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350 results for “Norwegian”
Ice extent in Norwegian fjords, 2001-2019
<p>Ice extent in Norwegian fjords between 2001 to 2019 derived using MODIS imagery. The associated polygons used to outline each fjord/coastal area are provided in the '01_polygons.txt'. Data is presented and analyzed further in:</p> <p>O’Sadnick M, Petrich C,, Brekke C., Skarðhamar J (2020). Ice extent in sub-arctic fjords and coastal areas from 2001 to 2019 analyzed from MODIS imagery. Annals of Glaciology 1–17. https://doi.org/10.1017/aog.2020.34</p> <p>In addition, an interactive map can be found at: https://ndat.no/fjords/ice/</p>
Dataset of Norwegian forest albedo carbon offset potential
<p>This dataset contains the following six files in geotiff format with additional user detail provided as a README.txt file: 1) Forest albedo effect in C-equivalent units for the present day climate 2) Forest albedo effect in C-equivalent units for the transient 21st century RCP4.5 climate 3) Forest albedo's carbon offset potential for the present day climate 4) Forest albedo's carbon offset potential for the transient 21st century RCP4.5 climate 5) Site Index (productivity class) of dominant tree species 6) Dominant tree species 7) README</p> <p>The dataset contains results and input data related the following publication: <br>Bright, R. M., Cataneo, N., Antón-Fernández, C., Eisner, S., Astrup, R., "Relevance of surface albedo to forestry policy in high latitude and altitude regions may be overvalued". <em>Environmental Research Letters, <span><a href="https://doi.org/10.1088/1748-9326/ad657e">https://doi.org/10.1088/1748-9326/ad657e</a></span></em> </p>
Ontolex-lemon and TIAD versions of Apertium Swedish-Norwegian dictionary
<p>OntoLex-lemon and TSV conversion of Apertium Bidix. For more details, see <a href="https://www.aclweb.org/anthology/2020.lrec-1.401/">https://www.aclweb.org/anthology/2020.lrec-1.401/</a></p> <p>Authors of the original data:</p> 2013-2019, Kevin Brubeck Unhammer 2016-2018, Trond Trosterud 2013-2016, Francis M. Tyers 2013, Sjur Nørstebø Moshagen
Ontolex-lemon and TIAD versions of Apertium Northern Sami-Norwegian Bokmål dictionary
<p>OntoLex-lemon and TSV conversion of Apertium Bidix. For more details, see <a href="https://www.aclweb.org/anthology/2020.lrec-1.401/">https://www.aclweb.org/anthology/2020.lrec-1.401/</a></p> <p>Authors of the original data:</p> Copyright (C) 2010--2015 Francis Tyers Copyright (C) 2010--2015 Kevin Brubeck Unhammer Copyright (C) 2010--2015 Trond Trosterud
GUV total ozone column and effective cloud transmittance from three Norwegian sites 1995-2019
<p>Total ozone column (TOC) and effective cloud transmittance (eCLT) from GUV-511 in Oslo (Norway), GUV-541 from Andøya/Tromsø (Norway), and GUV-541 from Ny-Ålesund (Svalbard, Norway).</p> <p>Responsible institute: NILU - Norwegian Institute for Air Research<br> Collaborative institute: Norwegian Radiation and Nuclear Safety Authority, DSA</p> <p>Method described in: Dahlback, A. (1996), Measurements of biologically effective UV doses, total ozone abundances, and cloud effects with multichannel, moderate bandwidth filter instruments, Appl. Opt. 35, 6514–6521</p> <p>1h average noon-time values, based on data with 1-minute time resolution.</p> <p>TOC retrievals from 305/320 nm channel ratio<br> eCLT retrievals from 340 nm channel </p> <p>Calibrations based on the FARIN2005-campaign and annual site visits with a travelling reference GUV instrument from DSA (https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2007JD009731)</p> <p>Funding: NILU - Norwegian Institute for Air Research, Norwegian Environment Agency, Norwegian Ministry of health and Care Services</p>
Wikipedia: wikipedia-nn (Norwegian (Nynorsk))
Wikipedia is a multilingual, web-based, free-content encyclopedia project supported by the Wikimedia Foundation and based on a model of openly editable content. EOL harvests articles from wikipedia that are indexed as species or higher taxa.<p></p><p></p>https://nn.wikipedia.org/
Brewer Global Iradiance (GI) total ozone data at two Norwegian sites (2000 to 2020)
<p>Total column ozone (TCO) derived from Global Irradiance (GI) measurements from the Brewer instruments B042 in Oslo (Norway) and B104 in Andøya (Norway) from 01-01-2000 to 31-12-2020.</p> <p>The data consist of daily values averaged +/-2 hours around local noon.</p> <p>GI calibrations where performed with a clear sky direct sun (DS) measurements in 06-2001, 08-2014, 08-2016, 08-2018, and 08-2019 at Andøya, and in 08-2005, 06-2019, and 08-2019 at Oslo. The data has been calibrated with standard lamp measurements and have been homogenized with DS measurements as a function of clouds and solar zenith angle.</p> <p>The method, calibration, and homogenization is described by Bernet et al. (2022) (Appendix A).</p> <p>Responsible institute: NILU - Norwegian Institute for Air Research</p> <p>Funded by the Swiss National Science Foundation and the Norwegian Environment Agency</p> <p>Bernet, L., Svendby, T., Hansen, G., Orsolini, Y., Dahlback, A., Goutail, F., Pazmiño, A., Petkov, B., and Kylling, A., Total ozone trends at three northern high-latitude stations, 2022.</p>
Measure While Drilling (MWD) dataset with rock type labels for 15 Norwegian hard rock tunnels
<p>The dataset is presented in the paper: </p> <p><em>Building and analysing a labelled Measure While Drilling dataset from 15 hard rock tunnels in Norway</em>, by T.F. Hansen, Z. Liu, J. Torressen</p> <p>The paper has a preprint on SSRN: <a href="http://dx.doi.org/10.2139/ssrn.4729646" target="_blank" rel="noopener">http://dx.doi.org/10.2139/ssrn.4729646</a> and is under review in a peer-reviewed journal.</p> <p>The dataset is utilised in a machine learning analysis in the paper:</p> <p><em>Predicting rock type from MWD tunnel data using a reproducible ML-modelling process</em>, by T.F. Hansen, Z. Liu, J. Torressen</p> <p>The paper is published in the journal <em>Tunnelling and Underground Space Technology</em>: </p> <p><a href="https://doi.org/10.1016/j.tust.2024.105843">https://doi.org/10.1016/j.tust.2024.105843</a></p> <p> </p> <p><strong>Description of the dataset:</strong></p> <p>Measure While Drilling (MWD) is a technique in rock drilling, mainly used in drill and blast tunnelling, where data about the rock mass is registered by sensors while drilling. The extensive and geologically diversified dataset contains corresponding MWD-data and rock mass mappings for 5205 blasting rounds from 15 hard rock tunnels in Norway. MWD-data are presented as tabular data. 10 different rocktypes are the corresponding labels.</p> <p>Four files are given:</p> <ul> <li>A csv-file of the training dataset - with outliers removed</li> <li>A csv-file of the testing dataset (split train/test 0.75/0.25) - with outliers removed</li> <li>A csv-file with the full unsplitted dataset, cleaned and with outliers removed</li> <li>A csv-file with the raw dataset, before cleaning, processing and outlier removal</li> </ul> <p>The author gratefully acknowledge the tunnel software/hardware company Bever Control, which have facilitated data from the clients Bane NOR, Statens Vegvesen, Nye Veier, and the contractor AF-Gruppen.</p> <p> </p> <p><strong>NOTE:</strong> The dataset is only available for research, no commercial use.</p>
Water Body Checklists 2019: Norwegian Sea Species List
Species checklists created using effechecka and modified polygons from IHO. The polygons were reduced in resolution.<p></p>List of species collected from the Norwegian Sea using effechecka and a modified polygon from the International Hydrographic Association. A filter was applied (based on data from WoRMS) to remove all non-marine taxa.
Water Body Checklists: Norwegian Sea Species List
Species checklists created using effechecka and modified polygons from IHO. The polygons were reduced in resolution.<p></p>List of species collected from the Norwegian Sea using effechecka and a modified polygon from the International Hydrographic Association. A filter was applied (based on data from WoRMS) to remove all non-marine taxa.
Parasite communities of Coregonus spp. from Swiss and Norwegian Lakes
<p>Data on the parasite communities of Coregonus spp. from 5 lakes in Switzerland and 2 lakes in northern Norway. These data represent 15 communities from Switzerland and 5 from Norway that were used in the Host sampling completeness analysis in Llopis‐Belenguer, C., J. A. Balbuena, I. Blasco‐Costa, A. Karvonen, V. Sarabeev, and J. Jokela. 2022. Sensitivity of bipartite network analyses to incomplete sampling and taxonomic uncertainty. Ecology.</p>
Modelled hydrodynamic profiles and salmon louse larval densities at Norwegian salmon farms
<p>Data compiled for use by the PreventLice web app, a decision support tool intended to help Norwegian salmon farmers avoid salmon louse infestations: <a href="https://havforskningsinstituttet.shinyapps.io/preventlice">https://havforskningsinstituttet.shinyapps.io/preventlice</a></p> <p>Each file contains the relevant data for a registered salmonid farm in Norway, identified by its locality number according to the Norwegian <a href="https://sikker.fiskeridir.no/akvakulturregisteret/web/sites">Aquaculture Registry</a>. A total of 1023 localities are included in version 1.0.0.</p> <p>The data are in long rectangular format, with each row corresponding to a single depth interval on a single date. Each row provides variables for locality number ("loc"), date ("date"), depth (m, "depth"), daily mean temperature (°C, "meanTemp"), daily mean salinity (ppt, "meanSal"), daily mean current speed (ms<sup>-1</sup>, "meanCurrSpd"), daily 95th percentile current speed (ms<sup>-1</sup>, "95PercCurrSpd"), daily salmon louse infestation pressure (copepodids m<sup>-3</sup>, "meanCopDensity"), and daily mean significant wave height (m, "SignWaveHeight").</p> <p>Temperature, salinity and current speeds are taken from the NorFjords-160 model (<a href="https://doi.org/10.1016/j.ecss.2020.107028">Dalsøren et al. 2020</a>), a finer-scale update of the NorKyst-800 model (<a href="https://doi.org/10.1007/s10236-020-01378-0">Asplin et al. 2020</a>). Wave height data are taken from the MyWaveWAM800m Norwegian coastal wave forecasting system (<a href="https://thredds.met.no/thredds/fou-hi/mywavewam800.html">Norwegian Meteorological Institute</a>). Salmon louse copepodid densities are estimated by coupling louse biology and behaviour parameters with hydrodynamic predictions from NorKyst-800 (<a href="https://doi.org/10.1371/journal.pone.0201338">Myksvoll et al. 2018</a>).</p>
Reference data set for a Norwegian medium voltage power distribution system
<p>This reference data set describes a representative Norwegian radial, medium voltage (MV) electric power distribution system operated at 22 kV. The data set is developed in the Norwegian research centre CINELDI and will in brief be referred to as the CINELDI MV reference system.</p> <p>Data for a real Norwegian distribution system were provided by a distribution grid company. The data have been anonymized and processed to obtain a simplified but still realistic grid model with 124 nodes. The data set consists of the following three parts:<br> 1. Grid data files: describe the base version of the reference system that represents the present-day state of the grid, including information about topology, electrical parameters, and existing load points.<br> 2. Load data files: comprise load demand time series for a year with hourly resolution and scenarios for the possible long-term development of peak load. These data describe an extended version of the reference system with information about possible new load points being added to the system in the future.<br> 3. Reliability data files: contain data necessary for carrying out reliability of supply analyses for the system.</p> <p>The data set is described in detail in the following data article:<br> I. B. Sperstad, O. B. Fosso, S. H. Jakobsen, A. O. Eggen, J. H. Evenstuen, and G. Kjølle, “Reference data set for a Norwegian medium voltage power distribution system,” Data in Brief, 109025, 2023, doi: 10.1016/j.dib.2023.109025.</p>
Figure 9 in Behaviour and habitat of Neohela monstrosa (Boeck, 1861) (Amphipoda: Corophiida) in Norwegian Sea deep water
Figure 9. Glacial eelpout (Lycodes frigidus) is often observed in the same habitat as dense populations of Neohela monstrosa and may represent an important predator from which the latter has to hide in its burrow.
Final spatial dataset for native Norwegian vascular plants
<p>Occurrence data for the native Norwegian vascular plant species obtained from the Global Biodiversity Information Facility (GBIF). The dataset contains 3,597,865 occurrences.</p>
Norwegian results from the monitoring of pesticide residues in food
<p>This dataset contains the analytical results of pesticide residues measured in the food products analysed by the national competent authorities. Pesticide residues resulting from the use of plant protection products on crops that are used for food or feed production may pose a risk factor for public health. For this reason, a comprehensive legislative framework has been established in the European Union (EU), which defines rules for the approval of active substances used in plant protection products, the use of plant protection products and for pesticide residues in food. In order to ensure a high level of consumer protection, legal limits, so called “maximum residue levels” or briefly “MRLs”, are established in Regulation (EC) No 396/2005. EU-harmonised MRLs are set for all pesticides covering all types of food products. A default MRL of 0.01 mg/kg is applicable for pesticides not explicitly mentioned in the MRL legislation. Regulation (EC) No 396/2005 imposes on Member States the obligation to carry out controls to ensure that food placed on the market is compliant with the legal limits.</p> <p>A sample is considered <strong>free of quantifiable residues</strong> if the analytes were not present in concentrations at or above the limit of quantification (LOQ). The LOQ is the smallest concentration of an analyte that can be quantified with the analytical method used to analyse the sample. It is commonly defined as the minimum concentration of the analyte in the test sample that can be determined with acceptable precision and accuracy.</p> <p>If a sample <strong>contains quantifiable residues</strong> but within the legally permitted limit (maximum residue level, MRL), it is described as a sample with quantified residue levels within the legal limits (below or at the MRL)</p> <p>A sample is considered <strong>non-compliant</strong> with the legal limit (MRL), if the measured residue concentrations clearly exceed the legal limits, taking into account the measurement uncertainty. It is current practice that the uncertainty of the analytical measurement is taken into account before legal or administrative sanctions are imposed on food business operators for infringement of the MRL legislation.</p> <p> </p> <p><strong>REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION:</strong></p> <p>MOPER_2023 - NIBIO - Norwegian Institute of Bioeconomy Research</p> <p>MOPER_2022 - NIBIO - Norwegian Institute of Bioeconomy Research</p> <p>MOPER_2021 - NIBIO - Norwegian Institute of Bioeconomy Research</p> <p>MOPER_2020 - NIBIO - Norwegian Institute of Bioeconomy Research</p> <p>MOPER_2019 - NIBIO - Norwegian Institute of Bioeconomy Research</p> <p>MOPER_2018 - Norwegian Institute for Agricultural and Environmental Research</p> <p>MOPER_2017 - Norwegian Institute for Agricultural and Environmental Research</p> <p>MOPER_2016 - Norwegian Institute for Agricultural and Environmental Research</p> <p>MOPER_2015 - Norwegian Institute for Agricultural and Environmental Research</p> <p>MOPER_2014 - Norwegian Institute for Agricultural and Environmental Research</p> <p>MOPER_2013 - Norwegian Institute for Agricultural and Environmental Research</p> <p>MOPER_2012 - Norwegian Institute for Agricultural and Environmental Research</p> <p>MOPER_2011 - Norwegian Institute for Agricultural and Environmental Research</p> <p> </p> <p><strong>We are seeking feedback on our open data please complete the survey at the link below:<br>https://ec.europa.eu/eusurvey/runner/9344dfa0-f384-cb72-65f6-6c187a6d0f14</strong></p>
NorHand v3 / Dataset for Handwritten Text Recognition in Norwegian
<p>This dataset comprises Norwegian letter and diary documents from 19th and early 20th century. It can be used to train Handwritten Text Recognition (HTR) models.</p>
Svalbard Protect Our Waters campaign video - Norwegian
<p>Video for the social awareness campaign Protect Our Waters developed as part of the CLIMAREST EU Horizon 2020 project. The video is provided in several formats (16:9, 9:16, and 1:1) for use in different applications. The language in the video is Norwegian. </p>
Dataset from "Merging Digital Humanities and Discourse Analysis in the Study of COVID-19 Vaccine Distribution in Norwegian Newspapers" (Sverdljuk et al. 2022)
<p>Contains URNs (identifiers) for the newspapers used in the corpus study "Merging Digital Humanities and Discourse Analysis in the Study of COVID-19 Vaccine Distribution in Norwegian Newspapers".</p> <p>For each subcorpus there is an Excel file containing references to the objects used, together with basic metadata.</p> <p>The corpus definitions can be used in various webapps of the DH-LAB at the National Library of Norway, e.g.:</p> <p><a href="https://beta.nb.no/dhlab/concordances/">https://beta.nb.no/dhlab/concordances/</a></p> <p><a href="https://beta.nb.no/dhlab/collocations/">https://beta.nb.no/dhlab/collocations/</a></p> <p>See more at <a href="https://www.nb.no/dh-lab/">https://www.nb.no/dh-lab/</a></p>
Datasets and R-codes complementing the Opinion of the Norwegian Scientific Committee for Food and Environment (VKM) "Risk-Benefit Assessment of Sunscreen"
<p>These datasets complement the Opinion of the Norwegian Scientific Committee for Food and Environment (VKM) "Risk-Benefit Assessment of Sunscreen". They contain:</p> <p>i) data on concentration of the UV filters bis-ethyl-hexyloxyphenol methoxyphenyl triazine (BEMT), butyl methoxydibenzoyl methane (BMDBM), 2-ethylhexyl salicylate (EHS), ethylhexyl triazone (EHT), octocrylene (OC), and titanium dioxide in nanoform (NP-TiO<sub>2</sub>) in commercially available sunscreens,</p> <p>ii) data on amount sunscreen used, and</p> <p>iii) data on dermal absorption of the UV filters bis-ethyl-hexyloxyphenol methoxyphenyl triazine (BEMT), butyl methoxydibenzoyl methane (BMDBM), 2-ethylhexyl salicylate (EHS), ethylhexyl triazone (EHT), octocrylene (OC), and titanium dioxide in nanoform (NP-TiO<sub>2</sub>).</p> <p>The data are used in the probabilistic exposure estimations in the Opinion. The data were retrieved from open sources.</p> <p>In addition, the R-codes used to perform the exposure estimation, are included.</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.