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)
The information required to properly cite a dataset is normally provided in the discovery metadata the datasets.
If you use data retrieved through this portal, please acknowledge the SAON Data Portal.
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 through the drop down menu above the text field. Text strings that are not quoted are treated as separate words and will match any of the words (i.e. assuming the OR operator). Phrases may be prefixed with '-' to indicate no occurence of the phrase in the results.
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.
NDVI, GCC, soil and surface temperature, and soil water content data from Adventdalen, Svalbard. This data was collected with a time-lapse RGB camera and NDVI sensor installed on a two meter high metal rack to monitor tundra vegetation. The time-lapse photos have gone through a manual quality check and were automatically adjusted with an algorithm to correct for lateral and rotational movements. A mask was used to calculate Green Chromatic Channel (GCC) from the photos. The NDVI data was quality controlled by removing outliers that were two standard deviations removed from the mean value of the growing season, and by removing dates where there was snow on the ground (as indicated by the time-lapse photos). In addition, soil and surface temperature and soil moisture were measured to facilitate the interpretation of shifts in the vegetation indices.
This collection contains a high-resolution (2.5 km) dataset of glacier mass balance and runoff in Franz Josef Land and Novaya Zemlya from 1991-2022, situated in one of the fastest warming regions in the Arctic. The dataset is created using a full energy balance model (the CryoGrid community model) forced by the Copernicus Arctic Regional ReAnalysis (CARRA) dataset (1991-2022). Each variable is available at both a daily and monthly resolution.
This collection contains a high-resolution (2.5 km) dataset of glacier mass balance, runoff and snow conditions in Svalbard from 1991-2022, one of the fastest warming regions in the Arctic. The dataset is created using a full energy balance model (the CryoGrid community model) forced by both the Copernicus Arctic Regional ReAnalysis (CARRA) dataset (1991-2021) and AROME-ARCTIC forecasts (2016-2022). Each variable is available at both a daily and monthly resolution.
a) Sea bed mapping and b) Glacial geological and paleo climatic research.Acustical profile data from seismic, penetration echo sounder and side-scanning sonar.
Repeated DGPS measurements of (~20) mass balance stakes on the Austfonna ice cap and continuous GPS records on two fast flowing outlets (along the central flowlines of Basin-3 and Duvebreen; 5 units each). The continous measurements are made in cooperation with IMAU, Utrecht, The Netherlands and the present data set overlaps with the one provided by Dr. C.H. Tijm-Reijmer (entry-ID: Flow_Arctic_Glaciers_Tijm-Reijmer_IPY37_NL)
The Nansen Legacy cruise Q1 was part of the seasonal investigation of the northern Barents Sea and adjacent Arctic Basin. The cruise was conducted in 2-24 March 2021 onboard R/V Kronprins Haakon, and focused on studying the physical, chemical and biological conditions along the Nansen Legacy main transect in open waters and within the sea ice. While in sea ice we conducted ten regional scale sea ice helicopter-borne surveys of ice conditions along the Nansen Legacy transect using a helicopter-borne electromagnetic instrument (HEM) EM-bird. This dataset presents processed EM-bird data on total snow and sea-ice thickness along the flight tracks.
This is a contribution to the Research Council of Norway project “Nansen Legacy” (https://arvenetternansen.com/), WP RF-1 “Physical drivers”.
Quality
See the attached docuement “AeN_Q1_202103_HEM_icethickness_metadata_v1.0.pdf” for details on the data acqusition, processing and structure.
The automated nivological station was installed in November 2020 in a flat area over the tundra about 80 meters far from the Gruvebadet Atmospheric Laboratory and nearby a snow sampling site from where weekly snow samples are collected for chemical analysis. Sensors (Pt100 1/3 DIN) have been calibrated by their companies before installation and are connected to a datalogger for continuous acquisition. For all the parameters, data are logged with 10-minute time resolution and then averaged over 1 hour. This activity is carried out by the Aldo Pontremoli Centre part of the Joint Research Agreement ENI-CNR, in the framework of the SnowCorD project (SIOS Core Data).
The automated station is operating at the Amundsen-Nobile Climate Change Tower since 2010, which is in a tundra site almost flat, located in the Kolhaugen area. The station is part of a complex infrastructure where multi-disciplinary observations are routinely performed. The instrument used for the meauserements is a PT100 thermocouple. This activity is carried out in the framework of the SnowCorD project (SIOS Core Data).
The automated station to measures snow cover is operating at the Amundsen-Nobile Climate Change Tower since 2010, which is in a tundra site almost flat, located in the Kolhaugen area. The station is part of a complex infrastructure where multi-disciplinary observations are routinely performed. Data were collected using an ultrasonic distance sensor. This activity is carried out in the framework of the SnowCorD project (SIOS Core Data).
The automated nivological station was installed in November 2020 in a flat area over the tundra about 80 meters far from the Gruvebadet Atmospheric Laboratory and nearby a snow sampling site from where weekly snow samples are collected for chemical analysis. Sensors (NESA LU06) have been calibrated by their companies before installation and are connected to a datalogger for continuous acquisition. For all the parameters, data are logged with 10-minute time resolution and then averaged over 1 hour. This activity is carried out by the Aldo Pontremoli Centre part of the Joint Research Agreement ENI-CNR, in the framework of the SnowCorD project (SIOS Core Data).
Marine geological sampling points with with associated information on shell sand content (must be over 50%) and shell sand class in the upper part (about 0-40cm) of seabed. Samples are obtained with grab or box corer and geological descriptions are based on visual observations of sediments.
The data table includes information about sampling, depth, geology and biology.
MAREANO, GEOS Oslofjorden, Marine grunnkart i Astafjord, fase III, ICZPM – AquaReg pilotprosjekt, Marine grunnkart i Sør Sunnmøre, Marine Grunnkart i Sore Sunnmore, Kartlegging av Saltstraumen marine verneomtåde, Frisk Oslofjord (MAREANO, GEOS Oslofjorden, AstafjordIII, AQUAREG, MGG, MG Sore Sunnmore, Saltstraumen MVO, Frisk Oslofjord)
Last metadata update: 2010-04-07T12:00:00Z
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Abstract:
Anchoring and mooring conditions in some coastal areas with detailed data coverage, as interpreted from bottom type (hard or soft bottom) and depth. It is distinguished between anchoring and mooring conditions. In this context mooring means the possibility for divers to mount bolts into exposed bedrock (to fasten marine installations), usually at depths less than 30m. Anchoring conditions mean the anticipated relative hold of anchors in the substrate.
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.