farming land in and around Addis Ababa, Ethiopia
<p>This dataset contains 11 data files obtained from a high purity Germanium gamma spectrometry while analysing surface soil samples gathered from vegetable producing area in and around Addis Ababa. The measurement was done in the Ethiopian radiation protection authority laboratory, Addis Ababa, Ethiopia, from August 11 to September 7, 2022. The purpose of the measurement was to evaluate activity concentrations and associated radiological dangers in surface soil from vegetable agricultural area. </p>
Standing stone at Standingstone Farm, Traprain
Canmore 56405, NT 5774 7363. Within the orchard of Standingstone Farm, East Lothian, Scotland, SW of Traprain Law and 0.5km due S of the Loth standing stone. The monolith is 2.80m high and averaging 0.64m on its 4 sides. The stone stands at an angle of 85 degrees. The stone is unmarked apart from a modern letter R inscribed on the W face. Model produced from 240 photographs using Canon 7D Mk2 and 10-18mm lens. Source: Objaverse 1.0 / Sketchfab
Lurgan Farm 12, Perthshire
One of a group of over 15 panels at Lurgan, this panel has been decorated with several cups. For more information, see: rockart.scot Attribution: ScRAP (c) HES Source: Objaverse 1.0 / Sketchfab
Lurgan Farm 8 Lower, Perthshire
The panel forms the lower (western) part of a larger carved surface (Lurgan Farm 8) which is situated on a large schist outcrop. This part of the panel features several cupmarks, a rosette, two cups with rings and radial grooves, and two motifs comprised of two cups connected by a raidal groove and surrounded by a groove. Source: Objaverse 1.0 / Sketchfab
Lurgan Farm 15, near Aberfeldy, Perthshire
One of a large group of panels on an extended outcrop above Lurgan. This panel lies to the W of the most intensely decorated panel (Lurgan Farm 1). It has been decorated with a single large cupmark. Attribution: ScRAP (c) HES Source: Objaverse 1.0 / Sketchfab
Lurgan Farm 3, Perthshire
One of a group of over 15 panels near Lurgan, this panel has been decorated with several motifs including a clear, distinct cup and ring with a tail. For more information, see: rockart.scot Attribution: ScRAP (c) HES Source: Objaverse 1.0 / Sketchfab
Lurgan Farm 2, Perthshire
One of a large group of at least 15 panels, at Lurgan, this panel has been carved with 3 cupmarks. For more information, see: rockart.scot Attribution: ScRAP (c) HES Source: Objaverse 1.0 / Sketchfab
Old brick water tank - abandoned farm - Portugal
Source: Objaverse 1.0 / Sketchfab
Quinolone Resistance Profiles and Mechanisms of Staphylococcus Aureus and Escherichia Coli From Humans, Chicken and Catfish Farms in Indonesia
ClinicalTrials.gov study NCT05652556. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
Farm Work & Preterm Low Birthweight Among Hispanic Women
ClinicalTrials.gov study NCT00015613. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Effects of agricultural pesticides in aquafeeds on wild fish feeding on leftover pellets near fish farms
GEO Series GSE133594. Gadus morhua. 36 samples. Type: Expression profiling by high throughput sequencing.
Soil properties and their interactions on organic farms in Nebraska
Open the record for dataset details and reuse information.
Natural Resources Conservation Service SD State Farm Service Agency Color Slide Scans
The unique landscape of South Dakota, known for its diverse wetlands and large areas of native prairie, provides critical habitat for many of the nation’s migratory birds, including grassland birds.
Distinct early-life stage gene expression effects of hybridization among European and North American farmed and wild Atlantic salmon populations
GEO Series GSE184425. Salmo salar. 36 samples. Type: Expression profiling by array.
AgriLink - Data Set on Suppliers of farm advice in 7 European countries
<p>This Data Set is derived from the WP4 of the AgriLink project.</p> <p>It is part of task T4.4 of Work Package (WP) 4 of the H2020 AgriLink project. AgriLink [Agricultural Knowledge: linking farmers, advisors and researchers to boost innovation] aims at better understanding the role of advisory services in farmers’ decision making and at boosting their contribution to innovation for sustainable development of agriculture. WP4 addresses more specifically the governance of farm advisory services. The objective of the research presented in this report is to understand the institutions that influence how farm advisory services function on the ground, and to discuss implications for the support for sustainable development innovation.</p> <p><strong>Data were collected in seven European countries: the Czech Republic, France, Greece, Poland, Portugal, Spain and the UK.</strong></p> <p><strong>Data were collected for a diversity of types of innovation: Market, Technological, Process, and Social Innovation.</strong></p> <p>The Data set was built based on interviews with farm advisory suppliers.</p> <p>In total 170 farm advisory suppliers were interviewed.</p> <p>The table below provides the distribution of interviews according to countries.</p> <table> <tbody> <tr> <td> <p><strong>Country</strong></p> </td> <td> <p><strong>Market innovation (NCRO & RETRO)</strong></p> </td> <td> <p><strong>Technological innovation (TECH)</strong></p> </td> <td> <p><strong>Process innovation (BIOP & SOIL)</strong></p> </td> <td> <p><strong>Social innovation </strong><strong>(LABO & COMM)</strong></p> </td> <td> <p><strong>TOTAL</strong></p> </td> </tr> <tr> <td> <p><strong>Czech Republic</strong></p> </td> <td> <p> </p> </td> <td> <p>4</p> </td> <td> <p>16</p> </td> <td> <p> </p> </td> <td> <p><strong>20</strong></p> </td> </tr> <tr> <td> <p><strong>France</strong></p> </td> <td> <p>14</p> </td> <td> <p> </p> </td> <td> <p> </p> </td> <td> <p>11</p> </td> <td> <p><strong>25</strong></p> </td> </tr> <tr> <td> <p><strong>Greece</strong></p> </td> <td> <p>11</p> </td> <td> <p> </p> </td> <td> <p>10</p> </td> <td> <p> </p> </td> <td> <p><strong>21</strong></p> </td> </tr> <tr> <td> <p><strong>Poland</strong></p> </td> <td> <p> </p> </td> <td> <p>6</p> </td> <td> <p> </p> </td> <td> <p>18</p> </td> <td> <p><strong>24</strong></p> </td> </tr> <tr> <td> <p><strong>Portugal</strong></p> </td> <td> <p> </p> </td> <td> <p>11</p> </td> <td> <p>20</p> </td> <td> <p> </p> </td> <td> <p><strong>31</strong></p> </td> </tr> <tr> <td> <p><strong>Spain</strong></p> </td> <td> <p>9</p> </td> <td> <p> </p> </td> <td> <p>29</p> </td> <td> <p> </p> </td> <td> <p><strong>38</strong></p> </td> </tr> <tr> <td> <p><strong>UK</strong></p> </td> <td> <p> </p> </td> <td> <p>7</p> </td> <td> <p> </p> </td> <td> <p>4</p> </td> <td> <p><strong>11</strong></p> </td> </tr> <tr> <td> <p><strong>TOTAL</strong></p> </td> <td> <p><strong>34</strong></p> </td> <td> <p><strong>28</strong></p> </td> <td> <p><strong>75</strong></p> </td> <td> <p><strong>33</strong></p> </td> <td> <p><strong>170</strong></p> </td> </tr> </tbody> </table> <p>The data has two aims.</p> <p><strong>First, to characterise farm advisory suppliers, in terms of (table below):</strong></p> <ul> <li><strong>what do they provide?</strong></li> <li><strong>Who is in control of the supplier?</strong></li> </ul> <table> <tbody> <tr> <td><strong>What do they provide</strong></td> <td><strong>Farmers</strong></td> <td><strong>NGO</strong></td> <td><strong>Private</strong></td> <td><strong>Public</strong></td> <td><strong>semi-public</strong></td> <td><strong>Total</strong></td> </tr> <tr> <td><strong>Advice and Bookkeeping</strong></td> <td>8</td> <td> </td> <td>4</td> <td>1</td> <td> </td> <td>13</td> </tr> <tr> <td><strong>Advice and Digital tech</strong></td> <td>1</td> <td> </td> <td>3</td> <td> </td> <td> </td> <td>4</td> </tr> <tr> <td><strong>Advice and Education</strong></td> <td>2</td> <td>4</td> <td>3</td> <td>5</td> <td> </td> <td>14</td> </tr> <tr> <td><strong>Advice and Health services</strong></td> <td> </td> <td> </td> <td>1</td> <td>2</td> <td> </td> <td>3</td> </tr> <tr> <td><strong>Advice and Inputs</strong></td> <td>1</td> <td> </td> <td>14</td> <td> </td> <td> </td> <td>15</td> </tr> <tr> <td><strong>Advice and Inputs and Outputs</strong></td> <td>15</td> <td> </td> <td>5</td> <td> </td> <td> </td> <td>20</td> </tr> <tr> <td><strong>Advice and Machinery</strong></td> <td> </td> <td> </td> <td>7</td> <td> </td> <td> </td> <td>7</td> </tr> <tr> <td><strong>Advice and Outputs</strong></td> <td>8</td> <td>1</td> <td>8</td> <td>2</td> <td> </td> <td>19</td> </tr> <tr> <td><strong>Advice and Research</strong></td> <td>2</td> <td>2</td> <td>5</td> <td>12</td> <td>1</td> <td>22</td> </tr> <tr> <td><strong>Only advice and training</strong></td> <td>16</td> <td> </td> <td>26</td> <td>10</td> <td>1</td> <td>53</td> </tr> <tr> <td><strong>Total</strong></td> <td>53</td> <td>7</td> <td>76</td> <td>32</td> <td>2</td> <td>170</td> </tr> </tbody> </table> <p><strong>Second, we have set a series of variables to characterise the services they provide. The main variables are:</strong></p> <ul> <li><strong>Number of advisors of the organisation</strong></li> </ul> <table> <tbody> <tr> <td><strong>Number of advisors</strong></td> <td><strong>Number of organisations in that group</strong></td> </tr> <tr> <td><strong>[0:5]</strong></td> <td>96</td> </tr> <tr> <td><strong>]10:50]</strong></td> <td>35</td> </tr> <tr> <td><strong>]5:10]</strong></td> <td>16</td> </tr> <tr> <td><strong>>50</strong></td> <td>19</td> </tr> <tr> <td><strong>n.a.</strong></td> <td>4</td> </tr> <tr> <td><strong>Total</strong></td> <td>170</td> </tr> </tbody> </table> <ul> <li><strong>Percentage of advisors in the staff of the organisation</strong></li> </ul> <table> <tbody> <tr> <td><strong>% of advisors</strong></td> <td><strong>Number of organisations</strong></td> </tr> <tr> <td><strong>[0:25[</strong></td> <td>43</td> </tr> <tr> <td><strong>[25:50[</strong></td> <td>17</td> </tr> <tr> <td><strong>[50:75[</strong></td> <td>30</td> </tr> <tr> <td><strong>[75:100]</strong></td> <td>70</td> </tr> <tr> <td><strong>n.a.</strong></td> <td>10</td> </tr> <tr> <td><strong>Total</strong></td> <td>170</td> </tr> </tbody> </table> <ul> <li><strong>Share of back-office activities in the staff of the organisation</strong></li> </ul> <table> <tbody> <tr> <td><strong>Share of back-office (%)</strong></td> <td><strong>Number of organisations</strong></td> </tr> <tr> <td><strong>[0:25[</strong></td> <td>41</td> </tr> <tr> <td><strong>[25:50[</strong></td> <td>26</td> </tr> <tr> <td><strong>[50:75[</strong></td> <td>66</td> </tr> <tr> <td><strong>[75:100]</strong></td> <td>24</td> </tr> <tr> <td><strong>n.a.</strong></td> <td>13</td> </tr> <tr> <td><strong>Total </strong></td> <td>170</td> </tr> </tbody> </table> <ul> <li><strong>Number of farmers client of the supplier per advisor</strong></li> </ul> <table> <tbody> <tr> <td><strong>Number of clients per organisation</strong></td> <td><strong>Number of organisation</strong></td> </tr> <tr> <td><strong>[0:25[</strong></td> <td>31</td> </tr> <tr> <td><strong>[25:75[</strong></td> <td>43</td> </tr> <tr> <td><strong>[50:75[</strong></td> <td>3</td> </tr> <tr> <td><strong>[75:175[</strong></td> <td>28</td> </tr> <tr> <td><strong>>175</strong></td> <td>36</td> </tr> <tr> <td><strong>n.a.</strong></td> <td>29</td> </tr> <tr> <td><strong>Total </strong></td> <td>170</td> </tr> </tbody> </table> <ul> <li><strong>Main advisory method</strong></li> </ul> <table> <tbody> <tr> <td><strong>Main Advisory method</strong></td> <td><strong>Number of organisations</strong></td> </tr> <tr> <td><strong>Group Advice</strong></td> <td>19</td> </tr> <tr> <td><strong>IT tool (app, software…)</strong></td> <td>2</td> </tr> <tr> <td><strong>n.a.</strong></td> <td>1</td> </tr> <tr> <td><strong>One to One Advice</strong></td> <td>129</td> </tr> <tr> <td><strong>Phone or web helpdesk</strong></td> <td>15</td> </tr> <tr> <td><strong>Publications</strong></td> <td>4</td> </tr> <tr> <td><strong>Total</strong></td> <td>170</td> </tr> </tbody> </table> <ul> <li>Main funding source</li> </ul> <table> <tbody> <tr> <td><strong>Main funding source</strong></td> <td><strong>Number of organisations</strong></td> </tr> <tr> <td><strong>EU funds</strong></td> <td>15</td> </tr> <tr> <td><strong>Fee-for-advice</strong></td> <td>46</td> </tr> <tr> <td><strong>Joint trade</strong></td> <td>42</td> </tr> <tr> <td><strong>Membership</strong></td> <td>11</td> </tr> <tr> <td><strong>Membership fee</strong></td> <td>6</td> </tr> <tr> <td><strong>n.a.</strong></td> <td>16</td> </tr> <tr> <td><strong>Public funding</strong></td> <td>3</td> </tr> <tr> <td><strong>Public funds</strong></td> <td>4</td> </tr> <tr> <td><strong>State budget</strong></td> <td>27</td> </tr> <tr> <td><strong>Total</strong></td> <td>170</td> </tr> </tbody> </table> <p>More detailed information about the variables collected can be found in the questionnaire that is available in the appendix of the deliverable D4.2 of AgriLink</p> <p> </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.