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Replication refined dataset for: A lightweight and extensible cell segmentation and classification model for H&E-stained cancer whole slide images
No full textThe refined PanNuke and MoNuSAC Cell Segmentation and Classification Dataset is a unified collection of H&E-stained image patches with cell instance annotations and seven cell-type labels. It is created by combining the PanNuke and MoNuSAC datasets while improving label granularity and consistency across both sources.
The dataset is generated using a cross-relabeling workflow that refines broad or ambiguous classes in each dataset using two ResNet50-based cell classifiers trained on extracted single-cell crops. A classifier trained on MoNuSAC immune cells is used to split the PanNuke inflammatory class into lymphocytes, neutrophils, and macrophages. A classifier trained on PanNuke epithelial subclasses is used to split the MoNuSAC epithelial class into epithelial (benign) and neoplastic (malignant). The relabeled instances are merged with the remaining original classes to form a single dataset with harmonized labels.
The resulting refined dataset includes seven cell types with the following instance counts: neoplastic 105,451; epithelial 29,926; lymphocytes 65,275; neutrophils 3,833; macrophages 3,410; connective 50,585; dead 2,908.</p
Replication Data for: Postnatal ablation of hippocampal Cajal-Retzius cells impairs spatial representation in CA1 superficial pyramidal cells.
No full textNWB files that include the processed and raw in-vivo recording data and behavioral tracking data, which are organized by animal ID. All metadata is included in the .nwb files. See detailed instructions in the .txt file
Gross annual increment (of AGB) (GAI) map for 2020
No full textThis dataset provides a high-resolution (10 m) pan-European map of forest Gross annual increment (of AGB) (GAI) for the year 2020, along with an accompanying standard deviation layer. It is part of the PathFinder collection of forest structure maps, which integrates Sentinel-2 satellite imagery, auxiliary geospatial layers, and National Forest Inventory (NFI) data to deliver detailed forest attribute predictions across Europe. The map supports applications in forest management, biomass estimation, carbon accounting, and ecological modeling. For methodology and data integration details, see the documentation dataset of the PathFinder collection (https://doi.org/10.18710/OEYKEG) and the following publication: Miettinen, J., Breidenbach, J. et al. (2025). PathFinder's High-Resolution Pan-European Forest Structure Maps: An Integration of Earth Observation and National Forest Inventory Data. Zenodo. https://doi.org/10.5281/zenodo.17107267
Abies (P_Abi) map for 2020
No full textThis dataset provides a high-resolution (10 m) pan-European map of forest Abies (P_Abi) for the year 2020, along with an accompanying standard deviation layer. It is part of the PathFinder collection of forest structure maps, which integrates Sentinel-2 satellite imagery, auxiliary geospatial layers, and National Forest Inventory (NFI) data to deliver detailed forest attribute predictions across Europe. The map supports applications in forest management, biomass estimation, carbon accounting, and ecological modeling. For methodology and data integration details, see the documentation dataset of the PathFinder collection (https://doi.org/10.18710/OEYKEG) and the following publication: Miettinen, J., Breidenbach, J. et al. (2025). PathFinder's High-Resolution Pan-European Forest Structure Maps: An Integration of Earth Observation and National Forest Inventory Data. Zenodo. https://doi.org/10.5281/zenodo.17107267
Diet data for Atlantic cod (Gadus morhua) from the Steigen and Hamaroy area in Nordland County, Norway, during 1993-1996.
No full textThe data set gives diet composition of Atlantic cod (Gadus morhua) sampled using gill-nets at three locations at 7-50 m depth in the Steigen and Hamaroy area during 1993-1996. Proportions of prey wet weight of each prey group are given for seven predator length intervals and in total, 754 cod stomachs were analyse
Replication Data for: Are large-scale differences in temperature and reindeer management regime affecting the quality of reindeer’s summer forage?
No full textThe dataset is an aggregation of data from different studies aimed at developing near-infrared reflectance spectroscopy (NIRS) calibrations of plant parts to analyze leaf nutrients and defense compounds content.
This study was designed to investigate whether the chemical composition of plants was varying with warmer temperatures and different grazing intensity from reindeer throughout the summer season.
Plants were collected in several areas of Troms and Finnmark (Norway) over a large spatial scale: 140 kilometers North to South and 285 kilometers West to East.
We selected 10 sites in summer pastures and 5 migratory pastures, spanning A 2,5°C gradient in mean July temperatures.
Plant data were collected during two consecutive summers (2011-2012) both in early July and late August to capture seasonal variation in chemical composition. Plants were also sampled in grassland vegetation and dwarf shrub heath vegetation to check for variation in the chemical composition of plants between the 2 vegetation types
Drone-based glacier mapping of Borebreen in Svalbard, 2025
No full textThis database contains drone-based mapping data of Borebreen, in Svalbard, Norway. Borebreen is a tidewater-terminating surge-type glacier located on the north-side of Isfjorden. The dataset was generated using a structure-from-motion (SfM) method using drone-based imagery. The data was processed with Agisoft Metashape and the processed data consists of digital elevation models (DEMs) in georeferenced .TIF file format, orthomosaic maps in georeferenced .TIF, .JPG, and .PNG file format, and textured 3D models in .STL and .JPG file format. A 3D model of the glacier is also provided in .OBJ file format. In addition, a process report in archived .PDF file format is included for each dataset. Mapping was conducted with a large fixed-wing drone, the Mugin-2 Pro as well as with a smaller quadcopter, the DJI Mavic 3 Pro Enterprise. The Mugin was used to map a very large area of the glacier (approx 40km²) whereas the Mavic was only used to map the front of the glacier. Data collection was conducted during Autumn 2025 (08.09.2025)
Replication data for "Combined short- and long-read metabarcoding of the soil fungi Archaeorhizomycetes reveals high phylogenetic diversity structured by vegetation and climate"
No full textArchaeorhizomycetes is a class of globally widespread soil-dwelling fungi, originally proposed to be associated with plant roots, but their ecology and nutritional mode are not clearly defined. To increase the knowledge about Archaeorhizomycetes’ ecology and biogeography, we investigate how they are distributed along major environmental gradients, as well as different soil compartments. The dataset consists of mapping files for raw sequence data deposited to ENA under accession numbers ERR15529369- ERR15529373 for PacBio long-read amplicon sequences of Archaeorhizomycetes (partial 18S, ITS, partial 28S, approx. 2500 bp) and accession numbers ERR15529374- ERR15529378 for raw sequencing files for V4 of the 18S using general eukaryotic primers (TAReuk454FWD1 and TAReukREV3). The dataset also consists of OTU tables for both sequencing runs, metadata and R scripts to analyse the data
Python code for hierarchical cluster analysis of detected R-strategies from rule-based NLP on 500 circular economy definitions
No full textDATASET MIGRATED FROM FIGSHARE: The dataset used in this analysis consists of 500 peer-reviewed circular economy (CE) definitions systematically collected from key academic sources. The definitions were processed using a rule-based NLP model to extract the presence of R-strategies (R0-R9), which operationalize circularity in CE frameworks. Each definition was analyzed for the presence of these strategies, and the results were structured into a binary format (1 if detected, 0 if not) for statistical and clustering analysis.The hierarchical cluster analysis was performed on this dataset to reveal co-occurrence patterns among R-strategies, using Ward’s method for clustering and Euclidean distance as the similarity metric. The resulting dendrogram visually represents how different strategies are conceptually related based on their co-occurrence in CE definitions.This Python code was optimized and debugged using ChatGPT-4o to ensure implementation efficiency, accuracy, and clarity.</p
Replication data for: The social light field in eco-centric outdoor lighting
No full textDATASET MIGRATED FROM FIGSHARE: Cubic lighting metrics and subjective data for a lighting study on pavements.</p