The core partner data centres that are integrated in NorDataNet are listed in https://www.nordatanet.no/en/node/69. In addition to this NorDataNet harvests information on relevant datasets from a number of other data centres. The data centre responsible for the data presented is usually (but not always) listed in the discovery metadata. In essence NorDataNet is an aggregating service that combines information from a number of existing data centres.
Citation of data and service
If you use data retrieved through this portal, please acknowledge our funding source:
Research Council of Norway, project number 245967/F50, Norwegian Scientific Data Network.
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)
All partner repositories of NorDataNet support Digital Object Identifiers (DOI), but not all datasets are minted. Whether or not minted depends often on source of the data (e.g. operational data are often yet not minted). However, all data centres support persistent identifiers according to local systems. The information required to properly cite a dataset is normally provided in the discovery metadata the datasets.
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 identified in the drop down menu with and phrases embedded in quotation marks. Prefixing a phrase with '-' negates the phrase (i.e. should not occur in the results). Searches are case insensitive.
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. The combination of search fields (including facets) is based on a logical "AND" combination of the fields, i.e. all conditions are fulfilled for the results provided.
Zooplankton were collected from Liefdefjorden (79°37 N, 12°57 E), and Kongsfjorden (78°96 N, 11°94 E), Svalbard, Norway, during cruises with R/V Teisten and R/V Lance (18-27 July 2008). In addition, a smaller set of samples was collected on the shelf break outside of Kongsfjorden (78°94 N, 8°54 E), for reference/comparative purposes.
a) Sea bed mapping and b) Glacial geological and paleo climatic research.Acustical profile data from seismic, penetration echo sounder and side-scanning sonar.
Background: Long time series of marine fauna and flora in the Arctic are rare. However, since the 1970’s, Norwegian scientists have both jointly with other international partners and independently been investigating the fjords and coastal areas of the arctic archipelago of Svalbard and surrounding seas. More recently, these research co-operation activities have been formalised through participation in the ARCTOS network. These research groups have access to the best available data to assess past changes in shallow Arctic pelagic and benthic ecosystems. In particular good baseline data from Kongsfjorden. In 1996, a transect of ten stations (NPI) was established from the inner part of the Kongsfjord to outside the shelf break at five discrete depth strata, and has been sampled several times a year. The data have been continuously processed until summer 2006. Additionally, a large data set has been gathered on fatty acid trophic markers and stable isotopes of zooplankton, fish and marine birds. Data on the taxonomic composition and structure of soft sediment environments have been gathered approximately every fifth year since 1997 by Akvaplan-niva and the Institute of Oceanology, PAS. The state of the Kongsfjorden ecosystem has been reviewed by several authors and the potential effect of climate swings by Falk-Petersen et al. (2007).Concurrent with the efforts made by ARCTOS, the Alfred Wegener Institute for Polar and Marine Research (AWI) established the 'HAUSGARTEN' in 1999 as the first and only long-term deep-sea observatory at high latitude (Soltwedel et al., 2005). It comprises 15 permanent sampling stations along a bathymetric transect from the Vestnesa Ridge to the Molloy Hole (1200-5500 m) and a latitudinal transect along the 2500 m isobath. These transects cross at the central HAUSGARTEN station, which serves as an experimental area for long-term experiments. Long-term investigations at HAUSGARTEN comprise various compartments of the ecosystem, including the water column and the deep seafloor. Repeated sampling and the deployment of moorings and long-term free-falling systems (bottom landers) has been conducted on an annual basis since 1999 and yielded an unrivalled time-series data set.Aim:•Connect the “Kongsfjord” and “HAUSGARTEN” bathymetric transects •Standardise the sampling strategy and protocol of both transects •Investigate the spatial distribution of zooplankton and benthos by use of existing data and new data collected by remote sensing techniques •Investigate seasonal and diel vertical migration by use of sediment traps and acoustic methods•Assess Arctic pelagic and benthic ecosystem changes in relation to climate factors such as sea ice, hydrography, NAO and AO indices•Adapt and apply existing models on marginal ice zone (MIZ) pelagic-benthic interactions in shallow waters to the HAUSGARTEN bathymetric transect data set•Set a baseline for future monitoring programmes with respect to megafaunal communities and food web structure at selected stations
Anthropogenic pollution and climate change are the two most significant threats for Arctic biodiversity and ecosystem functioning. Because of food chain biomagnification of lipophilic persistent organic pollutants (POPs), the polar bear is one of the species which have the highest levels of these harmful chemicals. Since POPs may have effects on hormone regulation and physiological homeostasis, reproduction and survival, POPs may adversely affect the plasticity of responses that polar bears have to environmental changes. Thus, in combination these two major anthropogenic factors may have a significant effect on Arctic ecosystem functions. The International Polar Year (IPY) project “BearHealth” aims at studying adverse health effects of POPs in polar bears, and the interacting effects of POPs and climate change on polar bears. In the circumpolar international project, several biomarker endpoints, such as immune, hormonal, vitamin, bone, and histological variables will be examined in relation to exposure to POPs and other emerging novel environmental pollutants. Analyses of chemicals and biomarkers will be conducted on archived material from biobanks, and on samples which will be sampled during the project period. In the Norwegian part of the project we will focus on health effects of POPs related to thyroid and reproductive hormone homeostasis and on vitamin A, E and D status, and on interactions between biomarkers, environmental pollutants and climate change variables, and on including new samples from polar bears from Svalbard and Barents Sea region. Efforts will also be made to obtain samples from the Russian Arctic. In cooperation with Danish researchers (which are the coordinators of the international BearHealth project), a study on POP related effects on bone density and structure will be performed on a large collection of polar bears skulls from the Norwegian Arctic and Greenland, and Russia if possible. The results from the Norwegian study will be integrated with the studies conducted by the other participating countries, and the project will end up in an integrated health risk assessment of the interactive effects of POPs and climate change in polar bears.
This dataset quantifies atmospheric, surface and sub-surface (active-layer) water fluxes in the proglacial area of the Svalbard glacier Finsterwalderbreen (77˚ N), through a combination of field measurements, physical modelling and statistical estimation, to determine the proglacial water balance over a complete annual cycle.
Geosystem monitoring at the Polish Polar Station Hornsund
Institutions: Institute of Geophysics, Polish Academy of Sciences
Last metadata update: 2022-04-29T13:30:00Z
Show more...
Abstract:
Raw imagery from the time-lapse camera system installed close to the Fugleberget summit in Hornsund. The imagery covers the lower part of Fuglebekken catchment and the coastline of Isbjørnhamna. Imagery downloaded at the end of the melting season. Imagery is taken every 3 hours. Occasional gaps due to clouds, icing and equipment failure. Calculation of Fractional Snow Cover (FSC) is the main purpose of the dataset. FSC was processed for the time period: 2014-2016
Flow-recession analysis and linear- reservoir simulation of runoff time series are used to evaluate seasonal and inter-annual variability in the drainage system of the glacier Finsterwalderbreen, Svalbard Arctic archipelago, in 1999 and 2000, with particular reference to the inferred structure of subglacial flow pathways. Original publication data are included and also an introductory, Microsoft Excel-based tutorial on the methods used.
This is a dataset containing SWE data for the period 1982-2015, generated using a coupled energy balance - snow model. This is a selection of data contained in the larger dataset of surface and snow conditions in Svalbard, described in Van Pelt et al. (2019; https://doi.org/10.5194/tc-13-2259-2019). The data is used in the SESS report 2020, and contains MATLAB structures with daily SWE maps, rescaled to a 4x4 km resolution from the original 1x1 km resolution.
Institutions: Institute of Geophysics, Polish Academy of Sciences
Last metadata update: 2022-04-29T13:30:00Z
Show more...
Abstract:
Seismic data recorded by a permanent seismological station located in Spitsbergen. Seismic records can be used for seismological and cryoseismological studies, data is gathered continuously and access is open.
Seismic data recorded by a permanent seismological array located in Spitsbergen. Seismic records can be used for seismological and cryoseismological studies, data is gathered continuously and access is open.