https://researchdata.se/en/catalogue Search results en This dataset contains 20 audio files and raw data from three studies about the effect of accents on the expectations and perceptions of food. The audio files are small descriptions of the food stimuli recorded by a dialect specialist in four different accents from four Swedish counties (Skåne, Värmland, Stockholm, and Norrland) chosen to represent, respectively, the south, west, east, and north of the country. Study 1 contains data on 302 consumers’ liking of a vegan cream cheese and jam sandwich after they heard a description of the sandwich in the four mentioned accents. It also shows the willingness to meet (WTM) and a check-all-that-apply (CATA) description of the person telling a short story in the four different accents. Study 2 contains data on 314 consumers’ liking and CATA description of one dried pork sausage and one dried vegan sausage after hearing descriptions in two different accents (northern and southern). Study 3 contains data on 314 consumers’ willingness to try (WTT) and CATA description of four regional dishes after seeing a picture and listening to a description of them in the four different accents. All data was collected through online questionnaires hosted on EyeQuestion between February and Juni of 2025. Fri, 29 May 2026 11:59:46 GMT https://researchdata.se/en/catalogue/dataset/2025-262 https://researchdata.se/en/catalogue/dataset/2025-262 Örebro University Iuri Baptista Johan Swahn This dataset contains the results of a consumer sensory test with 66 participants evaluating three beer types (a pilsner, an IPA, and a wheat beer) in their alcoholic (AL) and non-alcoholic (NA) versions, a total of six beers. All participants tasted each beer sample twice, first alone, then paired with skagenröra, a traditional Swedish shrimp salad. Participants evaluated liking using a 7-points hedonic scale; and flavor intensity, sourness, and bitterness using a 5-points just-about-right (JAR) scale. The data was collected at campus Grythyttan of Örebro University, Sweden, in November of 2025. Fri, 29 May 2026 11:10:50 GMT https://researchdata.se/en/catalogue/dataset/2025-378 https://researchdata.se/en/catalogue/dataset/2025-378 Örebro University Henrik Scander Johan Swahn Iuri Baptista This dataset contains observational count data on passenger presence on subway platforms in the Stockholm metro system, collected as part of a quasi-experimental field study examining behavioural responses to blue LED lighting, BLED. Data were collected at four platforms across three subway stations between September 2025 and April 2026. Two platforms were equipped with blue LED luminaires and two served as non-exposed control platforms. Note: For the purpose of preregistration and documentation, the files provided at this stage contain simulated data only. These simulated files mirror the structure, variables, formats, and temporal alignment of the real data that will be analysed once data collection is complete. The core data consist of time stamped detections from the station camera system, provided as event level logs that is aggregated to minute-by-minute counts. For each platform, two zones were defined within the camera system, an exposure zone located at the platform end where trains enter the station and an adjacent reference zone with standard lighting. Automated video analytics identified human presence within these zones and recorded detections over time. The dataset does not include images, video recordings, or individual level tracking, only anonymised numerical event counts that can be summarised to passenger density measures. Lighting conditions at the exposed platforms alternated between BLED switched on and switched off, primarily in two-week periods with one four-week period, allowing within platform and between platform comparisons over time. Each camera based observation is time stamped and linked to station, platform, zone, experimental condition, and period identifiers. The dataset also includes aggregated station passage data derived from ticket gate systems at the same stations. These data describe the number of passengers entering and exiting each station at minute resolution and serve as indicators of overall station usage that can be aligned temporally with the camera data to control for variation in passenger volume unrelated to lighting conditions. To account for ambient lighting conditions, the dataset further includes environmental data from an outdoor reference station. This file contains time stamped measurements of solar irradiance and is used as a control variable for changes in natural light exposure over the study period. The data material is provided as structured tabular files corresponding to these three sources, camera detections, station passage counts, and outdoor sun exposure. The files are linked through shared timestamps and station identifiers and can be read using standard statistical software. No proprietary software is required, and the original analyses were conducted in R, although reuse is not restricted to any specific software environment. Thu, 21 May 2026 15:14:36 GMT https://researchdata.se/en/catalogue/dataset/2025-348 https://researchdata.se/en/catalogue/dataset/2025-348 Karolinska Institutet Danielle Berglund Gergö Hadlaczky Jesper Alvarsson-Hjort This dataset contains data for catchment characteristics and lake water chemistry for lakes in the Swedish Lake Survey, SLS (omdrevstationer), and trend lake (trendlakestationer) monitoring programs. Both surveys, the Swedish Lake Survey and the trend lake survey, are compiled at the Swedish University of Agricultural Sciences (SLU) as part of the university's environmental monitoring and assessment programme Lakes and Watercourses. This makes up a dataset of 5140 lakes (110 of which are trend lakes monitored 4 times a year and 5030 survey lakes monitored every 6 years, some lakes are in both programs), all >1 ha in lake area. For each of these programs this dataset includes (1) time series of water chemistry for all the stations, (2) shapefile with the catchment delineation and station coordinates, and (3) a file summarizing catchment characteristics. Catchment characteristics include land cover, soil depth, peat coverage, ditch density, ditch density in peat areas, NDVI, lake water chemistry, atmospheric deposition, precipitation, temperature, precipitation as snow, percentage above the high coast line, and runoff. An extra file, 'significance.csv', was added in version 2 of this dataset containing the significance (p-value) of slope estimators, where applicable. This dataset also includes the code used to extract the data used to generate this time series and characteristics. As such this data can be reproduced, and extended from the information contained in the dataset. The following files are included in the dataset: **Documentation** readme_overview.md: An overview of what the dataset contains (further elaborated in readme_data.md) and how it was generated (further elaborated in readme_code.md). readme_data.md: Documentation of the final datasets files, including units, reference to the code used to generate, and original data source. readme_code.md: Documentation of the code and functions used to generate the dataset. A static version can be found in the dataset as git_freeze and a live version of the code can be found at https://github.com/aalackner/DOC_catchments. **Data** chemistry_SLS.csv: 14107 x 46, 4.8MB chemistry_trend.csv: 16018 x 46, 5.1MB characteristics_SLS.csv: 5030 x 81, 6MB characteristics_trend.csv: 110 x 93, 0.16MB significance.csv: 5137 × 27, 1.21 MB SLS.zip: 6194 polygons, 20MB trend.zip: 111 polygons, 0.3MB etc.zip: 114 MB etc.zip is a folder with additional timeseries data used in the calculation of characteristics. Tue, 19 May 2026 07:31:12 GMT https://researchdata.se/en/catalogue/dataset/2025-256 https://researchdata.se/en/catalogue/dataset/2025-256 Swedish University of Agricultural Sciences Anna Lackner Emil Back Near-ground multispectral orthomosaics collected from UAV platforms, by means of mulstispectral cameras containing red, green, red edge and NIR bands. Nominal pixel resolution is 5 cm. Abisko Scientific Research Station (2026). UAV - Multispectral orthomosaic from Stordalen Mire UAV Mire, 2024-07-30 [Data set]. Swedish Infrastructure for Ecosystem Science (SITES). https://hdl.handle.net/11676.1/2lkxMQGdVcLdEujGXzcy-MiE Sun, 17 May 2026 00:00:00 GMT https://researchdata.se/en/catalogue/dataset/sites-2lkxmqgdvcldeujgxzcy-mie https://researchdata.se/en/catalogue/dataset/sites-2lkxmqgdvcldeujgxzcy-mie Swedish Polar Research Secretariat Near-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 (2026). UAV - Red Green Blue (RGB) Orthomosaic from Stordalen Mire UAV Mire, 2024-07-30 [Data set]. Swedish Infrastructure for Ecosystem Science (SITES). https://hdl.handle.net/11676.1/CCb6NcxTmZVI-5EzRSJhEjwI Sun, 17 May 2026 00:00:00 GMT https://researchdata.se/en/catalogue/dataset/sites-ccb6ncxtmzvi-5ezrsjhejwi https://researchdata.se/en/catalogue/dataset/sites-ccb6ncxtmzvi-5ezrsjhejwi Swedish Polar Research Secretariat Lönnstorp Research Station (2026). UAV - Multispectral Point Cloud (PC) from SAFE Agroecological Field Experiment, 2025-08-11 [Data set]. Swedish Infrastructure for Ecosystem Science (SITES). https://hdl.handle.net/11676.1/DPXw3ZMRoC-kpTzF-avOnmmO Sun, 17 May 2026 00:00:00 GMT https://researchdata.se/en/catalogue/dataset/sites-dpxw3zmroc-kptzf-avonmmo https://researchdata.se/en/catalogue/dataset/sites-dpxw3zmroc-kptzf-avonmmo Swedish University of Agricultural Sciences Abisko Scientific Research Station (2026). UAV - Multispectral Point Cloud (PC) from Stordalen Mire UAV Mire, 2024-07-30 [Data set]. Swedish Infrastructure for Ecosystem Science (SITES). https://hdl.handle.net/11676.1/jrTYyfE7PqztpsmkvpeXj16l Sun, 17 May 2026 00:00:00 GMT https://researchdata.se/en/catalogue/dataset/sites-jrtyyfe7pqztpsmkvpexj16l https://researchdata.se/en/catalogue/dataset/sites-jrtyyfe7pqztpsmkvpexj16l Swedish Polar Research Secretariat Digital Surface Model generated from photos taken from an UAV platform using photo-stereography techniques. Nominal pixel size is 5 cm. Abisko Scientific Research Station (2026). UAV - Digital Terrain Elevation Model (DTM) from Stordalen Mire UAV Mire, 2024-07-30 [Data set]. Swedish Infrastructure for Ecosystem Science (SITES). https://hdl.handle.net/11676.1/L1cgpx0ymLJ-TV5aJe2iQkw0 Sun, 17 May 2026 00:00:00 GMT https://researchdata.se/en/catalogue/dataset/sites-l1cgpx0ymlj-tv5aje2iqkw0 https://researchdata.se/en/catalogue/dataset/sites-l1cgpx0ymlj-tv5aje2iqkw0 Swedish Polar Research Secretariat Near-ground Normalized Difference Vegetation Index (NDVI) orthomosaics calculated from multispectral orthomosaics' red and NIR bands. Nominal pixel resolution is 5 cm. Lönnstorp Research Station (2026). UAV - Normalized Difference Vegetation index (NDVI) Orthomosaic from SAFE Agroecological Field Experiment, 2025-08-11 [Data set]. Swedish Infrastructure for Ecosystem Science (SITES). https://hdl.handle.net/11676.1/o_rxuZ6pujib8PNnDJGcbsxc Sun, 17 May 2026 00:00:00 GMT https://researchdata.se/en/catalogue/dataset/sites-o-rxuz6pujib8pnndjgcbsxc https://researchdata.se/en/catalogue/dataset/sites-o-rxuz6pujib8pnndjgcbsxc Swedish University of Agricultural Sciences