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Biologiskt nedbrytbart löst organiskt kol (BDOC) och tillhörande fysikaliska och kemiska mätningar från en boreal första ordningens ström.
No full textNine riparian sites along a boreal first-order stream were sampled for the purposes of assessing the percentage of biodegradable dissolved organic carbon (bDOC) in soil, groundwater, streamwater and lake water across 8 occasions between July to October 2022. These sites were sampled to encompass the variation in riparian hydrogeomorphology present within boreal headwaters, and to investigate bDOC concentrations within a land to water continuum. All water samples and soil solutions from extractions were also analysed for dissolved organic carbon, dissolved nutrients and optical properties. All soils were analysed for bulk organic matter content, extracellular enzyme activity (total of 5 enzymes) and phospholipid fatty acid (PLFA) content.
This data was collected from the Stortjärnbäcken stream reach in the Krycklan Catchment Study within the Svartberget Research Station (64°14ʹN, 19°46ʹE, Vasterbottens lan, Sweden) in collaboration with the Swedish University of Agricultural Sciences (SLU).Vi tog prover från nio strandområden längs Stortjärnbäcken som är ett boreal biflöde av första ordning. Syftet var att mäta andelen biologiskt nedbrytbart vattenlösligt organiskt kol (bDOC) i jord, grundvatten, älvvatten och sjövatten vid 8 tillfällen mellan juli och oktober 2022. Dessa platser valdes för att undersöka bDOC-koncentrationer i ett land-till-vatten-kontinuum och för att ta hänsyn till variationen i kustens hydrogeomorfologi som finns i boreala källflöden. Alla vattenprover och jordextrakt analyserades också för lösliga oorganiska kol, lösliga näringsämnen och optiska egenskaper. Alla jordprover analyserades med avseende på innehåll av total mängd organiskt material, extracellulär enzymaktivitet (totalt 5 enzymer) och innehåll av fosfolipidfettsyror (PLFA).
Dessa data har samlats in från Stortjärnbäckens i Krycklans avrinningsområde vid Svartbergets forskningsstation (64°14ʹN, 19°46ʹE, Västerbottens lan, Sverige) i samarbete med Sveriges Lantbruksuniversitet (SLU)
COI data from: Invasive species detection along coastal harbours in northern region of Vastra Gotaland 2024
No full textEnvironmental DNA sequence data of invasive species along the harbors in the northern regions of Vastra Gotaland. Sequence data was obtained from both water samples, and plankton samples of two sampling events, one in the summer and one in the autumn of 2024. The amplicons were amplified by COI Leray-XT primers: Wangensteen et al. 2018 and annotated against an inhouse database of invasive and non-indigenous species of Norway, Sweden and EEA created with EchoPipe: Stensrud et al. in press. The data was created for Länsstyrelsen Vastra Gotaland and financed through HaV.
This dataset was published via the SBDI ASV portal. (https://asv-portal.biodiversitydata.se/
Dataset för: Microgravity Penetrometry Flight Campaign in Support of MMX Sampler Science Exploitation
No full textThis dataset includes penetration data collected from a parabolic flight experiment described in Smyth-Moore et al. 2025: "Microgravity Penetrometry Flight Campaign in Support of MMX Sampler Science Exploitation". Data includes Reaction Force and penetration depth measurements for penetrometer penetrations, separated for each individual penetrometer, plus video footage obtained of each penetration for each parabola. A key is provided to understand which specific set of data is related to the penetration that has a specific penetration velocity, tip shape and sample material.Denna datauppsättning innehåller penetrationsdata som samlats in från ett parabolflygexperiment som beskrivs i Smyth-Moore et al. 2025: "Microgravity Penetrometry Flight Campaign in Support of MMX Sampler Science Exploitation". Data inkluderar reaktionskrafts- och penetreringsdjupmätningar för penetrometerpenetrationer, separerade för varje enskild penetrometer, plus videofilmer från varje penetrering för varje parabel. En nyckel tillhandahålls för att förstå vilken specifik uppsättning data som är relaterad till penetrationen som har en specifik penetrationshastighet, spetsform och provmaterial
Lake variables - Sonde profiling from Bolmen, Subbasin West
No full textManual or high frequency lake profiling using sonde technology over various water depths to measure lakes of SITES Water.
Bolmen Research Station (2025). Lake variables - Sonde profiling from Bolmen, Subbasin West, 2023-10-23–2024-11-28 [Data set]. Swedish Infrastructure for Ecosystem Science (SITES). https://hdl.handle.net/11676.1/pngLWxSW7AawIqXNZGJsXwC
Pre-release of v1 for the Processed ASV data from the Insect Biome Atlas Project.
No full textThe data was collected and processed in the context of the Swedish Insect Biome Atlas (https://www.insectbiomeatlas.org/) (IBA). This dataset is a pre-release of v1 for the Processed ASV data from the Insect Biome Atlas Project.
For more detailed information see Processed ASV data from the Insect Biome Atlas Project: https://doi.org/10.17044/scilifelab.27202368.v1
References:
- Iwaszkiewicz-Eggebrecht, E., Łukasik, P., Buczek, M., Deng, J., Hartop, E. A., Havnås, H., ... & Miraldo, A. (2023). FAVIS: Fast and versatile protocol for non-destructive metabarcoding of bulk insect samples. PloS one, 18(7), e0286272.
- Miraldo, A., Iwaszkiewicz-Eggebrecht, E., Sundh, J., Manoharan, L., Granqvist, E., Andersson, A., Łukasik, P., Roslin, T., Tack, A. J. M., & Ronquist, F. (2024). Amplicon sequence variants from the Insect Biome Atlas project (Version 1). SciLifeLab. https://doi.org/10.17044/scilifelab.25480681.v1
- Sundh, J. (2022). COI reference sequences from BOLD DB (Version 4). SciLifeLab. https://doi.org/10.17044/scilifelab.20514192.v
MultiGEC
No full textDataset description
MultiGEC is a dataset for Multilingual Grammatical Error Correction in 12 European languages (Czech, English, Estonian, German, Greek, Icelandic, Italian, Latvian, Russian, Slovene, Swedish and Ukrainian) compiled by the CompSLA working group and over 20 external data providers in the context of MultiGEC-2025, the first text-level GEC shared task.
The MultiGEC dataset is divided into 17 subcorpora covering different languages, domains and correction styles, summarized below. More detailed information about each subcorpus is available as machine-readable metadata, whose format is described .Beskrivning
MultiGEC är en datamängd för automatisk korrigering av grammatiska fel -- på engelska Grammatical Error Correction (GEC) -- på 12 olika europeiska språk (tjeckiska, engelska, estniska, tyska, grekiska, isländska, italienska, lettiska, ryska, slovenska, svenska och ukrainska) som sammanställts av CompSLA-arbetsgruppen och över 20 externa dataleverantörer inom ramen för MultiGEC-2025, den första shared task för GEC på textnivå.
MultiGEC är indelat i 17 delkorpusar som täcker olika språk, domäner och korrigeringsstilar, vilka sammanfattas nedan. Mer detaljerad information om varje subkorpus finns tillgänglig som maskinläsbara metadata, vars format beskrivs här
DReaM-Copyright-Protected
No full textThis resource contains a multilingual digitized version of thousands of documents describing natural languages of the world. The corpus is annotated with various meta, word, and text level attributes, and is password protected for
copyright reasons. More details about the data and annotations can be found in the reference given below:
There is also an openly available part of the corpus which can be found here.
Standard reference:
{publication 295338}Den skyddade delen av DReaM-korpusen — som är skyddad på grund av upphovsrättsliga hänsynstaganden — består av tusentals flerspråkiga digitala dokument som beskriver världens språk. Dokumenten är berikade med metadata och
språkteknologiska analyser. För mer information hänvisar vi till publikationen som anges nedan, som även utgör samlingens standardreferens.
Det finns också en öppet tillgänglig del av korpusen som kan hittas här.
Standard reference:
{publication 295338
SMHI IFCB Plankton Image Reference Library
No full textThis repository includes four datasets of manually annotated plankton images by phytoplankton experts at the Swedish Meteorological and Hydrological Institute (SMHI). These images can be used for training automatic image classifiers to identify various plankton species. The images were captured using an Imaging FlowCytobot (IFCB, McLane Research Laboratories (https://mclanelabs.com/imaging-flowcytobot/) ) from different locations and seasons in the Skagerrak, Kattegat, and Baltic Proper. The specifics of the three datasets are as follows:
- smhi_ifcb_svea_baltic_proper: Images were gathered during monthly monitoring cruises (https://www.smhi.se/en/publications/publications/cruise-reports-from-the-marine-monitoring) from 2022 to 2025, utilizing an IFCB mounted as part of the underway FerryBox system on the R/V Svea. This collection consists of 27,914 annotated images across 65 different classes.
- smhi_ifcb_svea_skagerrak_kattegat: Images were also collected during the regular monitoring cruises from 2022 to 2025. This archive comprises of 10,381 annotated images from 103 distinct classes.
- smhi_ifcb_tångesund: In 2016, the IFCB was deployed in situ at depths between 3 and 18 meters, near a mussel farm in Tångesund, Mollösund (Skagerrak). This dataset contains 43,828 annotated images from 39 different classes.
- smhi_ifcb_iRfcb: This subset of the smhi_ifcb_svea_skagerrak_kattegat dataset can be used for user and unit tests for the iRfcb R package (https://europeanifcbgroup.github.io/iRfcb/) .
Datasets 1-3 comprises two zip archives: one (annotated_images) containing .png images organized into subfolders for each class, and another (matlab_files) including raw data files (.roi, .hdr, .adc) and .mat-files for developing a random forest image classifier using the MATLAB code from the ifcb-analysis (https://github.com/hsosik/ifcb-analysis) repository. Dataset 4 only comprise of a MATLAB data package.
The images in this dataset undergo continuous quality control, and new images are regularly added. Consequently, this dataset will be updated on a regular basis. If you find any mislabeled images, please contact the authors.
Version history
- Version 5 (2025-12-19): 82,123 annotated images.
- Version 4 (2024-11-04): 76,032 annotated images. Corrected class names to better match WoRMS, and continued quality control of images in the Tångesund dataset.
- Version 3 (2024-08-05): 72,086 annotated images. Added iRfcb dataset for user and unit testing.
- Version 2 (2024-06-03): 71,525 annotated images. Updated class names and corrected manual files in the Tångesund dataset. Continued quality control of images in the Tångesund dataset.
- Version 1 (2024-05-31): 65,435 annotated image
Antibiotikaresistens i kommensala E. coli-bakterier, samt gårdskaraktäristika, på vietnamesiska kycklinggårdar
No full textTo increase the understanding of the antibiotic resistance situation small- and medium-scale chicken farming in Vietnam, a study was performed at 305 chicken farms in Thai Nguyen province in Northern Vietnam. The study presents data on antibiotic resistance in commensal E. coli bacteria from healthy chickens (3 from each farm). In total 764 E. coli isolates were analysed for resistance against 15 antibiotic substances belonging to 11 antibiotic classes. Data on multi-drug resistance was also compiled.
During the same farm visits, data for a questionnaire-based study was also collected (dataset, and related paper, already published - see related resource), to evaluate farmers' practices and knowledge regarding AMR, as well as farm characteristics. Knowledge and practices were evaluated by using a statistical method called item response theory (IRT). This method is described in more detail in the already published paper (see related resource).
Some of those variables are also included in the current dataset since the purpose of the study, besides presenting resistance data, was to search for associations between farm(-er) characteristics and AMR occurrence.
The dataset consists of 765 rows and 37 columns. Variable names and answers are coded and explanations can be found in a separate file, "Chicken_farm_AMR_Vietnam_2025_explanations". Some of the variables that are re-used in this dataset has been renamed in the data analysis process. For easier comparisons of the datasets, both the old and new variable names are included in the explanation file. The questionnaire can be found in the data description published elsewhere (see associated data description).För att öka förståelsen för antibiotikaresistenssituationen i små- och medelskalig kycklinguppfödning i Vietnam, har en studie genomförts på 305 kycklinggårdar i Thai Nguyen-provinsen, norra Vietnam. Studien presenterar data gällande resistens i kommensala E. coli-bakterier från friska kycklingar/höns (3 per gård). Totalt analyserades 764 E. coli-isolat för resistens mot 15 antibiotikasubstanser från 11 antibiotikaklasser. Data om multiresistens genererades också.
En enkätbaserad studie genomfördes vid samma gårdsbesök (datasetet, och relaterad artikel, redan publicerade - se relaterad resurs). I den tidigare publicerade studien undersöktes kycklinguppfödarnas praktik och kunskap relaterad till antibiotikaresistens, samt allmänna gårdskaraktäristika. Kunskap och praktik utvärderades med en statistisk metod som heter item response theory (IRT), läs mer om denna metod i tidigare publikation (relaterad resurs).
Vissa av variablerna från det tidigare publicerade datasetet är inkluderade även i detta dataset då den aktuella studiens syfte innefattade att leta efter associationer mellan bönders kunskap och praktik, samt gårdskaraktäristika, och förekomst av antibiotikaresistens.
Datasetet består av 765 rader och 37 kolumner. Variabelnamn och svar är kodade och beskrivning av dessa finns i en separat fil, "Chicken_farm_AMR_Vietnam_2025_explanations". Vissa av de återanvända variablerna har döpts om under databearbetningensprocessen i denna studie. För enklare jämförelse av dataseten så är både de gamla och nya variabelnamnen inkluderade i beskrivningsfilen. Enkäten som användes vid gårdsbesöken kan hittas i databeskrivningen som är publicerad sedan tidigare (se relaterade resurser)
UAV - Red Green Blue (RGB) Orthomosaic from Stordalen Mire UAV Mire
No full textNear-ground RGB orthomosaics collected from UAV platforms, by means of RGB cameras containing red, green and blue bands. Nominal pixel resolution is 5 cm.
Abisko Scientific Research Station (2025). UAV - Red Green Blue (RGB) Orthomosaic from Stordalen Mire UAV Mire, 2024-06-12 [Data set]. Swedish Infrastructure for Ecosystem Science (SITES). https://hdl.handle.net/11676.1/8vOCdvm0tCmkD-TfaSqt1Fx