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.
icemod_monthly.tar.gz contains the gridded monthly averaged quantities used in the manuscript "Modelling the evolution of Arctic multiyear sea ice over 2000-2018" for each year between 2000 and 2018.Multiyear ice variables are conc_myi (concentration of multiyear ice in a grid cell) and thick_myi (cell average thickness of multiyear ice in a grid cell, in metres), along with source and sink terms (units per day) for multiyear concentration (dci_mlt_myi, dci_ridge_myi and dci_rplnt_myi, for melt, ridging and replenishment) and volume (dvi_mlt_myi and dvi_rplnt_myi, for melt and replenishment).transports_monthly_sections.zip contains the transports of multiyear ice through the sections defining each region in Figure 8 of the paper. MYIsiaXport indicates multiyear ice area transport, while myiXport indicates multiyear ice volume transport.In case information is missing, do not hesitate to contact heather.regan@nersc.no, guillaume.boutin@nersc.no, or einar.olason@nersc.no.
The dataset contains 2 archives. The first archive contains all data (saved as netCDF files) relative to the Figures presented in Boutin et al. (2023). The second archive contains monthly averaged fields (saved as netCDF files) of the simulation described in Boutin et al. (2023). They include quantities relative to sea ice properties (icemod files) and to the mass balance (ice growth/melt etc... simba files). They cover the north Atlantic and the Arctic Ocean (north of Bering Strait) for the period 2000-2018.
Institutions: UiT The Arctic University of Norway, UiT The Arctic University of Norway
Last metadata update: 2024-01-19T11:29:43Z
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Abstract:
An X-ray scan of Priapulopsis bicaudatus. Sample collected by Bodil Bluhm in field (2019-08-16), preserved in 70% EtOH, then stored as a voucher specimen at The Arctic University Museum of Norway with collection number TSZY 427. Before scanning the specimen was encapsuled in wax, then imaged in a Zeiss Xradia Versa 620.
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).
Dissolved inorganic nutrients (nitrate, phosphate and silicic acid) from the combined Nansen Legacy and A-TWAIN cruise Mooring service cruise 2021 (cruise 2021713).
The cruise 2021713 in November 2021 aboard the Research Vessel Kronprins Haakon is part of the projects A-TWAIN and the Nansen LEGACY. The A-TWAIN project is focusing on monitoring of the Atlantic Water boundary current north of Svalbard. The Nansen LEGACY is the Norwegian Arctic research community’s joint effort to establish a holistic understanding of a changing marine Arctic climate and ecosystem.
Water column temperature and salinity profiles were obtained with a conductivity-temperature-depth (CTD) sensor system Sea-Bird SBE 911+ mounted on a General Oceanics rosette sampler equipped with 24 Niskin bottles used for seawater sampling of chemical variables in the water column. Samples for the determination of dissolved inorganic nutrients were collected from full water column at a total of six stations starting from the shelf northern Barents Sea to the Nansen Basin along the moored A-TWAIN line. The seawater samples were collected from Niskin bottles in 20 ml plastic HDPE vials (rinsed three times) and preserved with 250 µL chloroform and stored +4C and dark until post-cruise analysis of nitrite (NO2), nitrate (NO3-), phosphate (PO43-), and silicate (Si(OH)4), using spectrophotometry according to standard protocols (Grasshoff et al., 2009; Gundersen et al., 2022) at the chemical laboratory at Institute of Marine Research, Bergen, Norway. Three replicates were analyzed for each sample. The detection limits based on QUASIMEME ring-test are 0.06 µmol/L, 0.5 µmol/L, 0.06 µmol/L and 0.7 µmol/L for NO2, NO3-, PO43-, and Si(OH)4, respectively. The sampling and sample analysis were supported by the Research Council of Norway through the projects The Nansen LEGACY (RCN #276730) and SIOS-InfraNor (RCN #269927).
This dataset is a collection of averaged acid-corrected Chlorophyll a (Chla) and phaeopigments, and inorganic nutrient measurements taken as part of the combined Nansen Legacy and A-TWAIN mooring service cruise onboard RV Kronprins Haakon in November 2019, covering the northern Barents Sea and the Atlantic Water inflow region north of Svalbard. Water samples were taken from the CTD rosette at 11-12 depths throughout the water column for determination of Chla, and inorganic nutrients (nitrate plus nitrite (NO3− plus NO2−), phosphate (PO43-) and silicic acid (Si(OH)4 )/silicate (SiO2);concentrations in mmol m−3). For Chla, triplicates of 200 ml were filtered onto GF/F glass microfiber filters (Whatman, England) and frozen until further processing back in the laboratory at UiT The Arctic University of Norway. At UiT, samples were extracted in 5ml of methanol in darkness at 4C for ca. 24 h (Holm-Hansen and Riemann, 1978) and measured with a Turner Triology (Turner, USA). For inorganic nutrients, water samples of 200 mL were collected in acid-washed plastic bottles or in new and rinsed falcon tubes (3x 50 ml) and immediately frozen at -20C until further processing. Following standard methods (Grasshoff et al., 2009) back in the laboratory at UIT The Arctic University of Norway (Tromsø), three replicates were analyzed for each sample. Samples were analysed with a QuAAtro39 AutoAnalyzer (SEAL Analytical), calibrated with reference sea water (Ocean Scientific International Ltd., UK), with detection limits of 0.02 mmol m−3 for nitrate plus nitrite, 0.01 mmol m−3 for nitrite, 0.004 mmol m−3 for phosphate and 0.02 mmol m−3 for silicate (SiO2). The sampling and sample analysis were supported by the Research Council of Norway through the projects The Nansen LEGACY (RCN #276730) and SIOS-InfraNor (RCN #269927), and the Fram Centre project A-TWAIN, project no. 66050.
Holm-Hansen, O., Riemann, B., 1978. Chlorophyll a determination: improvements in methodology. Oikos 30, 438–447. https://doi.org/10.2307/3543338. Grasshoff, K., Kremling, K., Ehrhardt, M., 2009. Methods of Seawater Analysis. John Wiley&Sons, Edition 3, pp. 632
The data set present the calculated sea ice back-trajectories of 30 sea ice stations conducted in the northern Barents Sea and in western Arctic Basin north of Svalbard between August 2018 to March 2022. The sea ice stations were made during eight research cruises to the area with R/V Kronprins Haakon in the framework of the Nansen Legacy project. For details on the back-tracking methodology and data structure please see the attached metadata file NansenLegacy_sea_ice_stations_back-trajectories.pdf
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.
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.
Fatty acid-specific stable isotopes of the fatty acids 16:1(n-7), 20:5(n-3) and 22:6(n-3) in pelagic particulate organic matter (PPOM), ice-associated particulate organic matter (IPOM) and pelagic zooplankton species (copepods, krill, amphipods, chaetognaths, appendicularians) collected from the Barents Sea during Nansen Legacy seasonal cruise Q3 in August 2019
This dataset compiles Fatty Acid composition (relative proportions) of 4-day old Calanus hyperboreus nauplii from mothers collected in the Northern Barents Sea.
Gravid Calanus hyperboreus females were collected from the Northern Barents Sea during the Q1 Nansen Legacy Seasonal Cruise in March 2021. After hatching, 4-day old Calanus hyperboreus nauplii were used for a short-term incubation assay (24h), exposing the nauplii to acidification (pH 8.01 and 7.50) and warming (0°C and 3°C), both individually and in combination. Nauplii larvae were added to each replicate at a density of ~0.6 larvae mL-1. The bottles were kept in the dark in incubators at the target temperature for 24 hours. After the incubation, all larvae from each treatment were extracted and checked for survival, and the remaining individuals were stored in Eppendorf tubes, freeze-dried, and kept at -80°C for lipid content analysis.
Quality
The lipid content and fatty acid compositions of the copepod nauplii obtained from the incubation assays were analysed at the Alfred Wegener Institute in Bremerhaven, Germany. To acquire sufficient sample material for the analysis, between 100 to 148 individual larvae were pooled per sample. Triplicate samples (except for Treatment 3, which had duplicates) were analysed for each treatment. Before lipid extraction, the samples were freeze-dried for 24 h at -80 °C and then mechanically homogenized using a Potter-Elvehjem homogenizer. Total lipids were extracted by using a modified protocol from Folch et al., (1957), with dichloromethane/methanol (2:1, v/v), followed by cleaning with 0.88% potassium chloride solution. The extracted lipids were then transformed into fatty acid methyl esters (FAMEs) and free fatty alcohols derived from wax esters by transesterification in methanol containing 3% concentrated sulfuric acid, at 80 °C for 4 h. The FAMEs and alcohols were separated via an Agilent 6890N Network gas chromatograph (Agilent Technologies, USA) with a DB-FFAP capillary column (30 m, 0.25 mm I.D., 0.25 µm film thickness), equipped with a flame-ionization detector using a temperature program (160 to 240 °C). The samples were injected at 160 °C with helium as the carrier gas. The FAMEs were identified using standard mixtures, and the total lipid content was quantified as the sum of FAs and fatty alcohols using an internal standard (23:0) that was added prior to lipid extraction. The fatty acids are expressed in the nomenclature A:Bn-X, where A represents the number of carbon atoms, B the amount of double bonds, and X is the position of the first double bond starting from the methyl end of the carbon chain. The proportions of individual FAs are expressed as mass percentages of the total FA content.
This dataset compiles Fatty Acid composition (relative proportions) of 4-day old Calanus hyperboreus nauplii from mothers collected in the Northern Barents Sea. Gravid Calanus hyperboreus females were collected from the Northern Barents Sea during the Q1 Nansen Legacy Seasonal Cruise in March 2021. After hatching, 4-day old Calanus hyperboreus nauplii were used for a short-term incubation assay (24h), exposing the nauplii to acidification (pH 8.01 and 7.50) and warming (0°C and 3°C), both individually and in combination. Nauplii larvae were added to each replicate at a density of ~0.6 larvae mL-1. The bottles were kept in the dark in incubators at the target temperature for 24 hours. After the incubation, all larvae from each treatment were extracted and checked for survival, and the remaining individuals were stored in Eppendorf tubes, freeze-dried, and kept at -80°C for lipid content analysis.
Quality
The lipid content and fatty acid compositions of the copepod nauplii obtained from the incubation assays were analysed at the Alfred Wegener Institute in Bremerhaven, Germany. To acquire sufficient sample material for the analysis, between 100 to 148 individual larvae were pooled per sample. Triplicate samples (except for Treatment 3, which had duplicates) were analysed for each treatment. Before lipid extraction, the samples were freeze-dried for 24 h at -80 °C and then mechanically homogenized using a Potter-Elvehjem homogenizer. Total lipids were extracted by using a modified protocol from Folch et al., (1957), with dichloromethane/methanol (2:1, v/v), followed by cleaning with 0.88% potassium chloride solution. The extracted lipids were then transformed into fatty acid methyl esters (FAMEs) and free fatty alcohols derived from wax esters by transesterification in methanol containing 3% concentrated sulfuric acid, at 80 °C for 4 h. The FAMEs and alcohols were separated via an Agilent 6890N Network gas chromatograph (Agilent Technologies, USA) with a DB-FFAP capillary column (30 m, 0.25 mm I.D., 0.25 µm film thickness), equipped with a flame-ionization detector using a temperature program (160 to 240 °C). The samples were injected at 160 °C with helium as the carrier gas. The FAMEs were identified using standard mixtures, and the total lipid content was quantified as the sum of FAs and fatty alcohols using an internal standard (23:0) that was added prior to lipid extraction. The fatty acids are expressed in the nomenclature A:Bn-X, where A represents the number of carbon atoms, B the amount of double bonds, and X is the position of the first double bond starting from the methyl end of the carbon chain. The proportions of individual FAs are expressed as mass percentages of the total FA content.
This dataset compiles individual oxygen uptake rates of 4-day old Calanus hyperboreus nauplii when exposed to ocean acidification and warming, individually and in combination.
Quality
Gravid Calanus hyperboreus females were collected from the Northern Barents Sea during the Q1 Nansen Legacy Seasonal Cruise in March 2021. After hatching, 4-day old Calanus hyperboreus nauplii were used for a respiration assay, exposing the nauplii to acidification (pH 8.01 and 7.50) and warming (0°C and 3°C), both individually and in combination. The measurement of the metabolic rates took place by means of the loligo microplate system and took 12h. Subequently, the oxygent uptake rates were obtained by means of the RespR package in R (Rstudio) and were calculated into ng O2 per individual per hour. To our knowledge, this is the first dataset on naupliar oxygen uptake rates in a multiple stressor experimental design for Calanus hypeboreus from the Northern Barents Sea.
The dataset includes water column measurements of spectral beam attenuation and absorption coefficients by non-water constituents. Measurements were collected in May 2021 during cruise 2021704, Q2, in the northern Barents Sea as part of the Nansen Legacy project. The WET Labs ac-s spectrophotometer (Seabird Scientific) were used to collect in situ profiles, with a constant descent velocity (∼0.3 m/s) down to a depth of 350 m, or ~10 m below the ocean floor. Measurements were corrected for temperature and salinity effects. The proportional method was used to correct the scattering error of the absorption measurements, assuming zero absorption at 709 nm. The measurements were binned with 2.0 m (dbar) spacing, applying the median to average the data. See the referenced article for more information.