cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7483/opendata.cms.ta04.xxlj
title: /WtoLNuBB_VBF_TypeIHeavyN-El_MN500_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.13021/orc2020/hzi4lj/u6m0e1
title: 03102023_DL_JC_1_neutral.MP4
DOI: 10.13021/orc2020/hzi4lj/x3zmnh
title: 03102023_as_ENGR_2_neutral.MP4
DOI: 10.13021/orc2020/hzi4lj/rlwcnl
title: 03102023_as_ENGR_4_neutral.MP4
DOI: 10.13021/orc2020/hzi4lj/omxdtl
title: 03102023_DL_ENGR_Jc_1_neutral.MP4
DOI: 10.7483/opendata.cms.wk87.pekx
title: /WtoLNuBB_VBF_TypeIHeavyN-El_MN700_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v3/MINIAODSIM
DOI: 10.13021/orc2020/hzi4lj/p94oqg
title: 03102023_as_ENGR_1_neutral.MP4
DOI: 10.6084/m9.figshare.28219796
title: Landscape Words NA - Kand..xlsx

description: Raw data for the BA thesis "Inverted Stones and Shaman Houses: Semantic Typology of Landscape in Languages of North America" - Daniel Wahlström
DOI: 10.6084/m9.figshare.28219796.v1
title: Landscape Words NA - Kand..xlsx

description: Raw data for the BA thesis "Inverted Stones and Shaman Houses: Semantic Typology of Landscape in Languages of North America" - Daniel Wahlström
DOI: 10.13021/orc2020/hzi4lj/jc9nfh
title: 03102023_DL_JC_2_neutral.MP4
DOI: 10.13021/orc2020/hzi4lj/x7igwg
title: 03102023_as_ENGR_3_neutral.MP4
DOI: 10.7483/opendata.cms.46dd.tpu5
title: /WtoLNuBB_VBF_TypeIHeavyN-El_MN700_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.6084/m9.figshare.28219733.v1
title: <b>Biotic and abiotic drivers of </b><b>ecosystem </b><b>temporal</b><b> stability </b><b>in herbaceous </b><b>wetlands</b><b> in China</b>

description: Maintaining the stability of ecosystems is critical for supporting essential ecosystem services over time. However, our understanding of the contribution of the diverse biotic and abiotic factors to this stability in wetlands remains limited. Here, we combined data from a field vegetation survey of 725 herbaceous wetland sites in China with remote sensing information from the Enhanced Vegetation Index (EVI) from 2010 to 2020 to explore the contribution of biotic and abiotic factors to the temporal stability of primary productivity. We found that plant species richness directly contributed to stability on a national scale, but that this contribution differed among climate zones, hydrological regimes, and vegetation types. In addition, many abiotic factors including soil properties, geographical location, and climate also contributed to stability. Piecewise structural equation modeling identified that soil properties including soil pH, total nitrogen, and soil organic carbon emerged as primary factors modulating ecosystem stability, both directly and indirectly by affecting species richness and vegetation type. Higher species richness and soil organic carbon were related to higher ecosystem stability in peatlands but less so in coastal and inland marshes. These findings enhance our ability to forecast how wetland ecosystems may respond to future environmental changes and biodiversity loss and can inform policy decisions related to ecosystem stability.
DOI: 10.13021/orc2020/hzi4lj/fifltw
title: 03102023_ar_Inside_JC_2_neutral.bag
DOI: 10.6084/m9.figshare.28219733
title: <b>Biotic and abiotic drivers of </b><b>ecosystem </b><b>temporal</b><b> stability </b><b>in herbaceous </b><b>wetlands</b><b> in China</b>

description: Maintaining the stability of ecosystems is critical for supporting essential ecosystem services over time. However, our understanding of the contribution of the diverse biotic and abiotic factors to this stability in wetlands remains limited. Here, we combined data from a field vegetation survey of 725 herbaceous wetland sites in China with remote sensing information from the Enhanced Vegetation Index (EVI) from 2010 to 2020 to explore the contribution of biotic and abiotic factors to the temporal stability of primary productivity. We found that plant species richness directly contributed to stability on a national scale, but that this contribution differed among climate zones, hydrological regimes, and vegetation types. In addition, many abiotic factors including soil properties, geographical location, and climate also contributed to stability. Piecewise structural equation modeling identified that soil properties including soil pH, total nitrogen, and soil organic carbon emerged as primary factors modulating ecosystem stability, both directly and indirectly by affecting species richness and vegetation type. Higher species richness and soil organic carbon were related to higher ecosystem stability in peatlands but less so in coastal and inland marshes. These findings enhance our ability to forecast how wetland ecosystems may respond to future environmental changes and biodiversity loss and can inform policy decisions related to ecosystem stability.
DOI: 10.13021/orc2020/hzi4lj/x2msnd
title: 03102023_ar_Eng_JC_2_neutral.bag
DOI: 10.7483/opendata.cms.7ek4.jzk0
title: /WtoLNuBB_VBF_TypeIHeavyN-Mu_MN1000_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v3/MINIAODSIM
DOI: 10.13021/orc2020/hzi4lj/1zzsed
title: 03102023_ar_Inside_JC_1_neutral.bag
DOI: 10.13021/orc2020/hzi4lj/oa2d52
title: 03102023_ar_Eng_JC_1_neutral.bag
DOI: 10.7483/opendata.cms.zshm.pblh
title: /WtoLNuBB_VBF_TypeIHeavyN-Mu_MN1000_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.13021/orc2020/hzi4lj/lo9eae
title: 03102023_ar_Eng_JC_3_neutral.bag
DOI: 10.15468/dl.zjsa5n
title: Occurrence Download

description: A dataset containing 85060 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Brassica napus L."
 ]
}

 The dataset includes 85060 records from 1149 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0072770-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7483/opendata.cms.xuq6.98mv
title: /WtoLNuBB_VBF_TypeIHeavyN-Mu_MN1500_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.13021/orc2020/hzi4lj/noaegy
title: 03252023_mn_fairfax_street_4_neutral.bag
DOI: 10.7483/opendata.cms.367y.bvpz
title: /WtoLNuBB_VBF_TypeIHeavyN-Mu_MN1500_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.13021/orc2020/hzi4lj/msmzdk
title: 03252023_mn_fairfax_street_3_neutral.bag
DOI: 10.13021/orc2020/hzi4lj/lw8r2n
title: 03252023_mn_fairfax_street_2_neutral.bag
DOI: 10.7483/opendata.cms.uc0s.1d1c
title: /WtoLNuBB_VBF_TypeIHeavyN-Mu_MN2000_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v3/MINIAODSIM
DOI: 10.13021/orc2020/hzi4lj/ij96ky
title: frontal_approach_8.MP4
DOI: 10.13021/orc2020/hzi4lj/p82srr
title: frontal_approach_3.MP4
DOI: 10.7483/opendata.cms.3pkz.aufz
title: /WtoLNuBB_VBF_TypeIHeavyN-Mu_MN2000_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.13021/orc2020/hzi4lj/2owurb
title: 03252023_mn_fairfax_street_6_neutral.bag
DOI: 10.13021/orc2020/hzi4lj/6bz8js
title: 03252023_mn_fairfax_street_5_neutral.bag
DOI: 10.13021/orc2020/hzi4lj/g2sq8n
title: 03252023_mn_fairfax_street_1_neutral.bag
DOI: 10.13021/orc2020/hzi4lj/qkix2f
title: 03252023_mn_fairfax_street_7_neutral.bag
DOI: 10.13021/orc2020/hzi4lj/0tbvcz
title: frontal_approach_1.MP4
DOI: 10.13021/orc2020/hzi4lj/jp8vqj
title: 03252023_mn_fairfax_street_8_neutral.bag
DOI: 10.7483/opendata.cms.qll1.n7wu
title: /WtoLNuBB_VBF_TypeIHeavyN-Mu_MN3000_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v3/MINIAODSIM
DOI: 10.13021/orc2020/hzi4lj/oi8atq
title: frontal_approach_19.MP4
DOI: 10.13021/orc2020/hzi4lj/w08a4i
title: frontal_approach_2.MP4
DOI: 10.13021/orc2020/hzi4lj/tw162v
title: frontal_approach_6.MP4
DOI: 10.13021/orc2020/hzi4lj/sbmgah
title: frontal_approach_15.MP4
DOI: 10.7483/opendata.cms.8rnb.lz6b
title: /WtoLNuBB_VBF_TypeIHeavyN-Mu_MN3000_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.13021/orc2020/hzi4lj/ki80il
title: frontal_approach_11.MP4
DOI: 10.13021/orc2020/hzi4lj/jnt4hb
title: frontal_approach_18.MP4
DOI: 10.7483/opendata.cms.28rs.sjbi
title: /WtoLNuBB_VBF_TypeIHeavyN-Mu_MN500_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v3/MINIAODSIM
DOI: 10.13021/orc2020/hzi4lj/pd75wm
title: frontal_approach_14.MP4
DOI: 10.13021/orc2020/hzi4lj/wwty72
title: frontal_approach_13.MP4
DOI: 10.7483/opendata.cms.dasb.0fsu
title: /WtoLNuBB_VBF_TypeIHeavyN-Mu_MN500_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.13021/orc2020/hzi4lj/hbxnex
title: frontal_approach_7.MP4
DOI: 10.13021/orc2020/hzi4lj/mhkek4
title: mn_gmu_engr.MP4
DOI: 10.13021/orc2020/hzi4lj/mj7oa8
title: frontal_approach_12.MP4
DOI: 10.7483/opendata.cms.ak9h.kd5c
title: /WtoLNuBB_VBF_TypeIHeavyN-Mu_MN700_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.13021/orc2020/hzi4lj/lbzyre
title: frontal_approach_4.MP4
DOI: 10.13021/orc2020/hzi4lj/kdomkh
title: frontal_approach_17.MP4
DOI: 10.7483/opendata.cms.cs35.ilc5
title: /WtoLNuBB_VBF_TypeIHeavyN-Mu_MN700_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.13021/orc2020/hzi4lj/ywec3u
title: frontal_approach_9.MP4
DOI: 10.13021/orc2020/hzi4lj/1jjwpv
title: frontal_approach_5.MP4
DOI: 10.13021/orc2020/hzi4lj/6rfzni
title: frontal_approach_20.MP4
DOI: 10.7483/opendata.cms.wsal.n0w6
title: /WtoLNuJJ_TypeIHeavyN-El_MN1000_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v3/MINIAODSIM
DOI: 10.13021/orc2020/hzi4lj/zz32ly
title: frontal_approach_16.MP4
DOI: 10.13021/orc2020/hzi4lj/pbdvi9
title: frontal_approach_10.MP4
DOI: 10.7483/opendata.cms.48wd.5n2n
title: /WtoLNuJJ_TypeIHeavyN-El_MN1000_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.13021/orc2020/hzi4lj/tmujww
title: tags.tab

description: Data files and their interaction tags
DOI: 10.13021/orc2020/hzi4lj/lvjkoc
title: 06272023_SA_JC_2_neutral.bag
DOI: 10.13021/orc2020/hzi4lj/qblxbg
title: 06272023_SA_JC to ENGR_1_neutral.bag
DOI: 10.13021/orc2020/hzi4lj/pm7tvn
title: 06272023_SA_JC_1_neutral.bag
DOI: 10.7483/opendata.cms.41oj.2mkg
title: /WtoLNuJJ_TypeIHeavyN-El_MN1500_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v3/MINIAODSIM
DOI: 10.13021/orc2020/hzi4lj/pmzjcs
title: 06282023_HE_MIX_1_neutral.bag
DOI: 10.13021/orc2020/hzi4lj/w43xdo
title: 06272023_KS_JC_2_neutral.bag
DOI: 10.7483/opendata.cms.uzv4.7nh9
title: /WtoLNuJJ_TypeIHeavyN-El_MN1500_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.13021/orc2020/hzi4lj/ygpzy1
title: 06272023_WW_ENGR2JC_1_neutral.bag
DOI: 10.13021/orc2020/hzi4lj/75smq4
title: 06282023_PR_JC_1_neutral.bag
DOI: 10.7483/opendata.cms.9cmo.cto3
title: /WtoLNuJJ_TypeIHeavyN-El_MN2000_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v3/MINIAODSIM
DOI: 10.13021/orc2020/hzi4lj/yx0gxu
title: 06282023_HE_MIXTOeng_1_neutral.bag
DOI: 10.13021/orc2020/hzi4lj/abdab6
title: 06282023_WW_ENGR to JC_1_neutral.bag
DOI: 10.13021/orc2020/hzi4lj/1rwg93
title: 06282023_PR_MIX_1_neutral.bag
DOI: 10.7483/opendata.cms.708k.2jmx
title: /WtoLNuJJ_TypeIHeavyN-El_MN2000_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.13021/orc2020/hzi4lj/isvdcj
title: 06272023_KS_JC_1_neutral.bag
DOI: 10.13021/orc2020/hzi4lj/5ccxtj
title: 07032023_PR_GMUCampus2_3_neutral.bag
DOI: 10.7483/opendata.cms.wn7x.4c5g
title: /WtoLNuJJ_TypeIHeavyN-El_MN200_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v3/MINIAODSIM
DOI: 10.13021/orc2020/hzi4lj/tmyvnt
title: 07032023_PR_GMUCampus2_2_neutral.bag
DOI: 10.13021/orc2020/hzi4lj/ko1xks
title: 07032023_HE_GMUCampus2_2_neutral.bag
DOI: 10.13021/orc2020/hzi4lj/rbpptd
title: 07032023_PR_GMUCampus2_4_neutral.bag
DOI: 10.7483/opendata.cms.xmou.snfk
title: /WtoLNuJJ_TypeIHeavyN-El_MN200_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.13021/orc2020/hzi4lj/kdzicc
title: 07032023_PR_GMUCampus2_1_neutral.bag
DOI: 10.13021/orc2020/hzi4lj/fziwac
title: 07032023_HE_GMUCampus2_1_neutral.bag
DOI: 10.57745/czawzv
title: Dimensionnement_travail.zip

description: :unav
DOI: 10.57745/lbxlqp
title: Module_dimensionnement_travail.xlsx

description: :unav
DOI: 10.57745/mfah6j
title: Module_dimensionnement_travail.ods

description: :unav
DOI: 10.7483/opendata.cms.149m.rbi4
title: /WtoLNuJJ_TypeIHeavyN-El_MN3000_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.13021/orc2020/hzi4lj/6up3ih
title: 07032023_SA_GMUCampus_1_neutral.bag
DOI: 10.13021/orc2020/hzi4lj/quflfk
title: 07032023_SA_NGYtoJC_1_neutral.bag
DOI: 10.13021/orc2020/hzi4lj/xhyzm8
title: 07032023_WW_GMUCampus2_1_neutral.bag
DOI: 10.7483/opendata.cms.udd9.q73z
title: /WtoLNuJJ_TypeIHeavyN-El_MN3000_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.13021/orc2020/hzi4lj/qqlwzx
title: 07032023_HE_GMUCampus2_3_neutral.bag
DOI: 10.13021/orc2020/hzi4lj/4qpdnh
title: 07052023_PR_UnivMall_1_neutral.bag
DOI: 10.13021/orc2020/hzi4lj/7iwinf
title: 07052023_HE_UnivMall_2_neutral.bag
DOI: 10.7483/opendata.cms.gbhr.ugmj
title: /WtoLNuJJ_TypeIHeavyN-El_MN300_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v3/MINIAODSIM
DOI: 10.13021/orc2020/hzi4lj/jxcedf
title: 07032023_WW_GMUCampus_1_neutral.bag
DOI: 10.13021/orc2020/hzi4lj/7jicye
title: 07032023_WW_GMUCampus2_1_neutral.bag.active
DOI: 10.7483/opendata.cms.b9sp.u81p
title: /WtoLNuJJ_TypeIHeavyN-El_MN300_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.13021/orc2020/hzi4lj/70bs3t
title: 07052023_HE_UnivMall_3_neutral.bag
DOI: 10.13021/orc2020/hzi4lj/whdnm9
title: 07052023_PR_UnivMall_2_neutral.bag
DOI: 10.7483/opendata.cms.punf.889u
title: /WtoLNuJJ_TypeIHeavyN-El_MN400_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v3/MINIAODSIM
DOI: 10.13021/orc2020/hzi4lj/veblri
title: 07052023_PR_UnivMall_4_neutral.bag
DOI: 10.13021/orc2020/hzi4lj/xkfux1
title: 07052023_HE_UnivMall_4_neutral.bag
DOI: 10.13021/orc2020/hzi4lj/liqvds
title: 07052023_HE_UnivMall_1_neutral.bag
DOI: 10.7483/opendata.cms.75yi.adwc
title: /WtoLNuJJ_TypeIHeavyN-El_MN400_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.13021/orc2020/hzi4lj/pukwyt
title: 07052023_PR_UnivMall_3_neutral.bag
DOI: 10.2908/inn_cis13_pub_ip
title: Enterprises by access to public funding, innovation profile, type of public funding and effect, NACE Rev. 2 activity and size class (CIS2022)
title: Entreprises par accès au financement public, profil d’innovation, type de financement public et effet, activité de la NACE Rév. 2 et classe de taille (CIS2022)
title: Unternehmen nach Zugang zu öffentlicher Finanzierung, Innovationsprofil, Art der öffentlichen Finanzierung und Wirkung, NACE Rev. 2 Tätigkeit und Größenklasse (CIS2022)
DOI: 10.13021/orc2020/hzi4lj/luumfs
title: 07072023_SA_FairfaxCorner_5_neutral.bag
DOI: 10.2908/inn_cis13_co_ip
title: Enterprises that co-operated on business activities with other entities, by innovation profile, NACE Rev. 2 activity and size class (CIS2022)
title: Entreprises ayant coopéré à leurs activités avec d’autres entités par profil d’innovation, activité de la NACE Rév. 2 et classe de taille (CIS2022)
title: Unterhemen, die Unternehmensaktivitäten mit anderen Einheiten zusammen durchgeführt haben, nach Innovationsprofil, NACE Rev. 2 Tätigkeit und Größenklasse (CIS2022)
DOI: 10.2908/inn_cis13_coop_ip
title: Innovation-active enterprises that co-operated with other entities, by innovation profile, kind and location of co-operation partner, NACE Rev. 2 and size class (CIS2022)
title: Entreprises menant des activités d’innovation ayant coopéré avec d’autres entités, par profil d’innovation, nature et localisation du partenaire de coopération, activité de la NACE Rév. 2 et classe de taille (CIS2022)
title: Innovationsaktive Unternehmen, die mit anderen Einheiten kooperiert haben, nach Innovationsprofil, Art und Sitz des Kooperationspartners, NACE Rev. 2 Tätigkeit und Größenklasse (CIS2022)
DOI: 10.2908/inn_cis13_yreg_ip
title: Enterprises by age and innovation profile, NACE Rev. 2 activity and size class (CIS2022)
title: Entreprises par âge et profil d’innovation, activité de la NACE Rév. 2 et classe de taille (CIS2022)
title: Unternehmen nach Alter und Innovationsprofil, NACE Rev. 2 Tätigkeit und Größenklasse (CIS2022)
DOI: 10.2908/inn_cis13_fin_ip
title: Enterprises by access to private funding, innovation profile, type of private funding and effect, NACE Rev. 2 activity and size class (CIS2022)
title: Entreprises par accès au financement privé, profil d’innovation, type de financement privé et effet, activité de la NACE Rév. 2 et classe de taille (CIS2022)
title: Unternehmen nach Zugang zu privater Finanzierung, Innovationsprofil, Art der privaten Finanzierung und Wirkung, NACE Rev. 2 Tätigkeit und Größenklasse (CIS2022)
DOI: 10.2908/inn_cis13_finrd_ip
title: Enterprises that obtained private funding by usage for R&D or other innovation activities, by innovation profile, type of private funding, NACE Rev. 2 activity and size class (CIS2022)
title: Entreprises ayant obtenu un financement privé par utilisation pour la R&D ou d’autres activités d’innovation, par profil d’innovation, type de financement privé, activité de la NACE Rév. 2 et classe de taille (CIS2022)
title: Unternehmen, die eine private Finanzierung erhalten haben, nach Nutzung für F&E oder andere Innovationsaktivitäten, Innovationsprofil, Art der privaten Finanzierung, NACE Rev. 2 Tätigkeit und Größenklasse (CIS2022)
DOI: 10.7483/opendata.cms.xh9g.i1xv
title: /WtoLNuJJ_TypeIHeavyN-El_MN500_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.13021/orc2020/hzi4lj/ar0xng
title: 07072023_KS_FairfaxCorner_1_neutral.bag
DOI: 10.2908/inn_cis13_eco_ip
title: Innovation-active enterprises that introduced innovations with environmental benefits within the enterprise, by innovation profile, type of contribution and effect, NACE Rev. 2 activity and size class (CIS2022)
title: Entreprises menant des activités d’innovation ayant introduit des innovations présentant des avantages environnementaux au sein de l’entreprise, par profil d'innovation, type de contribution et effet, activité de la NACE Rév. 2 et classe de taille (CIS2022)
title: Innovationsaktive Unternehmen, nach Art und Wichtigkeit des Nutzens, der durch Umweltinnovationen bei den Unternehmensprozessen erreicht worden ist, Innovationsprofil, NACE Rev. 2 Tätigkeit und Größenklasse (CIS2022)
DOI: 10.13021/orc2020/hzi4lj/xxdyap
title: 07072023_SA_FairfaxCorner_6_neutral.bag
DOI: 10.13021/orc2020/hzi4lj/nailjq
title: 07072023_SA_FairfaxCorner_4_neutral.bag
DOI: 10.7483/opendata.cms.p4q3.0sld
title: /WtoLNuJJ_TypeIHeavyN-El_MN500_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.13021/orc2020/hzi4lj/eedsyk
title: 07072023_SA_FairfaxCorner_1_neutral.bag
DOI: 10.13021/orc2020/hzi4lj/eiihsw
title: 07072023_SA_FairfaxCorner_3_neutral.bag
DOI: 10.7483/opendata.cms.8v7m.ukpg
title: /WtoLNuJJ_TypeIHeavyN-El_MN700_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v3/MINIAODSIM
DOI: 10.13021/orc2020/hzi4lj/qpaugp
title: 07052023_WW_UnivMall_4_neutral.bag
DOI: 10.13021/orc2020/hzi4lj/9snqxn
title: 07052023_WW_UnivMall_2_neutral.bag
DOI: 10.13021/orc2020/hzi4lj/ma0i8f
title: 07052023_WW_UnivMall_3_neutral.bag
DOI: 10.7483/opendata.cms.5u3z.t3gg
title: /WtoLNuJJ_TypeIHeavyN-El_MN700_TuneCP5_13TeV-amcatnlo-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.13021/orc2020/hzi4lj/zyghu9
title: 07072023_SA_FairfaxCorner_2_neutral.bag
DOI: 10.13021/orc2020/hzi4lj/dfsoed
title: 07132023_KS_FairfaxCorner_6_neutral.bag
DOI: 10.13021/orc2020/hzi4lj/ll2x7t
title: 07132023_SA_FairfaxCorner_2_neutral.bag
DOI: 10.15468/dl.btuhqs
title: Occurrence Download

description: A dataset containing 1045934 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Carassius auratus (Linnaeus, 1758), Carassius carassius (Linnaeus, 1758), Ctenopharyngodon idella (Valenciennes, 1844), Cyprinus carpio Linnaeus, 1758, Esox lucius Linnaeus, 1758)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1045934 records from 1127 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0072763-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dwa3tt
title: Occurrence Download

description: A dataset containing 396 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Brazil",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Senegalia piauhiensis"
 ]
}

 The dataset includes 396 records from 60 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001148-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.23728/b2share.76ce70e888b04f0a8b86308ec9a06189
title: NP-M01

description: Nanopublication example for AP3 Quantencomputing in FDOConnect
DOI: 10.15468/dl.f8by2m
title: Occurrence Download

description: A dataset containing 625 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Potamotrygon orbignyi)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 625 records from 35 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001150-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.23728/b2share.a53bc45c3c34419eb8d44bc1d427e349
title: NP-M02

description: Nanopublication example for AP3 Quantencomputing in FDOConnect
DOI: 10.23728/b2share.38cd73f8ba3940a9a4669e674d01c753
title: NP-M03

description: Nanopublication example for AP3 Quantencomputing in FDOConnect
DOI: 10.15468/dl.ym9pbf
title: Occurrence Download

description: A dataset containing 10372 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is North America",
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "StateProvince is one of (Tlaxcala, Puebla, Estado de Mexico, Hidalgo, Distrito Federal)",
 "TaxonKey is one of (Fagaceae, Lamiaceae)",
 "Year 1994-2025"
 ]
}

 The dataset includes 10372 records from 53 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001152-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.23728/b2share.f6020a07728d4c2a8dc92fd183109b69
title: NP-M03

description: Nanopublication example for AP3 Quantencomputing in FDOConnect