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.
Orthophoto Image is an image that color aerial photograph is converted to orthophoto and mosaic effects are added to it. Geometrically corrected data is available
The Japanese Ny-Alesund Observatory, which is cal1ed "Rabben" was established in April 1991 there. It is located at about 1.5 km north west from the center of Ny-Alesund. The latitude, longitude and altitude of the observatory are 78o55'N,11o56'E and about 40m, respectively. We developed an automatic system for meteorological data acquisition, because no permanent stuff stayed at the observatory throughout the year to maintain instruments. Their sensors were installed nearby Rabben. Ground based measurements of meteorological elements have been made continuously since August 16, 1992 at the observatory. This data report shows the data from January 2003 to December 2006.
Orthophoto Image is an image that color aerial photograph is converted to orthophoto and mosaic effects are added to it. Geometrically corrected data is available
Orthophoto Image is an image that color aerial photograph is converted to orthophoto and mosaic effects are added to it. Geometrically corrected data is available
The harbor seal population on Svalbard, the northernmost breeding site for this species, appears to have a truncatedage distribution with older animals being largely absent.PCBs and pesticides were measured in harbor seal males,females, milk and pups from Svalbard to explore whether contaminant exposure or accumulation is a possible causeof premature death for these animals.The levels and patterns of these contaminants were assessed. In addition,transfer of these compounds from females to their pups during lactation was assessed.Both PCB and pesticide levelswere low compared to more southern harbor seal populations.Animals from Svalbard contained 5–10 times lowercontaminant levels, compared to seals from the Norwegian mainland, and 30 times lower concentrations than thoseof harbor seals from the Gulf of St.Lawr ence in eastern Canada. Ringed seals from Svalbard have contaminant levelsthat are comparable to the harbor seals, probably because the diet, as well as the metabolic capacity, of the twospecies is similar at this location.The findings of this study indicate that the early mortality observed for harbor sealson Svalbard, is not likely to be due to contaminant exposure.Female harbor seals transfer a modified contaminantmixture to their pups compared to that found within their own tissues; compounds with higher log Kow, such as somepenta-chlorinated PCBs, were selectively transferred into milk.As a result, the contaminant pattern between malesand females differed, with penta-chlorinated PCBs more abundant in males than in females.In addition, pups receivea relatively high amount of the less lipophylic compounds and a low amount of the more lipophylic compounds.Thesimilar contaminant pattern in milk and pups suggested that they are probably unable to metabolize contaminants andconsequently, accumulate all ingested chemicals.
This data set provides the main results from a remote sensing study of the Ross and Filchner-Ronne ice shelves in Antarctica (Moholdt et al. 2014, J. Geophys. Res.). The downloadable zip-file contains an archive of georeferenced rasters (GeoTIFF format) and polygons (shapefile format). The key parameters are ice-shelf extent, ice thickness and change rates of surface elevation and ice mass during a reference period between 2003 and 2009, coincident with NASA’s ICESat altimetry mission. Please refer to the attached readme-file and the paper publication for more details.
This dataset provides the first-of-the-kind inventory of Antarctic ice rises and rumples, which was developed and described by Matsuoka et al. (2015). The inventory is based on available grounding-zone products and some additional visual interpretation of satellite imagery. Beginning with the island polygons of the MODIS Mosaic of Antarctica (MOA) 2003-2004 product (Haran et al., 2005; Scambos et al., 2007), we extracted all island polygons that were contained within an ice shelf, assuming that they represent ice rises or rumples. We then updated this dataset using the new MOA 2009 product as well as independent grounding-zone points from SAR interferometry (Rignot et al., 2011) and ICESat altimetry (Fricker et al., 2009; Brunt et al., 2010). This preliminary inventory was then manually edited and updated based on visual interpretation of the two MOA image mosaics, the high-resolution Landsat Image Mosaic of Antarctica (LIMA) (Bindschadler et al., 2008), and the IPY-MEaSUREs Antarctica velocity map (Rignot et al., 2011). We also digitized polygons around the most prominent ice ridges and domes within the continental grounding zone. We classified the features into four classes (ice rises, promontories/ridges, ice rumples and nunataks) and extracted basic statistical attributes on parameters such as area, surface velocity, surface elevation, bed elevation, ice thickness and surface slope. Please refer to Matsuoka et al. (2015) and the relevant metadata for more details.
Quality
Description of inventory attributes
id_icerise: Unique id code for each feature (sorted after longitude) type, type_text: 1 = Ice rise (topographic feature within an ice shelf, with distinct dynamics) 2 = Ice ridge (major promontory/ridge between ice shelves/streams, with a clear divide) 3 = Ice rumple (smaller grounded feature with irregular geometry, limited prominence and typically ice-shelf flow across it) 4 = Nunatak (visible sediments or rock) name: Name of feature for those that have, mainly based on SCAR database divide: 0 = no clear divide 1 = clear divide island: 0 = grounded below sea level 1 = partly grounded above sea level (in Bedmap2) isolated: 0 = inside or connected with an ice shelf 1 = not connected to an ice shelf (only applies to type 2 ice ridges, mainly in Siple Coast) MOA2003, MOA2009, InSAR (data source): 0 = not represented in that data set 1 = represented in that data set (three zeros imply manual identification in satellite imagery) Area_km2: Polygon area in square kilometers, Lambert Equal Area Projection nrofpoints: Number of 1 km2 grid cells used for statistics calculation vel_mean: Mean absolute velocity over each feature based on the Antarctica Velocity Map h_mean, h_min, h_max: Mean, minimum and maximum surface elevation of each feature extracted from Bedmap2 h_rise: Relative height of the feature (h_max-h_min) bed_mean, bed_min, bed_max: Mean, minimum and maximum bedrock elevation of each feature extracted from Bedmap2 thick: Mean ice thickness (h_mean-h_bed) slope_mean: Mean absolute slope of each feature extracted from Bedmap2 Width, length: Shortest and longest distances (in unit km) from the summit to the edge of each feature longi, lati: longitude and latitude of the center point of each feature —
References for external data sources
MOA2003 and MOA2009: Scambos, T. A., T. M. Haran, M. A. Fahnestock, T. H. Painter, and J. Bohlander (2007), MODIS-based Mosaic of Antarctica (MOA) data sets: Continent-wide surface morphology and snow grain size, Remote Sens. Environ., 111, 242-257, https://doi.org/10.1016/j.rse.2006.12.020
InSAR grounding line: Rignot, E., J. Mouginot, and B. Scheuchl (2011a), Antarctic grounding line mapping from differential satellite radar interferometry, Geophys. Res. Lett., 38(L10504), https://doi.org/10.1029/2011gl047109
Antarctica Velocity Map: Rignot, E., J. Mouginot, and B. Scheuchl (2011b), Ice Flow of the Antarctic Ice Sheet, Science, 333, 1427-1430, https://doi.org/10.1126/science.1208336
Bedmap2: Fretwell, P., et al. (2013), Bedmap2: improved ice bed, surface and thickness datasets for Antarctica, Cryosphere, 7, 375-393, https://doi.org/10.5194/tc-7-375-2013
Institutions: CH01L, Swiss Federal Laboratories for Materials Science and Technology, EMPA, Section Air Pollution, Überlandstrasse 133, 8600, Dübendorf, Switzerland, CH01L, Swiss Federal Laboratories for Materials Science and Technology, EMPA, Section Air Pollution, Überlandstrasse 133, 8600, Dübendorf, Switzerland
Last metadata update: 2023-10-16T00:00:00Z
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Abstract:
Ground based in situ observations of high_vol_sampler at Chaumont (CH0004R). These measurements are gathered as a part of the following projects EMEP and they are stored in the EBAS database (http://ebas.nilu.no/). Parameters measured are: pm10_mass in pm10 (mass_concentration_of_pm10_ambient_aerosol_particles_in_air), pm1_mass in pm1 (mass_concentration_of_pm1_ambient_aerosol_particles_in_air), pm25_mass in pm25 (mass_concentration_of_pm2p5_ambient_aerosol_particles_in_air)
Institutions: EE01L, Estonian Environmental Research Centre, EKUK, Marja 4D, 10617, Tallinn, Estonia, EE01L, Estonian Environmental Research Centre, EKUK, Marja 4D, 10617, Tallinn, Estonia
Last metadata update: 2021-02-11T00:00:00Z
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Abstract:
Ground based in situ observations of nitrogen_dioxide at Lahemaa (EE0009R) using chemiluminescence_photolytic. These measurements are gathered as a part of the following projects HELCOM, EMEP and they are stored in the EBAS database (http://ebas.nilu.no/). Parameters measured are: nitrogen_dioxide in air (mass_concentration_of_nitrogen_dioxide_expressed_as_nitrogen_in_air)
License : HELCOM: Public open access. We encourage contacting data originators if substatial use of individual time series is planned (fair use data policy)., EMEP: Public open access. We encourage contacting data originators if substatial use of individual time series is planned (fair use data policy).
Ground based in situ observations of nitrogen_dioxide at Brotjacklriegel (DE0005R) using NaJ_solution. These measurements are gathered as a part of the following projects EMEP and they are stored in the EBAS database (http://ebas.nilu.no/). Parameters measured are: nitrogen_dioxide in air (mass_concentration_of_nitrogen_dioxide_expressed_as_nitrogen_in_air)
License : EMEP: Public open access. We encourage contacting data originators if substatial use of individual time series is planned (fair use data policy).
Ground based in situ observations of filter_3pack at Westerland (DE0001R). These measurements are gathered as a part of the following projects EMEP and they are stored in the EBAS database (http://ebas.nilu.no/). Parameters measured are: sulphur_dioxide in air (mass_concentration_of_sulphur_dioxide_expressed_as_sulphur_in_air), sum_nitric_acid_and_nitrate in air+aerosol (mass_concentration_of_sum_nitric_acid_and_nitrate_expressed_as_nitrogen_in_aerosol)
License : EMEP: Public open access. We encourage contacting data originators if substatial use of individual time series is planned (fair use data policy).
The dataset contains thermograph data from one of the Hurtigruten ships, MS Vesterålen, in 2003. Temperature at 4 m depth and ship position is logged every 5 minutes between Bergen and Kirkenes.