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.
The Hive Wireless sensor network project designed and assembled automatic weather stations that are currently installed at Kongsvegen glacier in Svalbard and records near surface meteorological variables: air temperature, relative humidity, air pressure, snow height, wind, surface skin temperature... The HiveWSN kit consists of: 1) a brain box containing the power system, the microcontroller, the communication system and the connectivity to the sensors, 2) A set of sensors either commercially available or custom built at the Department of Geosciences at UiO as part of the UiO Hive project. The kit is autonomous and packaged as a beam that can be installed on simple mast. Currently, there are two versions of the WSN system: v1 from 2019, and v2 from 2021. Both are based on the board Wasmpote v15 which handle power, communication, and data brokerage. The firmware running all instances has been written as part of the project UiO Hive, and include a set of tools described on the HiveWSN project website: https://www.mn.uio.no/geo/english/research/projects/hive. Important note: the height of the sensor to the snow/ice surface is not corrected for variations in surface deposition or melt over time. The sensor box is fixed to a stake drilled into the snow/ice.
The Hive Wireless sensor network project designed and assembled automatic weather stations that are currently installed at Kongsvegen glacier in Svalbard and records near surface meteorological variables: air temperature, relative humidity, air pressure, snow height, wind, surface skin temperature... The HiveWSN kit consists of: 1) a brain box containing the power system, the microcontroller, the communication system and the connectivity to the sensors, 2) A set of sensors either commercially available or custom built at the Department of Geosciences at UiO as part of the UiO Hive project. The kit is autonomous and packaged as a beam that can be installed on simple mast. Currently, there are two versions of the WSN system: v1 from 2019, and v2 from 2021. Both are based on the board Wasmpote v15 which handle power, communication, and data brokerage. The firmware running all instances has been written as part of the project UiO Hive, and include a set of tools described on the HiveWSN project website: https://www.mn.uio.no/geo/english/research/projects/hive. Important note: the height of the sensor to the snow/ice surface is not corrected for variations in surface deposition or melt over time. The sensor box is fixed to a stake drilled into the snow/ice.
The Hive Wireless sensor network project designed and assembled automatic weather stations that are currently installed at Kongsvegen glacier in Svalbard and records near surface meteorological variables: air temperature, relative humidity, air pressure, snow height, wind, surface skin temperature... The HiveWSN kit consists of: 1) a brain box containing the power system, the microcontroller, the communication system and the connectivity to the sensors, 2) A set of sensors either commercially available or custom built at the Department of Geosciences at UiO as part of the UiO Hive project. The kit is autonomous and packaged as a beam that can be installed on simple mast. Currently, there are two versions of the WSN system: v1 from 2019, and v2 from 2021. Both are based on the board Wasmpote v15 which handle power, communication, and data brokerage. The firmware running all instances has been written as part of the project UiO Hive, and include a set of tools described on the HiveWSN project website: https://www.mn.uio.no/geo/english/research/projects/hive. Important note: the height of the sensor to the snow/ice surface is not corrected for variations in surface deposition or melt over time. The sensor box is fixed to a stake drilled into the snow/ice.
The Hive Wireless sensor network project designed and assembled automatic weather stations that are currently installed at Kongsvegen glacier in Svalbard and records near surface meteorological variables: air temperature, relative humidity, air pressure, snow height, wind, surface skin temperature... The HiveWSN kit consists of: 1) a brain box containing the power system, the microcontroller, the communication system and the connectivity to the sensors, 2) A set of sensors either commercially available or custom built at the Department of Geosciences at UiO as part of the UiO Hive project. The kit is autonomous and packaged as a beam that can be installed on simple mast. Currently, there are two versions of the WSN system: v1 from 2019, and v2 from 2021. Both are based on the board Wasmpote v15 which handle power, communication, and data brokerage. The firmware running all instances has been written as part of the project UiO Hive, and include a set of tools described on the HiveWSN project website: https://www.mn.uio.no/geo/english/research/projects/hive. Important note: the height of the sensor to the snow/ice surface is not corrected for variations in surface deposition or melt over time. The sensor box is fixed to a stake drilled into the snow/ice.
The Hive Wireless sensor network project designed and assembled automatic weather stations that are currently installed at Kongsvegen glacier in Svalbard and records near surface meteorological variables: air temperature, relative humidity, air pressure, snow height, wind, surface skin temperature... The HiveWSN kit consists of: 1) a brain box containing the power system, the microcontroller, the communication system and the connectivity to the sensors, 2) A set of sensors either commercially available or custom built at the Department of Geosciences at UiO as part of the UiO Hive project. The kit is autonomous and packaged as a beam that can be installed on simple mast. Currently, there are two versions of the WSN system: v1 from 2019, and v2 from 2021. Both are based on the board Wasmpote v15 which handle power, communication, and data brokerage. The firmware running all instances has been written as part of the project UiO Hive, and include a set of tools described on the HiveWSN project website: https://www.mn.uio.no/geo/english/research/projects/hive. Important note: the height of the sensor to the snow/ice surface is not corrected for variations in surface deposition or melt over time. The sensor box is fixed to a stake drilled into the snow/ice.
The Hive Wireless sensor network project designed and assembled automatic weather stations that are currently installed at Kongsvegen glacier in Svalbard and records near surface meteorological variables: air temperature, relative humidity, air pressure, snow height, wind, surface skin temperature... The HiveWSN kit consists of: 1) a brain box containing the power system, the microcontroller, the communication system and the connectivity to the sensors, 2) A set of sensors either commercially available or custom built at the Department of Geosciences at UiO as part of the UiO Hive project. The kit is autonomous and packaged as a beam that can be installed on simple mast. Currently, there are two versions of the WSN system: v1 from 2019, and v2 from 2021. Both are based on the board Wasmpote v15 which handle power, communication, and data brokerage. The firmware running all instances has been written as part of the project UiO Hive, and include a set of tools described on the HiveWSN project website: https://www.mn.uio.no/geo/english/research/projects/hive. Important note: the height of the sensor to the snow/ice surface is not corrected for variations in surface deposition or melt over time. The sensor box is fixed to a stake drilled into the snow/ice.
This data set contains GPS readings over Antarctica using the Trimble Trimflite differential GPS Navigation System. The readings include latitude, longitude, track, ground speed, off-distance, Positional Dilution of Precision (PDOP), GPS height, easting, northing, and time taken. The data were collected by scientists working on the Investigating the Cryospheric Evolution of the Central Antarctic Plate (ICECAP) project, which is funded by the National Science Foundation (NSF) and the Natural Environment Research Council (NERC), with additional support from NASA Operation IceBridge.
This data set contains measurements of the bidirectional reflectance distribution function (BRDF) for two locations in Colorado, USA: Grand Mesa, a snow-covered, forested study site about 40 miles east of Grand Junction; and Senator Beck Basin approximately 80 miles to the SSE of Grand Mesa.
Measurements were acquired using the NASA Cloud Absorption Radiometer (CAR), an airborne multi-angular, multi-wavelength scanning radiometer. The CAR instrument measures scattered light in 14 spectral bands between 0.34 μm and 2.30 μm, which lie in the UV, visible, and near-infrared atmospheric windows.
Data were obtained for a variety of conditions including snow grain size (or age), snow liquid water content, solar zenith angle, cloud cover, and snowpack thickness. The data set can be used to assess the accuracy of satellite reflectance and albedo products in snow-covered, forested landscapes.
This data set represents a typical single iceberg capsize experiment. Included in this data set are all the parameters of the plastic iceberg's density and dimensions, the density of the water surrounding the iceberg, and the value of gravitational acceleration. The timeseries data consists of all the kinematic and energetic variables as a function of time for the iceberg capsize experiment.
This data set provides digital terrain models, snow depth, and canopy height, acquired by a scanning lidar system and derived from Point Cloud Digital Terrain Models (PCDTMs) from two regions of Alaska, USA collected as part of the NASA SnowEx 2023 field campaign. The study sites include a boreal forest environment in the Fairbanks region of central Alaska (the Bonanza Creek Experimental Forest, Caribou Poker Creek watershed, and Farmer’s Loop/Creamer’s Field) and a coastal tundra environment in the North Slope region of the northern Alaska coastal plain (Arctic coastal plain and Upper Kuparuk Toolik). The raw data from which these data are derived are available as <a href="https://nsidc.org/data/SNEX23_Lidar_Raw">SnowEx23 Airborne Lidar Scans Raw, Version 1</a>.
This data set contains data on the physical flow characteristics, mass balance, sub-glacial topography, and recent fluctuations of the Heard Island glacier. The data were collected for The Antarctic Science Advisory Committee (ASAC) project 2363, a continuation of ASAC project 1158. A full report of the data collected and the work completed are available for download with the data.
The data were collected by the Heard Island glaciology team during the 2003-04 Australian Antarctic Division expedition, as well as some data from the previous expedition in November 2000.
This data set (ATL10) contains estimates of sea ice freeboard, calculated using three different approaches. Sea ice leads used to establish the reference sea surface and descriptive statistics used in the height estimates are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.
The data set SMEX03 Surface Roughness Data is comprised of data collected over the regional study areas of Alabama, Georgia, and Oklahoma, USA as part of the 2003 Soil Moisture Experiment (SMEX03).
This data set contains daily snow cover derived from radiance data acquired by the Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Joint Polar Satellite System's first satellite (JPSS-1). The data is a gridded composite, generated from 6 minute swaths, and projected to a 375 m Sinusoidal grid. Snow cover is identified using the Normalized Difference Snow Index (NDSI) and a series of screens designed to alleviate errors and flag uncertain snow cover detections.