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)
The information required to properly cite a dataset is normally provided in the discovery metadata the datasets.
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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 through the drop down menu above the text field. Text strings that are not quoted are treated as separate words and will match any of the words (i.e. assuming the OR operator). Phrases may be prefixed with '-' to indicate no occurence of the phrase in the results.
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.
Faeces countsHerbivore faeces were counted as index of presence and activity. In addition, activity signs of small rodents, such as burrows and runways, were recorded. Counts were carried out at four sites in Russia: 1) Erkuta tundra monitoring site on Yamal Peninsula (Yamal), 68.2°N, 69.1°E2) Nenetsky Ridge in Nenetsky Autonomous district (Nenetsky), 68.3°N, 53.3°E3) Dolgi Island in Nenetsky Autonomous district, 69.2°N, 59.2°E (Dolgy)4) Mys Vostochny on western Taimyr, Kransoyarskii Krai, 74.1°N, 86.8°E (Taimyr)Count data from each site are in a separate file and coordinates of the plots at each site are also in separate files.Fecal pellets were counted in eight permanently marked small quadrates of 0.5 x 0.5 m arranged around a 15 x 15 m study plot. In Nenetsky (2007 and 2008) and in Yamal (2008) counts were performed twice per year, shortly after snow melt in spring (spring) and in the middle of August (fall). After counting, faeces were removed from the plots. In Yamal (2007), on Dolgy Island (2007) and in Taimyr (2008) counts were carried out only once in July. As faeces had not been removed previous to spring 2007 in Nenetsky and Yamal, and previous to the counts on Dolgy and in Taimyr, these counts may represent cumulative use over more than one winter. In Yamal faeces were counted in 3 habitats:T: Lush meadows adjacent to willow thickets. On these plots one 3 of the small quadrats were in the willow thicket (thicket indicates whether the plot was in the thicket or not).W: Moist tundra characterized by thick layers of Shagnum moss with Carex spp and Eriphorum spp tussocks, interspersed with R. chamaemorus and B. nana. D: Dry tundra characterized by ericoid dwarf shrubs, mainly R. tomentosum but also Vaccinium spp, B. nana and Eriophorum spp.Plots were grouped in 2 units (K and R) which each comprised 6 plots in each type of habitat.In Nenetsky faeces were counted in 3 habitats:W: lush meadows adjacent to willow thickets. On these plots one 3 of the small quadrats were in the willow thicket thicket (thicket indicates whether the plot was in the thicket or not).H: Hummock tundra dominated by cottongrass tussocks (Eriophorum spp) interspersed with dwarf shrubs and R. chamaemorusS: Shrubby tundra characterized by B. nana and ericoid shrubs (Vaccinium spp, Rhododendron tomentosum), interspersed with sedges (Carex spp) and Rubus chamaemorus.Plots were grouped in triplets of plots in each type of habitat. Triplets were grouped into 3 units, each lying in a different river valley and separated by ca 3 km. On Dolgy Island faeces were counted in 2 habitats:G: Grass and sedge dominated tundra, often with dwarf shrubs of Salix sppS: Dwarf shrub dominated tundra with Betula nana and Vaccinium spp.Plots were grouped in pairs of plots in each type of habitat. Pairs were grouped into 2 units separated by ca 3 km. On Taimyr faeces were counted in 2 habitats:I: Humid grass-sedge tundra with Salix spp dwarf shrubsB: Drier hummock tundra with prostrate shrubs and herbs. Plots were grouped in pairs of plots in each type of habitat. Pairs were grouped into 3 units separated by ca 3 km.
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
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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
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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.
The ACS_Bayelva_class dataset contains 302 high-resolution binary snow cover images that were obtained by classifying orthrorectified photographs of a 1.77 km^2 area of interest in the Bayelva catchment. This catchment is close to Ny-Ålesund, the northernmost permanent civilian settlement in the world and a major hub for polar research, in the Norwegian high-Arctic Svalbard archipelago. The imagery has a (roughly) daily temporal resolution and a ground sampling distance (pixel spacing) of 0.5 m. The dataset spans 6 snowmelt seasons, covering the months May-August for the period 2012-2017. The orthophotos were obtained by processing oblique time-lapse photographs taken by a terrestiral automatic camera system (ACS) mounted at 562 m a.s.l. near the summit of Scheteligfjellet (719 m a.s.l.) a few kilometers west of Ny-Ålesund. The orthophotos were manually classified into binary snow cover images (0=no snow, 1=snow) by iteratively selecting a (visually) optimal threshold on the intensity in the blue band for each image. More details are provided in the study of Aalstad et al. (2020) [a copy is available in this repository] where this dataset was created. The ACS was maintained by scientists from the group of Sebastian Westermann at the Section for Physical Geography and Hydrology in the Department of Geosciences at the University of Oslo, Oslo, Norway.
Time-lapse cameras are important data sources enabling us to observe changes in the Svalbard environment in an efficient and economically favorable way. Focusing on snow cover monitoring using cameras, it is important to identify potential image providers, archived imagery, and processed datasets.
Data belonging to the manuscript: "Individual particle characteristics, optical properties and evolution of an extreme long range transported biomass burning event in the European Arctic (Ny-Ålesund, Svalbard Islands)" Journal of Geophysical Research: Atmospheres, 125(5), e2019JD031535
Data belonging to the manuscript: "Individual particle characteristics, optical properties and evolution of an extreme long range transported biomass burning event in the European Arctic (Ny-Ålesund, Svalbard Islands)" Journal of Geophysical Research: Atmospheres, 125(5), e2019JD031535
Data belonging to the manuscript: "Individual particle characteristics, optical properties and evolution of an extreme long range transported biomass burning event in the European Arctic (Ny-Ålesund, Svalbard Islands)" Journal of Geophysical Research: Atmospheres, 125(5), e2019JD031535
Trends of Aitken, accumulation and coarse mode fractions (a), temperature and relative humidity (b), aerosol scattering at 530 nm (c), absorption coefficients (d), single scattering albedo (SSA) at 530 nm (orange line, right scale) and absorption Angstrom exponent (AAE, grey line, left scale; e) of the aerosol at GVB during the BB event.