cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.18710/uezzus
title: Replication Data for: Svalbard through the prism of Russian media
title: A discourse and cognitive perspective

description: &lt;p&gt;The study applies Market Basket Analysis and Keymorph Analysis to analyze the articles related to Svalbard published in a sample of Russian mainstream federal and north-western regional media outlets produced between 2010 and 2021. The data for Market Basket Analysis is divided into six target subcorpora: Federal 2010-2013, Regional 2010-2013, Federal 2014-2017, Regional 2014-2017, Federal 2018-2021, and Regional 2018-2021. The data for Keymorph Analysis consists of six target subcorpora: Federal 2010-2013*, Regional 2010-2013*, Federal 2014-2017*, Regional 2014-2017*, Federal 2018-2021*, and Regional 2018-2021*. The data for Keymorph Analysis are the texts containing the keyword 'Spitsbergen' obtained from the data for Market Basket Analysis. Market Basket Analysis is used to retrieve Associative Arrays consisting of various keywords for the keyword meaning 'Spitsbergen'. Keymorph Analysis examines the prominence of the grammatical cases of nouns meaning 'Russia', 'Norway', and 'Spitsbergen'.&lt;/p&gt;
&lt;p&gt;The dataset includes: 1) the R code for keyword analysis (keywords serve as an input for Market Basket Analysis); 2) lists of keywords obtained from six target subcorpora Federal 2010-2013, Regional 2010-2013, Federal 2014-2017, Regional 2014-2017, Federal 2018-2021, and Regional 2018-2021; 3) the R code for Market Basket Analysis; 4) examples with the nouns meaning 'Russia', 'Norway', and 'Spitsbergen' extracted from six target subcorpora Federal 2010-2013*, Regional 2010-2013*, Federal 2014-2017*, Regional 2014-2017*, Federal 2018-2021*, and Regional 2018-2021* and annotated according to the grammatical cases of these nouns as well as the semantic meanings of the cases; 5) the calculated difference index (DIN*) values for the grammatical cases of the nouns meaning 'Russia', 'Norway', and 'Spitsbergen'. The DIN* was used in Keymorph Analysis as the effect size metric; 6) the R code for creation of the bar chart with DIN* values for the grammatical cases of the nouns meaning 'Russia', 'Norway', and 'Spitsbergen'.&lt;/p&gt;
description: Sketch Engine
description: RStudio, 1.4.1717
DOI: 10.18710/arlx23/frshdi
title: 20240709_BJN_REDOBS_gps.txt
DOI: 10.18710/arlx23/gd5hca
title: 20240729_BJN_REDOBS_gps.txt
DOI: 10.18710/arlx23/ghj1ti
title: 20240906_BJN_REDOBS_gps.txt
DOI: 10.18710/arlx23/kpccjk
title: 20240714_BJN_REDOBS_gal.txt
DOI: 10.18710/arlx23/kq4akh
title: 20240918_BJN_REDOBS_gal.txt
DOI: 10.18710/ivua0a/crfghf
title: 07_coll-profile_bekannt_POS.png
DOI: 10.18710/ivua0a/cxatui
title: 06_coll-profile_befinden_POS.txt
DOI: 10.18710/ivua0a/k842ma
title: 07_coll-profile_breit_POS.png
DOI: 10.18710/ivua0a/vlsjby
title: 07_coll-profile_neuADJA_Lemma.txt
DOI: 10.18710/arlx23/a0eafx
title: 20240805_BJN_REDOBS_gps.txt
DOI: 10.18710/arlx23/bflco9
title: 20240709_BJN_REDOBS_glo.txt
DOI: 10.18710/arlx23/ducjw5
title: 20240902_BJN_REDOBS_gps.txt
DOI: 10.18710/arlx23/fjchfz
title: 20241114_BJN_REDOBS_gal.txt
DOI: 10.18710/arlx23/q8fzjm
title: 20241107_BJN_REDOBS_glo.txt
DOI: 10.18710/arlx23/ukh6bn
title: 20240805_BJN_REDOBS_glo.txt
DOI: 10.18710/arlx23/uqloxf
title: 20240808_BJN_REDOBS_gps.txt
DOI: 10.18710/arlx23/vacqe0
title: 20241029_BJN_REDOBS_gps.txt
DOI: 10.18710/arlx23/vpcqfx
title: 20240727_BJN_REDOBS_gal.txt
DOI: 10.18710/arlx23/yphnpk
title: 20240718_BJN_REDOBS_glo.txt
DOI: 10.18710/dja6up/boaeeb
title: 20240523_KHO_REDTEC_gal.txt
DOI: 10.18710/dja6up/fqd0vn
title: 20240605_KHO_REDTEC_glo.txt
DOI: 10.18710/dja6up/gz8ka7
title: 20240701_KHO_REDTEC_gps.txt
DOI: 10.18710/dja6up/hgjqqn
title: 20240528_KHO_REDTEC_gps.txt
DOI: 10.18710/dja6up/llnv5d
title: 20240404_KHO_REDTEC_gal.txt
DOI: 10.18710/dja6up/luwd9s
title: 20240524_KHO_REDTEC_glo.txt
DOI: 10.18710/dja6up/mpjoc3
title: 20240819_KHO_REDTEC_gal.txt
DOI: 10.18710/dja6up/np75wk
title: 20240905_KHO_REDTEC_gps.txt
DOI: 10.18710/dja6up/wazmbh
title: 20240502_KHO_REDTEC_glo.txt
DOI: 10.18710/dja6up/z7oyy1
title: 20240610_KHO_REDTEC_glo.txt
DOI: 10.18710/h8ektm/dpkvtq
title: F063.2023-02-16.edi
DOI: 10.18710/hfif8k/xwhchi
title: ShortTransparentMeta.csv
DOI: 10.18710/ivua0a/2yapbf
title: 06_coll-profile_finden_POS.png
DOI: 10.18710/ivua0a/3dg6z5
title: 06_coll-profile_verlaufen_Lemma.png
DOI: 10.18710/ivua0a/3fd9f1
title: 07_coll-profile_jüdisch_POS.txt
DOI: 10.18710/ivua0a/3rgqwr
title: 07_coll-profile_nah_Lemma.txt
DOI: 10.18710/ivua0a/7ca8yu
title: 07_coll-profile_gutADJA_Lemma.png
DOI: 10.18710/ivua0a/7hkemj
title: 06_coll-profile_fahren_POS.png
DOI: 10.18710/ivua0a/7n7na9
title: 07_coll-profile_direkt_Lemma.txt
DOI: 10.18710/ivua0a/abc3by
title: 07_coll-profile_früh_Lemma.txt
DOI: 10.18710/ivua0a/acswys
title: 07_coll-profile_langADJD_POS.txt
DOI: 10.18710/ivua0a/bf9ena
title: 06_coll-profile_stehen_POS.png
DOI: 10.18710/ivua0a/frz9st
title: 06_coll-profile_stehen_POS.txt
DOI: 10.18710/ivua0a/ggchyt
title: 07_coll-profile_gelegen_POS.png
DOI: 10.18710/ivua0a/owrrzg
title: 06_coll-profile_verlaufen_POS.png
DOI: 10.18710/ivua0a/qs0lof
title: 07_coll-profile_einstig_Lemma.png
DOI: 10.18710/ivua0a/qxxyyi
title: 07_coll-profile_verschieden_POS.png
DOI: 10.18710/ivua0a/rby60x
title: 07_coll-profile_weitläufig_Lemma.txt
DOI: 10.18710/ivua0a/t0avlh
title: 06_coll-profile_errichten_POS.png
DOI: 10.18710/ivua0a/tpzb0p
title: 07_coll-profile_erbaut_Lemma.png
DOI: 10.18710/ivua0a/uaoz4d
title: 04_coll_PB4abxNouns_Lemma.txt
DOI: 10.18710/ivua0a/vkbb6u
title: 07_coll-profile_rot_POS.txt
DOI: 10.18710/ivua0a/wphiwa
title: 03_coll_PB0abcdxPB_POS.png
DOI: 10.18710/ivua0a/wv0qbp
title: 06_coll-profile_befinden_POS.png
DOI: 10.18710/ivua0a/xc5qpq
title: 07_coll-profile_weitläufig_POS.txt
DOI: 10.18710/ivua0a/yjynze
title: 07_coll-profile_zweit_Lemma.txt
DOI: 10.18710/l0vpw7/6jhz9u
title: SBL028_Subt4__14__16-03-40-502.txt
DOI: 10.18710/l0vpw7/glljan
title: SBL122_Subt2__8__18-32-59-794.txt
DOI: 10.18710/lmnlau/lkiupu
title: AnalyseÅlbusetra.xlsx
DOI: 10.18710/rxiuhf/0rhlgs
title: 03_Uniaxial_compression_B02_5.6-5.7_CL.txt
DOI: 10.18710/rxiuhf/4bcqhg
title: 03_Uniaxial_compression_B03_2.1-2.2_CL.txt
DOI: 10.18710/rxiuhf/4fbltj
title: 03_Uniaxial_compression_B02_4.2-4.3_CL.txt
DOI: 10.18710/rxiuhf/biyigz
title: 03_Uniaxial_compression_B02_5.80-5.90_CSR.txt
DOI: 10.18710/rxiuhf/cfvjcz
title: 03_Uniaxial_compression_B02_4.1-4.2_CL.txt
DOI: 10.18710/ugnife/apn0yc
title: PSGO_15.csv
DOI: 10.18710/ugnife/wmfte3
title: PSG_37.csv
DOI: 10.18710/3lt3qu/2oiln5
title: probabilisticupscaling_permeabilityporositychanges_v1.1.zip

description: Numerical simulation data files, including alterations in porous geometries over time/reaction progress and associated porosity-permeability
DOI: 10.18710/arlx23/vwldw9
title: 20240725_BJN_REDOBS_gal.txt
DOI: 10.18710/pabu7q
title: Supporting data for the article: The crystal structure of dypingite: Understanding the long-range disorder
title: Crystal Structure of Dehydrated Dypingite Dataset

description: The Crystal Structure of Dehydrated Dypingite Dataset comprises comprehensive experimental data supporting the first structural characterization of dehydrated dypingite (Mg5(CO3)4.5(2)(OH)0.96(3)·5.0(2)H2O), a hydrated magnesium carbonate hydroxide mineral that remained structurally unknown for over five decades due to aggregated morphology and structural disorder. 

The dataset provides systematic experimental evidence demonstrating that ambient humidity significantly influences dypingite's structural properties: high humidity (80% RH) causes inhomogeneous unit cell expansion along the c-axis with long-range lattice disorder, while low humidity (20% RH) yields reduced disorder and shorter lattice parameters, with samples differing by one water molecule of hydration. 

The dataset includes:
1) synchrotron powder X-ray diffraction patterns of hydrated and dehydrated dypingite samples (both synthetic and mineral);
2) time-resolved dehydration data;
3) results of thermogravimetric analysis of hydrated and dehydrated synthetic dypingite; 
4) refined crystal structure of dehydrated dypingite. 

By making these data publicly available, we hope to spark researchers’ interest in dypingite, paving the way for broader utilization of this eco-friendly material in everyday life.
description: Topas, v6
description: GSASII, 5790
description: NATSORB
DOI: 10.18710/arlx23/adwp0r
title: 20240705_BJN_REDOBS_gps.txt
DOI: 10.18710/arlx23/bzzzky
title: 20240814_BJN_REDOBS_gps.txt
DOI: 10.18710/arlx23/svemhh
title: 20241228_BJN_REDOBS_gal.txt
DOI: 10.18710/arlx23/swy2mt
title: 20240916_BJN_REDOBS_glo.txt
DOI: 10.18710/arlx23/tpthaa
title: 20240926_BJN_REDOBS_gps.txt
DOI: 10.18710/arlx23/utz1wt
title: 20240707_BJN_REDOBS_glo.txt
DOI: 10.18710/arlx23/wcqbkh
title: 20240706_BJN_REDOBS_gal.txt
DOI: 10.18710/arlx23/wfdt5j
title: 20240715_BJN_REDOBS_glo.txt
DOI: 10.18710/arlx23/zulv9k
title: 20241105_BJN_REDOBS_gal.txt
DOI: 10.18710/bsxna1/azotdz
title: 0_ReadMe.txt

description: plain text file
DOI: 10.18710/bzog3s/oebuvi
title: scHSC_4_T3_2.fq.gz
DOI: 10.18710/dja6up/msfw30
title: 20240606_KHO_REDTEC_gal.txt
DOI: 10.18710/dqzkmx/endawp
title: 00_README.txt

description: Dataset description
DOI: 10.18710/dqzkmx/ghcq19
title: 8-zoo.csv

description: Accuracy tables for the dataset: Zoo.

Forsyth, R. (1990). Zoo. UCI Machine Learning Repository. https://doi.org/10.24432/C5R59V. Licensed under CC BY 4.0.
DOI: 10.18710/ivua0a/r8edkp
title: 07_coll-profile_mittelalterlich_POS.png
DOI: 10.18710/l0vpw7/flor6z
title: SBL221_Subt2__10__18-29-32-020.txt
DOI: 10.18710/l0vpw7/ib5vtj
title: SBL167_C_Subt4__11__14-23-06-044.txt
DOI: 10.18710/l0vpw7/ja8gfk
title: SBL092_Subt2__15__10-16-40-890.txt
DOI: 10.18710/l0vpw7/y4x377
title: SBL063_Subt2__27__11-54-35-684.txt
DOI: 10.18710/mhgxdh/wslxo1
title: regretGBUSSG.txt

description: Tab-delimited data table containing the data
DOI: 10.18710/ugnife/uwnjys
title: PSGO_17.csv
DOI: 10.18710/vm0wkq/1wtwgb
title: Chromosome 12.csv

description: Contents: Gene (name of gene), 
 Gene ID (Ensemble ID of gene)
 Causal Estimate Least Squares (estimate of the causal effect of the gene on CAD using the least squares estimator), 
 Causal Estimate GMM (estimate of the causal effect of the gene on CAD using the Generalized method of moments estimator),
 se Least Squares/GMM (standard error of the least squares estimator and the GMM estimator, because the functional form is same, the standard error is same for both estimators),
 p-value GMM (p-value of the GMM estimator), 
 p-value Least Squares (p-value of the least squares estimator),
 Causal Estimate MVIVW (estimate of the causal effect of the gene on CAD using multivariable Mendelian randomization via the inverse-variance method using the Mendelian Randomization package), 
 se MVIVW (standard error of the estimate for multivariable Mendelian randomization via the inverse-variance method using the Mendelian Randomization package),
 p-value MVIVW (p-value of the estimate for multivariable Mendelian randomization via the inverse-variance method using the Mendelian Randomization package), 
 Causal effect MR (causal effect using univariate Mendelian Randomization), 
 F_stat (conditional F-statistic calculated using the Mendelian Randomization package), 
 Q_stat (cochran's Q-statistic calculated using the Mendelian Randomization package), 
 Q_pval (p-value of the cochran's Q-statistic calculated using the Mendelian Randomization package), 
 lead SNP (the SNP with the lowest p-value in the GWAS summary data for the given locus, hence the most significant SNP), 
 position (position in base pairs of the lead SNP), 
 chromosome (chromosome of the lead SNP), 
 tissue (name of the tissue from where the expression levels of genes are considered in the MVMR causal analysis), 
 No of SNPs (number of SNPs in the MVMR causal analysis), 
 study (GWAS study ebi-a-GCST003116), 
 determinant of LD matrix (the determinant of the Linkage disequilibrium matrix of the SNPs considered in the MVMR causal analysis), 
 determinant of instruments strength matrix (the determinant of the covariance matrix of the instruments and the genes for the SNPs considered in the MVMR causal analysis), 
 LD threshold (maximum allowed LD between SNPs considered as instruments for the causal MVMR analysis).
 
 Purpose: Collection of all results in the MVMR analysis
DOI: 10.18710/vzbzeo/9o5dhm
title: Consent_letter_University_A.pdf
DOI: 10.18710/vzbzeo/zj2mpn
title: Data_Protection_Impact_Assessment_Hermann_et_al_2023_VZBZEO.pdf
DOI: 10.18710/w5b9qd
title: Zooplankton behavioral data polar night 2023

description: The dataset is data of behavioral experiments conducted on diverse zooplankton collected in Svalbard in January 2023. It includes video files of the experiments, stimulus light information and experimental protocol. The dataset is collected as a part of the RCN project 315728 "Light as a Cue for Life in the Arctic and Northern Seas (LightLife)".
DOI: 10.18710/w5b9qd/7651wn
title: General_info.csv

description: Table containing general information about the experiments including possible deviations from the experimental protocol
DOI: 10.18710/w5b9qd/jav15f
title: Aglatha.mp4
DOI: 10.18710/wrgqam/aaqnua
title: 00_README_file_DEPjoint_v_1_0.txt

description: README File
DOI: 10.18710/dqzkmx/7jq0gq
title: 5-heart-c.csv

description: Accuracy tables for the dataset: Heart Disease (Cleveland).

Janosi, A.; Steinbrunn, W.; Pfisterer, M. and Detrano, R. (1988). Heart Disease. UCI Machine Learning Repository. https://doi.org/10.24432/C52P4X. Licensed under CC BY 4.0.
DOI: 10.18710/gziuzl/u7gqot
title: ECOSENS_HF22_B1_ocean_radiance.txt
DOI: 10.18710/ivua0a/1smenr
title: 03_coll_PB5xPB_POS.txt
DOI: 10.18710/ivua0a/ewmfac
title: 07_coll-profile_hochADJA_Lemma.txt
DOI: 10.18710/ivua0a/hrrjxb
title: 07_coll-profile_historisch_Lemma.png
DOI: 10.18710/ivua0a/jdi9rb
title: 04_coll_PB2xNouns_Lemma.txt
DOI: 10.18710/ivua0a/oy0ac3
title: 07_coll-profile_riesig_POS.png
DOI: 10.18710/ivua0a/oyakdu
title: 06_coll-profile_nutzen_Lemma.png
DOI: 10.18710/ivua0a/qbya9x
title: 06_coll-profile_erbauenVVPP_POS.png
DOI: 10.18710/ivua0a/vkmhrr
title: 07_coll-profile_ehemalig_POS.png
DOI: 10.18710/l0vpw7/9mn3ki
title: SBL082_Subt4__22__18-01-16-684.txt
DOI: 10.18710/dja6up/3bf6me
title: 20240802_KHO_REDTEC_gal.txt
DOI: 10.18710/dja6up/5e6gyc
title: 20240907_KHO_REDTEC_gps.txt
DOI: 10.18710/dja6up/bfk5t7
title: 20240812_KHO_REDTEC_glo.txt
DOI: 10.18710/dja6up/dep6re
title: 20240711_KHO_REDTEC_gps.txt
DOI: 10.18710/dja6up/sfxfnr
title: 20240621_KHO_REDTEC_gal.txt
DOI: 10.18710/h8ektm/2eufdz
title: FN36.2023-02-16.edi
DOI: 10.18710/h8ektm/rhfpkv
title: F095.2023-02-16.edi
DOI: 10.18710/hfif8k/odwgnw
title: GreekProduction.csv
DOI: 10.18710/hfif8k/qftsmr
title: TurkishProduction.csv
DOI: 10.18710/hmf7ee/5xlvry
title: 1B_selected-plan.csv
DOI: 10.18710/hmf7ee/olupat
title: 2SN-A_scenarios-found.csv
DOI: 10.18710/hmf7ee/pc4sye
title: 1A_scenarios-found.csv
DOI: 10.18710/hmf7ee/q2bndf
title: 1B-C_ASV-data.csv
DOI: 10.18710/hmf7ee/zuy5ac
title: 2SN_ASV-data.csv
DOI: 10.18710/ilryhb/pwqmui
title: 00_README_file.txt
DOI: 10.18710/ilryhb/qrn7zp
title: Cut_Comp_Adj_behavioral.csv

description: behavioral data
DOI: 10.18710/ivua0a/2rxhfi
title: 06_coll-profile_erbauen_Lemma.png
DOI: 10.18710/ivua0a/7kuxok
title: 07_coll-profile_weiter_Lemma.png
DOI: 10.18710/ivua0a/7u2r4g
title: 07_coll-profile_wichtig_Lemma.txt
DOI: 10.18710/ivua0a/9yg5mr
title: 07_coll-profile_ganz_POS.txt
DOI: 10.18710/ivua0a/asv7hg
title: 07_coll-profile_imposant_Lemma.txt
DOI: 10.18710/ivua0a/bquhzu
title: 07_coll-profile_bayerisch_Lemma.png
DOI: 10.18710/ivua0a/btaspp
title: 07_coll-profile_ursprünglich_Lemma.png
DOI: 10.18710/ivua0a/fzz3va
title: 06_coll-profile_lohnen_Lemma.txt
DOI: 10.18710/ivua0a/lsh95w
title: 07_coll-profile_einstig_POS.png
DOI: 10.18710/ivua0a/m59k2d
title: 06_coll-profile_verbinden_POS.png
DOI: 10.18710/ivua0a/pkcmed
title: 06_coll-profile_stehen_Lemma.txt
DOI: 10.18710/ivua0a/td6v7d
title: 07_coll-profile_sehenswert_POS.txt
DOI: 10.18710/ivua0a/vwnsk2
title: 07_coll-profile_prächtig_POS.png
DOI: 10.18710/ivua0a/xakta4
title: 07_coll-profile_hochADJA_POS.txt
DOI: 10.18710/ivua0a/xrkzhl
title: 06_coll-profile_heißen_Lemma.png
DOI: 10.18710/ivua0a/z3cgkq
title: 06_coll-profile_bauen_POS.txt
DOI: 10.18710/kwp9wa/lbr8pl
title: 00_README.txt
DOI: 10.18710/l0vpw7/0kxake
title: SBL056_Subt2__11__11-33-07-675.txt
DOI: 10.18710/l0vpw7/48vd3l
title: SBL113_Subt2__4__18-23-53-789.txt
DOI: 10.18710/l0vpw7/6phqt5
title: SBL083_Subt4__12__18-02-46-685.txt
DOI: 10.18710/l0vpw7/7b6voa
title: SBL196_Subt2__24__16-24-00-002.txt
DOI: 10.18710/l0vpw7/c3fcdx
title: SBL148_A_Subt8__30__17-41-40-493.txt
DOI: 10.18710/l0vpw7/dvvxcj
title: SBL218_Subt2__16__18-17-57-019.txt
DOI: 10.18710/l0vpw7/dytaxd
title: SBL090_Subt2__1__10-04-48-401.txt
DOI: 10.18710/l0vpw7/j182gb
title: SBL200_Subt2__16__16-40-21-004.txt
DOI: 10.18710/l0vpw7/kts1nq
title: SBL208_B_Subt2__42__17-33-18-012.txt
DOI: 10.18710/l0vpw7/mfmjog
title: SBL239_A_Subt2__8__15-29-44-373.txt
DOI: 10.18710/l0vpw7/ph7rca
title: SBL197_Subt2__20__16-27-51-003.txt
DOI: 10.18710/l0vpw7/rlkctg
title: SBL192_Subt2__54__14-40-30-476.txt
DOI: 10.18710/l0vpw7/tltab8
title: SBL069B_Subt4__7__14-35-21-889.txt
DOI: 10.18710/l0vpw7/uphxor
title: QEPro_NoCC_Calibration_OOIIrrad.cal

description: Calibration file needed for converting the raw digital counts of spectral measurements to energy units. The file is plain text and can be opened with a text editor, but the original file format is retained here to ensure the functionality of the file.
DOI: 10.18710/lmnlau/1uassa
title: AnalyseKvitvikaIIC55865.txt
DOI: 10.18710/lmnlau/lipoqj
title: AnalyseReglokAursjøenKHM.xlsx
DOI: 10.18710/m82d10/cord1v
title: 9_common_genes_hamster_ptarmigan.txt
DOI: 10.18710/mgmedp/jirty9
title: 4_Materialsamling_til_kapittel_6_Rauset-2022.xlsx
DOI: 10.18710/n4n1p4/2iacho
title: 07_upw_H.txt
DOI: 10.18710/uypcl0
title: Trace element GWAS summary statistics

description: Trace elements are important for human health but may exert toxic or adverse effects. Mechanisms of uptake, distribution, metabolism, and excretion are partly under genetic control but have not yet been extensively mapped. Here we report a comprehensive multi-element genome-wide association study (GWAS) of 57 essential and non-essential trace elements. This dataset contains GWAS meta-analysis summary statistics for 14 trace elements (aluminium, arsenic, cadmium, chromium, cobalt, copper, lead, manganese, mercury, molybdenum, nickel, selenium, thallium, zinc) measured in up to 6564 whole-blood samples from the Trøndelag Health Study (HUNT), the Norwegian Mother, Father and Child Cohort Study (MoBa) and the Prospective Investigateion of the Vasculature in Uppsala Seniors (PIVUS) study. Further, the dataset contains GWAS summary statistics of 41 additional trace elements (antimony, barium, beryllium, boron, bromine, calcium, cerium, cesium, chlorine, gallium, germanium, gold, holmium, indium, iridium, iron, lanthanum, lithium, magnesium, neodymium, niobium, palladium, phosphorus, platinum, praseodymium, rhenium, rhodium, rubidium, samarium, silicon, silver, strontium, sulfur, tantalum, terbium, tin, tungsten, uranium, vanadium, yttrium, zirconium) measured in up to 2819 whole-blood samples from HUNT.
DOI: 10.18710/yovaim/dssjik
title: Stranded_KW_data.txt
DOI: 10.18710/yovaim/fysttq
title: 00_ReadMe.txt
DOI: 10.18710/yunhfp/q4l983
title: Brathen_et_al_Biotic_Homogenization_Dataverse_cover_data_raw.csv
DOI: 10.18710/hmf7ee/qpkmhz
title: 2SN-B-C_ASV-data.csv
DOI: 10.18710/kbeqt9/utjqg7
title: Nanonlive_Data_SKC.zip
DOI: 10.18710/lx51r2
title: Replication Data for: "Likelihood of Early Contractor Involvement (ECI) benefits in infrastructure versus building projects: the client’s perception"

description: The use of collaborative project delivery models has been around for the last couple of decades in Norwegian infrastructure projects. Early Contractor Involvement (ECI) is a feature used in many collaborative projects as a means to onboard contractor competence early on in the project lifecycle. Recently there has been an increasing interest among practitioners in testing whether ECI can also be useful for building projects. Following a systematic literature review approach, a comprehensive list of potential benefits of ECI was identified. Using empirical data collected from 91 respondents from three client organizations through workshops and surveys, this study explores whether the use of ECI may have different effects in these two groups. Overall, results show that improved innovation, enhanced constructability, and greater collaboration are perceived to be the most likely benefits of ECI. The likelihood of benefits is also moderated by the type of project, with building projects more likely to benefit from ECI. Regarding job roles, project management professionals are the most optimistic about the likelihood of these benefits. The results also indicate that respondents without having experience with collaborative projects or ECI have a more positive outlook than those with experience. These findings contribute to creating a more holistic understanding of the effects of ECI.
description: Description of the dataset:
This dataset contains a compilation of survey responses used in the paper. This includes 91 respondents from 3 different client organisations.
description: SPSS, 29
DOI: 10.18710/m82d10/0z0gvj
title: 7_GO_analysis_heatmap_clusters.txt
DOI: 10.18710/arlx23/1fp7sd
title: 20240920_BJN_REDOBS_glo.txt
DOI: 10.18710/arlx23/akdtb2
title: 20241210_BJN_REDOBS_gps.txt
DOI: 10.18710/arlx23/b0tdtj
title: 20240902_BJN_REDOBS_gal.txt
DOI: 10.18710/arlx23/d7bxrh
title: 20241222_BJN_REDOBS_glo.txt
DOI: 10.18710/bzog3s/vc5yhg
title: scHSC_4_T2_2.fq.gz
DOI: 10.18710/bzog3s/xgxieg
title: scHSC_1_C2_2.fq.gz
DOI: 10.18710/dja6up/80sn84
title: 20240721_KHO_REDTEC_glo.txt
DOI: 10.18710/dja6up/g1whvf
title: 20240726_KHO_REDTEC_glo.txt
DOI: 10.18710/dja6up/ryqg9d
title: 20240810_KHO_REDTEC_glo.txt
DOI: 10.18710/dja6up/tmfwes
title: 20240929_KHO_REDTEC_glo.txt
DOI: 10.18710/dja6up/u2jezx
title: 20240715_KHO_REDTEC_glo.txt
DOI: 10.18710/gziuzl/01bgw2
title: ECOSENS_HF23_C1_a.txt
DOI: 10.18710/gziuzl/6azofs
title: ECOSENS_HF22_D3_ap_bp.txt
DOI: 10.18710/gziuzl/f7rmez
title: ECOSENS_HF23_C2_ap_bp.txt
DOI: 10.18710/gziuzl/iuizpd
title: ECOSENS_LF22_2_ap_bp.txt
DOI: 10.18710/gziuzl/khybpi
title: ECOSENS_GF21_2_a.txt
DOI: 10.18710/gziuzl/m50tty
title: ECOSENS_HF23_D2_meta.txt
DOI: 10.18710/gziuzl/tdczvo
title: ECOSENS_GF21_R_ap_bp.txt
DOI: 10.18710/gziuzl/wl62d8
title: ECOSENS_HF22_D3_ocean_irradiance.txt
DOI: 10.18710/gziuzl/x437t5
title: ECOSENS_HF23_B3_a.txt
DOI: 10.18710/gziuzl/ybktoi
title: ECOSENS_HF23_VT74_ap_bp.txt
DOI: 10.18710/hmf7ee/3co7ty
title: 2NS-A-C_selected-plan.csv
DOI: 10.18710/hmf7ee/6rf6ih
title: 1B_TS-data.csv
DOI: 10.18710/hmf7ee/7wpiwg
title: 1B-C_TS-data.csv
DOI: 10.18710/hmf7ee/gyrj3q
title: 2NS-A_selected-plan.csv
DOI: 10.18710/hmf7ee/hfdwqd
title: 2NS-A-C_TS-data.csv
DOI: 10.18710/hmf7ee/ljif7w
title: 2NS-B_explored-states.csv
DOI: 10.18710/hmf7ee/q0rgq5
title: 1B_scenarios-found.csv
DOI: 10.18710/hmf7ee/tpagtt
title: 2SN-B_ASV-data.csv
DOI: 10.18710/rvjqi4/voowdy
title: maturity.txt

description: Age at first reproduction and physiological age at first reproduction.
DOI: 10.18710/arlx23/3zvdqf
title: 20240724_BJN_REDOBS_glo.txt
DOI: 10.18710/arlx23/ooyk4y
title: 20240919_BJN_REDOBS_glo.txt
DOI: 10.18710/bzog3s/irp5wv
title: scHSC_4_ST3_2.fq.gz
DOI: 10.18710/bzog3s/kc5b5b
title: scHSC_4_T1_1.fq.gz
DOI: 10.18710/bzog3s/pcgopr
title: scHSC_1_C3_2.fq.gz
DOI: 10.18710/bzog3s/zvp3jm
title: scHSC_4_S2_1.fq.gz
DOI: 10.18710/dja6up/bybu62
title: 20240824_KHO_REDTEC_gps.txt
DOI: 10.18710/dja6up/ugcvox
title: 20240818_KHO_REDTEC_gal.txt
DOI: 10.18710/gziuzl/zpfxq6
title: ECOSENS_HF22_A1_ocean_irradiance.txt
DOI: 10.18710/lmnlau/duaez8
title: AnalyseC55852Vassenden.xlsx
DOI: 10.18710/lmnlau/zu6swg
title: AnalyseÅlbusetra.txt
DOI: 10.18710/mgmedp/y1c1cw
title: 1_Frasesamling_til_kapittel_5_Rauset-2022.txt
DOI: 10.18710/bzog3s/1ofs6m
title: scHSC_3_C1_2.fq.gz
DOI: 10.18710/bzog3s/7bdkvo
title: scHSC_1_C3_1.fq.gz
DOI: 10.18710/bzog3s/a4tkdl
title: scHSC_4_C3_1.fq.gz
DOI: 10.18710/bzog3s/acvhrz
title: scHSC_3_S2_1.fq.gz