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.
This data set is an inventory of some 2800 landslides that occurred in the High Mountain Asia (HMA) study area between 5 January 2007 and 31 December 2018 (plus one event from 28 January 1990). The catalog includes dates and locations of landslides, plus additional characteristics such as event triggers, country, length and area of the slide, and the number of injuries and fatalities.
The events in this catalog represent an HMA-specific subset of the Cooperative Open Online Landslide Repository (COOLR), a project that was created to build a more robust, publicly available inventory of landslides by supplementing data in the NASA Global Landslide Catalog with citizen science reports.
Geosystem monitoring at the Polish Polar Station Hornsund
Institutions: Institute of Geophysics, Polish Academy of Sciences
Last metadata update: 2022-04-29T13:30:00Z
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Abstract:
In-house developed time-lapse cameras are installed along the coast of Isbjornhamna, on Ariekammen slopes and in front of the Hansbreen. Imagery is mainly used for calving observations, icebergs tracking and sea ice concentration monitoring. Only raw imagery is avilable.
The data is used in the paper "Dynamic response of a high Arctic glacier to melt and runoff variations", published in Geophysical Research Letters. For more details about the data we refer to the paper (https://doi.org/10.1029/2018GL077252).
Results of the geochemical and magnetic studies on natural mineral aerosol deposited and trapped in glaciers (cryodust). Samples were collected from glacial cores taken from five glaciers of Southern Spitsbergen (Svalbard, Norway). The samples were collected by means of a hand-operated Kovacs Enterprise® Mark II coring system. Samples (90 mm in diameter) were packed into polyethylene bags, secured, and transported to the Polish Polar Station Hornsund. The core samples were rinsed using deionized water (Polwater DL100; Norm PN-EN ISO 117 3696:1999; conductivity <0.06 μS/cm) and melted at room temperature in the closed new polyethylene bags. After melting samples were filtered through pre-rinsed sterile Millipore Mixed Cellulose Esters filters (white gridded and 0.45 𝜇𝜇m pore size). After filtration, the filters with residuum were dryer at the temperature of 60oC.Solid particulates of cryodust were subjected to analysis by Electron MicroProbe (EMP) with special attention paid to their internal structure. A scanning electron microscope (SEM) fitted with a backscattered electron (BSE) detector was used to trace grains topography and composition. Special attention was given to monazite chemical dating. Magnetic methods comprised analyses of magnetic susceptibility κ vs temperature T variations and determination of magnetic hysteresis parameters.More about the methodology, analyses and results can be found here: https://doi.org/10.3390/atmos11121325
a) Sea bed mapping and b) Glacial geological and paleo climatic research.Acustical profile data from seismic, penetration echo sounder and side-scanning sonar.
Geosystem monitoring at the Polish Polar Station Hornsund
Institutions: Institute of Geophysics, Polish Academy of Sciences
Last metadata update: 2022-04-29T13:30:00Z
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Abstract:
Raw imagery from the time-lapse camera system installed close to the Fugleberget summit in Hornsund. The imagery covers the lower part of Fuglebekken catchment and the coastline of Isbjørnhamna. Imagery downloaded at the end of the melting season. Imagery is taken every 3 hours. Occasional gaps due to clouds, icing and equipment failure. Calculation of Fractional Snow Cover (FSC) is the main purpose of the dataset. FSC was processed for the time period: 2014-2016
This is a dataset containing SWE data for the period 1982-2015, generated using a coupled energy balance - snow model. This is a selection of data contained in the larger dataset of surface and snow conditions in Svalbard, described in Van Pelt et al. (2019; https://doi.org/10.5194/tc-13-2259-2019). The data is used in the SESS report 2020, and contains MATLAB structures with daily SWE maps, rescaled to a 4x4 km resolution from the original 1x1 km resolution.
The ACS_Bayelva_class dataset contains 302 high-resolution binary snow cover images that were obtained by classifying orthrorectified photographs of a 1.77 km^2 area of interest in the Bayelva catchment. This catchment is close to Ny-Ålesund, the northernmost permanent civilian settlement in the world and a major hub for polar research, in the Norwegian high-Arctic Svalbard archipelago. The imagery has a (roughly) daily temporal resolution and a ground sampling distance (pixel spacing) of 0.5 m. The dataset spans 6 snowmelt seasons, covering the months May-August for the period 2012-2017. The orthophotos were obtained by processing oblique time-lapse photographs taken by a terrestiral automatic camera system (ACS) mounted at 562 m a.s.l. near the summit of Scheteligfjellet (719 m a.s.l.) a few kilometers west of Ny-Ålesund. The orthophotos were manually classified into binary snow cover images (0=no snow, 1=snow) by iteratively selecting a (visually) optimal threshold on the intensity in the blue band for each image. More details are provided in the study of Aalstad et al. (2020) [a copy is available in this repository] where this dataset was created. The ACS was maintained by scientists from the group of Sebastian Westermann at the Section for Physical Geography and Hydrology in the Department of Geosciences at the University of Oslo, Oslo, Norway.
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
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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.
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
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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.
Quantarctica is a collection of Antarctic geographical datasets which works with the free, cross-platform, open-source software QGIS. It includes community-contributed, peer-reviewed data from ten different scientific themes and a professionally-designed basemap.
Quality
The Quantarctica Editorial Board selects peer-reviewed datasets for a wide range of Antarctic users, including over 150 basemap and scientific data layers and thematic coverage from Glaciology and Geophysics to other themes such as Atmospheric Science, Biology, Oceanography, Social Sciences, and more. The Quantarctica project team at the Norwegian Polar Institute then incorporates these layers into the Quantarctica data package by importing, reprojecting, styling, labeling, and organizing them for user-friendly presentation.