cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.18710/d4glzz/apiiwx
title: FOODS_TOXINS_PAH_C.FRONDOSA.txt

description: Raw data of the DDT content of gutted orange-footed sea cucumber (C. frondosa). Footnotes are explained as followed: &lt; : Lower than limit of detection/limit of quantification (avg of blanks + 3*SD) according to IUPAC (http://goldbook.iupac.org/L03540.html); (i): Possible interference. This may be due to instrumental noise or/and chemical interferenc Results are not accredited according to NS-EN ISO / IEC 17025; g: Recovery of added standard is not according to NILUs quality criteria Results are not accredited according to NS-EN ISO / IEC 17025; 1 : Member of "EPA 16" according to US EPA PAH priority list; 2 : Probably or possibly carcinogenic to humans among the EPA 16 according to IARC (IARC Monographs Vol. 32, Suppl. 7, 1987); 3 : Member of Borneff 6; 4 : Sum PAH4 according to COMMISSION REGULATION (EU) 835/2011; 5 : Based on internal standard D10 2-Metylanaphtalene; 6 : Based on internal standard D12 Benzo(e)pyrene. Samples are noted with a number (C. frondosa 1). Presented in TXT format to enable ease of access.
DOI: 10.18710/dwoupl/s350we
title: 01-044S-part1.segy
DOI: 10.18710/emjbeo/9d7nnt
title: 20220814_HOP_REDOBS_gps.txt
DOI: 10.18710/emjbeo/gttjbv
title: 20220829_HOP_REDOBS_gal.txt
DOI: 10.18710/emjbeo/r7exeu
title: 20220808_HOP_REDOBS_gal.txt
DOI: 10.18710/emjbeo/wp7d7b
title: 20220716_HOP_REDOBS_gal.txt
DOI: 10.18710/gzj75r
title: Supporting data for Symptoms and signs of urogenital cancer in primary care

description: The data were collected in the project "Early diagnosis of abdominal cancer in general practice - a cohort study" and used for the analysis presented in the article "Symptoms and signs of urogenital cancer in primary care" by Knut Holtedahl et al., BMI Primary Care 2022.
The dataset includes 511 cases of cancer recorded prospectively among 61,802 patients in primary care in six European countries.
Initial data were collected by completion of standardised forms containing closed questions about symptoms recorded during the consultation. 
Follow-up data were provided by the general practitioner (GP) after diagnosis, based on medical record data made after the consultation.
DOI: 10.18710/mwvqfd/gickyz
title: 20220518_BJN_REDOBS_gal.txt
DOI: 10.18710/mwvqfd/rdsk0b
title: 20220614_BJN_REDOBS_gps.txt
DOI: 10.18710/mwvqfd/toyjsy
title: 20220506_BJN_REDOBS_glo.txt
DOI: 10.18710/mwvqfd/wzd0nn
title: 20220524_BJN_REDOBS_gal.txt
DOI: 10.18710/ngisoa/5indkv
title: Interval_BC_individualCurves.pdf

description: Individual curves for intervals B and C
DOI: 10.18710/ngisoa/h8pglg
title: optDepth.m

description: Optical depth dep on solar zenith angle
DOI: 10.18710/ngisoa/rrb27u
title: Interval_all_Average_normalized.pdf

description: Normalized average of all intervals
DOI: 10.18710/ovwsam
title: Supporting code and data for: Seasonality, density dependence and spatial population synchrony

description: &lt;p&gt;This project corresponds to the scripts and data files necessary to replicate the analysis in the manuscript "Seasonality, density dependence and spatial population synchrony" by Pedro G. Nicolau, Rolf A. Ims, Sigrunn H. Sørbye & Nigel G. Yoccoz&lt;/p&gt;
&lt;p&gt;The folder structure is
&lt;ul&gt;
&lt;li&gt;Data: important files used to reproduce the code. Raw files are .csv and processed files are in .rds&lt;/li&gt;
&lt;li&gt;Scripts: R scripts necessary for analysis, numbered by order of sequence (some with subnumbering). 0 contains the important functions to compute Bayesian R^2 and correlograms; 01 contains processing for 1; 03 contains processing for 3.&lt;/li&gt;
&lt;li&gt;Plots: diverse plots used (or not) in the manuscript; not needed for analysis&lt;/li&gt;
&lt;/ul&gt;
&lt;/p&gt;
description: R, 4.0.3
DOI: 10.18710/q2zvbc
title: Raw multibeam echosounder data collected on-board R/V Helmer Hanssen during the CAGE 17-2 AMGG cruise to the Olga Basin, northern Barents Sea

description: &lt;p&gt;This dataset includes raw multibeam echosounder data collected on-board R/V Helmer Hanssen during the CAGE 17-2 AMGG cruise to the Olga Basin, northern Barents Sea between June 21st to July 3rd, 2017. Data were collected using a Kongsberg Simrad EM302 multibeam echosounder system. The nominal sonar frequency of the sound waves is 30 kHz with an angular coverage sector of up to 150° and 432 beams per ping. The system was typically used with a 60°/60° opening angle.&lt;/p&gt;

&lt;p&gt;The dataset comprises Kongsberg bathymetry files, as well as water column data files and sound velocity profiles gathered from 8 CTD casts. Water column data collection was not continuous during the cruise, for example during transits between study areas. &lt;/p&gt;
description: &lt;p&gt;Data coverage includes the transit from Longyearbyen, Outer Storfjordrenna, the Olga Basin (Storbanken), and transit to Tromsø over West Sentralbanken, with files split according to their day of collection. A rough itinerary is as follows:&lt;/p&gt;
&lt;p&gt;21: Isfjorden&lt;/p&gt;
&lt;p&gt;22: West Svalbard – Storfjordrenna&lt;/p&gt;
&lt;p&gt;23: Storfjordrenna&lt;/p&gt;
&lt;p&gt;24: West Svalbard&lt;/p&gt;
&lt;p&gt;25: Spitsbergenbanken – Hopendjupet&lt;/p&gt;
&lt;p&gt;26-29: Olga Basin (Storbanken)&lt;/p&gt;
&lt;p&gt;30: Storbankrenna&lt;/p&gt;
&lt;p&gt;01: Sentralbanken&lt;/p&gt;
description: CAGE 17-2 AMGG cruise
DOI: 10.18710/yutp35/k9hvsq
title: Analysis_Code_Klassenetal2022.R
DOI: 10.18710/emjbeo/aui71k
title: 20220707_HOP_REDOBS_gal.txt
DOI: 10.18710/emjbeo/ieehdq
title: 20220830_HOP_REDOBS_gps.txt
DOI: 10.18710/emjbeo/k6tn2z
title: 20220917_HOP_REDOBS_gal.txt
DOI: 10.18710/emjbeo/n5mzu8
title: 20220929_HOP_REDOBS_glo.txt
DOI: 10.18710/emjbeo/ngoomi
title: 20220730_HOP_REDOBS_gps.txt
DOI: 10.18710/emjbeo/p36n8j
title: 20220920_HOP_REDOBS_gps.txt
DOI: 10.18710/emjbeo/pj1sb7
title: 20220711_HOP_REDOBS_glo.txt
DOI: 10.18710/emjbeo/qzlbio
title: 20220924_HOP_REDOBS_gal.txt
DOI: 10.18710/i3l0bq/a5ylzz
title: CAGE_19-2_0240-0249_HH.zip
DOI: 10.18710/i3l0bq/fm8wqw
title: CAGE_19-2_0100-0109_HH.zip
DOI: 10.18710/mwvqfd/31ughf
title: 20220421_BJN_REDOBS_gal.txt
DOI: 10.18710/mwvqfd/h3vvxg
title: 20220430_BJN_REDOBS_gal.txt
DOI: 10.18710/mwvqfd/imbhpz
title: 20220531_BJN_REDOBS_gal.txt
DOI: 10.18710/mwvqfd/papylm
title: 20220526_BJN_REDOBS_glo.txt
DOI: 10.18710/qhuaz2/iepjap
title: dtm10_Tileinndeling.sos
DOI: 10.18710/qhuaz2/ngmjbo
title: 2021-02-16-00_00_2021-02-16-23_59_DEM_COPERNICUS_30_DEM_(Raw) (1).tiff
DOI: 10.18710/vw1m5l/yos7li
title: Figure8.txt

description: Trap depth vs. particle radii
DOI: 10.18710/3uf8mq/2pz4fd
title: 03_Architecture_Statues.xlsx

description: Table 3 in the article
DOI: 10.18710/dwoupl/ogmjcl
title: 02JM821.segy
DOI: 10.18710/emjbeo/2vei69
title: 20220831_HOP_REDOBS_glo.txt
DOI: 10.18710/emjbeo/8scvav
title: 20220803_HOP_REDOBS_gal.txt
DOI: 10.18710/emjbeo/dnk0z7
title: 20220927_HOP_REDOBS_glo.txt
DOI: 10.18710/emjbeo/poc3uh
title: 20220805_HOP_REDOBS_glo.txt
DOI: 10.18710/hrbywg/9rlncc
title: RawDataAlkalineEtching_Dataverse.zip

description: Full data package; see file 00_readme.txt for details.
DOI: 10.18710/mwvqfd/cggzps
title: 20220416_BJN_REDOBS_gps.txt
DOI: 10.18710/mwvqfd/d4bswu
title: 20220518_BJN_REDOBS_gps.txt
DOI: 10.18710/mwvqfd/i38qrc
title: 20220511_BJN_REDOBS_glo.txt
DOI: 10.18710/mwvqfd/ofousw
title: 20220505_BJN_REDOBS_gal.txt
DOI: 10.18710/mwvqfd/p4o68z
title: 20220428_BJN_REDOBS_gps.txt
DOI: 10.18710/mwvqfd/s00np0
title: 20220520_BJN_REDOBS_glo.txt
DOI: 10.18710/ovwsam/5fpfnu
title: Simulations.pdf
DOI: 10.18710/ovwsam/cok60n
title: S14 temp.csv
DOI: 10.18710/ovwsam/dlphbv
title: S16 prec.csv
DOI: 10.18710/ovwsam/iulq6o
title: modIII_fall.pdf
DOI: 10.18710/ovwsam/ntzzyq
title: S14 prec.csv
DOI: 10.18710/ovwsam/sdzrkg
title: S7 prec.csv
DOI: 10.18710/ovwsam/tydiqr
title: S2 temp.csv
DOI: 10.18710/ovwsam/ycpc79
title: S20 prec.csv
DOI: 10.18710/qhuaz2/dnakef
title: air quality data Summer.csv
DOI: 10.18710/qhuaz2/s5zusi
title: eksport Radal winter.csv
DOI: 10.18710/qigsyu/vf97t3
title: 006_Annonymisering_Fjerne_Kommune_Number.txt

description: VISER HVORDAN DATAFILEN ER ANNONYMISERT
DOI: 10.18710/u4jmiv
title: Replication Data for: Characterizing porous disk wakes in different turbulent inflow conditions with higher-order statistics

description: This dataset contains all data necesary to produce the figures containing original data in the paper "Characterizing porous disk wakes in different turbulent inflow conditions by higher-order statistics" (DOI to be provided after publication). It contains single wire hot-wire anemometry (HWA) of the far wakes of two different porous disks under two different incoming turbulence intensities (TIs). The porous disks are one with non-uniform disk blockge, ND, and one with uniform blockage, UD.
DOI: 10.18710/u4jmiv/pntagf
title: Figure4.zip
DOI: 10.18710/uoc8cp/fcj3mx
title: DCS_2022_Q09_Domain_type_of_response_data.tsv
DOI: 10.18710/xoepui/6qubvg
title: 00_README.txt
DOI: 10.18710/ovwsam/fdkxd1
title: CR_CaptHist_KMdata_18_20.csv
DOI: 10.18710/ovwsam/tezlfs
title: S3 temp.csv
DOI: 10.18710/qhuaz2/ozxcur
title: crowd-db-description.pdf
DOI: 10.18710/uoc8cp/cs04eh
title: DCS_2022_Q34_Alignment_and_Compliance_Important_data.xlsx
DOI: 10.18710/xoepui
title: Supplementary materials for "Sexually dimorphic regulation of gonadotrope cell hyperplasia in medaka pituitary via mitosis and transdifferentiation"

description: This file is a supplementary figures for the manuscript "Sexually dimorphic regulation of gonadotrope cell hyperplasia in medaka pituitary via mitosis and transdifferentiation"
description: The two pituitary gonadotropins, Fsh and Lh, regulate the reproductive function in vertebrates. While many studies have investigated the regulation of gonadotropin production and release by the sex steroid feedback, its role on the regulation of gonadotrope cell number remains unclear. Using medaka as a model and an optimized protocol to restore physiological sex steroids levels following gonadectomy, we show that gonadal sex steroids not only decrease fshb transcript levels, but also Fsh cell number in both sexes. We then investigated the origin of the Fsh cell hyperplasia induced by gonadectomy. In both sexes, BrdU incubation shows that this is achieved via Fsh cell mitosis. In situ hybridization reveals that new Fsh cells also originate from transdifferentiating Tsh cells in females, but not in males. Both phenomena are inhibited by sex steroid supplementation via feeding. In males (but not females), gonadectomy (without recovery with sex steroid supplementation) also reduces sox2 transcript levels and Sox2-immunopositive population volume, suggesting that sox2-progenitors may be recruited to produce new Fsh cells. Opposite to Fsh cells, gonadectomy decreases lhb levels in both sexes, and levels are not restored by sex steroid supplementation. In addition, the regulation of Lh cell number also seems to be sex dependent. Removal of gonadal sex steroids stimulates Lh cell mitosis in male (like Fsh cells), but not in females. To conclude, our study provides the first evidence on sexually dimorphic mechanisms used in the fish pituitary to remodel gonadotrope populations in response to sex steroids.
description: Jamovi, 2.3.18
description: FIJI, 1.53t
description: Inkscape, 1.2.2
DOI: 10.18710/2bqtjp/bp70oj
title: SOLDAT-HUS-B04-BL01.bam

description: Binary alignment/map file generated using Illumina DRAGEN for the male DNA sample B04
DOI: 10.18710/2bqtjp/qvhnqn
title: SOLDAT-HUS-A42-BL01.bam

description: Binary alignment/map file generated using Illumina DRAGEN for the male DNA sample A42
DOI: 10.18710/6cv6c1/yyujmy
title: S8 - M1-narrow-margin-conjugate.mp4

description: Animation showing the evolution of Model M1 of the conjugate narrow salt-bearing rifted margin (right margin) with reference salt viscosity and reference post-salt sediment flux.
DOI: 10.18710/6vwvmq/wfmexu
title: Supplementary_File_1c.txt
DOI: 10.18710/dwoupl/kbucxv
title: 01-040S-part2.segy
DOI: 10.18710/dwoupl/u3hqpv
title: 00-002-part3.segy
DOI: 10.18710/i3l0bq/sjyzhk
title: CAGE_19-2_0150-0159_HH.zip
DOI: 10.18710/ovwsam/jnvgoz
title: S7 temp.csv
DOI: 10.18710/qgk54k/g3ip3a
title: 07_Figure-6.png
DOI: 10.18710/qhuaz2/b5nkqs
title: IMG_1683.JPG
DOI: 10.18710/qhuaz2/y5fecj
title: IMG_1681.JPG
DOI: 10.18710/qigsyu/c46ikg
title: 008_Recode_Etter_Dato.txt

description: VISER ALL OMKODING TIL NYE VARIABLE
DOI: 10.18710/uoc8cp/dc0irs
title: DCS_2022_Q04_re3data_chart.png
DOI: 10.18710/uoc8cp/hp73o7
title: DCS_2022_Q35_Topic_09_Repository_Features_Importance_Preservation_chart.png
DOI: 10.18710/uoc8cp/pi7hac
title: DCS_2022_Q35_Topic_Summary_Repository_Features_Importance_data.tsv
DOI: 10.18710/vw1m5l/ctu03t
title: Figure4.txt

description: Sensitivity of height
DOI: 10.18710/2bqtjp/xbnwbl
title: SOLDAT-HUS-A32-BL01.bam

description: Binary alignment/map file generated using Illumina DRAGEN for the male DNA sample A32
DOI: 10.18710/3uf8mq/1dfyfc
title: 09_Roman_Roads_PPA.shp
DOI: 10.18710/3uf8mq/zvtaxo
title: 04_PPA.dbf
DOI: 10.18710/59xoi4/hwrcmn
title: AeN_FRAM_water_PAH.csv

description: This file contains water chemistry analyses for 44 PAHs conducted by SINTEF. This file includes what day the sample was taken and the level of various PAHs found in the water sample. Water samples were either taken from crude-oil-exposed tanks or control tanks (clean water).
DOI: 10.18710/6cv6c1/igxlff
title: S3 - M3-wide-margin.mp4

description: Animation showing the evolution of Model M3 of a wide salt-bearing rifted margin (left-margin) with reference salt viscosity and reference post-salt sediment flux.
DOI: 10.18710/bznypf/nqde6a
title: Triaxial_test_1.txt

description: Results from triaxial test 1
DOI: 10.18710/dwoupl/52i2tz
title: 01-043S-part2.segy
DOI: 10.18710/dwoupl/nxsbwd
title: 01-042S-part2.segy
DOI: 10.18710/dwoupl/qluwvr
title: -00ReadMe.txt
DOI: 10.18710/dwoupl/rhrsq7
title: 00-002-part4.segy
DOI: 10.18710/dwoupl/v7f5lo
title: 02JM817S_32N.segy
DOI: 10.18710/hnttsn
title: Background data for: Stable organization of the early lexical-semantic network in 18- and 24-month-old preterm and full-term infants: an eye-tracker study

description: &lt;p&gt;&lt;b&gt;Description of dataset&lt;/b&gt;&lt;/p&gt;
&lt;p&gt;The dataset presents the results of the investigation of the early lexical-semantic knowledge organization capabilities of 18- and 24-month-old toddlers. We were interested in the maturational differences in age and language proficiency. We included full-term (FT) and late preterm (PT) Hungarian-speaking infants. The PT and FT groups were matched according to their maturational ages.&lt;/p&gt;
&lt;p&gt;We conducted an infant-adapted target-absent Visual World Paradigm for eye-tracker presenting a Target Word verbally. It was followed by a visual panel with four pictures (aphonological distractor, a categorical distractor, and two unrelated images). We also tested children with the Hungarian version of the MacArthur-Bates Communicative Development Inventory (CDI).&lt;/p&gt;
&lt;p&gt;The dataset includes descriptive data of the participants, the CDI results (word count per category and the total sentence length), and fixation duration and count data registered by the eye-tracker for the presented stimuli. We provide the raw fixation data and the calculated variables per stimulus picture categories.&lt;/p&gt;
description: &lt;p&gt;&lt;b&gt;Article abstract&lt;/b&gt;&lt;/p&gt;
&lt;p&gt;An organized mental lexicon determines new information acquisition by orienting
attention during language processing. Adult-like lexical-semantic knowledge
organization has already been demonstrated in 24-month-olds. However,
the outcomes of earlier studies have been contradictory in terms of the
organizational capacities of 18-month-olds, thus our aim was to examine lexical-semantic organization in this younger age group. In prematurely born infants,
audiovisual integration deficits have been found alongside disruptions in language
perception. By including late preterm infants with corrected ages in our study,
we aimed to test whether maturational differences influence lexical-semantic
organization when vocabulary is growing rapidly. We tested 47 late preterm and
full-term 18- and 24-month-old infants by means of an infant-adapted target-absent
task using a slightly modified version of the original visual world paradigm
for eye tracker. We found a longer fixation duration for the lexical and semantic
distractors compared to the neutral pictures. Neither language proficiency nor
age affected the looking time results. We found a dissociation by age between
taxonomic and associative semantic relations. Maturational differences were
detectable in the initial processing of taxonomic relations, as processing in the
preterm group was slightly delayed and qualitatively different in the first half of the
looking time. The size and composition of the expressive vocabulary differed only
by age. In general, our study demonstrated a stable lexical-semantic organization
between 18 and 24 months of age, regardless of maturational differences.&lt;/p&gt;
description: Tobii Pro Studio, Tobii T60 XL
DOI: 10.18710/lemwj0/g45dst
title: AnalysisCode.Rmd

description: RStudio analysis file that is set up to allow those accessing this dataset to easily examine how analysis was done.
DOI: 10.18710/ovwsam/oiedz1
title: S8 temp.csv
DOI: 10.18710/qgk54k/koxzhx
title: 03_Figure-3.png
DOI: 10.18710/qhuaz2
title: TURBAN – Observational datasets for studies of urban air quality hazard scenarios in Bergen, Norway
title: Background data for the TURBAN project

description: The Turbulent-resolving urban modeling of air quality and thermal comfort (TURBAN) project aims to develop an integrated urban modeling system on basis of the large-eddy simulation code PALM. Urban simulations require a large number of datasets representing urban environment. This dataset is a collection of available observations for the model development and testing. 
The dataset has a value beyond the technical model development. It represent two observed periods of extreme deterioration of the urban air quality in Bergen, Norway. The observational dataset for studies of urban air quality hazard scenarios combines a selection of meteorological, air quality, and geospatial (urban features) data. The data are sampled for two distinct periods:
• Summer – covers 2019-07-20 to 2019-07-27 when one of the strongest historical heatwaves with maximum air temperatures exceeding +30C affected Bergen.
• Winter – covers 2021-02-04 to 2021-02-15 when one of the strongest historical coldwaves with temperatures below -10C and ice covering some the fjords (not observed since 1986) affected Bergen
The dataset combines the observations and surface features within the central urban area – the Bergen valley and Byfjorden where (1) air quality observations are available and (2) the most of available data records are found.
description: python, 3.10
description: matlab, v2017
description: ARCGIS
description: see the description file
Esau 2023 Observational datasets for studies of urban air quality hazard scenarios
DOI: 10.18710/qhuaz2/0bhod8
title: air quality data Summer.xlsx
DOI: 10.18710/qhuaz2/7s1vdc
title: Luftmålinger for februar 2021.pdf
DOI: 10.18710/qhuaz2/cbljfw
title: netatmo_bergen_data_feb_2021.csv
DOI: 10.18710/qhuaz2/gzldit
title: dtm50_Klippefil.zip
DOI: 10.18710/qhuaz2/j1hnkc
title: dtm10_67m1_2_10m_z33.tfw
DOI: 10.18710/qhuaz2/rqm1mf
title: dtm50_67M1_50m_33.tif.ovr
DOI: 10.18710/qigsyu/kd0zjr
title: 003_1_Tilrettelagte_Data_fil.dat

description: Den tilrettelagte data fil med .dat format
DOI: 10.18710/uoc8cp/7gu24u
title: DCS_2022_Q14_Software_Distribution_data.xlsx
DOI: 10.18710/uoc8cp/a3zpux
title: DCS_2022_Q37_Guides_data.xlsx
DOI: 10.18710/uoc8cp/awb0ww
title: DCS_2022_Q22_Configurable_Optional_Features_API_Client_Libraries_data.xlsx
DOI: 10.18710/uoc8cp/iwlkco
title: DCS_2022_Q15_Software_Version_data.tsv
DOI: 10.18710/uoc8cp/ldd9lq
title: DCS_2022_data.tsv
DOI: 10.18710/uoc8cp/newur6
title: DCS_2022_Q34_Alignment_and_Compliance_data.xlsx
DOI: 10.18710/uoc8cp/qsax2y
title: DCS_2022_Q06_Continent_data.xlsx
DOI: 10.18710/uoc8cp/tbfsyw
title: DCS_2022_Q18_Software_Deployment_Tools_data.xlsx
DOI: 10.18710/uoc8cp/tyyrxr
title: DCS_2022_Q09_Domain_chart.png
DOI: 10.18710/uoc8cp/xzeqqz
title: DCS_2022_Q14_Software_Distribution_chart.png
DOI: 10.18710/uoc8cp/zdv24j
title: DCS_2022_Q28_Configurable_Optional_Features_Metadata_Management_data.xlsx
DOI: 10.18710/vw1m5l/fja6aw
title: Figure2.txt

description: Raman enhancement factor
DOI: 10.18710/9x52wa/fni0dj
title: 20221006_HOP_REDTEC_glo.txt
DOI: 10.18710/9x52wa/wvnfdb
title: 20221208_HOP_REDTEC_glo.txt
DOI: 10.18710/cuvrzx/josyfs
title: 20220130_KHO_REDTEC_gal.txt
DOI: 10.18710/cuvrzx/ju01kd
title: 20220116_KHO_REDTEC_gal.txt
DOI: 10.18710/cuvrzx/vbbjlo
title: 20220103_KHO_REDTEC_gps.txt
DOI: 10.18710/cuvrzx/xz4wtn
title: 20220130_KHO_REDTEC_glo.txt
DOI: 10.18710/emjbeo/6kbpps
title: 20220801_HOP_REDOBS_gal.txt
DOI: 10.18710/emjbeo/7rywuo
title: 20220809_HOP_REDOBS_gps.txt
DOI: 10.18710/emjbeo/9zxbt8
title: 20220905_HOP_REDOBS_glo.txt
DOI: 10.18710/emjbeo/fhmmm8
title: 20220829_HOP_REDOBS_gps.txt
DOI: 10.18710/emjbeo/mjjagx
title: 20220726_HOP_REDOBS_glo.txt
DOI: 10.18710/mwvqfd/fzzxl9
title: 20220609_BJN_REDOBS_gal.txt
DOI: 10.18710/mwvqfd/g4ooci
title: 20220417_BJN_REDOBS_gal.txt
DOI: 10.18710/mwvqfd/o9nzeb
title: 20220424_BJN_REDOBS_glo.txt
DOI: 10.18710/ovwsam/6rzkrn
title: S11 prec.csv
DOI: 10.18710/ovwsam/de4n41
title: 1_populationmodels_and_residuals.R
DOI: 10.18710/ovwsam/lihpp2
title: S18 temp.csv
DOI: 10.18710/ovwsam/mnuxmg
title: modIII_spring.pdf
DOI: 10.18710/ovwsam/unenbd
title: T3 S1 prec.csv
DOI: 10.18710/q1avuu
title: Replication Data for: The acquisition of Differential Object Marking: a longitudinal study on L1 Dutch learners of Hindi as a foreign language

description: &lt;b&gt;Dataset abstract&lt;/b&gt;
&lt;p&gt;
The dataset includes annotated spoken corpus data of N = 3685 utterances, created with a picture description task that elicited semi-spontaneous oral production data from N = 5 learners of Hindi at a Belgian institute. Following a longitudinal design, we gathered data during four observations. These found place in the second (Time1), third (Time2; Time3) and fourth semester (time4) of their Hindi course trajectory. The corpus data is annotated for (i) Learner, (ii) Time of elicitation, (iii) the use of -ko as a Differential Object Marker and (iv) -ko as another marker, as well as multiple features associated with ko-marking, including: (v) Specificity of the Direct Object, (vi) Animacy of the Direct Object, (vii) the (lemmatized) sentence verb, (viii) the (lemmatized) head of the Direct Object Noun Phrase, (ix) the (lemmatized) head of the Noun Phrase associated with other uses of -ko, and (x) the semantic role of these other uses of the ko-marker. &lt;/p&gt;
description: &lt;b&gt;Article abstract&lt;/b&gt;
&lt;p&gt;
This article investigates the acquisition of Differential Object Marking (DOM) in Hindi as a foreign language based on a longitudinal study with five L1 Dutch speakers. A first aim of the study is to verify findings in previous cross-sectional studies. DOM in Hindi is governed by animacy and specificity and is particularly hard to acquire, with heritage speakers and advanced L2 learners omitting the direct object (DO) marker. A second aim is to investigate whether we can find evidence of either L1 influence, item-based learning or semantic mapping, testing explanations by Montrul et al. (2012, 2015, 2019), Narasimhan (2005, 2020) and Baten and Ponnet (2023). Data collected over four observation points confirmed high DOM omissions. Using a mixed effects logistic regression analysis, we found an increase in marking for human animate, specific DOs, and also for non-human animate and inanimate specific nouns. Our findings suggest that learners initially expand the optionality of -ko due to the complex syntactic-semantic constraints (possibly enhanced by L1 transfer) before gradually adapting to its constraints (possibly emerging through item-based learning).&lt;/p&gt;
description: MS Excel, 16.16.27
description: ELAN, 6.4
description: R, 4.2.2
description: RStudio, 2022.12.0
DOI: 10.18710/uoc8cp/1lmzi4
title: DCS_2022_Q31_Contribution_data.tsv