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176 results for “gathering”
Supplementary Materials: A primer on gathering and analysing multi-level quantitative evidence for differential student outcomes in higher education
<p>Example data sets, syntax files and macros for the tutorials in: Balloo, K., & Winstone, N. E. (2021). A primer on gathering and analysing multi-level quantitative evidence for differential student outcomes in higher education.<em> Frontline Learning Research</em>. <a href="https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.14786%2Fflr.v9i2.675&data=04%7C01%7Ck.balloo%40surrey.ac.uk%7C50bb47bb433744dc8da208d8c2116202%7C6b902693107440aa9e21d89446a2ebb5%7C0%7C0%7C637472728228002863%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=fyA0y2hUkHESUJ7sVJ3s42Re4Yqa5XbgwW7AvEyGDdk%3D&reserved=0">https://doi.org/10.14786/flr.v9i2</a><a href="https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.14786%2Fflr.v9i2.675&data=04%7C01%7Ck.balloo%40surrey.ac.uk%7C50bb47bb433744dc8da208d8c2116202%7C6b902693107440aa9e21d89446a2ebb5%7C0%7C0%7C637472728228002863%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=fyA0y2hUkHESUJ7sVJ3s42Re4Yqa5XbgwW7AvEyGDdk%3D&reserved=0">.675</a> </p> <p><strong>The data for all examples are fictional, and have only been designed to simulate the possible behaviour of institutional data for the purposes of demonstrating the analytical approaches in the primer. No inferences or conclusions should be drawn from the findings of these examples, because the results are not real. </strong></p> <p>We anticipate that readers can use the example data sets as templates and substitute in their own data.</p>
A global dataset gathering 37 field experiments involving cereal-legume intercrops and their corresponding sole crops.
<p>The overall description of the dataset is reported in the <strong>data_report.pdf</strong> file. The methodology for data curation and tidying is published in Peer Community Journal (<a href="https://doi.org/10.24072/pcjournal.389">Mahmoud2024</a>).</p> <p>This dataset gathers the results of 37 field experiments, which involved cereal-legume intercrops and their corresponding sole crops. The field experiments were carried in 5 European countries (France, Denmark, Italy, Germany and England) from 2001 to 2017. The dataset includes:</p> <ul> <li>5 legume species , <em>i.e.</em> chickpea (<em>Cicer arietinum</em> L.), faba bean (<em>Vicia faba</em> L.), lentil (<em>Lens culinaris</em> Med.), lupin (<em>Lupinus albus</em> L.) and pea (<em>Pisum sativum</em> L.),</li> <li>3 cereal species, <em>i.e.</em> barley (<em>Hordeum vulgare</em> L.), durum wheat (<em>Triticum turgidum</em> L.) and soft wheat (<em>Triticum aestivum</em> L.), </li> <li>8 resulting intercrops, <em>i.e.</em> i) barley associated with faba bean, lupin or pea, ii) durum wheat associated with chickpea, faba bean or pea, and iii) soft wheat associated with lentil or pea. </li> </ul> <p>In total, the dataset contains 299 sole crop and 308 intercrop experimental units, one given experimental unit being defined as the unique combination of {site, year, crop management}, with the crop management including species and cultivar choice as well as agricultural interventions (sowing conditions, inputs).</p> <p>The global dataset includes four tables, all sharing a common identifier (experiment_id):</p> <ul> <li>data_trials.csv: the global features describing the experimental sites,</li> <li>data_management.csv: the agricultural management actions carried out on each of the experimental sites,</li> <li>data_traits.csv: measured plant and crop characteristics,</li> <li>data_climate.csv: climate for the experimental sites, retrieved from NASA POWER API.</li> </ul> <p>Additionally, a metadata file is provided (<strong>metadata.xlsx</strong>), describing the table to which the variables belong (variable_type, i.e. trials, management, traits or climate), their name (variable_name), their significance (description) and their unit (unit). Finally, a table including the original references related to experimental files gathered (<strong>references.xlsx</strong>) is also provided.</p> <p>Data providers and field experiments: Laurent Bedoussac, Eric Justes, Etienne-Pascal Jour- net, Christophe Naudin, Henrik Hauggaard-Nielsen, Erik Steen Jensen, Elise Pelzer, Guénaëlle Corre-Hellou, Bochra Kammoun, Loic Viguier, Romain Barillot, Antoine Couëdel, Philippe Hinsinger</p> <p>Database and management: Noémie Gaudio, Rémi Mahmoud, Pierre Casadebaig</p>
CROSSBOW HLU2-UC1-TC1 measurements: Substation measurements gathered during curtailment activation
<p>The data comprises the measurements read at the Konjsko substation before, during and after a curtailment in Pometeno Brno plant.</p> <p>The measurements gathered from the SCADA are:</p> <ul> <li>P, Q and V of the 110, 220 and 400 Kv buses at the substation</li> </ul> <p>P, Q and V of the line connecting the substation with the plant</p>
gathering_8
This is the process of making a carafe Bontemps. The step depicted is called gathering(from the Mingei project).
gathering_6
This is the process of making a carafe Bontemps. The step depicted is called gathering(from the Mingei project).
gathering_7
This is the process of making a carafe Bontemps. The step depicted is called gathering(from the Mingei project).
gathering_3
This is the process of making a carafe Bontemps. The step depicted is called gathering(from the Mingei project).
gathering_4
This is the process of making a carafe Bontemps. The step depicted is called gathering(from the Mingei project).
gathering_5
This is the process of making a carafe Bontemps. The step depicted is called gathering(from the Mingei project).
gathering_2
This is the process of making a carafe Bontemps. The step depicted is called gathering(from the Mingei project).
gathering_1
This is the process of making a carafe Bontemps. The step depicted is called gathering(from the Mingei project).
Glass_Procedure_second_gather_Mingei
Documentation material from the Mingei project
Data gathered during the first and second stage of carrying out the NCN research project "Odmieńcy. Performances of otherness in the Polish transition culture" (year 2022 and 2023) - PI
<p>Data gathered during the first and secon phase of the project "Odmieńcy. Performances of otherness in Polish transition culture" by Dorota Sosnowska used as a basis for two papers: <a href="https://open.icm.edu.pl/items/9117fe29-528d-43ff-99c7-2e1fe0a8a93a">Blasted 1999. Sarah Kane’s Body Against the Archive (icm.edu.pl)</a> and <a href="https://open.icm.edu.pl/items/0aa7964c-b690-42af-8f7c-3d4fc62084b5">Brzydkie uczucia. O nudzie w sztuce i teatrze lat’ 90 (icm.edu.pl)</a></p>
Data gathered during the first and second stage of carrying out the NCN research project "Odmieńcy. Performances of otherness in the Polish transition culture" (year 2022 and 2023)
<p>Data gathered during the first and secon phase of the project "Odmieńcy. Performances of otherness in Polish transition culture" by Łukasz Kiełpiński used as a basis for two papers: <a href="../records/10625768">Zarządzanie ambiwalencją. Polski dyskurs ekspercki wokół HIV/AIDS na przełomie lat osiemdziesiątych i dziewięćdziesiątych XX wieku (zenodo.org)</a> and <a href="../records/10625805">Gra o sumie zerowej. Ekonomia wstydu w filmie "Pora na czarownice" (zenodo.org)</a></p>
Geographic variation of tree height of Pinus pinea L. gathered from common gardens in Europe
<p>This dataset collects individual georeferenced tree height data from <em>Pinus pinea </em>L. planted in common gardens in France and Spain, between years 1993 and 1997. The experimental design varies depending on the common garden, from a randomized complete to incomplete block design, RCB or RIB, respectively. The final dimensions of this database is 56,624 individual tree height measurements <em> </em>with 9 common gardens and 55 different provenances. The data can be used to assess genetic variation and phenotypic plasticity with further applications in biogeography and forest management. </p>
Geographic variation of tree height of Pinus nigra Arn. gathered from common gardens in Europe
<p>This dataset collects individual georeferenced tree height data from <em>Pinus nigra</em> Arn. planted in common gardens in France, Germany and Spain, between years 1968 and 2009. The experimental design varies depending on the common garden, from a randomized complete to incomplete block design, RCB or RIB, respectively. The final dimension of the dataset is 194,642 individual tree height data measurements <em> </em>with 15 common gardens and 78 different provenances. The data can be used to assess genetic variation and phenotypic plasticity with further applications in biogeography and forest management. </p> <p> </p>
Geographic variation of tree height of Pinus pinaster Aiton gathered from common gardens in Europe and North-Africa
<p>This dataset collects individual georeferenced tree height data from <em>Pinus pinaster</em> Aiton planted in common gardens in France, Morocco and Spain, between years 1966 and 1992. The experimental design varies depending on the common garden, from a randomized complete to incomplete block design, RCB or RIB, respectively. The final dimension of the dataset is 123,801 individual tree height data measurements <em> </em>with 14 common gardens and 182 different genetic units. The data can be used to assess genetic variation and phenotypic plasticity with further applications in biogeography and forest management. </p>
CLDF dataset derived from Bowern et al.'s "Hunter - Gatherer Language Database" from 2021
<p>Cite the source of the dataset as:</p> <blockquote> <p>Bowern, Claire, Patience Epps, Jane Hill, and Patrick McConvell. Hunter - Gatherer Language Database. https://huntergatherer.la.utexas.edu/ Accessed 2021-04-27.</p> </blockquote>
GNSS training - dataset - Wrocław - 1st GATHERS Summer School
<p>The files in the collection contain a 3D time-series of displacements in [m]. Data were collected before 1st GATHERS Summer School in Wrocław as a reference data. The observations were taken at the roof of Wrocław University of Environmental and Life Sciences - Institute of Geodesy and Geoinformatics: <a href="https://goo.gl/maps/W94mr2UhJKn7XH1z9">Location in Google Maps</a></p> <p>Please note that each file is containing 3 time-series in North, East and Up direction.</p> <p>There are three headers beginning each of the time-series.</p> <p>The GNSS_PPP.ascii contains the results of kinematic PPP (Precise Point Positioning)</p> <p>The GNSS_VAD.ascii contains the results of a kinematic variometric approach to GNSS data processing (from VADASE software).</p> <p>The ACC_DISPL.ascii contains the displacements calculated from accelerations measured with GeoTiny!AC accelerometer.</p> <p>The GNSS antenna and the accelerometer were co-located with a distance of 10 cm and rigidly connected.</p> <p>If some questions arise, please send a message to:</p> <p><a href="mailto:jan.kaplon@upwr.edu.pl">jan.kaplon@upwr.edu.pl</a>, </p> <p> </p>
Collection of narratives gathered by academia, governments, and think-tanks.
<p>Examples of Russian revisionist narratives. Source: own study based on the collection of narratives gathered by academia, governments, and think-tanks. The examples of narratives have been selected to represent diverse character of narratives and historical events. </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.