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
Outline of the data portal search interface.
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.
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.
Arctic ABC Development, Deep Impact, Centre for Autonomous Marine Operations and Systems (NFR grant 245929, NFR project no 300333, NFR project no 223254)
Institutions: UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, Norwegain Infrastructure for Research Data (NIRD)
Last metadata update: 2022-11-15T15:30:23Z
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Abstract:
UiT The Arctic University of Norway (UiT) and the Norwegian University of Science and Technology (NTNU) established a light observatory at Kings Bay, Ny-Ålesund (Svalbard, Norway) in January 2017. The observatory consists of an array of light sensors including an all sky camera. It is located outside the settlement of Ny-Ålesund, approximately 1 km N-NW of the airport towards Brandalspynten. The array of sensors is mounted on a tripod under a transparent dome. This dataset contains the data of the hyperspectral radiometer USSIMO (In-situ Marine Optics, Perth, WA, Australia), converted to E(PAR) by the following equation: PAR is approximated as an integral of micromolespersec=(uirr/(h*c/(lambda*1e-9)))/microavo for wavelengths(lambda) in range from 400 to 700nm, where: uirr = USSIMO irradiance for wavelength equal to lambda, h=6.63e-34 [Js], c=3.00e+08 [m/s], microavo=6.022e17. The sensor is equipped with a Zeiss MMS1 UV-VIS NIR detector with National Institute of Standards and Technology, USA traceable radiometric calibration between 380 and 900 nm. This instrument is used for time-series measurement of down-welling spectral irradiance in energy Wm-2 nm-1. Spectral resolution is 10 nm (3.3 nm pixel spacing) and a cosine-corrected polytetrafluoroethylene (PTFE) light diffusor with cosine error: <3% (0 - 60°), <10% (60 - 87.5°), is fitted. The device acquired measurements with a 16 bit analogue to digital converter. It samples continuously internally. Integration time is controlled by the sensor depending on the light intensity, with a maximum of 6 seconds. Actual integration time is stored with the data in each sample. The sensor output is saved on a PC with custom software which records 30 seconds of output data every 29:30 min. The number of samples collected in that period depends on the USSIMO integration time. The sensor is equipped with a pitch and roll sensor which is used to ensure that the spectroradiometer remains in the fixed position throughout the time-series acquisition. For re-use of the data, please refer to the dataset and the original publication. This is an aggregated dataset that combines the invidual datasets into a continous timeseries. For details check out https://archive.norstore.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00039,https://archive.norstore.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00044,https://archive.norstore.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00045 and https://archive.norstore.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00046.
Institutions: UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, Norwegain Infrastructure for Research Data (NIRD)
Last metadata update: 2022-11-15T15:30:23Z
Show more...
Abstract:
UiT The Arctic University of Norway (UiT) and the Norwegian University of Science and Technology (NTNU) established a light observatory at Kings Bay, Ny-Ålesund (Svalbard, Norway) in January 2017. The observatory consists of a range of light sensors including an all sky camera. It is located outside the settlement of Ny-Ålesund, approximately 1 km N-NW of the airport towards Brandalspynten. The array of sensors, including the camera, is mounted on a tripod under a transparent dome. This dataset contains the E(PAR) data derived from pictures taken during 2017 at hourly intervals by the all-sky-camera. The camera (Canon EOS 5D Mark III) is equipped with a fish-eye lens with a focal length set to 8 mm with aperture manually set to open (f/4) to ensure maximum sensitivity (Canon EF 8-15mm f/4L), providing a 180° image of the atmosphere (only possible with a full-size sensor). Both shutter speed (exposure time, ranging from 0.000125 to 30 seconds) and ISO (sensitivity, ranging from 100 at Midnight Sun period and up to 6400 during Polar Night) are set to auto. White balance manually set to “day light”. It is remotely controlled by a PC, pictures were stored in a cloud storage. Short gaps in the time series are due to power failures. In this dataset there are two large gaps: 2019-01-09 to 2019-03-08 and 2019-06-24 to 2019-09-25 caused by a crash of the controlling PC which was not monitored at that time. The equations for the picture-to-E(PAR) conversion can be found in: Johnsen et al 2021, An all-sky camera system providing high temporal resolution annual time-series of irradiance in the Arctic, Applied Optics. The pictures on which this dataset is based on can be found at . For re-use of the data, please refer to the dataset and the original publication. this is an aggregated dataset where the individual timeseries have been combined into a continous timeseries. For details on the dataset please check https://archive.norstore.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00040,https://archive.norstore.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00041,https://archive.norstore.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00042 and https://archive.norstore.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00043.
The data has been collected during the Nansen Legacy Seasonal Study Q1 from 2 - 25 March 2021 on research vessel RV Kronprins Haakon (cruise number 2021703), along a transect in the northern Barents Sea from 76N to 82N. The dataset contains abundance of pelagic marine protists, including phytoplankton (autotrophic) and protozooplankton (heterotrophic). Protists were identified and counted with light microscopy using the Utermöhl method and the result are given as cells per liter (cells/L) called organismQuantity.
The data has been collected during the Nansen Legacy Seasonal Study Q2 from 27 April - 20 May 2021 on research vessel Kronprins Haakon (cruise number 2021704), along a transect in the northern Barents Sea from 76N to 82N. The dataset contains abundance of pelagic marine protists, including phytoplankton (autotrophic) and protozooplankton (heterotrophic). Protists were identified and counted with light microscopy using the Utermöhl method and the result are given as cells per liter (cells/L) called organismQuantity.
Time-series data from moorings covering the Svalbard Branch of the Atlantic Water inflow over the upper continental slope north of Svalbard, Sep 2017 to Nov 2019. The data comprise temperature, salinity and other parameters from CTDs, and water currents from ADCPs.
The data has been collected during the Nansen Legacy Joint Cruise 2-1 from 12 - 29 July 2021 on the research vessel RV Kronprins Haakon (cruise number 2021708), along a transect in the northern Barents Sea from 76N to 82N. The dataset contains abundance of pelagic marine protists, including phytoplankton (autotrophic) and protozooplankton (heterotrophic). Protists were identified and counted with light microscopy using the Utermöhl method and the result are given as cells per liter (cells/L) called organismQuantity.
Time-series data from moorings covering the Svalbard Branch of the Atlantic Water inflow over the upper continental slope north of Svalbard, Sep 2013 to Sep 2015. The data comprise temperature, salinity and other parameters from CTDs, and water currents from ADCPs.
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.
The data has been collected during the Nansen Legacy Seasonal Study Q3 from 5 - 27 August 2019 on research vessel RV Kronprins Haakon (cruise number 2019706), along a transect in the northern Barents Sea from 76N to 82N. The dataset contains abundance of ice algae marine protists, including ice algae (autotrophic) and protozoa (heterotrophic). Protists were identified and counted with light microscopy using the Utermöhl method and the result are given as cells per liter (cells/L) called organismQuantity