The SIOS Data Management Service (SDMS) integrates information from SIOS partner data repositories into a unified virtual data centre, the SIOS Data Access Portal, allowing users to search for and access data regardless of where they are archived. Providers and users have to commit to the SIOS data policy.
The current focus is on dataset discovery through standardised metadata, and retrieval, visualisation & transformation of data. Ultimately, the Data Management Service works towards integration of datasets which requires a high level of interoperability at the data level.
SDMS currently harvests information on SIOS relevant datasets from a number of data centres (see below), some hosted by SIOS partners and some not. Data centres hosted by SIOS partners work to harmonise access to the data allowing integrated visualisation etc for the relevant datasets.
Data centres SDMS is harvesting information from.
SIOS partner data centres
Other
AWI (DE)
British Antarctic Survey
CNR (IT) - temporarily disabled due to server issues
National Snow and Ice Data Center
IGPAS (PL)
IMR (NO)
IOPAN (PL)
MET (NO) - weather stations have not been updated for a while, update in progress
NERSC (NO)
NILU (NO)
NIPR (JP)
NPI (NO)
UiS (PL)
Citation of data and service
If you use data retrieved through this portal, please acknowledge our funding source: Research Council of Norway, project number 291644, Svalbard Integrated Arctic Earth Observing System – Knowledge Centre, operational phase.
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)
SIOS recommends all partner data repositories to mint Digital Object Identifiers (DOI) on all datasets. The information required to properly cite a dataset is normally provided in the discovery metadata the datasets.
SIOS Core Data
In order to find SIOS Core Data please use the searchable item marked "Collection" on the right hand side of the map and select "SIOSCD". Quick access to SIOS Core Data is provided here.
Nansen Legacy Data
The Nansen Legacy project is using the SIOS Data Management system as the data portal. Quick access to all Nansen Legacy related datasets is available here.
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 from the drop down above the text field and prefixing words with '+' to require their presence and '-' to require their non presence.
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.
Spatiotemporal variability in mortality and growth of fish larvae and zooplankton in the Lofoten-Barents Sea ecosystem, The Nansen Legacy (SVIM, NLEG)
Institutions: Institute of Marine Reseach - Norway, Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute
Last metadata update: 2024-01-03T11:42:12Z
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Abstract:
The SVIM archive contains results from an ocean and sea ice hindcast. The original version of the archive covered the period 1960-2011, and has later been extended on several occasions. The results are provided on a 4km polar stereographic grid projection, and the ocean model has a vertical resolution of 32 s layers. The focus is an adequate representation of the Atlantic influenced water masses within the Nordic Seas and the Barents Sea. Less emphasize has been put on the areas downstream of the Arctic bound Atlantic Water flow, i.e. the Arctic Ocean and the Greenland Sea. There were multiple aims for this product, including (1) process studies within physical oceanography, (2) representation of oceanographic conditions for other applications such as primary production models and individual-based models for zoo- and ichtyoplankton, (3) boundary values for smaller scale model studies. For ocean circulation the Regional Ocean Modeling System (ROMS; https://www.myroms.org/) was used (v.3.2 up to and including September 2018, v.3.5 thereafter). The sea-ice model used is similar to the module described in Budgell (Ocean Dyn. 2005). Boundary values for the ocean model were derived from the Simple Ocean Data Assimilation dataset (SODA v.2.1.6), while boundary values for the sea ice conditions were taken from a regional simulation (Sandø et al., JGR 2012). After 2008, the ocean boundaries were forced with monthly climatologies from 2000-2008, while for ice conditions after 2007, the 2000-2007 monthly climatologies were used. Tidal forcing was based on the global ocean tides model TPXO4. The quality of the model results for the original archive period were assessed by Lien et al. (2013; https://www.hi.no/resources/publikasjoner/fisken-og-havet/2013/fh_7-2013_swim_til_web.pdf).
Spatiotemporal variability in mortality and growth of fish larvae and zooplankton in the Lofoten-Barents Sea ecosystem, The Nansen Legacy (SVIM, NLEG)
Institutions: Institute of Marine Reseach - Norway, Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute
Last metadata update: 2024-01-03T11:42:12Z
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Abstract:
The SVIM archive contains results from an ocean and sea ice hindcast. The original version of the archive covered the period 1960-2011, and has later been extended on several occasions. The results are provided on a 4km polar stereographic grid projection, and the ocean model has a vertical resolution of 32 s layers. The focus is an adequate representation of the Atlantic influenced water masses within the Nordic Seas and the Barents Sea. Less emphasize has been put on the areas downstream of the Arctic bound Atlantic Water flow, i.e. the Arctic Ocean and the Greenland Sea. There were multiple aims for this product, including (1) process studies within physical oceanography, (2) representation of oceanographic conditions for other applications such as primary production models and individual-based models for zoo- and ichtyoplankton, (3) boundary values for smaller scale model studies. For ocean circulation the Regional Ocean Modeling System (ROMS; https://www.myroms.org/) was used (v.3.2 up to and including September 2018, v.3.5 thereafter). The sea-ice model used is similar to the module described in Budgell (Ocean Dyn. 2005). Boundary values for the ocean model were derived from the Simple Ocean Data Assimilation dataset (SODA v.2.1.6), while boundary values for the sea ice conditions were taken from a regional simulation (Sandø et al., JGR 2012). After 2008, the ocean boundaries were forced with monthly climatologies from 2000-2008, while for ice conditions after 2007, the 2000-2007 monthly climatologies were used. Tidal forcing was based on the global ocean tides model TPXO4. The quality of the model results for the original archive period were assessed by Lien et al. (2013; https://www.hi.no/resources/publikasjoner/fisken-og-havet/2013/fh_7-2013_swim_til_web.pdf).
File “Fig_11_catch_harvestrate_and_stock.xls” give annual catches, stock abundance and harvest rates for the main commercial Barents Sea fish stocks (including shrimp which is the main shellfish stock). The harvest rates are derived from catches and stock abundance. Catches are given from 1965 onwards for all stocks, while the time series of stock abundance and thus harvest rates start later than 1965 for several stocks.
The maximum observed fast-ice thickness per season at Hopen (part of the Svalbard) during the period 1965/66 - 2007/08. The data file has two columns: a) the year the data connects to, and b) the thickness numbers in meters. If an observation is missing, data is set to 999.
Most ice thickness data were collected from drill holes in shore-fast sea ice within 150 m of shore. The accuracy for an ice thickness reading is 0.01 m (reading interval). Drill sites are not at the identical spot for each measurement throughout a season, resulting in apparent thickness changes due to local variability in ice thickness.
See also Søreide, O., 1994. Hopen. Ishavsøy og meteorologisk stasjon, 158 pp., Friske Tankar A. S., Øystese, Norway.
Quality
Since 1946, a Norwegian permanently manned meteorological station has been in operation on Hopen’s east coast (76° 30´N, 25° 01´E) where standard meteorological data are collected (Søreide, 1994). Regular ice thickness measurements were initiated in the 1960s by Torgny Vinje, Norwegian Polar Institute, resulting in 40 years of ice thickness measurements since winter 1965/1966 (Gerland et al., 2008). The fieldwork is conducted by the Hopen wintering teams of the Meteorological Institute of Norway (met.no), on request by and in collaboration with the Norwegian Polar Institute. The fast ice monitoring was recently updated and follows now a procedure similar to the Norwegian Polar Institute’s fast ice monitoring at Kongsfjorden at the western coast of Spitsbergen, Svalbard (Gerland and Renner, 2007).
The Norwegian Polar Institute measures mass balance on three glaciers, all in the Kongsfjorden area of north-western Spitsbergen, Svalbard. They are: Austre Brøggerbreen (data since 1967, Midtre Lovénbreen (since 1968) and Kongsvegen (since 1987). The first two are among the longest continuous high arctic glacier mass balance time-series. The Norwegian Polar Institute uses the so-called “combined method”, a mixture of the fixed-date and the stratigraphic methods, and comprises sounding of winter snow depth and repeated measurement of heights of an array of 8-10 stakes along the glacier centerline. Winter balance is obtained by snow-depth soundings over much of the glacier, an estimate of the autumn superimposed ice by shallow ice-cores along the longitudinal axis or at least by a measurement at the bottom of snow pits, stake height measurements, and snow density measurements. The work is carried out at the end of the accumulation period, in May. Stake positions are measured using differential GPS every year to monitor long-term velocity and elevation changes, both of which respond to the yearly mass fluctuations. Summer balance is obtained directly by comparing stake heights made in spring to fall stake measurements. The latter work is usually done at the end of the ablation period (in September and sometimes in October). Balance estimates are extrapolated over the entire glacier basin by using the distribution of glacier area per 50-m elevation band (hypsometry) obtained from maps or digital elevation models (DEMs). Net, winter and summer mass balance values are reported each year to MOSJ and as well to the World Glacier Monitoring Service.
Institutions: Norwegian Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-11-15T15:00:52Z
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Abstract:
The product is based on a manual interpolation of available satellite data and insitu observations and provides a gridded map. It is a continuation of the previous sea ice chart which basically identified the ice edge.
Timeseries recorded at the mooring S1, at nominal depth of 1000 m during different deployments. The scope of the measurements is to study the temporal variability of the thermohaline properties of the Norvegian Deep Water, and assosiated deep flow
Time-series recorded at the mooring MDI in inner Kongsfjorden, at nominal depths of 35 m and 85 m during different deployments.
MDI allows us to continuously monitor the variations of the thermohaline characteristics of:
a) intermediate water that derives from the intrusion of Atlantic-type water;
b) bottom water produced locally during the winter.
Furthermore, through the collection of particulate matter, information is acquired on sedimentary processes and interactions between water and particulate matter with microzooplankton, glaciers and coastal runoff.
To study the Svalbard reindeer and their basis of existence.Part of Nils Are Øritslands work over many years. Based on field work and hunting material. The hunting material is from 1984, 1986 and 1987 and contains the age mix of the animals.Countings, observations and experiments
Spectral measurements of radiation over the wavelength range 300-800nm in Ny-Ålesund. Six types of measurements: 1) Clear sky and sun 2) Clear sky alone 3) Sky totally covered by clouds 4) Sky totally covered by fog 5) Zenith clear sky 6) Zenith overcast skyMeasurements with equipment from the roof of NPI's research station.
Comparative studies of vocal repertoires over the geographical range of a species can improve ourunderstanding of the function and evolution of animal vocalizations. They may also help to elucidaterelationships between populations, where genetic studies are missing or difficult to perform. We recordedmale bearded seal vocalizations from four sites throughout their Arctic distribution. We measured 16parameters for each vocalization and examined variability using classification tree analyses. There werefour major call categories: trill, ascent, sweep and moan. Trills divided further into three subcategories:trills with ascent/plume, long trills and short trills. Not all call categories were present at all sites: the ascentoccurred only in Alaska and western Canada, the sweep occurred only in Svalbard and in the High CanadianArctic, and the trill with ascent/plume occurred at all sites except Svalbard. Geographical differencesbetween sites were apparent in repertoire size as well as in vocal structure. Furthermore, an eastwestgradient in structural similarities between call types was apparent. The vocal repertoire of bearded sealsseemed to be relatively stable; for example, over a period of 16 years no calls were lost or added to theAlaskan repertoire. The most likely explanation for the observed vocal differences between sites is thegeographical isolation of populations by physical distance. Other factors, such as varying ecological influences(e.g. adaptation to varying ice habitats) or sexual selection, may also contribute to vocal variabilityand result in the observed geographical variation.
The dataset contains high resolution seismic reflection profiles from the inner part of Kongsfjorden, printed on paper, with selected profiles photocopied. The profiles were taken in summer 1974 during an investigation into glacial processes and the glacial history of Svalbard by G.S.Boulton. There was no attempt to systematically cover the whole of Kongsfjorden but to establish some profiles in what were judged to be critical or representative locations. It was hoped that the profiling would provide a seismic stratigraphy.
The dataset and data collection methods are described in the attached data report. The printed profiles are in storage at the Norwegian Polar Institute (geology archive).
Quality
The profiling system was based on a multi-electrode sparker. It was an analogue system with real time display of the profiling results, and no recording of the data to enable post acquisition processing. Adjustments to get optimum quality had to be done whist operating in the field situation, sometimes a quite difficult - and frustrating - task. Recording parameters could be quite sensitive.
The index of temperature and salinity is calculated by averaging the values over an area within the routinely monitored hydrographical fixed section. The data are from cruises in: January, March, April/ May/June, August/September, October.
This is a bedrock geological map of Jan Mayen distributed as vector files, a georeferenced raster and a related non-spatial lithostratigraphy table.
The map was compiled by W.K. Dallmann and published in Gabrielsen et al. (1997). A version was also published in Dallmann (2014), and the geology of this current edition is equivalent to that publication. The compilation was based on Imsland (1978), Roberts and Hawkins (1965) and Siggerud (1972, 1986)
Institutions: Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute
Last metadata update: 2023-10-26T11:47:12Z
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Abstract:
Quality controlled timeseries from Norwegian weather station 0-578-0-99760. Data are climate consistent following a number of automated and manual quality control routines.