cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.18710/lblyqt/95hsoo
title: 00_README.txt
DOI: 10.18710/lblyqt/ai2ied
title: 090015.hdf5
DOI: 10.18710/lblyqt/pezjbc
title: 090325.hdf5
DOI: 10.18710/qxqgwb/7jccuk
title: 20240915_NYA_REDTEC_gal.txt
DOI: 10.18710/qxqgwb/anntm5
title: 20240923_NYA_REDTEC_glo.txt
DOI: 10.18710/qxqgwb/d7gcpl
title: 20240711_NYA_REDTEC_gps.txt
DOI: 10.18710/qxqgwb/it83ws
title: 20240828_NYA_REDTEC_gal.txt
DOI: 10.18710/qxqgwb/ywfop1
title: 20240914_NYA_REDTEC_glo.txt
DOI: 10.18710/sglchg/0htygy
title: NKS_2022_S04_Arbeidsoppgaver_pivot.tsv
DOI: 10.18710/sglchg/e1ia4z
title: NKS_2022_S09_Arkivtjenester_processed_data.tsv
DOI: 10.18710/sglchg/gza3iq
title: NKS_2022_S01_Utdanningsbakgrunn_pivot.xlsx
DOI: 10.18710/sglchg/ktfxks
title: NKS_2022_S20_Bidrag_kuratornettverk_data.xlsx
DOI: 10.18710/sglchg/pgdqf7
title: NKS_2022_S19_Kollegaveiledning_figur.png
DOI: 10.18710/sglchg/psphoy
title: NKS_2022_S08_Datastoerrelse_pivot.xlsx
DOI: 10.18710/sglchg/tsbbk5
title: NKS_2022_S22_Deltakelse_data.tsv
DOI: 10.18710/dqjwab/lf8i0d
title: Final_demo_2020_stdev_P_Euc_E29_N34.tif
DOI: 10.18710/dqjwab/vk2wsf
title: Final_demo_2020_stdev_P_Euc_E49_N19.tif
DOI: 10.18710/egrqrc/bmfve3
title: 00Readme.txt

description: Detailed dataset description and methods.
DOI: 10.18710/hdjrjn/5ssjvv
title: Final_demo_2020_P_OthBL_E34_N19.tif
DOI: 10.18710/hdjrjn/cxtyd3
title: Final_demo_2020_P_OthBL_E34_N34.tif
DOI: 10.18710/hdjrjn/yrrmcw
title: Final_demo_2020_P_OthBL_E24_N24.tif
DOI: 10.18710/hdjrjn/z4iuye
title: Final_demo_2020_P_OthBL_E49_N24.tif
DOI: 10.18710/j1k5xq/60obi1
title: 20240813_HOP_REDOBS_gal.txt
DOI: 10.18710/j1k5xq/cygext
title: 20240119_HOP_REDOBS_glo.txt
DOI: 10.18710/qxqgwb/lt0z8z
title: 20240310_NYA_REDTEC_glo.txt
DOI: 10.18710/sglchg/0xobvm
title: NKS_2022_S05_Kurateringserfaring_figur.png
DOI: 10.18710/sglchg/1mcfuu
title: NKS_2022_S12_Ansatte_kuratering_samme_datatyper_pivot.xlsx
DOI: 10.18710/sglchg/asltiy
title: NKS_2022_S18_Tilnaerming_figur.png
DOI: 10.18710/sglchg/hyxick
title: NKS_2022_S14_Behov_for_kompetanseheving_figur_2.png
DOI: 10.18710/sglchg/mp2u9p
title: NKS_2022_S13_Kompetanseheving_figur.png
DOI: 10.18710/sglchg/nq8w15
title: NKS_2022_S22_Deltakelse_processed_data.tsv
DOI: 10.18710/sglchg/of8vsh
title: NKS_2022_S18_Tilnaerming_data.tsv
DOI: 10.18710/sglchg/pcq93h
title: NKS_2022_data.xlsx
DOI: 10.18710/sglchg/s9vyih
title: NKS_2022_S10_Kurateringsaktiviteter_filorganisering_2_pivot.xlsx
DOI: 10.18710/sglchg/ve7x5g
title: NKS_2022_S14_Behov_for_kompetanseheving_data.xlsx
DOI: 10.18710/j1k5xq/kce8hw
title: 20240110_HOP_REDOBS_gal.txt
DOI: 10.18710/j1k5xq/x0zxkq
title: 20240226_HOP_REDOBS_gal.txt
DOI: 10.18710/j1k5xq/zgqfpx
title: 20240129_HOP_REDOBS_gal.txt
DOI: 10.18710/qxqgwb/kgbyvx
title: 20240207_NYA_REDTEC_glo.txt
DOI: 10.18710/qxqgwb/wiktkq
title: 20240823_NYA_REDTEC_gal.txt
DOI: 10.18710/sglchg/uo3g4m
title: NKS_2022_S10_Kurateringsaktiviteter_juss+etikk_2_pivot.tsv
DOI: 10.18710/j1k5xq/3gdfu1
title: 20240331_HOP_REDOBS_glo.txt
DOI: 10.18710/j1k5xq/4sjvzp
title: 20240122_HOP_REDOBS_gps.txt
DOI: 10.18710/j1k5xq/5r4dex
title: 20240912_HOP_REDOBS_gal.txt
DOI: 10.18710/j1k5xq/8sa3bu
title: 20240125_HOP_REDOBS_gps.txt
DOI: 10.18710/j1k5xq/b3maod
title: 20240229_HOP_REDOBS_gal.txt
DOI: 10.18710/j1k5xq/cgi9mm
title: 20240810_HOP_REDOBS_gps.txt
DOI: 10.18710/j1k5xq/dheaix
title: 20240102_HOP_REDOBS_gal.txt
DOI: 10.18710/j1k5xq/fatj9n
title: 20240108_HOP_REDOBS_gal.txt
DOI: 10.18710/j1k5xq/im1sck
title: 20240109_HOP_REDOBS_glo.txt
DOI: 10.18710/j1k5xq/iynins
title: 20240806_HOP_REDOBS_glo.txt
DOI: 10.18710/j1k5xq/q2mhkl
title: 20240301_HOP_REDOBS_glo.txt
DOI: 10.18710/j1k5xq/qlvrj5
title: 20240229_HOP_REDOBS_glo.txt
DOI: 10.18710/j1k5xq/stqozx
title: 20240219_HOP_REDOBS_gps.txt
DOI: 10.18710/j1k5xq/tdorv4
title: 20240906_HOP_REDOBS_gal.txt
DOI: 10.18710/j1k5xq/uwzlu9
title: 20240104_HOP_REDOBS_glo.txt
DOI: 10.18710/j1k5xq/xsudta
title: 20240808_HOP_REDOBS_glo.txt
DOI: 10.18710/j1k5xq/xvvqyx
title: 20240408_HOP_REDOBS_gps.txt
DOI: 10.18710/qxqgwb/cnv6h3
title: 20240323_NYA_REDTEC_glo.txt
DOI: 10.18710/qxqgwb/inwfkl
title: 20240328_NYA_REDTEC_gal.txt
DOI: 10.18710/qxqgwb/l51qcq
title: 20240107_NYA_REDTEC_glo.txt
DOI: 10.18710/qxqgwb/mvic4n
title: 20240824_NYA_REDTEC_gps.txt
DOI: 10.18710/qxqgwb/pkusor
title: 20240702_NYA_REDTEC_gps.txt
DOI: 10.18710/qxqgwb/s1rgux
title: 20240225_NYA_REDTEC_glo.txt
DOI: 10.18710/qxqgwb/vpr5mb
title: 20240810_NYA_REDTEC_gal.txt
DOI: 10.18710/sglchg/mrg75k
title: NKS_2022_S04_Arbeidsoppgaver_data.tsv
DOI: 10.18710/d9mh96/bh16zy
title: Final_demo_2020_P_Pic_E39_N29.tif
DOI: 10.18710/hdjrjn/kzaqdn
title: Final_demo_2020_stdev_P_OthBL_E39_N24.tif
DOI: 10.18710/hdjrjn/t7gd0m
title: Final_demo_2020_stdev_P_OthBL_E49_N19.tif
DOI: 10.18710/j1k5xq/ec4hjx
title: 20240925_HOP_REDOBS_gps.txt
DOI: 10.18710/qxqgwb/lixhea
title: 20240824_NYA_REDTEC_gal.txt
DOI: 10.18710/sglchg/eb35sv
title: NKS_2022_S15_Hjelpemidler_omraader_pivot.tsv
DOI: 10.18710/d9mh96/dmuolq
title: Final_demo_2020_stdev_P_Pic_E44_N44.tif
DOI: 10.18710/d9mh96/iyqner
title: Final_demo_2020_P_Pic_E29_N39.tif
DOI: 10.18710/dja6up/0xnrjm
title: 20240602_KHO_REDTEC_glo.txt
DOI: 10.18710/dja6up/32pdwe
title: 20240602_KHO_REDTEC_gps.txt
DOI: 10.18710/dja6up/awrwlh
title: 20240617_KHO_REDTEC_gps.txt
DOI: 10.18710/dja6up/q7l1ab
title: 20240530_KHO_REDTEC_glo.txt
DOI: 10.18710/hdjrjn/1jcs5e
title: Final_demo_2020_P_OthBL_E44_N14.tif
DOI: 10.18710/hdjrjn/g1xosv
title: Final_demo_2020_stdev_P_OthBL_E44_N54.tif
DOI: 10.18710/hdjrjn/kbqdtc
title: Final_demo_2020_P_OthBL_E54_N29.tif
DOI: 10.18710/hdjrjn/ratwva
title: Final_demo_2020_stdev_P_OthBL_E54_N14.tif
DOI: 10.18710/hdjrjn/slahrj
title: Final_demo_2020_stdev_P_OthBL_E39_N39.tif
DOI: 10.18710/hdjrjn/upwns2
title: Final_demo_2020_stdev_P_OthBL_E29_N14.tif
DOI: 10.18710/hdjrjn/vt56gn
title: Final_demo_2020_stdev_P_OthBL_E34_N39.tif
DOI: 10.18710/hdjrjn/ztjsfw
title: Final_demo_2020_stdev_P_OthBL_E24_N24.tif
DOI: 10.18710/j1k5xq/czqusk
title: 20240320_HOP_REDOBS_gps.txt
DOI: 10.18710/j1k5xq/iz60bg
title: 20240115_HOP_REDOBS_gal.txt
DOI: 10.18710/j1k5xq/jxv8sk
title: 20240224_HOP_REDOBS_glo.txt
DOI: 10.18710/j1k5xq/smjwxs
title: 20240303_HOP_REDOBS_glo.txt
DOI: 10.18710/l4ony6/ojhklv
title: 20240301_HOP_REDTEC_gal.txt
DOI: 10.18710/l4ony6/pgorzk
title: 20240330_HOP_REDTEC_gal.txt
DOI: 10.18710/l4ony6/rrqcvg
title: 20240125_HOP_REDTEC_glo.txt
DOI: 10.18710/l4ony6/ttbise
title: 20240111_HOP_REDTEC_gps.txt
DOI: 10.18710/ozpaww/5ncdlq
title: 20241103_BJN_REDTEC_glo.txt
DOI: 10.18710/ozpaww/6aliwe
title: 20241023_BJN_REDTEC_gal.txt
DOI: 10.18710/ozpaww/c1pqag
title: 20241101_BJN_REDTEC_glo.txt
DOI: 10.18710/ozpaww/elinma
title: 20241015_BJN_REDTEC_gal.txt
DOI: 10.18710/ozpaww/jj1yl5
title: 20240824_BJN_REDTEC_glo.txt
DOI: 10.18710/ozpaww/krhqwr
title: 20241004_BJN_REDTEC_glo.txt
DOI: 10.18710/ozpaww/lmphgj
title: 20241005_BJN_REDTEC_gal.txt
DOI: 10.18710/ozpaww/nib3f7
title: 20241227_BJN_REDTEC_gal.txt
DOI: 10.18710/ozpaww/t6uwmp
title: 20240828_BJN_REDTEC_gal.txt
DOI: 10.18710/ozpaww/v43mkq
title: 20241019_BJN_REDTEC_gal.txt
DOI: 10.18710/ozpaww/weioxw
title: 20241026_BJN_REDTEC_gal.txt
DOI: 10.18710/ozpaww/wi3brm
title: 20241101_BJN_REDTEC_gps.txt
DOI: 10.18710/ozpaww/wm4ojw
title: 20241216_BJN_REDTEC_glo.txt
DOI: 10.18710/ozpaww/xthn7x
title: 20241016_BJN_REDTEC_glo.txt
DOI: 10.18710/ozpaww/y4xkud
title: 20241209_BJN_REDTEC_glo.txt
DOI: 10.18710/ozpaww/ywv3gd
title: 20241031_BJN_REDTEC_glo.txt
DOI: 10.18710/qxqgwb/5ojbhb
title: 20240314_NYA_REDTEC_gps.txt
DOI: 10.18710/qxqgwb/gf7ybc
title: 20240115_NYA_REDTEC_gps.txt
DOI: 10.18710/qxqgwb/jjbuvw
title: 20240309_NYA_REDTEC_glo.txt
DOI: 10.18710/j1k5xq/0fthhg
title: 20240708_HOP_REDOBS_gal.txt
DOI: 10.18710/j1k5xq/ff5tbi
title: 20240810_HOP_REDOBS_glo.txt
DOI: 10.18710/j1k5xq/fyfcfm
title: 20240310_HOP_REDOBS_gps.txt
DOI: 10.18710/j1k5xq/jbujct
title: 20240718_HOP_REDOBS_gal.txt
DOI: 10.18710/j1k5xq/jibnlu
title: 20240222_HOP_REDOBS_gps.txt
DOI: 10.18710/j1k5xq/nes1gr
title: 20240708_HOP_REDOBS_glo.txt
DOI: 10.18710/j1k5xq/pzuhmr
title: 20240304_HOP_REDOBS_gal.txt
DOI: 10.18710/j1k5xq/sq3li5
title: 20240312_HOP_REDOBS_glo.txt
DOI: 10.18710/j1k5xq/vh1wmt
title: 20240901_HOP_REDOBS_glo.txt
DOI: 10.18710/qxqgwb/hbi30i
title: 20240123_NYA_REDTEC_glo.txt
DOI: 10.18710/qxqgwb/i06tqp
title: 20240503_NYA_REDTEC_glo.txt
DOI: 10.18710/qxqgwb/ijd4nl
title: 20240320_NYA_REDTEC_glo.txt
DOI: 10.18710/qxqgwb/mddhpl
title: 20240829_NYA_REDTEC_glo.txt
DOI: 10.18710/qxqgwb/ms9zpp
title: 20240307_NYA_REDTEC_gal.txt
DOI: 10.18710/qxqgwb/nfaepe
title: 20240101_NYA_REDTEC_gps.txt
DOI: 10.18710/qxqgwb/nl8itb
title: 20240718_NYA_REDTEC_gps.txt
DOI: 10.18710/qxqgwb/ue6pts
title: 20240217_NYA_REDTEC_gps.txt
DOI: 10.18710/qxqgwb/uvwiw5
title: 20240622_NYA_REDTEC_glo.txt
DOI: 10.5073/20210308-154150
title: Segmentation of wine berries

description: Dataset contains high resolution images collected with a moving field phenotyping platform, the Phenoliner. 
The collected images show 3 different varieties (Riesling, Felicia, Regent) in 2 different training systems (VSP=vertical shoot positioning and SMPH= semi minimal pruned hedges), collected in 2 points in time (before and after thinning) in 2018. For each image we provide a manual masks which allow the identification of single berries.
The folder contains: 1. List with image details (imagename, acquisition date, year, variety, training system and variety number)and 2. Dataset folder with 2 subfolders, namely 1. img – 42 original RGB images and 2. lbl – 42 corresponding labels (manual annotation, with berry, edge, background definition)
The data were used to train a neural network with the main goal to detect single berries in images. The method is described in detail in the specified papers.
DOI: 10.18710/d9mh96/fa7u3f
title: Final_demo_2020_stdev_P_Pic_E54_N44.tif
DOI: 10.18710/hca0au/menalx
title: Shishuoxinyu.csv

description: The conventionality of frequent two-character combinations in Shishuoxinyu (about 400 AE).
DOI: 10.18710/j1k5xq/daemgw
title: 20240331_HOP_REDOBS_gal.txt
DOI: 10.18710/j1k5xq/sz2vpw
title: 20240204_HOP_REDOBS_glo.txt
DOI: 10.18710/qxqgwb/e1w4tr
title: 20240406_NYA_REDTEC_gal.txt
DOI: 10.18710/qxqgwb/vu5kk9
title: 20240501_NYA_REDTEC_glo.txt
DOI: 10.18710/sglchg/fkskrl
title: NKS_2022_S15_Hjelpemidler_omraader_data.xlsx
DOI: 10.18710/d9mh96
title: Picea (P_Pic) map for 2020

description: This dataset provides a high-resolution (10 m) pan-European map of forest Picea (P_Pic) 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 (&lt;a href="https://doi.org/10.18710/OEYKEG" title="Documentation" target="_blank"&gt;https://doi.org/10.18710/OEYKEG&lt;/a&gt;) 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. &lt;a href="https://doi.org/10.5281/zenodo.17107267" title="Documentation" target="_blank"&gt;https://doi.org/10.5281/zenodo.17107267&lt;/a&gt;.
description: Picea (P_Pic)
DOI: 10.18710/do0r0j/rwmysy
title: TS5253a_3D_ambient_o_kompositt.jpg
DOI: 10.18710/do0r0j/yd17rx
title: TS11140_BH_cruciform.jpg
DOI: 10.18710/ga1ftv/ydmhnr
title: 05_2025_Fridtjovbreen_Model.stl
DOI: 10.18710/hca0au/0u5kzf
title: 01_Correlation_Analysis.csv

description: The correlation between the results from the native speakers' word segmentation test and the conventionality of the frequent two-character combinations in the Modern Mandarin sample.
DOI: 10.18710/hca0au/8lbxc1
title: Zuozhuan.csv

description: The conventionality of frequent two-character combinations in Zuozhuan (about the 4th century BCE, representative Old Chinese).
DOI: 10.18710/hdjrjn/64mxi3
title: Final_demo_2020_stdev_P_OthBL_E44_N14.tif
DOI: 10.18710/hdjrjn/i6wqx6
title: Final_demo_2020_stdev_P_OthBL_E54_N34.tif
DOI: 10.18710/hdjrjn/wgnrsf
title: Final_demo_2020_stdev_P_OthBL_E44_N34.tif
DOI: 10.18710/j1k5xq/0fe7pd
title: 20240104_HOP_REDOBS_gps.txt
DOI: 10.18710/j1k5xq/0xdwyy
title: 20240307_HOP_REDOBS_gps.txt
DOI: 10.18710/j1k5xq/6kk3hz
title: 20240112_HOP_REDOBS_glo.txt
DOI: 10.18710/j1k5xq/a9olln
title: 20240321_HOP_REDOBS_gal.txt
DOI: 10.18710/j1k5xq/gzxh7k
title: 20240202_HOP_REDOBS_glo.txt
DOI: 10.18710/j1k5xq/navtht
title: 20240412_HOP_REDOBS_gps.txt
DOI: 10.18710/j1k5xq/trkqw0
title: 20240218_HOP_REDOBS_gal.txt
DOI: 10.18710/jgccmb/k9cm7c
title: 0_Sample_overview_com-Sb2Se3-cells.csv

description: Overview of battery cells based on commercial (com) Sb2Se3
DOI: 10.18710/l4ony6/xobrqy
title: 20240308_HOP_REDTEC_gal.txt
DOI: 10.18710/ozpaww/3fntsq
title: 20241105_BJN_REDTEC_gal.txt
DOI: 10.18710/qxqgwb/6fdc6b
title: 20240603_NYA_REDTEC_gal.txt
DOI: 10.18710/qxqgwb/8mdtbk
title: 20240522_NYA_REDTEC_gps.txt
DOI: 10.18710/qxqgwb/bwcwlr
title: 20240325_NYA_REDTEC_gps.txt
DOI: 10.18710/qxqgwb/gqixjw
title: 20240602_NYA_REDTEC_gal.txt
DOI: 10.18710/qxqgwb/mqp3qa
title: 20240617_NYA_REDTEC_gps.txt
DOI: 10.18710/qxqgwb/myn0jo
title: 20240128_NYA_REDTEC_glo.txt
DOI: 10.18710/qxqgwb/sgy7jj
title: 20240331_NYA_REDTEC_gal.txt
DOI: 10.18710/qxqgwb/uopp0g
title: 20240211_NYA_REDTEC_glo.txt
DOI: 10.18710/sglchg/6v1eh1
title: NKS_2022_S22_Deltakelse_pivot_2.xlsx
DOI: 10.18710/sglchg/dlcps3
title: NKS_2022_S01_Utdanningsbakgrunn_data.xlsx
DOI: 10.18710/sglchg/fbsulu
title: NKS_2022_S21_Undergrupper_pivot.tsv
DOI: 10.18710/sglchg/lfbytw
title: NKS_2022_S08_Datastoerrelse_data.tsv
DOI: 10.18710/sglchg/ognd9j
title: NKS_2022_S22_Deltakelse_figur.png
DOI: 10.18710/sglchg/qydm23
title: NKS_2022_S09_Arkivtjenester_figur.png
DOI: 10.18710/sglchg/ts9et9
title: NKS_2022_S20_Bidrag_kuratornettverk_pivot.tsv
DOI: 10.18710/vk8lus/iswe5f
title: Final_demo_2020_P_Abi_E54_N44.tif
DOI: 10.18710/dja6up/4dsdgr
title: 20240603_KHO_REDTEC_gal.txt
DOI: 10.18710/dja6up/6p2dlu
title: 20240516_KHO_REDTEC_glo.txt
DOI: 10.18710/dja6up/az29ih
title: 20240703_KHO_REDTEC_glo.txt
DOI: 10.18710/dja6up/aziq1i
title: 20240925_KHO_REDTEC_gal.txt
DOI: 10.18710/dja6up/e8hazp
title: 20240614_KHO_REDTEC_gal.txt
DOI: 10.18710/dja6up/l6rj4x
title: 20240419_KHO_REDTEC_gal.txt
DOI: 10.18710/dja6up/uf8uve
title: 20240421_KHO_REDTEC_gal.txt
DOI: 10.18710/dja6up/uusw36
title: 20240710_KHO_REDTEC_gal.txt
DOI: 10.18710/ga1ftv/49qirs
title: 03_2025_Paulabreen-Scheelebreen_Ortho.tif
DOI: 10.18710/jli2bv/g0nsub
title: 00_README.txt
DOI: 10.18710/sinrxp
title: Replication Data for: Biological N2-fixation and grain yield of pigeon pea: The role of biochar and conservation agriculture in low-input systems

description: This dataset contains original research data from Mubende (central Uganda), Alebtong and Gulu (Northern Uganda), for two growing seasons in 2022 and 2023. We investigated the effect of biochar and conservation agriculture on nitrogen derived from the atmosphere (Ndfa%), biological N2-fixation, biomass, grain yield, and soil parameters.
DOI: 10.18710/cl5rsp
title: Maps of soil organic carbon stocks in Norwegian forests

description: Spatial patterns of predicted organic carbon stocks in Norwegian forest soils. The predictions are generated from boosted regression tree models and represent the predicted soil organic carbon stock for three soil depth intervals: (1) soil surface down to 100 cm depth, (2) forest floor (LFH layer), and (3) 0–30 cm into the mineral soil.
description: R, 3.5.2
description: qGIS, 3.22.5
description: INVENT project
description: ICP forest monitoring program on forest health.
description: Lorenz, M., 1995. International co-operative programme on assessment and monitoring of air pollution effects on forests-ICP forests. Water Air Soil Pollut. 85, 1221–1226. https://doi.org/10.1007/BF00477148.
DOI: 10.18710/d9mh96/1dxtow
title: Final_demo_2020_stdev_P_Pic_E39_N29.tif
DOI: 10.18710/d9mh96/65jcy6
title: Final_demo_2020_stdev_P_Pic_E24_N14.tif
DOI: 10.18710/d9mh96/7yv9jy
title: Final_demo_2020_stdev_P_Pic_E34_N14.tif
DOI: 10.18710/d9mh96/dyxi8h
title: Final_demo_2020_stdev_P_Pic_E49_N39.tif
DOI: 10.18710/d9mh96/ku3cgi
title: Final_demo_2020_stdev_P_Pic_E54_N19.tif
DOI: 10.18710/d9mh96/piudct
title: Final_demo_2020_P_Pic_E44_N44.tif
DOI: 10.18710/d9mh96/rfu0a5
title: Final_demo_2020_stdev_P_Pic_E29_N19.tif
DOI: 10.18710/d9mh96/w8fwnu
title: Final_demo_2020_P_Pic_E39_N44.tif
DOI: 10.18710/dja6up/4a1yty
title: 20240513_KHO_REDTEC_glo.txt
DOI: 10.18710/dja6up/oxuvjq
title: 20240606_KHO_REDTEC_gps.txt
DOI: 10.18710/dja6up/tunvpi
title: 20240626_KHO_REDTEC_gal.txt
DOI: 10.18710/do0r0j/yzq74w
title: TS956_bunn00001.JPG
DOI: 10.18710/j1k5xq/njvka3
title: 20240813_HOP_REDOBS_gps.txt
DOI: 10.18710/losnxk/4lkxlu
title: Final_demo_2020_P_Pin_E39_N34.tif
DOI: 10.18710/losnxk/5xgh9g
title: Final_demo_2020_P_Pin_E29_N14.tif
DOI: 10.18710/mmvqdf/gbjkl6
title: respiration_and_cognition_for_dataverseNO.csv
DOI: 10.18710/qxu0fq
title: Replication Data for: Evaluating the effect of risk metrics for supporting operational decision-making by autonomous surface vehicles

description: This dataset contains replication data for the study reported in the paper “Evaluating the effect of risk metrics for supporting operational decision-making by autonomous surface vehicles” (submitted). The goal was to investigate how the choice of risk metric affects the behavior of an autonomous surface vehicle (ASV) that uses risk information from a risk model to support its decision-making during operation. 
This dataset contains data from path planning for an ASV in simulations and field trials. A case study of an ASV operating in cooperation with an autonomous underwater vehicle (AUV) was used. The ASV had to plan a path that considered the risk of collision with another vessel, grounding, and losing communication connection with the AUV. The risk estimate from a risk model was expressed using different risk metrics. The path planning was done using a method for dynamic probabilistic risk assessment named K-shortest paths probabilistic risk assessment (KPRA). The ASV was given the same task, i.e., planning a path between two points while avoiding undesired consequences, but with different risk metrics used to support the decision-making. The resulting paths chosen under the information from different risk metrics were recorded. 
Several datasets are included here, both from simulation studies, where the ASV, AUV, and a target ship (TS) were simulated, and from field trials with a real ASV. The datasets include the location, heading and speed of the vehicles, information about the plans selected by the ASV, and about the waypoints that were explored when searching for the plan. The area of operation was close to the Munkholmen Island in the Trondheimsfjord, Norway.
description: Robot operating system (ROS)
description: DUNE unified navigation environment
description: Python
DOI: 10.18710/sfrkck
title: Supplementary Methods for: "Ethanol Ablation of Metastatic Lymph Nodes in Patients with Papillary Thyroid Carcinoma - Predictors of Clinical Outcome"
title: BRAF-immunohistological staining (IHC) technique, histopathological assessment procedures, and biochemical analysis

description: This file contains the method description for the BRAF-immunohistological staining (IHC) technique, the histopathological assessment procedures, and the biochemical analysis methods in the article “Ethanol Ablation of Metastatic Lymph Nodes in Patients with Papillary Thyroid Carcinoma - Predictors of Clinical Outcome”. The methods described were used to collect and analyze the data underlying the study. The file also includes relevant references to prior work supporting the chosen methodology.
DOI: 10.18710/vk8lus/9rtd8g
title: Final_demo_2020_P_Abi_E44_N24.tif
DOI: 10.18710/vk8lus/d6pbtg
title: Final_demo_2020_P_Abi_E44_N14.tif
DOI: 10.18710/vk8lus/gqatab
title: Final_demo_2020_stdev_P_Abi_E54_N19.tif
DOI: 10.18710/vk8lus/liyqfh
title: Final_demo_2020_P_Abi_E39_N29.tif
DOI: 10.18710/j1k5xq/avlfbw
title: 20240229_HOP_REDOBS_gps.txt
DOI: 10.18710/j1k5xq/exqev0
title: 20240120_HOP_REDOBS_gps.txt
DOI: 10.18710/j1k5xq/gzcwdu
title: 20240111_HOP_REDOBS_gps.txt
DOI: 10.18710/j1k5xq/hxbmat
title: 20240309_HOP_REDOBS_gps.txt
DOI: 10.18710/j1k5xq/mirlax
title: 20240307_HOP_REDOBS_gal.txt
DOI: 10.18710/j1k5xq/mn9nkn
title: 20240101_HOP_REDOBS_gal.txt
DOI: 10.18710/j1k5xq/uxltgp
title: 20240401_HOP_REDOBS_gps.txt
DOI: 10.18710/qxqgwb/4wlt7s
title: 20240629_NYA_REDTEC_glo.txt
DOI: 10.18710/qxqgwb/ftlwl8
title: 20240606_NYA_REDTEC_gal.txt
DOI: 10.18710/qxqgwb/vopz23
title: 20240627_NYA_REDTEC_glo.txt
DOI: 10.18710/vk8lus/my7nhu
title: Final_demo_2020_P_Abi_E29_N14.tif
DOI: 10.18710/do0r0j/6bbv3s
title: TS1240_cruciform.ply
DOI: 10.18710/do0r0j/ahargb
title: TS1131_3D_ambient_o_kompositt.jpg
DOI: 10.18710/do0r0j/cn67mo
title: TS5781A_front00006.JPG
DOI: 10.18710/do0r0j/dr3uce
title: TS1123_front.JPG
DOI: 10.18710/do0r0j/hucncp
title: TS1127_A_knife.jpg
DOI: 10.18710/do0r0j/iuwwkq
title: TS3539A_front00002.JPG
DOI: 10.18710/do0r0j/l97i2h
title: TS3539_D_smallbrooch.ply
DOI: 10.18710/do0r0j/muimne
title: TS15258.4_cruciform.jpg
DOI: 10.18710/do0r0j/pizadi
title: TS1513_front00001.JPG
DOI: 10.18710/do0r0j/tujna7
title: TS2134_cruciform.ply
DOI: 10.18710/do0r0j/xhsmsh
title: TS2070_3D_ambient_o_kompositt.jpg
DOI: 10.18710/j1k5xq/b35wqz
title: 20240926_HOP_REDOBS_gps.txt
DOI: 10.18710/jgccmb/h56n3y
title: PDF.zip

description: Pair distribution function (PDF) files of key stages of (de)sodiation of s-Sb2Se3
DOI: 10.18710/l4ony6/foa3xk
title: 20240118_HOP_REDTEC_glo.txt
DOI: 10.18710/l4ony6/ljil7a
title: 20240108_HOP_REDTEC_gal.txt
DOI: 10.18710/l4ony6/pbqau8
title: 20240315_HOP_REDTEC_gal.txt
DOI: 10.18710/l4ony6/qwwbkz
title: 20240207_HOP_REDTEC_gps.txt
DOI: 10.18710/l4ony6/ylxvir
title: 20240108_HOP_REDTEC_glo.txt
DOI: 10.18710/losnxk/9jfkxy
title: Final_demo_2020_stdev_P_Pin_E34_N19.tif
DOI: 10.18710/losnxk/m9nshf
title: Final_demo_2020_P_Pin_E44_N54.tif
DOI: 10.18710/losnxk/ugasno
title: Final_demo_2020_P_Pin_E24_N14.tif
DOI: 10.18710/ozpaww/imiynj
title: 20241110_BJN_REDTEC_glo.txt
DOI: 10.18710/ozpaww/nby5ff
title: 20241001_BJN_REDTEC_gal.txt
DOI: 10.18710/ozpaww/vobeqj
title: 20241015_BJN_REDTEC_glo.txt
DOI: 10.18710/ozpaww/zdutkg
title: 20241122_BJN_REDTEC_gps.txt
DOI: 10.18710/ozpaww/zih6hr
title: 20241230_BJN_REDTEC_gal.txt
DOI: 10.18710/qxqgwb/vzjnun
title: 20240707_NYA_REDTEC_gps.txt
DOI: 10.18710/vk8lus
title: Abies (P_Abi) map for 2020

description: This 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 (&lt;a href="https://doi.org/10.18710/OEYKEG" title="Documentation" target="_blank"&gt;https://doi.org/10.18710/OEYKEG&lt;/a&gt;) 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. &lt;a href="https://doi.org/10.5281/zenodo.17107267" title="Documentation" target="_blank"&gt;https://doi.org/10.5281/zenodo.17107267&lt;/a&gt;.
description: Abies (P_Abi)
DOI: 10.18710/vk8lus/7bsnzn
title: Final_demo_2020_P_Abi_E49_N34.tif
DOI: 10.18710/vk8lus/hixtfq
title: Final_demo_2020_stdev_P_Abi_E39_N14.tif
DOI: 10.18710/vk8lus/mfgnbw
title: Final_demo_2020_P_Abi_E44_N29.tif
DOI: 10.18710/vk8lus/ocozk4
title: Final_demo_2020_stdev_P_Abi_E29_N29.tif
DOI: 10.18710/vk8lus/ogtbyb
title: Final_demo_2020_stdev_P_Abi_E24_N19.tif