cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.20366/unimib/unidata/sn207-1.0
title: Digital Well-Being – Parental Phubbing (2018)
title: Benessere Digitale – Parental Phubbing (2018)

description: Digital Well-Being - Parental Phubbing is a cross-sectional database extracted from the second wave of data collection of the Digital Well-being - Schools project, funded by the University of Milano-Bicocca (Innovation Project Grant).<br> <br> The invitation to take part in this project was extended to all the high school in the territorial areas 23, 27 and 28 of the provinces of Milan and Monza-Brianza (Lombardy region, Northern Italy). At the end of the recruitment process, 18 out of 42 schools signed the training agreement, with a final enrollment rate of 43%. In May 2018, all the students at grade 10 (15-16 years old) of the 18 participating schools were surveyed through a CAWI methodology (Computer Assisted Web Interviewing) under the supervision of external observers. The questionnaire was finally administered to 3,289 participants located in 171 classes, achieving a total response rate of 90%.<br> <br> The dataset refers to an extract from the original questionnaire and provide detailed information on students perceived parental phubbing, social disconnection, and a set of socio-demographic and school related characteristics. Thanks to this dataset, the authors developed a brief and psychometrically valid scale to assess parental phubbing in adolescents, the Parental Phubbing Scale (PPS). Indeed, the PPS measures perceived phubbing distinctly and separately from each parent and, at the same time, these two dimensions jointly measure the overall dimension of parental phubbing.<br>
description: Analysis Unit: individual<br>Universe: Students enrolled in the academic year 2017-2018 at all high school in the territorial areas 23 (Province of Milan), 27 and 28 (Province of Monza-Brianza)<br>Sample Procedure: 3,289 individuals. Convenience sampling based on a voluntary acceptance. The sampling involved 3 stage enrollment procedure: 1) sending information material about the project to all the schools included in the three territorial areas and the subsequent acquisition of the expression of interest to participate in the study; 2) presentation of the project to the schools that showed an interest in participation; 3) formal acceptance to the project – and then the official involvement of the students – through the signing of the training agreement.<br>Weight: No weight used<br>Collection Mode: web-based self-administered questionnaire (CAWI)
DOI: 10.11587/f3drng/44lj5h
title: 10054_da_en_v2_1.tab

description: Core data file - STATA format - 1204 Variables, 3084 Observations (English)
DOI: 10.11587/f3drng/qq9iyd
title: 10054_da_en_v2_1.zsav

description: Core data file - compressed SPSS format - 1204 Variables, 3084 Observations (English)
DOI: 10.11587/f3drng/dtlrtc
title: 10054_da_de_v2_1.zsav

description: Core data file - compressed SPSS format - 1204 Variables, 3084 Observations (German)
DOI: 10.11587/f3drng/xnyfgu
title: 10054_qu_en_v1_0.pdf

description: Questionnaire - English
DOI: 10.11587/f3drng/vmbvow
title: 10054_vi_de_v2_1.tab

description: Variable identifiers and descriptions - machine-readable (German)
DOI: 10.11587/f3drng/v9bwnj
title: 10054_curation.pdf

description: Data curation protocol
DOI: 10.11587/f3drng/pigxgz
title: 10054_mr_en_v1_0.pdf

description: Method report
DOI: 10.11587/f3drng/evktql
title: 10054_vi_en_v2_1.tab

description: Variable identifiers and descriptions - machine-readable (English)
DOI: 10.11587/f3drng/uejqhi
title: 10054_errata_v2_1.pdf

description: Errata
DOI: 10.11587/f3drng/6ba0gy
title: 10054_qu_de_v1_0.pdf

description: Questionnaire - German
DOI: 10.11587/lbahiz/lrtfsa
title: :unav

description: :unav
DOI: 10.11587/lbahiz/1tjffm
title: :unav

description: :unav
DOI: 10.11587/lbahiz/iksbzd
title: :unav

description: :unav
DOI: 10.11587/lbahiz/if4x5u
title: :unav

description: :unav
DOI: 10.11587/lbahiz/emhu0d
title: :unav

description: :unav
DOI: 10.11587/lbahiz/fv0foz
title: :unav

description: :unav
DOI: 10.11587/lbahiz/t93zbq
title: :unav

description: :unav
DOI: 10.11587/lbahiz/ryu5xi
title: :unav

description: :unav
DOI: 10.11587/lbahiz/wexxfu
title: :unav

description: :unav
DOI: 10.11587/lbahiz/vx8kax
title: :unav

description: :unav
DOI: 10.11587/lbahiz/zztz2u
title: :unav

description: :unav
DOI: 10.11587/lbahiz/fxebde
title: :unav

description: :unav
DOI: 10.11587/lbahiz/mthris
title: 10056_da_de_v3_0.tab

description: Core data file – STATA format – 550 Variables, 3266 Observations – German
DOI: 10.11587/lbahiz/asrnbf
title: 10056_da_en_v3_0.tab

description: Core data file – STATA format – 550 Variables, 3266 Observations – English
DOI: 10.11587/lbahiz/s8tiix
title: 10056_da_de_v3_0.zsav

description: Core data file – compressed SPSS format – 550 Variables, 3266 Observations – German
DOI: 10.11587/lbahiz/p0od2y
title: 10056_da_en_v3_0.zsav

description: Core data file – compressed SPSS format – 550 Variables, 3266 Observations – English
DOI: 10.11587/lbahiz/9fln0k
title: 10056_readme.pdf

description: Data curation protocol
DOI: 10.11587/lbahiz/lfwb8j
title: 10056_mr_en_v2_2.pdf

description: Method report and codebook
DOI: 10.11587/lbahiz/nytxff
title: 10056_qu_de_v2_1.pdf

description: Questionnaire – German
DOI: 10.11587/lbahiz/c3kjqf
title: 10056_qu_en_v2_1.pdf

description: Questionnaire – English
DOI: 10.11587/lbahiz/0ht6vb
title: 10056_vi_de_v3_0.tab

description: Variable identifiers and descriptions – machine-readable – German
DOI: 10.11587/lbahiz/mw7xm2
title: 10056_vi_en_v3_0.tab

description: Variable identifiers and descriptions – machine-readable – English
DOI: 10.11587/lbahiz/a4lbd6
title: 10056_da_en_v3_0.zip

description: Core data file – compressed CSV format – 550 Variables, 3266 Observations – English
DOI: 10.11587/lbahiz/bv12b5
title: 10056_da_de_v3_0.zip

description: Core data file – compressed CSV format – 550 Variables, 3266 Observations – German
DOI: 10.15468/dl.edkzxp
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lathyrus odoratus",
 "Country is Croatia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032076-250827131500795/datasets/export for details.
DOI: 10.11587/ftw4sd/jziqoh
title: 10065_co_en_v1_0.pdf

description: Codebook
DOI: 10.11587/ftw4sd/ovonbp
title: 10065_da_en_v1_0.tab

description: Core data file - STATA format - 77 Variables, 1630 Observations
DOI: 10.11587/ftw4sd/1eqoc5
title: 10065_da_en_v1_0.zip

description: Core data file - compressed csv format - 77 Variables, 1630 Observations
DOI: 10.11587/ftw4sd/ugseq7
title: 10065_vi_en_v1_0.tab

description: Variable identifiers and descriptions - machine-readable
DOI: 10.11587/ftw4sd/rha5bp
title: 10065_da_en_v1_0.zsav

description: Core data file - compressed SPSS format - 77 Variables, 1630 Observations
DOI: 10.11587/ci2ww9/fcpme8
title: 10068_co_en_v1_0.pdf

description: Codebook
DOI: 10.11587/ci2ww9/2do5xy
title: 10068_da_en_v1_0.zip

description: Core data file - compressed csv format - 43 Variables, 1954 Observations
DOI: 10.11587/ci2ww9/y5grec
title: 10068_da_en_v1_0.tab

description: Core data file - STATA format - 43 Variables, 1954 Observations
DOI: 10.15468/dl.3n8dj3
title: Occurrence Download

description: A dataset listing the 130 species recorded in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "GadmGid is USA.18.34_1",
 "Month is December",
 "TaxonKey is Aves",
 "Year 2020-2024"
 ]
}

 The dataset's 130 records were derived from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032057-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.11587/ci2ww9/c9t6t6
title: 10068_da_en_v1_0.zsav

description: Core data file - compressed SPSS format - 43 Variables, 1954 Observations
DOI: 10.11587/ci2ww9/fq8r2w
title: 10068_vi_en_v1_0.tab

description: Variable identifiers and descriptions - machine-readable
DOI: 10.15468/dl.hu47zv
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lathyrus odoratus",
 "Country is Cyprus",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032077-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.16922968
title: TPCpp-10M: Simulated proton–proton collisions in Time Projection Chamber for AI Foundation Models

description: TPCpp-10M Dataset

A large-scale particle physics dataset designed for machine learning applications in high-energy physics research.

Dataset Overview

The TPCpp-10M dataset contains simulated particle collision events from a Time Projection Chamber (TPC) detector, commonly used in particle physics experiments. This dataset is specifically designed for:



Foundation model training for particle and nuclear physics applications

Particle track reconstruction

Particle identification

Signal vs. noise discrimination


Dataset Characteristics



Total Events: over 10 million simulated proton-proton collision events at 200GeV

Input Data Format: Structured spacepoint data with 4D coordinates (energy and x,y,z positions)

Labels: including track IDs, particle types, and noise classification

Splits:



unlabeled (for pretrain): 10M

labeled 



train: 70k

validation: 13k 

test: 7k





Data type: Numpy compressed data (.npz)


Data Components



Spacepoints: 4D spacepoints with energy and spatial coordinates

Track IDs (only for labeled data): Unique identifiers for particle trajectories

Particle ID Labels (only for labeled data): Classification labels for different particle types

Noise Tags (only for labeled data): Binary labels distinguishing signal from detector noise


Scripts



demo.ipynb: data loading, interactive plots, statistics of the dataset

plot.py: plot functions


Publication



FM4NPP: A Scaling Foundation Model for Nuclear and Particle Physics (https://arxiv.org/abs/2508.14087)


Files



TPCpp-10M.zip



unlabeled 



spacepoints_[000-099].npz



labeled:



train



spacepoints_[000-006].npz

track_ids_[000-006].npz

pid_labels_[000-006].npz

noise_tags_[000-006].npz



validation



spacepoints.npz

track_ids.npz

pid_labels.npz

noise_tags.npz



test



spacepoints.npz

track_ids.npz

pid_labels.npz

noise_tags.npz





scripts



demo.ipynb

plot.py





TPCpp-10M_labeled_test.zip: The same as labeled/test in TPCpp-10M.zip for a quick peek

TPCpp-10M_scripts.zip: The same as scripts in TPCpp-10M.zip for a quick peek
DOI: 10.5281/zenodo.16970029
title: TPCpp-10M: Simulated proton–proton collisions in Time Projection Chamber for AI Foundation Models

description: TPCpp-10M Dataset

A large-scale particle physics dataset designed for machine learning applications in high-energy physics research.

Dataset Overview

The TPCpp-10M dataset contains simulated particle collision events from a Time Projection Chamber (TPC) detector, commonly used in particle physics experiments. This dataset is specifically designed for:



Foundation model training for particle and nuclear physics applications

Particle track reconstruction

Particle identification

Signal vs. noise discrimination


Dataset Characteristics



Total Events: over 10 million simulated proton-proton collision events at 200GeV

Input Data Format: Structured spacepoint data with 4D coordinates (energy and x,y,z positions)

Labels: including track IDs, particle types, and noise classification

Splits:



unlabeled (for pretrain): 10M

labeled 



train: 70k

validation: 13k 

test: 7k





Data type: Numpy compressed data (.npz)


Data Components



Spacepoints: 4D spacepoints with energy and spatial coordinates

Track IDs (only for labeled data): Unique identifiers for particle trajectories

Particle ID Labels (only for labeled data): Classification labels for different particle types

Noise Tags (only for labeled data): Binary labels distinguishing signal from detector noise


Scripts



demo.ipynb: data loading, interactive plots, statistics of the dataset

plot.py: plot functions


Publication



FM4NPP: A Scaling Foundation Model for Nuclear and Particle Physics (https://arxiv.org/abs/2508.14087)


Files



TPCpp-10M.zip



unlabeled 



spacepoints_[000-099].npz



labeled:



train



spacepoints_[000-006].npz

track_ids_[000-006].npz

pid_labels_[000-006].npz

noise_tags_[000-006].npz



validation



spacepoints.npz

track_ids.npz

pid_labels.npz

noise_tags.npz



test



spacepoints.npz

track_ids.npz

pid_labels.npz

noise_tags.npz





scripts



demo.ipynb

plot.py





TPCpp-10M_labeled_test.zip: The same as labeled/test in TPCpp-10M.zip for a quick peek

TPCpp-10M_scripts.zip: The same as scripts in TPCpp-10M.zip for a quick peek
DOI: 10.11587/2kduor/okgnaz
title: 10067_co_en_v1_0.pdf

description: Codebook
DOI: 10.11587/2kduor/mwtlk5
title: 10067_vi_en_v1_0.tab

description: Variable identifiers and descriptions - machine-readable
DOI: 10.11587/2kduor/sev1rb
title: 10067_da_en_v1_0.zip

description: Core data file - compressed csv format- 57 Variables, 10943 Observations
DOI: 10.11587/2kduor/8mu7mg
title: 10067_da_en_v1_0.zsav

description: Core data file - compressed SPSS format - 57 Variables, 10943 Observations
DOI: 10.11587/2kduor/g7l2x3
title: 10067_da_en_v1_0.tab

description: Core data file - STATA format - 57 Variables, 10943 Observations
DOI: 10.14288/1.0450027
title: Structural variants underlie parallel adaptation following global invasion

description: &lt;b&gt;Abstract&lt;/b&gt;&lt;br/&gt;&lt;p&gt;Rapid adaptation during invasion has historically been considered limited and unpredictable. We leverage whole-genome sequencing of &gt;2600 plants across six continents to investigate the relative roles of colonization history and adaptation during the worldwide invasion of Trifolium repens. Introduced populations contain high levels of genetic variation with independent colonization histories evident on different continents. Five large structural variants on three chromosomes exist as standing genetic variation within the native range, and exhibit strong signatures of parallel climate-associated adaptation across continents. Common gardens in the native and introduced ranges demonstrate that three structural variants exhibit patterns of selection consistent with local adaptation across each range. Our results provide strong evidence that rapid and parallel adaptation during invasion is caused by large-effect structural variants introduced throughout the world.&lt;/p&gt;
DOI: 10.11587/dapg5q/cbcexg
title: 10058_vi_en_v1_0.tab

description: Variable identifiers and descriptions - machine-readable - English
DOI: 10.14288/1.0450026
title: Data from: A proof-of-concept experimental-theoretical model to predict pesticide resistance evolution

description: &lt;b&gt;Abstract&lt;/b&gt;&lt;br/&gt;&lt;p&gt;Insecticide resistance poses a major challenge to sustainable agriculture, yet studying its evolution in laboratory settings is notoriously difficult due to challenges related to maintaining large populations of pest species. While theoretical models offer valuable predictions, an experimental system for validating insecticide resistance management strategies remains lacking. Here, we explore &lt;em&gt;C. elegans&lt;/em&gt; as a model organism for studying insecticide resistance evolution. We developed an &lt;em&gt;in silico&lt;/em&gt; population genetics model and tested its predictive power in laboratory experiments, comparing the computational predictions to experimental resistance selection dynamics. Two compounds with distinct modes of action were tested to assess the generalizability of this system across different resistance mechanisms. Our results showed that &lt;em&gt;in silico&lt;/em&gt; predictions generally resembled multigenerational &lt;em&gt;in vivo&lt;/em&gt; resistance selection outcomes, demonstrating the feasibility of integrating &lt;em&gt;in vivo&lt;/em&gt; and &lt;em&gt;in silico&lt;/em&gt; modelling approaches in resistance research. By bridging the gap between theoretical and empirical research, this framework paves the way for addressing a wide range of open questions in resistance management, permitting the development of better-informed and more effective resistance management strategies for the agricultural industry.&lt;/p&gt; &lt;p&gt;The data archived here contains information relevant to the wild isolate chemical susceptibility screen, baseline dose-survival, and fitness data on PD4792, SR42, and JD608 strains, which were further characterised in this study, as well as the data on experimental microevolution of chemical resistance.&lt;/p&gt;
DOI: 10.15468/dl.eg5khv
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Brachypetersius gabonensis, Brachypetersius huloti, Brachypetersius pseudonummifer, Alestes bouboni, Brycinus nurse, Brycinus brevis, Brycinus carmesinus, Brycinus derhami, Bryconalestes derhami, Brycinus grandisquamis, Brachyalestes imberi, Brycinus imberi, Brycinus leuciscus, Brycinus longipinnis, Bryconalestes longipinnis, Brycinus luteus, Brycinus macrolepidotus, Brachyalestes nurse, Brycinus poptae, Brycinus rhodopleura, Bryconaethiops boulengeri, Bryconaethiops macrops, Bryconaethiops microstoma, Bryconaethiops quinquesquamae, Bryconalestes tholloni, Clupeocharax schoutedeni, Hemigrammopetersius barnardi, Hemigrammopetersius pulcher, Hydrocynus brevis, Hydrocynus forskahlii, Hydrocynus goliath, Hydrocynus tanzaniae, Hydrocynus vittatus, Ladigesia roloffi, Lepidarchus adonis, Micralestes acutidens, Micralestes ambiguus, Micralestes argyrotaenia, Micralestes comoensis, Micralestes congicus, Micralestes eburneensis, Micralestes elongatus, Micralestes fodori, Micralestes holargyreus, Micralestes humilis, Micralestes lualabae, Micralestes occidentalis, Micralestes pabrensis, Micralestes sardina, Micralestes schelly, Micralestes stormsi, Micralestes vittatus, Phenacogrammus ansorgei, Nannopetersius ansorgii, Nannopetersius lamberti, Petersius conserialis, Phenacogrammus aurantiacus, Phenacogrammus bleheri, Phenacogrammus deheyni, Phenacogrammus interruptus, Phenacogrammus major, Phenacogrammus polli, Phenacogrammus stigmatura, Phenacogrammus taeniatus, Phenacogrammus urotaenia, Rhabdalestes aeratis, Rhabdalestes brevidorsalis, Rhabdalestes leleupi, Rhabdalestes tangensis, Rhabdalestes maunensis, Rhabdalestes rhodesiensis, Rhabdalestes septentrionalis, Tricuspidalestes caeruleus, Citharidium ansorgii, Citharinops distichodoides, Citharinus citharus, Citharinus congicus, Citharinus eburneensis, Citharinus gibbosus, Citharinus latus, Citharinus macrolepis, Belonophago hutsebouti, Belonophago tinanti, Congocharax olbrechtsi, Distichodus affinis, Distichodus altus, Distichodus antonii, Distichodus atroventralis, Distichodus brevipinnis, Distichodus decemmaculatus, Distichodus engycephalus, Distichodus fasciolatus, Distichodus hypostomatus, Distichodus kolleri, Distichodus langi, Distichodus lusosso, Distichodus maculatus, Distichodus mbiniensis)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((1.1382 29.0599,-7.8618 29.0599,-7.8618 20.0599,1.1382 20.0599,1.1382 29.0599))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032078-250827131500795/datasets/export for details.
DOI: 10.11587/dapg5q/etsqmc
title: 10058_mr_de_v1_0.pdf

description: Method Report and Codebook - German
DOI: 10.11587/dapg5q/oxb9j3
title: 10058_mr_en_v1_0.pdf

description: Method Report and Codebook - English
DOI: 10.11587/dapg5q/i7ou5j
title: 10058_vi_de_v1_0.tab

description: Variable identifiers and descriptions - machine-readable - German
DOI: 10.11587/dapg5q/recrjq
title: 10058_da_en_v1_0.tab

description: Core data file - STATA format - 294 Variables, 1085 Observations - English
DOI: 10.11587/dapg5q/jc7rtp
title: 10058_da_en_v1_0.zsav

description: Core data file - compressed SPSS format - 294 Variables, 1085 Observations - English
DOI: 10.11587/dapg5q/jcdrtc
title: 10058_da_de_v1_0.tab

description: Core data file - STATA format - 294 Variables, 1085 Observations - German
DOI: 10.11587/dapg5q/y5enyd
title: 10058_da_de_v1_0.zip

description: Core data file - compressed CSV format - 294 Variables, 1085 Observations - German
DOI: 10.17026/dans-xjd-fta8
title: Tiel, Latensteinse rondweg Tiel, Laternsteinse rondweg. Aanvullend proefsleuvenonderzoek

description: &lt;p&gt;In opdracht van de gemeente Tiel heeft BAAC bv (onderzoeks- en adviesbureau voor Bouwhistorie, Archeologie, Architectuur- en Cultuurhistorie) een aanvullend proefsleuvenonderzoek uitgevoerd in plangebied Latensteinse rondweg te Tiel, gemeente Tiel. Het onderzoek vormt een aanvulling op het proefsleuvenonderzoek dat BAAC heeft uitgevoerd op 28 en 29 september 2015.&lt;/p&gt;&lt;p&gt;Ter aanvulling op het onderzoek uit 2015 dienden drie opgravingsputten te worden aangelegd: één werkput (werkput 7) van ca. 6 bij 50 meter haaks op de hoofdburcht en twee werkputten van 6 bij 50 meter haaks op de hoeken van de voorburcht (werkput 5 en 6 (afb.2.3).1 Indien mogelijk dienden de werkputten iets doorgetrokken te worden tot op het eigenlijke kasteelterrein om zo in beeld te krijgen waar hier de archeologisch relevante niveaus aanwezig zijn. De opgravingsputten worden tot in de natuurlijke ondergrond verdiept om zo de gehele opbouw van de gracht in beeld te krijgen.&lt;/p&gt;&lt;p&gt;Tijdens het onderzoek kon een groot deel van de omgrachting van de voorburcht van het huis Latenstein worden vastgesteld. Bij de hoofdburcht is dit door de terreinomstandigheden niet gelukt. Bebouwing op de voorburcht is niet vastgesteld, wel is een deel van de boerderij Latenstein aangesneden. Gezien de ligging nabij de gracht, die van oorsprong breder was, zal de bebouwing op de voorburcht meer westelijk hebben gelegen. Met behulp van de kadastrale minuut kan de contour van de voorburcht (zie afb.4.1) in grote lijnen worden gereconstrueerd.&lt;/p&gt;&lt;p&gt;Op basis van het onderzoek en de daaruit voortvloeiende waardering is de vindplaats behoudenswaardig. Gezien de plannen komt dat gedeeltelijk neer op behoud ex situ. Dat wil zeggen dat de resten voor een deel opgegraven en gedocumenteerd dienen te worden vóór er bodemverstorende ingrepen plaats gaan vinden. Gezien de geringe verstoringsdiepte wordt hier een archeologische begeleiding protocol opgraven geadviseerd. Bij deze begeleiding zou de nadruk moeten liggen op het documenteren van de grachtstructuur en omliggende infrastructuur. Het verdient hierbij aanbeveling dat de resten die hierbij niet verstoord worden, afgedekt worden en zo in situ behouden kunnen blijven, hetgeen neerkomt op een dubbelbestemming van het plangebied. Bij een eventuele bescherming van het plangebied zouden ook de resten van Latenstein die buiten het plangebied liggen betrokken moeten worden.&lt;/p&gt;
DOI: 10.11587/dapg5q/a4izmq
title: 10058_da_en_v1_0.zip

description: Core data file - compressed CSV format - 294 Variables, 1085 Observations - English
DOI: 10.11587/dapg5q/jwqn07
title: 10058_da_de_v1_0.zsav

description: Core data file - compressed SPSS format - 294 Variables, 1085 Observations - German
DOI: 10.11587/dapg5q/bncd7i
title: 10058_readme.pdf

description: Data curation protocol
DOI: 10.11587/jcozjb/d846ct
title: 10063_da_de_v1_0.zsav

description: Core data file - compressed SPSS format - 78 Variables, 85338 Observations
DOI: 10.11587/jcozjb/c7a481
title: 10063_mr_en_v1_0.pdf

description: Method report
DOI: 10.11587/jcozjb/ijkicq
title: 10063_co_de_v1_0.pdf

description: Codebook
DOI: 10.11587/jcozjb/wty9dg
title: 10063_vi_de_v1_0.tab

description: Variable identifiers and descriptions - machine-readable