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.
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 insitu observations. This dataset is the predecessor of the gridded ice charts based on satellite data and other sources. This dataset primarily identifies the sea ice edge.
Institutions: Norwegian Water Resources and Energy Directorate (NVE)
Last metadata update: 2024-03-13T11:33:04Z
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Abstract:
The climate change indicator products of glaciers in mainland Norway include surface mass balance and length change (from NVE’s field observations) and area changes (from satellite imagery and topographical maps) for a selection of glaciers. Glacier surface mass balance and glacier length change are obtained directly from NVE’s databases. https://glacier.nve.no/Glacier/viewer/CI/en/cc
Institutions: Norwegian Water Resources and Energy Directorate (NVE)
Last metadata update: 2024-03-13T11:33:04Z
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Abstract:
Glacier Periodic photos (GPP) from Norwegian glaciers. The photo series illustrate how the extent of a selection of Norwegian glaciers have changed. The pictures are not taken from the same position each year. The earliest photos are from the 1860s. The majority of the pictures are from the last 20 years. The number of photos per glacier varies. The source of the data is NVEs photo archive, with contributions from NVE collaborators. https://glacier.nve.no/Glacier/viewer/gpp/en/cc/
The UNIS Hydrographic Database (UNIS HD) is a collection of temperature and salinity profiles from the area (0-34°E and 75-83°N). Main data contributors are The University Centre in Svalbard (UNIS), University of Bergen (UiB), Institute of Marine Research (IMR), Norwegian Polar Institute (NPI), the Arctic University of Norway (UiT), Institute of Oceanology Polish Academy of Sciences (IOPAS), The Scottish Association for Marine Science (SAMS), Arctic and Antarctic Research Institute (AARI), and Alfred Wegener Institut (AWI). Additional data in the database have been extracted from other data publishers; the Norwegian Marine Data Centre (NMDC, https://www.nmdc.no), the dataset catalogue of the Norwegian Polar Institute (https://data.npolar.no/dataset), the International Council for the Exploration of the Sea (ICES) dataset on ocean hydrography (https://ocean.ices.dk/HydChem), the PANGAEA data publisher (https://www.pangaea.de), the North Atlantic and Nordic Seas hydrography collection (NANSHY; Nilsen, 2015) based on the dataset from the project Norwegian Iceland Seas Experiment (NISE; Nilsen et al., 2008), and the Unified Database for Arctic and Subarctic Hydrography (UDASH; Behrendt et al., 2018). Data are processed with standard software from the instrument manufacturers, and most of them calibrated with in situ water bottle analysis and post-cruise calibration. However, calibration has not been quality checked in all the data, so use with caution (salinity values in particular). Duplicate data and outliers are removed. Remaining profiles are provided with information of owner or source institution and citation when possible (see Citation list).
Acknowledgment: The compiling of UNIS HD was financially supported by the projects REOCIRC (#222696/F50) and GrønnBille (#227067, RIS-ID 6700) funded by the Research Council of Norway (RCN). We would like to thank all the students and colleagues at UNIS for their valuable effort in collecting data during the UNIS student and research cruises over the years.
The Sea Bird Colony Database contains current and historical data for all known seabird colonies in Svalbard and around the Barents Sea, including total counts, surveillance data, photographic documentation and references. The database is owned and annually maintained by the Norwegian Polar Institute in partnership with seven Russian institutions.
MS Access database, originally created by Vidar Bakken.
Quality
The data quality is “best available”, and highly variable as the database contains historical data, as well as data from recent surveys and censuses. A few, selected colonies are revisited and counted annually, while others are rarely revisited due to their remote locations. A substantial number of colonies are registered with historically recorded positions that are not accurate.
A brief explanation of all the fields in the seabird-colony database:
colony_name - Colony’s name.
colony_alternative_name - Colony’s alternative name.
region - the region the colony belongs to.
zone:The zone the colony belongs to which could be f.ex. Hornsund, Bellsund, Isfjorden, Prins Karls Forland etc. From a collection of names.
latitude: The colony’s latitude.
longitude: The colony’s longitude.
location_accuracy: How accurate is the given latitude/longitude? Measured in meters, by GPS or on digital map.
conservation_type: Is the colony located in an area which holds a particular conservation status?
colony_type: The type of terrain the colony is situated in.
ownership: Who owns the colony location.
island: Name of island if colony not situated on the mainland.
island_size: Size of island if colony not situated on the mainland.
island_archipelago: The island belongs to this archipelago.
length: Length of coastline where the colony is situated - usually applies to coast colonies.
distance: Distance from colony to closest coastline.
distance_mainland: Distance from colony to the mainland.
exposure: Direction of the colony- south, west, etc.
area: Area of cliff wall if situated on a vertical cliff (or hillside).
confirmed: Year the colony first were described in literature.
map: The map that shows the colony place, for Svalbard typically numbered maps f.ex. “E8-BARENTSJØKULEN”.
comment: Comment about the colony.
geometry: GeoJSON object outlining the colony
historical_colony: Where the colony first was described - field used f.ex. if colony can’t be found anymore to keep old data.
colony_area: 1 if there exists a location area polygon for the colony an 0 if not.
predators: Who is predating the colony.
access_id: The corresponding MS access database id for count.
species: Which species.
start_date: Start date of counting.
end_date: End date of counting.
mean: Mean count value for the species in the colony.
max: Max count value for the species in the colony.
min: Min count value for the species in the colony.
accuracy: Count accuracy.Exact or rough estimate.
unit: Unit used for counting - pair, individual, nest, apparently occupied nest etc
method: Counting method used - direct count, from photograph, extrapolated, combination etc.
platform: Viewed from platform - land, boat, helicopter etc.
breeding: Stage of breeding - pre-laying period, eggs only, hatching period etc.
useful: Useful as total count.
count_comment: comment about the count.
colony_reference: This is one or more literature references where the colony has been described.
colony_reference.ref_id: RefenceID from MS database.
colony_reference.ref_unique_id: refence id most likely from the old DBase database.
colony_reference.authors: Publication authors.
colony_reference.title: Publication title.
colony_reference.year: Year publication was published.
Institutions: Norwegian Water Resources and Energy Directorate (NVE)
Last metadata update: 2022-11-15T12:01:24Z
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Abstract:
Glacier Area Outline (GAO) for western Finnmark from the period 1895-1907. Source:
"Gradteigskart" constructed from land surveys between 1895-1907, three paper maps printed at a scale of 1:100 000 include the five largest ice caps - Normannsjøkelen, Seilandsjøkelen, Øksfjordjøkelen, Svartfjelljøkelen and Langfjordjøkelen. The maps were georeferenced and digitised by NVE. The maps have poorer accuracy compared to N50-maps, and rubber sheeting was needed to do a transformation. The glacier outlines are uncertain and must be taken as a rough estimate due to the poorer quality of these old maps.
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 0-578-0-99840. Data are climate consistent following a number of automated and manual quality control routines.
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 0-578-0-99765. Data are climate consistent following a number of automated and manual quality control routines.
Digital geological map of Svalbard at the scale of 1:750000.
Subdivision of geology is according to stratigraphic group, subgroup or formation, depending on which is best applicable to the given scale. Where no formations are defined in parts of the geological basement, lithological units are defined instead
Quality
Spatial Reference: WGS84/UTM zone 33N (EPSG: 32633)
Digital geological map of Svalbard at the scale of 1:250000.
Subdivision of geology is according to stratigraphic group, subgroup or formation, depending on which is best applicable to the given scale. Where no formations are defined in parts of the geological basement, lithological units are defined instead.
Quality
Spatial Reference: WGS84/UTM zone 33N (EPSG: 32633)
Datasettet består av start- og sluttpunkt for kartlegging av strandsøppel og linjene mellom disse. Fra 2011 er det lagt om til ny metodikk, og overvåkingen vil heretter bare foregå på Brucebukta og Luftskipodden (ny lokalitet).Tidligere ble også Breibogen og Isflakbukta overvåka (med MOSJ-metodikk). OSPAR- og MOSJlokaliteter har ulik overvåkingsmetodikk.
Data on various environmental resources have been assessed for vulnerability to acute oil pollution and given a priority 1 to 3, 3 being the most vulnerable. Resources included are shoreline cultural heritage sites, walrus and harbour seal haul-out sites, seabird colonies, anadromous Arctic charr river outlets, and shoreline substrate. The dataset is meant to help prioritize clean-up efforts in the immediate phase after a spill has occurred.
Datasettet viser områder med begrensninger på jakt utover dei generelle reglane i Svalbardmiljølova på Svalbard.
Rundt Longyearbyen er forskrift om skyteforbud på høring i 2012. Planlagt utvidelse av skyteforbudssonendenne sonen. Følgjande forskrifter regulerer forbudsområder for jakt på Svalbard:
- Skyteforbudssone rundt Longyearbyen
- Alt vilt freda (=jaktforbud) i naturreservat på østsvalbard og i fuglereservat
- Rypejakt tillatt etter søknad i Sør-Spitsbergen, Forlandet og Nordvest-Spitsbergen nasjonalparker
- Bjørnøya naturreservat
- Hopen naturreservat
- Moffen naturreservat
- Midterhuken Reinsjakt og fangst av fjellrev er kun tillatt i nærmere bestemte områder.
Endringer i jaktforbudsområder krever i de fleste tilfeller endring av forskrifter.
Quality
Scale Range: Maximum (zoomed in) 1:5000; Minimum (zoomed out) 1:150000000 Spatial Reference: WGS84/UTM zone 33N (EPSG: 32633)