cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.gu3na2
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dothidotthia quercicola (Ellis & Everh.) M.E.Barr",
 {
 "not" : {
 "DatasetKey" : [
 "is Global database of alien macrofungi"
 ]
 }
 },
 {
 "or" : [
 "Country is United States of America",
 "Country is United States",
 "Country is United States of America",
 "Country is Canada",
 "Continent is North America"
 ]
 }
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0137140-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.em7sn7
title: Occurrence Download

description: A dataset containing 9776 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Caragana arborescens Lam."
 ]
}

 The dataset includes 9776 records from 229 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0261691-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mhbcqn
title: Occurrence Download

description: A dataset containing 3719 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Adrastus rachifer (Geoffroy, 1785), Agonum viduum (Panzer, 1796))",
 "Geometry POLYGON((-9.36035 44.71551,-10.59082 42.81152,-11.82129 36.80928,-7.69043 36.17336,-3.38379 35.88905,3.12012 38.13456,9.18457 38.20366,11.7334 37.16032,12.78809 34.74161,17.09473 33.79741, 23.15918 34.23451,30.10254 32.62087,33.2666 32.99024,35.72754 35.03,33.00293 35.53223,28.69629 35.17381,28.34473 36.31513,25.7959 37.50973,24.91699 39.90974,28.78418 40.6473,30.71777 41.17865,36.87012 45.213,38.18848 46.98025,38.71582 47.7541,39.94629 47.93107,40.20996 49.61071,37.0459 50.34546,35.72754 50.40152,33.79395 52.26816,31.68457 51.94426,31.4209 53.27835,32.56348 53.43572,30.98145 54.77535,30.89355 55.52863,28.43262 56.02295,27.20215 57.65716,27.37793 58.30949,27.90527 59.17593,29.66309 59.88894,27.6416 60.58697,31.50879 62.75473,28.78418 69.83962,30.89355 70.28912,29.22363 71.55274,21.75293 71.30079,14.28223 70.14036,11.38184 67.47492,4.87793 63.66576,-5.53711 71.52491,-10.63477 71.69129,-21.5332 67.74276,-28.56445 65.36684,-24.3457 61.35461,-9.36035 44.71551))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2021"
 ]
}

 The dataset includes 3719 records from 148 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0156206-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mcdgub
title: Occurrence Download

description: A dataset containing 134880 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Alectura lathami J.E.Gray, 1831)",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Human Observation, Observation, Machine Observation)",
 "OccurrenceStatus is Present",
 "Country is Australia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 134880 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0265121-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3xxufe
title: Occurrence Download

description: A dataset containing 9901 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Year is greater than or equal to 1970",
 "TaxonKey is Bactrocera dorsalis (Hendel, 1912)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 9901 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0261763-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7855ty
title: Occurrence Download

description: A dataset containing 6084 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Huerteales"
 ]
}

 The dataset includes 6084 records from 204 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0192801-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5ng92h
title: Occurrence Download

description: A dataset containing 270 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Dipterocarpus hasseltii Blume"
 ]
}

 The dataset includes 270 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0426523-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hfsav3
title: Occurrence Download

description: A dataset containing 50878 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Ginkgoales"
 ]
}

 The dataset includes 50878 records from 71 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0104988-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2ar9k9
title: Occurrence Download

description: A dataset containing 133 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Year is greater than or equal to 1970",
 "TaxonKey is Bactrocera papayae Drew & Hancock, 1994",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 133 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0261769-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wm6hm5
title: Occurrence Download

description: A dataset containing 289 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Tachigali paraensis (Huber) Barneby"
 ]
}

 The dataset includes 289 records from 39 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021513-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mnyv73
title: Occurrence Download

description: A dataset listing the 60671 species recorded in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "HasCoordinate is true",
 "Year is greater than or equal to 1996",
 "Year is less than 2021",
 "HasGeospatialIssue is false"
 ]
}

 The dataset's 60671 records were derived from 770 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0140170-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2kk6kb
title: Occurrence Download

description: A dataset containing 232 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Zanthoxylum coco Gillies ex Hook. & Arn.",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 232 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027760-190918142434337/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6085/aa/knb-lter-sbc.11.4
title: SBCLTER: Ocean: Ocean Currents and Biogeochemistry: Moored CTD and ADCP Data
DOI: 10.6085/aa/knb-lter-sbc.11.3
title: SBCLTER: Ocean: Ocean Currents and Biogeochemistry: Moored CTD and ADCP Data
DOI: 10.6085/aa/knb-lter-sbc.11.2
title: SBCLTER: Ocean: Ocean Currents and Biogeochemistry: Moored CTD and ADCP Data
DOI: 10.6085/aa/knb-lter-sbc.11.1
title: SBCLTER: Ocean: Ocean Currents and Biogeochemistry: Moored CTD and ADCP Data
DOI: 10.6085/aa/knb-lter-sbc.1108.1
title: SBCLTER: UNOLS Cruises in the Santa Barbara Channel: LTER08, 2003-10-08 to 2003-10-17
DOI: 10.6085/aa/knb-lter-sbc.1107.1
title: SBCLTER: UNOLS Cruises in the Santa Barbara Channel: LTER07, 2003-05-14 to 2003-05-23
DOI: 10.6085/aa/knb-lter-sbc.1106.1
title: SBCLTER: UNOLS Cruises in the Santa Barbara Channel: LTER06, 2003-02-25 to 2003-03-06
DOI: 10.6085/aa/knb-lter-sbc.1105.1
title: SBCLTER: UNOLS Cruises in the Santa Barbara Channel: LTER05, 2002-09-03 to 2002-09-12
DOI: 10.6085/aa/knb-lter-sbc.1104.1
title: SBCLTER: UNOLS Cruises in the Santa Barbara Channel: LTER04, 2002-04-24 to 2002-05-03
DOI: 10.6085/aa/knb-lter-sbc.1103.1
title: SBCLTER: UNOLS Cruises in the Santa Barbara Channel: LTER03, 2002-02-18 to 2002-02-27
DOI: 10.6085/aa/knb-lter-sbc.1102.1
title: SBCLTER: UNOLS Cruises in the Santa Barbara Channel: LTER02, 2001-09-07 to 2001-09-15
DOI: 10.6085/aa/knb-lter-sbc.1101.1
title: SBCLTER: UNOLS Cruises in the Santa Barbara Channel: LTER01, 2001-03-20 to 2001-03-26
DOI: 10.6085/aa/knb-lter-sbc.1.1
title: SBCLTER: Land: Hydrology: NCDC Climate Data
DOI: 10.15468/dl.mv8jfr
title: Occurrence Download

description: A dataset containing 4265 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Mesosphaerum suaveolens (L.) Kuntze"
 ]
}

 The dataset includes 4265 records from 86 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029968-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2c3kp6
title: Occurrence Download

description: A dataset containing 14537 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Chromolaena odorata (L.) R.M.King & H.Rob."
 ]
}

 The dataset includes 14537 records from 121 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029965-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.26303548
title: Busan Inchon Survey, October 2019

description: Survey data of Busan and Inchon, conducted online in October, 2019.
DOI: 10.6084/m9.figshare.26303548.v1
title: Busan Inchon Survey, October 2019

description: Survey data of Busan and Inchon, conducted online in October, 2019.
DOI: 10.15468/dl.h4sw8j
title: Occurrence Download

description: A dataset containing 10471 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Eucalyptus amygdalina Labill."
 ]
}

 The dataset includes 10471 records from 48 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024512-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.26303329.v1
title: Anonymous data set for AN and BN patietns

description: Psychometric and genotypic data obtained for AN and BN patients
DOI: 10.5281/zenodo.12180450
title: RIFS - Spring 2019 PurpleAir-Grimm experiment at Berliner Str in Potsdam

description: This is the data that was used as the basis for the manuscript "Particle number size distribution evaluation of Plantower PMS5003 low-cost PM sensors – A field experiment".
DOI: 10.5281/zenodo.12180451
title: RIFS - Spring 2019 PurpleAir-Grimm experiment at Berliner Str in Potsdam

description: This is the data that was used as the basis for the manuscript "Particle number size distribution evaluation of Plantower PMS5003 low-cost PM sensors – A field experiment".
DOI: 10.6084/m9.figshare.26303329
title: Anonymous data set for AN and BN patients

description: Psychometric and genotypic data obtained for AN and BN patients
DOI: 10.6084/m9.figshare.26303329.v2
title: Anonymous data set for AN and BN patietns

description: Psychometric and genotypic data obtained for AN and BN patients
DOI: 10.6084/m9.figshare.26303329.v3
title: Anonymous data set for AN and BN patients

description: Psychometric and genotypic data obtained for AN and BN patients
DOI: 10.35003/eu0dz0/0w29po
title: d4ja00153b-f4.gif

description: :unav
DOI: 10.35003/eu0dz0/cywsqj
title: d4ja00153b-f5.gif

description: :unav
DOI: 10.35003/eu0dz0/eutrrn
title: tables_1_and_2.tab

description: :unav
DOI: 10.35003/eu0dz0/kq0btp
title: d4ja00153b-f7.gif

description: :unav
DOI: 10.35003/eu0dz0/oyxood
title: d4ja00153b-f1.gif

description: :unav
DOI: 10.35003/eu0dz0
title: Replication Data for: Effects of Faraday cup deterioration on Sr and Cr isotope analyses by thermal ionization mass spectrometry

description: Abstract By comparing data from an extensive set of Sr and Cr isotope measurements performed on two different thermal ionization mass spectrometers (TIMS), using three sets of Faraday cups with different usage histories, we assess the effects of Faraday cup deterioration on high-precision isotope measurements by TIMS. We find that dynamic 84Sr/ 86Sr and 87Sr/ 86Sr measurements provide stable and reproducible results over the entire 56 months of this study, regardless of which set of Faraday cups is used. By contrast, static 84Sr/ 86Sr and 87Sr/ 86Sr measurements lead to deviant results, drifts over time, and in general exhibit larger scatter. For the most part, these differences can be attributed to changing Faraday cup efficiencies. For the instruments of this study we find that the center cup is most affected, consistent with this cup often receiving the highest ion beam intensities during measurements conducted in our laboratory. For Cr isotopes, we find that the correlation between mass fractionation-corrected 53Cr/ 52Cr and 54Cr/ 52Cr ratios observed for static measurements in several prior studies also reflects different Faraday cup efficiencies. Again, the changing efficiency of predominantly the center cup can account for the observed drift and correlation in 53Cr/ 52Cr and 54Cr/ 52 Cr. Multi-static Cr isotope measurements reduce this drift, but still result in a residual correlation between the two ratios, suggesting this correlation in part also reflects unaccounted mass fractionation effects.
DOI: 10.35003/eu0dz0/h1jwus
title: figure_captions.docx

description: :unav
DOI: 10.35003/eu0dz0/jdxsdr
title: d4ja00153b-f3.gif

description: :unav
DOI: 10.35003/eu0dz0/ybbam1
title: d4ja00153b-f6.gif

description: :unav
DOI: 10.35003/eu0dz0/yvbkb2
title: d4ja00153b-f2.gif

description: :unav
DOI: 10.5281/zenodo.12565503
title: Modeling Languages for Digital Twins - A Survey Among the German Automotive Industry

description: This repository contains the replication package for the paper _Modeling Languages for Digital Twins: A Survey Among the German Automotive Industry_ by Jérôme Pfeiffer, Dominik Fuchß, Thomas Kühn, Robin Liebhart, Dirk Neumann, Christer Neimöck, Christian Seiler, Anne Koziolek, and Andreas Wortmann. The paper has been submitted to the practice track of  [MODELS 2024](https://conf.researchr.org/track/models-2024/models-2024-technical-track#Practice-Track).

Data

This replication package contains all information from the survey:- `results.csv`: A csv version of all data exported from LimeSurvey (German). Personal information from the participants has been removed. This file can be imported to reproduce the extraction results described in our paper.- `survey_german.pdf`: The pdf version of the original survey in German.  - `survey_german.md`: A markdown version of the original survey in German. - `survey_english.md`: A markdown version of the survey translated into English. 

Selection of participants and distribution

With both versions, the survey can be executed again with a different target audience in English or German. In our case we wanted to reach as much participants from diverse work areas as possible, where we invited the participants by email via an internal mailing list of 189 members of the SofDCar project.  To improve the response rate, we implemented two deadline extensions from the initial one-month-long time frame with 2 weeks of additional response time. Together with the deadline extension, we sent a mail to inform and remind the members of the consortium of the survey.

Data extraction

In total, we had 96 participants, of which 43 completed the questionnaire. For incomplete survey responses, we took only the available answers and did not include the missing answers in our data analysis. For data analysis we utilized the commercial Tool IBM SPSS and custom python scripts.

Research Questions 

- RQ1: How is the DT understood in the automotive industry?    - RQ1.1: For which phases of automotive development are DTsimportant?    - RQ1.2: What are desired properties of DTs?    - RQ1.3: What are desired purposes of using DTs?    - RQ1.4: How do these purposes change in relation to different phases of automotive development?- RQ2: Which modeling languages and modeling tools are currently employed in the automotive industry?    - RQ2.1: Which kinds of models are important during automotive development?    - RQ2.2: How important are which models in the phases of automotive development?    - RQ2.3: Which tools are used to create and maintain these models?
DOI: 10.5281/zenodo.12529996
title: Modeling Languages for Digital Twins - A Survey Among the German Automotive Industry

description: This repository contains the replication package for the paper _Modeling Languages for Digital Twins: A Survey Among the German Automotive Industry_ by Jérôme Pfeiffer, Dominik Fuchß, Thomas Kühn, Robin Liebhart, Dirk Neumann, Christer Neimöck, Christian Seiler, Anne Koziolek, and Andreas Wortmann. The paper has been submitted to the practice track of  [MODELS 2024](https://conf.researchr.org/track/models-2024/models-2024-technical-track#Practice-Track).

Data

This replication package contains all information from the survey:- `results.csv`: A csv version of all data exported from LimeSurvey (German). Personal information from the participants has been removed. This file can be imported to reproduce the extraction results described in our paper.- `survey_german.pdf`: The pdf version of the original survey in German.  - `survey_german.md`: A markdown version of the original survey in German. - `survey_english.md`: A markdown version of the survey translated into English. 

Selection of participants and distribution

With both versions, the survey can be executed again with a different target audience in English or German. In our case we wanted to reach as much participants from diverse work areas as possible, where we invited the participants by email via an internal mailing list of 189 members of the SofDCar project.  To improve the response rate, we implemented two deadline extensions from the initial one-month-long time frame with 2 weeks of additional response time. Together with the deadline extension, we sent a mail to inform and remind the members of the consortium of the survey.

Data extraction

In total, we had 96 participants, of which 43 completed the questionnaire. For incomplete survey responses, we took only the available answers and did not include the missing answers in our data analysis. For data analysis we utilized the commercial Tool IBM SPSS and custom python scripts.

Research Questions 

- RQ1: How is the DT understood in the automotive industry?    - RQ1.1: For which phases of automotive development are DTsimportant?    - RQ1.2: What are desired properties of DTs?    - RQ1.3: What are desired purposes of using DTs?    - RQ1.4: How do these purposes change in relation to different phases of automotive development?- RQ2: Which modeling languages and modeling tools are currently employed in the automotive industry?    - RQ2.1: Which kinds of models are important during automotive development?    - RQ2.2: How important are which models in the phases of automotive development?    - RQ2.3: Which tools are used to create and maintain these models?
DOI: 10.5281/zenodo.12530096
title: Modeling Languages for Digital Twins - A Survey Among the German Automotive Industry

description: This repository contains the replication package for the paper _Modeling Languages for Digital Twins: A Survey Among the German Automotive Industry_ by Jérôme Pfeiffer, Dominik Fuchß, Thomas Kühn, Robin Liebhart, Dirk Neumann, Christer Neimöck, Christian Seiler, Anne Koziolek, and Andreas Wortmann. The paper has been submitted to the practice track of  [MODELS 2024](https://conf.researchr.org/track/models-2024/models-2024-technical-track#Practice-Track).

Data

This replication package contains all information from the survey:- `results.csv`: A csv version of all data exported from LimeSurvey (German). Personal information from the participants has been removed. This file can be imported to reproduce the extraction results described in our paper.- `survey_german.pdf`: The pdf version of the original survey in German.  - `survey_german.md`: A markdown version of the original survey in German. - `survey_english.md`: A markdown version of the survey translated into English. 

Selection of participants and distribution

With both versions, the survey can be executed again with a different target audience in English or German. In our case we wanted to reach as much participants from diverse work areas as possible, where we invited the participants by email via an internal mailing list of 189 members of the SofDCar project.  To improve the response rate, we implemented two deadline extensions from the initial one-month-long time frame with 2 weeks of additional response time. Together with the deadline extension, we sent a mail to inform and remind the members of the consortium of the survey.

Data extraction

In total, we had 96 participants, of which 43 completed the questionnaire. For incomplete survey responses, we took only the available answers and did not include the missing answers in our data analysis. For data analysis we utilized the commercial Tool IBM SPSS and custom python scripts.

Research Questions 

- RQ1: How is the DT understood in the automotive industry?    - RQ1.1: For which phases of automotive development are DTsimportant?    - RQ1.2: What are desired properties of DTs?    - RQ1.3: What are desired purposes of using DTs?    - RQ1.4: How do these purposes change in relation to different phases of automotive development?- RQ2: Which modeling languages and modeling tools are currently employed in the automotive industry?    - RQ2.1: Which kinds of models are important during automotive development?    - RQ2.2: How important are which models in the phases of automotive development?    - RQ2.3: Which tools are used to create and maintain these models?