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561 results for “Ireland”
Characterisation of Social Vulnerability to the environmental hazard of flooding in Cork City and County, Ireland, derived from national census and EU Copernicus datasets.
<p>This dataset includes all input information for indicators that were used to derive social vulnerability and the overall processed data of the social vulnerability index score for the region of Cork, Ireland. The input variables used in this dataset come from the national census data for Ireland and EU Copernicus data.</p> <div> <p>The social vulnerability indicators used in these datasets are based on research including a review of existing literature and the interpretation of factors affecting social vulnerability. Interpretation of some indicators are contestable and open to debate.</p> </div>
Table of Indications and Regimens from the National Cancer Control Programme, Ireland
<h4>Description:</h4> <p>A table containing all indications published by the National Cancer Control Programme (NCCP), Ireland. Each entry has an indication code, description, and disease; regimen code, name, and URL; and information regarding whether the indication contains molecular diagnostic criteria. Entries were last updated from the NCCP website on 2025-May-27.</p> <h4>Headings:</h4> <ul> <li>IndicationCode: NCCP indication code (ex: 00537a).</li> <li>IndicationDesc: Description of the indication taken from its relevant regimen (ex: "Monotherapy for the treatment of adults with relapsed or refractory CD22-positive B cell precursor acute lymphoblastic leukaemia (ALL). Adult patients with Philadelphia chromosome positive (Ph+) relapsed or refractory B cell precursor ALL should have failed treatment with at least 1 tyrosine kinase inhibitor (TKI).")</li> <li>CancerType: Manual annotation of disease category for the indication (ex: Leukaemia).</li> <li>HasGeneticCriteria: Manual TRUE/FALSE annotation indicating the presence or absence of genetic criteria for the indication, as described in the indication description or regimen document.</li> <li>GeneticCriteria: If HasGeneticCriteria is TRUE, the relevant criteria listed (ex: BCR-ABL1 positive).</li> <li>HasBiomarkerCriteria: Manual TRUE/FALSE annotation indicating the presence or absence of cellular biomarker criteria for the indication, as described in the indication description or regimen document.</li> <li>BiomarkerCriteria: If HasBiomarkerCriteria is TRUE, the relevant criteria listed (ex: CD22+).</li> <li>HasMolecularCriteria: For convenience, column stating TRUE if HasBiomarkerCriteria is True or HasGeneticCriteria is True.</li> <li>RegimenCode: NCCP code for the regimen associated with the indication (ex: 537).</li> <li>RegimenName: NCCP regimen name (ex: Inotuzumab ozogamicin Monotherapy)</li> <li>NCCPRegimenCategories: NCCP disease categories associated with the regimen (ex: Leukaemia/BMT).</li> <li>RegimenURL: URL to the NCCP regimen document.</li> <li>Notes: Miscellaneous notes containing notes from NCCP regimen documents or further explanations.</li> </ul> <p><br> </p>
Space Weather ElectroMagnetic Database for Ireland (SWEMDI)
<p>This is a database containing electromagnetic (EM) data that can contribute to better understand and quantify the electric fields caused by space weather events at the Earth's surface, and the physical properties of Ireland’s lithosphere. The database is named Space Weather Electromagnetic Database for Ireland (SWEMDI).</p> <p>It contains measured electromagnetic time series using magnetotelluric equipment, electromagnetic tensor relationships, 3D electrical resistivity model of Ireland's lithosphere, modelled electric and magnetic time series for Ireland between 1991 and 2018, documents and publications that used parts of this database, and a series of scripts that were used to generate the database.</p>
Weather and Air Quality data for Ireland as RDF data cube
<p>Weather, Air Pollution and Events data represented as RDF data cube. The original weather data has been downloaded from https://www.met.ie//climate/available-data/historical-data and the Air Quality data from <a href="https://discomap.eea.europa.eu/map/fme/AirQualityExport.htm">https://discomap.eea.europa.eu/map/fme/AirQualityExport.htm</a> and <a href="https://discomap.eea.europa.eu/map/fme/AirQualityExportAirbase.htm">https://discomap.eea.europa.eu/map/fme/AirQualityExportAirbase.htm</a>. The Events data refers to random events within the Republic of Ireland.</p> <p>The data has then been uplifted by running the {eeaMapping, metMapping, eventsMapping}.py scripts, which generate R2RML mappings to convert the CSV data to RDF. The mappings re-use vocabularies and ontologies that are W3C recommendations for dataset descriptions (DCAT, https://www.w3.org/TR/vocab-dcat-2/), statistical data (RDF Data Cube, https://www.w3.org/TR/vocab-data-cube/) and provenance data (PROV-O, https://www.w3.org/TR/prov-o/). The scripts use the R2RML engine from https://github.com/chrdebru/r2rml to execute the mappings which generate a data and metadata files for each of the datasets.</p> <p> </p>
Vertical profiles of urban wind speed, wind direction and turbulence measured by LiDAR on campus of University College Cork, Ireland
<p><strong>Vertical Profiles of Urban wind speed, wind direction and turbulence measured by LiDAR on campus of University College Cork, Ireland</strong></p> <p>=================================</p> <p>README version 1.3, 21/07/2022</p> <p>==================================</p> <p>Contact info:</p> <p>Paul Leahy, University College Cork</p> <p>paul.leahy@ucc.ie | +353 21 4902017</p> <p>================================</p> <p> </p> <p><strong>Contents</strong></p> <p><strong>1. Measurement location and time period</strong></p> <p><strong>2. What is measured (brief description)</strong></p> <p><strong>3. Instrumentation</strong></p> <p><strong>4. CSV file detailed descriptions</strong></p> <p>================================</p> <p> </p> <p><strong>1. Measurement location and time period: </strong></p> <p>North roof of Kane Building, University College Cork (UCC), Ireland.</p> <p>Lat 51 d 53 m 34 s N.</p> <p>Long 8 d 29 m 39 s W.</p> <p>Roof is c. 39 m above sea level, and c. 26 m above ground level (ground level reference point is the car park West of the UCC Kane Building).</p> <p>The measurements were taken over a time period of several months in the years 2013 / 2014.</p> <p>=================================</p> <p><strong>2. What is measured (brief description):</strong></p> <p>* LiDAR Wind speed (horizontal and vertical), wind direction, turbulence intensity at 5 altitudes; reference point (0 m) for these altitudes is the top of the LiDAR instrument c. 1.2 m above roof level.</p> <p>* Air temperature, atmospheric pressure, relative humidity.</p> <p>* Wind speed and direction from an ultrasonic anemometer mounted on top of the instrument (c. 1.2 m above roof level).</p> <p>* 10-minute average values (2 files) and high-resolution (c. 23 sec) data (1 file) are provided.</p> <p>See 'CSV file detailed description' below for detailed information.</p> <p>* Diagnostic information.</p> <p>=================================</p> <p><strong>2.1 Surrounding terrain:</strong></p> <p>Surrounding area is urban/suburban. The aspect is northerly.</p> <p>To the West: 2-5 storey buildings, open spaces, suburban.</p> <p>To the South: 2-3 storey buildings, open spaces, trees, river.</p> <p>To the East: 2-3 storey buildings, open spaces.</p> <p>To the North: A higher section of the Kane Building roof (47 m asl), 1-3 storey buildings, suburban.</p> <p>=================================</p> <p><strong>3. Instrumentation:</strong></p> <p>ZephIR 175 continuous wave wind profiling LiDAR with integrated sonic anemometer, temperature, humidity, air temperature pressure sensors and GPS.</p> <p>=================================</p> <p><strong>4. CSV files detailed description:</strong></p> <p><strong>4.1 Data on 10-minute averages:</strong></p> <p>Filename 05092013-03122013_10min_res.csv contains:</p> <p>10 minute averaged data from 05/09/2013 to 03/12/2013.</p> <p>Measurement altitudes: 148 m, 90 m, 69 m, 44 m, 19m above instrument level.</p> <p> </p> <p>Filename 03122013-07082014_10min_res.csv contains:</p> <p>10 minute averaged data from: 03/12/2013 to 07/08/2014.</p> <p>Measurement altitudes: 148 m, 90 m, 50 m, 35 m, 15 m above instrument level.</p> <p>Note: from 19/06/2014 onwards, LiDAR data missing (MET data continues).</p> <p> </p> <p>The first two rows contain header information.</p> <p>Row 1 contains location information (GPS record)) and the measurement altitudes for wind speeds.</p> <p>Sample GPS record: N51535775W8296590 = 51 d 53.5775 m North; 8 d 29.6590 m West.</p> <p>Row 2 contains the data column headers including units.</p> <p> </p> <p>Wind speeds at each altitude are recorded:</p> <p>No of Packets (= number of scan units averaged over) []</p> <p>Wind direction (mean) [deg]</p> <p>Horizontal wind speed (mean) & standard deviation [m/s]</p> <p>Vertical wind speed (mean) & standard deviation [m/s]</p> <p>Horizontal variance [m^2/s^2] </p> <p>Horizontal min [m/s] </p> <p>Horizontal max [m/s] </p> <p>TI (turbulence intensity) []</p> <p> </p> <p>Other meteorological data:</p> <p>Air temperature [<sup>o</sup>C]</p> <p>Pressure [mbar]</p> <p>Rel. Humidity [%]</p> <p>Rain indicator [unitless] Higher values indicate more rain during the averaging interval.</p> <p>Wind Speed [m/s] (column 'MET Wind Speed' measured at the top of the instrument by the ultrasonic anemometer)</p> <p>Wind direction [deg] (column 'MET Direction' measured at the top of the instrument by the ultrasonic anemometer).</p> <p> </p> <p>Other housekeeping and diagnostic data:</p> <p>Instrument tilt [deg]</p> <p>Instrument bearing [deg]</p> <p>GPS data [degrees N, degrees W]</p> <p>Battery voltage [V] </p> <p>Optics, electronics and battery temperature [<sup>o</sup>C]</p> <p> </p> <p>=====================================================</p> <p> </p> <p><strong>4.2 Data with high time resolution (~23 s):</strong></p> <p> </p> <p>Filename 05092013-11112013_23s_res.csv contains:</p> <p>High resolution data from 05/09/2013 to 11/11/2013</p> <p>Measurement altitudes: 148 m, 90 m, 69 m, 44 m, 19m.</p> <p> </p> <p>Note on time resolution:</p> <p>The time resolution of processed wind measurements is c. 3 seconds per wind level, and around 8 seconds to reset to the first level. A full wind profile measurement at 5 altitudes therefore takes around (5 x 3) + 8 = 23 s to complete.</p> <p>The raw scanning resolution of the instrument is higher than this, as each wind measurement is an average of several values.</p> <p> </p> <p>Row 1 contains location information (lat, long) and the vertical measurement levels for wind speeds.</p> <p>Row 2 contains the data column headers including units.</p> <p> </p> <p>Wind speeds at each altitude are recorded:</p> <p>No of Packets (= scan units averaged over) []</p> <p>Wind direction (mean) [deg]</p> <p>Horizontal wind speed (mean) & standard deviation [m/s]</p> <p>Vertical wind speed (mean) & standard deviation [m/s]</p> <p>Horizontal variance [m^2/s^2] not defined as measurement interval is too short.</p> <p>Horizontal min [m/s] not defined as measurement interval is too short. </p> <p>Horizontal max [m/s] not defined as measurement interval is too short. </p> <p>TI (turbulence intensity) [] not defined as measurement interval is too short.</p> <p> </p> <p>Other meteorological data:</p> <p>Air temperature [<sup>o</sup>C]</p> <p>Pressure [mbar]</p> <p>Rel. Humidity [%]</p> <p>Rain indicator [unitless] Higher values indicate more rain during the scanning interval.</p> <p>Wind Speed [m/s] (column 'MET Wind Speed' measured at the top of the instrument by the ultrasonic anemometer)</p> <p>Wind direction [deg] (column 'MET Direction' measured at the top of the instrument by the ultrasonic anemometer.</p> <p> </p> <p>Other housekeeping and diagnostic data:</p> <p>Instrument tilt [deg]</p> <p>Instrument bearing [deg]</p> <p>GPS data [degrees N, degrees W]</p> <p>Battery voltage [V] </p> <p>Optics, electronics and battery temperature [<sup>o</sup>C]</p> <p> </p> <p>=====================================================</p> <p><strong>4.3 Quality control indicators:</strong></p> <p> </p> <p>9998 atmospheric conditions which adversely affect LiDAR wind speed measurements e.g. fog</p> <p>9999 high quality wind speed measurement not possible e.g. very low wind speed or obscuration of optical path</p> <p>Status Flag 'Green' => good</p> <p>=======================================================</p> <p> </p>
Plant Atlas 2020 — Plant native statuses for Britain, Ireland and the Channel Islands
<p>Plant Atlas 2020 is the most comprehensive survey of plants (flowering plants, ferns and charophytes) ever undertaken in Britain and Ireland. It is based on over 30 million records, collected mainly by volunteer recorders of the Botanical Society of Britain and Ireland (BSBI) between 2000 and 2019, as well as previous nationwide surveys undertaken in the 1950s and 1990s. This resource provides the data behind statements concerning species’ native statuses, for various geographical levels and areas, presented in the Plant Atlas 2020 website (<a href="http://www.plantatlas2020.org"><span>www.plantatlas2020.org</span></a><span>) and book (Stroh et al., 2023).</span></p>
#retweetthe8th: twitter dataset from the 2018 Referendum to repeal the 8th Amendment of the Constitution of Ireland
<p>This dataset contains the tweet ids of 2,108,782 tweets related to the referendum to repeal the 8th Amendment of the Constitution of Ireland and replace it with the Thirty-sixth Amendment of the Constitution of Ireland on May 25, 2018. </p> <p>They were collected between March 9th, 2018 and May 30th, 2018 from the Twitter filter stream API using Twarc (<a href="https://github.com/DocNow/twarc">https://github.com/DocNow/twarc</a>). The set of terms that were used for the search were: #repealthe8th, #together4yes, #8thref, #savethe8th, #hometovote, #togetherforyes, #repealedthe8th, #loveboth, #voteyes, #voteno, #lovebothvoteno, #repealtheeighth.</p> <p>Note that the terms changed during the course of data collection and that the searches were not exhaustive.</p> <p>The GET statuses/lookup method supports retrieving the complete tweet for a tweet id (known as hydrating). Twarc can also be used to hydrate tweets.</p> <p>Per Twitter’s Developer Policy, tweet ids may be publicly shared for academic purposes; tweets may not.</p> <p>There are several practical reasons to leave the retweets, as it allows researchers to trace important tweets and their dissemination. </p> <p>However, for researchers that might be interested in NLP tasks for which retweets are not required, a set of 411,213 tweet ids without their retweets is also included in the zip file.</p> <p>Questions about this dataset can be sent to Emmet Ó Briain: <a href="mailto:emmet@quiddity.ie">emmet@quiddity.ie</a> .</p> <p>(24-05-20)</p>
Number of cases of coronavirus disease (COVID-19) in Ireland
<p>Datasets in this publication report the number of diagnoses with coronavirus disease (COVID-19) as reported by the Department of Health in Ireland. This includes new cases diagnosed per day and cumulative cases, hospitalisations, ICU admissions, deaths, number of healthcare workers, number of clusters, gender of cases, age groups of cases, mode of transmission, age groups of those hospitalised, and cases per county. To aid standardisation of age groups and cases per county, the population estimates by age group for 2019 and the actual county population in the 2016 Census from Ireland's Central Statistics Office are also included as separate datasets, to allow expression of cases per million population.</p> <p>These are </p> <ol> <li><em>doh_covid_ie_cases_analysis.csv</em>, where data from Ireland's Health Protection Surveillance Centre is included up to midnight on each included date (currently up to 16-Jun-2020). </li> <li><em>age_population_cso_2019.csv</em></li> <li><em>counties_population_cso_2016.csv</em></li> </ol> <p><em>age_population_cso_2019.csv </em>has been updated to include separate population estimates for those aged 65-74 years, 75-84 years, and 85 years and over. This is in response to the HSPC releasing case and hospitalisation data for these groups rather than a combined 65 years and over group.</p> <p><em>counties_population_cso_2016.csv </em>has been updated to remove trailing spaces in the 'county' column.</p> <p><em>doh_covid_ie_cases_analysis.csv </em>is regularly updated at <a href="https://github.com/frankmoriarty/covid_ie/blob/master/doh_covid_ie_cases_analysis.csv">https://github.com/frankmoriarty/covid_ie/blob/master/doh_covid_ie_cases_analysis.csv</a></p>
What is the clinical course of patients hospitalised for COVID-19 treatment Ireland: a retrospective cohort study in Dublin's North Inner City (the 'Mater 100')
<p><strong>Background: </strong>Since March 2020, Ireland has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). While several cohorts from China have been described, there is little data describing the epidemiological and clinical characteristics of patients with COVID-19 in Ireland. <strong>To improve our understanding of this emerging infection we carried out </strong>a retrospective review of patient data to<strong> examine the clinical characteristics </strong>of patients admitted for COVID-19 hospital treatment.</p> <p><strong>Methods<strong>:</strong></strong> Demographic, clinical and laboratory data on the first 100 adult patients admitted to Mater Misericordiae University Hospital (MMUH) for in-patient COVID-19 treatment after onset of the outbreak in March 2020 was extracted from clinical and administrative records.</p> <p><strong>R<strong>esults:</strong></strong> Fifty-eight per cent were male, 63% were Irish nationals, and median age was 45 years (interquartile range [IQR] =34-64 years). Patients had symptoms for a median of five days before diagnosis (IQR=2.5-7 days), most commonly cough (72%), fever (65%), dyspnoea (37%), fatigue (28%), myalgia (27%) and headache (24%). Of all cases, 54 had at least one pre-existing chronic illness (most commonly hypertension, diabetes mellitus or asthma). At initial assessment, the most common abnormal findings were: C-reactive protein >7.0mg/L (74%), ferritin >247μg/L (women) or >275μg/L (men) (62%), D-dimer >0.5μg/dL (62%), chest imaging (59%), NEWS Score (modified) of ≥3 (55%) and heart rate >90/min (51%). Twenty-seven required supplemental oxygen, of which 17 were admitted to the intensive care unit - 14 requiring ventilation. Forty received antiviral treatment (most commonly hydroxychloroquine or lopinavir/ritonavir). Four died, 17 were admitted to intensive care, and 74 were discharged home, with nine days the median hospital stay (IQR=6-11).</p> <p>C<strong>onclusion:</strong> Our findings reinforce the emerging consensus of COVID-19 as an acute life-threatening disease and highlights, the importance of laboratory (ferritin, C-reactive protein, D-dimer) and radiological parameters, in addition to clinical parameters. Further cohort studies involving larger samples followed longitudinally are a priority.</p>
Organisation for Economic Co-operation and Development (OECD) data for Antalya (Turkey), Antwerp (Belgium), Cork (Ireland), Thessaloniki (Greece) (source: OECD)
<p>The data have been collected via the official OECD Application Programming Interface (API)<strong> </strong>and<strong> </strong>includes the following indicators:</p> <ul> <li>EmpPlaRes - Employment at place of residence</li> <li>LfPartRa - Labour Force and Participation rate</li> <li>UnemReg - Unemployment in regions </li> <li>RegGdpTL2 - Regional Gross Domestic Product (Large regions TL2)</li> <li>GDPLT3 - Gross Domestic Product (Small regions TL3)</li> <li>RegEmIndu - Regional Employment by industry (ISIC rev 4)</li> <li>RegGVAWorker - Regional GVA per worker</li> <li>RegIncPC - Regional income per capita</li> </ul> <p>Source: https://data.oecd.org/api/</p>
Extreme to phenomenal storm wave impacts on a steep rocky coast, north Mayo, Ireland: video data, image analysis, runup and flow velocity calculations for waves of storms Fionn and Gareth.
<p>The primary data are video (.mp4) files of extreme storm wave impacts on the sites of high elevation (>=20m above high water mark) coastal boulder deposits, recorded during storms Fionn (16/01/2018) and Gareth (12/03/2019), at (54.320355, -9.569633) on the north Mayo coast of Ireland, while the significant wave height was in the range [11m,14m]. There are also .png and .jpg files derived from frames of some of the videos, relating to the analysis of the impacting wave kinematics (runup/landward propagation and flow velocities), together with physical measurements for scale determination and runup/velocity/measurement uncertainty calculations in Excel. The files EventX.mp4 are the primary data for the wave impacts EventX. The files EventX_Frame_Y.jpg are frames sampled from EventX.mp4 at constant time intervals in the temporal vicinity of the impact. The files EventX_Edges_Y.png are the edges derived from the frames with the Canny edge detector. The files EventX_Registration_Y.jpg are the impacting wavefront edges with topographical edges registered on the file ReferenceImage.jpg The files EventX.jpg are the stacked registrations for all Y, from which the impact kinematics are derived. The file Scale_Registration_Position_Velocity_Measurements_AndUncertainty.xlsx contains physical measurements for scale determination, measurements of registration error, and the calculations of impact runup/landward displacement and flow velocities, with their uncertainties. The files JetX_Leacht_a_Chúil.mp4/g are videos of large jet-producing impacts at another site.</p> <p>The files DSCN0066.MP4-DSC0085.MP4 are the raw video observations of Storm Gareth, recorded from 15:35-18:41 UT on 12 March 2019 with a Nikon Coolpix W100, while the significant wave height increased from 12m to in excess of 14m (the timestamp of these videos in Properties->Details->Media Created is one hour later than the UT of creation, because the camera's clock was set to Irish Summer Time). The file GPO15366.MP4 is an example of the GoPro (Hero 5) videos recorded simultaneously.</p>
Archaeobotanical results from Ballynacarriga 3, Cork, Ireland
<p>Dataset that resulted from the archaeobotanical analysis of samples from an archaeological excavation of a multi-period site (primarily Late Neolithic) at Ballynacarriga 3, Co. Cork, Ireland. Saved as .csv file.</p>
Archaeobotanical results from Mitchelstown 1, Cork, Ireland
<p>.csv file with results of archaeobotanical analysis from Mitchelstown 1, County Cork, Ireland. This dataset has been subject to minor modifications after peer review. This file supersedes the version published at DOI:10.5281/zenodo.7702 (https://zenodo.org/record/7702#.UuUbs9JFDwc).</p>
Dataset: Six years of surface remote sensing of stratiform warm clouds in marine and continental air over Mace Head, Ireland
<p>A total of 118 stratiform water clouds observed by ground-based remote sensing instruments at the Mace Head Atmospheric Research Station at the West coast of Ireland from 2009 to 2015 were analyzed in terms of microphysical and optical characteristics as well as the impact of aerosols on these properties. The microphysical and optical cloud properties in the files were obtained using the algorithm SYRSOC (SYnergistic Remote Sensing Of Clouds).</p>
National Open Access Monitor, Ireland - Research product metadata
<p>This dataset contains the foundational data for the National Open Access Monitor under an open license. OpenAIRE will routinely provide monthly data dumps to Zenodo, encompassing a comprehensive set of data and indicators related to the Open Access Monitor. This collaborative effort ensures accessibility and openness in sharing the data, promoting transparency and facilitating its use for research and analysis purposes.<br>The dataset comprises of the metadata of the research products metadata stored in the parquet format. The file contains two columns ("id", "xml"), the first of which is the OpenAIRE identifier of the research product and the the second the xml representation of the metadata. The schema of the metadata can be found in https://www.openaire.eu/schema/1.0/oaf-1.0.xsd and a detailed description of the contents can be found in https://graph.openaire.eu/docs/ and https://zenodo.org/records/2643199</p>
Shapefiles showing the locations of long-term climate change refugia and hotspots identified in the FairSeas report "A Climate Resilient Path for Ireland's Marine Protected Areas Network"
<p>Shapefiles created for the report "A Climate Resilient Path for Ireland’s Marine Protected Areas Network", an addendum chapter to "Revitalising Our Seas report: Identifying<br>Areas of Interest for Marine Protected Area Designation in Irish Waters"</p> <p>These shapefiles summarise long-term patterns that emerge from the spatial-meta analysis of physical-biogeochemical and species distribution modelling data, providing an overview of the distribution of climate change refugia and climate change hotspots across Ireland's National Marine Planning Framework between 2026 - 2069, and across the two emissions scenarios considered in the report (RCP4.5 and RCP8.5). </p> <p>Filenames refer to the specific analysis each set of shapefiles belong to: Benthic habitats, benthic megafauna, pelagic habitats, pelagic megafauna and forage fish. Details of the modelling datasets used in each of these analyses, the meta-analysis method and shapefile creation can be found in Annex A1 in the report "A Climate Resilient Path for Ireland’s Marine Protected Areas Network".</p>
Results complementing the European Union summary report on surveillance for the presence of transmissible spongiform encephalopathies (TSE) - Ireland
<p>This dataset contains TSE surveillance results in cattle, sheep, goats, cervids and other species, and genotyping in sheep, pursuant to Regulation (EC) 999/2001.</p> <p><strong>Reporting authorities contributing to each data collection</strong>:</p> <ul> <li>TSE_2023_IE: Department of Agriculture, Food and the Marine (DAFM)</li> <li>TSE_2022_IE: Department of Agriculture, Food and the Marine (DAFM)</li> <li>TSE_2021_IE: Department of Agriculture, Food and the Marine (DAFM)</li> <li>TSE_2020_IE: Department of Agriculture, Food and the Marine (DAFM)</li> <li>TSE_2019_IE: Department of Agriculture, Food and the Marine (DAFM)</li> </ul>
Results complementing the European Union summary report on surveillance for the presence of transmissible spongiform encephalopathies (TSE) - United Kingdom in respect of Northern Ireland
<p>This dataset contains TSE surveillance results in cattle, sheep, goats, cervids and other species, and genotyping in sheep, pursuant to Regulation (EC) 999/2001.</p> <p><strong>Reporting authorities contributing to each data collection</strong>:</p> <ul> <li>TSE_2023_XI - Department of Agriculture, Environment and Rural Affairs</li> <li>TSE_2022_XI - Department of Agriculture, Environment and Rural Affairs</li> <li>TSE_2021_XI - Department of Agriculture, Environment and Rural Affairs</li> </ul> <p> </p>
Modelled relative abundance of bird species in Britain and Ireland 2007-2011
<p>This data package describes the modelled relative (not absolute) abundance of Carrion Crow (<em>Corvus corone</em>), Magpie (<em>Pica pica</em>), Buzzard (<em>Buteo buteo</em>), Kestrel (<em>Falco tinnunculus</em>) and Red Kite (<em>Milvus milvus</em>) in Britain and Ireland.</p> <p>This was used to produce Bird Atlas 2007-2011 <a href="https://app.bto.org/mapstore/StoreServlet" target="_blank" rel="noopener">maps</a> of relative abundance at a tetrad (2x2km) resolution. </p> <p>Acknowledgement: These data originate from the Bird Atlas 2007–11 project which was run by the BTO in partnership with BirdWatch Ireland and the Scottish Ornithologists’ Club. We are grateful to the thousands of volunteers who undertook and organised the fieldwork for the atlas.</p> <p>Please refer to the metadata for a more detailed description, and for information on dataset usage.</p> <p>v1.3 update: added Red Kite (<em>Milvus milvus</em>) and put the species lookup back in.</p> <p><em>If you would like access to this data for another species, please get in touch with BTO via email: datarequests@bto.org</em></p> <p>........................................................................................</p> <p>BTO would also greatly appreciate if you could fill out <a href="https://forms.gle/DCc58VXpdmqnTmTk8" target="_blank" rel="noopener">this very short form</a> to tell us how you intend to use these data. Thanks in advance!</p>
Data from 18 fungicide trials on potato late blight in UK and Ireland 2013-2017
<p>The data set comprises records of disease incidence, crop growth stage and yield from untreated and treated plots.</p> <p>The data is provided as both a tab-separated text file and a binary R data file. The R files provides code to read and plot the data. The plot produced is also provided as a PNG file.</p> <p>The field trials were conducted by Corteva Agriscience, Germany.</p>
ScienceDex guides
Understand access before you commit
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.