The core partner data centres that are integrated in NorDataNet are listed in https://www.nordatanet.no/en/node/69. In addition to this NorDataNet harvests information on relevant datasets from a number of other data centres. The data centre responsible for the data presented is usually (but not always) listed in the discovery metadata. In essence NorDataNet is an aggregating service that combines information from a number of existing data centres.
Citation of data and service
If you use data retrieved through this portal, please acknowledge our funding source:
Research Council of Norway, project number 245967/F50, Norwegian Scientific Data Network.
Always remember to cite data when used!
Citation information for individual datasets is often provided in the metadata. However, not all datasets have this information embedded in the discovery metadata. On a general basis a citation of a dataset include the same components as any other citation:
author, title,
year of publication,
publisher (for data this is often the archive where it is housed),
edition or version,
access information (a URL or persistent identifier, e.g. DOI if provided)
All partner repositories of NorDataNet support Digital Object Identifiers (DOI), but not all datasets are minted. Whether or not minted depends often on source of the data (e.g. operational data are often yet not minted). However, all data centres support persistent identifiers according to local systems. The information required to properly cite a dataset is normally provided in the discovery metadata the datasets.
Brief user guide
The Data Access Portal has information in 3 columns. An outline of the content in these columns is provided above. When first entering the search interface, all potential datasets are listed. Datasets are indicated in the map and results tabulation elements which are located in the middle column. The order of results can be modified using the "Sort by" option in the left column. On top of this column is normally relevant guidance information to user presented as collapsible elements.
If the user want to refine the search, this can be done by constraining the bounding box search. This is done in the map - the listing of datasets is automatically updated. Date constraints can be added in the left column. For these to take effect, the user has to push the button marked search. In the left column it is also possible to specific text elements to search for in the datasets. Again pushing the button marked "Search" is necessary for these to take action. Complex search patterns can be constructed using logical operators identified in the drop down menu with and phrases embedded in quotation marks. Prefixing a phrase with '-' negates the phrase (i.e. should not occur in the results). Searches are case insensitive.
Other elements indicated in the left and right columns are facet searches, i.e. these are keywords that are found in the datasets and all datasets that contain these specific keywords in the appropriate metadata elements are listed together. Further refinement can be done using full text, date or bounding box constraints. Individuals, organisations and data centres involved in generating or curating the datasets are listed in the facets in the right column. The combination of search fields (including facets) is based on a logical "AND" combination of the fields, i.e. all conditions are fulfilled for the results provided.
Wind field ensembles from six CMIP5 models force wave model time slices of the northeast Atlantic over the last three decades of the 20th and the 21st centuries. The future wave climate is investigated by considering the RCP4.5 and RCP8.5 emission scenarios.The CMIP5 model selection is based on their ability to reconstruct the present (1971–2000) extratropical cyclone activity, but increased spatial resolution has also been emphasized.
a) Sea bed mapping and b) Glacial geological and paleo climatic research.Acustical profile data from seismic, penetration echo sounder and side-scanning sonar.
This is a collection of observations from several moored buoys in the Norwegian archipelago and fjords. The buoys measure wind and waves as well as currents, temperature and salinity at several depths in Halsafjord, Sulafjord and Vartdalsfjord and at an offshore location (winter 2019/2020). Both high-frequency recordings of 0,5 - 2 Hz and 10 - 20 minute mean values are provided. The data collection is co-located with the data collection Meteorological Observations in tall masts for the Coastal Highway E39 project in Mid-Norway ( https://adc.met.no/datasets/10.21343/z9n1-qw63 ). The first buoys were deployed October 2016 and the campaign will continue until at least 2024. The dataset is publicly available.
The dataset provides an overview of modern sedimentary environment and processes on the seabed in terms of deposition, transportation and erosion of sediments.
The data on this theme is based on the content of the grain size map. Regional mapping on Norwegian continental shelf by MAREANO.
The datasett comprises a set of seabed sediment samples, that were collected and analysed by MAREANO programme. The top layer (0-2cm or 0-3cm) of the core samples from different sedimentary environments of the Norwegian and Barents Seas were analysed for microplast content: type of plast and number of particles per kilogram sediment dry weight. The largest number of microplastic particles was found in samples from the Norwegian Sea. The analyses were carried out by to different laboratories: University og Gent and Norwegian Geotechnical Institute.
Selected groups of organic contaminants (hydrocarbons - 48 PAH, THC, 27 brominated flame retardants – PBDE, chlorinated contaminants – 9 PCB and 9 chlorinated pesticides), inorganic composition and physical properties are measured in surface and near-surface sediments from the Norwegian continental shelf in the Barents and Norwegian Seas since 2006. Several sampling cruises each year deliver on average 10-20 new locations for investigation annually. The results are available as maps as well as detailed reports on www.mareano.no (updated by the end of each year). The Geological Survey of Norway (NGU) is responsible for analysis of the inorganic chemical composition and of physical parameters, while IMR is responsible for analysis of the organic compounds. Dating of selected sediment cores, based on radioisotopes Pb-210 and Cs-137, provides information on rates of sedimentation and accumulation of contaminants. In some selected cores C-14 is also used for dating. In addition the dataset contains the same data for sediment samples collected by IMR in 2003-2004.
The files in this dataset contains raw datafiles from a NORTEK Signature rig. The rig was deployed in a fixed position just north of the South Orkney Islands in the Southern Ocean. The data is from a Signature 100 instrument, this instrument combines a 4 beam acoustic doppler current profiler with a vertically oriented echosounder (5.th beam, upwards looking). Information on instrument settings used etc. can be found in the binary files (NORTEK proprietary ad2cp format). For extraction of echosounder data we recommend NORTEK software, but these files are also readable using for instance the software packages of the IMOS toolbox (https://help.aodn.org.au/aodn-data-tools/imos-toolbox/). The current meter data in the files are also readable using the “oce” package (https://github.com/dankelley/oce) available under the software environment “R” ( R Core Team (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.)
The purpose of all this deployments was to study krill behaviour and the advective environment in a “krill hotspot”, an area with high importance to krill predators, both natural and human, as part of the NFR funded “SWARM” project (RCN 267416 “From swarming behaviour to trophic interactions: forecasting dynamics of Antarctic krill in ecosystem hotspots using behaviour-based models”).
The map service shows the bottom of the North-East Atlantic and the Barents Sea divided into large geographical areas with a visually homogeneous character (marine landscapes).
MAREANO, AQUREG, GEOS Oslofjorden, Marine grunnkart i Soer-Troms, Marine grunnkart i Astafjord, fase III, Marine grunnkart i Sør Sunnmøre, Marine grunnkart i Sogn og Fjordane, Marine Grunnkart i fem kommuner i Oforten (MAREANO, AQUREG, GEOS Oslofjorden, Astafjorprosjektet, AstafjordIII, MGG, MG_SFJ, MG Ofoten)
Last metadata update: 2010-09-28T12:00:00Z
Show more...
Abstract:
This geologically interpreted data is based on grain size distribution, and indicates how easy it would be to dig into the sea floor, and how stable the dugout depression would be. Sandy sediments, for example, will collapse more quickly after digging a trench than the sediments with finer grain size.
Subsea landscapes of Norwegian ocean areas based on low resolution bathymetry. The map covers areas of 2.4 mill. km2 and is made for presentation in small scale; 1:500 000 for the Barents Sea and the Mid-Norwegian shelf, and 1:1 000 000 for other Norwegian ocean areas. The map gives a good regional picture of terrain variations in areas that have so far been little studied.
The files in this dataset contains raw datafiles from a NORTEK Signature rig. The rig was deployed in a fixed position just north of the South Orkney Islands in the Southern Ocean. The data is from a Signature 100 instrument, this instrument combines a 4 beam acoustic doppler current profiler with a vertically oriented echosounder (5.th beam, upwards looking). Information on instrument settings used etc. can be found in the binary files (NORTEK proprietary ad2cp format). For extraction of echosounder data we recommend NORTEK software, but these files are also readable using for instance the software packages of the IMOS toolbox (https://help.aodn.org.au/aodn-data-tools/imos-toolbox/). The current meter data in the files are also readable using the “oce” package (https://github.com/dankelley/oce) available under the software environment “R” ( R Core Team (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.)
The purpose of all this deployments was to study krill behaviour and the advective environment in a “krill hotspot”, an area with high importance to krill predators, both natural and human, as part of the NFR funded “SWARM” project (RCN 267416 “From swarming behaviour to trophic interactions: forecasting dynamics of Antarctic krill in ecosystem hotspots using behaviour-based models”).
Marine grunnkart i Sør-Troms, Biologisk mangfold, Havbruk, areal, samordning og utvikling i Trøndelag (Astafjordprosjektet, Biologisk mangfold, HASUT)
Last metadata update: 2019-09-03T12:00:00Z
Show more...
Abstract:
The datasett is a geographic representation of over 800 ice marginal deposits in Norwegian fjords and coastal areas. The dataset is compiled of data from several mapping projects, litteratur and other sources. The main compilation was made in cooperation between NGU and Miljødirektoratet (Biomangfoldprosjektet). The interpretation of ice marginal deposits is based on detailed bathymetry data.
The dataset contains ship radar images with 1 min interval. Images cover the area of 15 * 15 km with nominal resolution of 12.5 m. The bow of the ship is always pointing to left. The images have been recorded with an independent radar server, developed by Image Soft Ltd. On the server, images have been pre-processed by temporal median filtering of 15-20 s. The image capturing is described in detail in Karvonen, 2016.
Karvonen, J. (2016): Virtual radar ice buoys – a method for measuring fine-scale sea ice drift (https://doi.org/10.5194/tc-10-29-2016), The Cryosphere, 10, 29–42.