cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.q3dae8
title: Occurrence Download

description: A dataset containing 124 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Machine Observation, Human Observation, Living Specimen)",
 "TaxonKey is Podocnemis lewyana"
 ]
}

 The dataset includes 124 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005941-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4rg456
title: Occurrence Download

description: A dataset listing the 2 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-35.78663 -9.5523,-35.75443 -9.60162,-35.74091 -9.6187,-35.73767 -9.63695,-35.7352 -9.6492,-35.73483 -9.65425,-35.73237 -9.65461,-35.73295 -9.63331,-35.73463 -9.61249,-35.74466 -9.59971,-35.74989 -9.59352,-35.78308 -9.55038,-35.78663 -9.5523))",
 "HasGeospatialIssue is false",
 "TaxonKey is Squamata"
 ]
}

 The dataset's 2 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005925-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g6as86
title: Occurrence Download

description: A dataset containing 1431 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is GLP.2.14_1",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 1431 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005942-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xzruc7
title: Occurrence Download

description: A dataset listing the 1 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-35.78663 -9.5523,-35.75443 -9.60162,-35.74091 -9.6187,-35.73767 -9.63695,-35.7352 -9.6492,-35.73483 -9.65425,-35.73237 -9.65461,-35.73295 -9.63331,-35.73463 -9.61249,-35.74466 -9.59971,-35.74989 -9.59352,-35.78308 -9.55038,-35.78663 -9.5523))",
 "HasGeospatialIssue is false",
 "TaxonKey is Amphibia"
 ]
}

 The dataset's 1 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005934-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kpj376
title: Occurrence Download

description: A dataset containing 522 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen, Observation, Occurrence evidence, Material sample, Material citation)",
 "Country is Spain",
 "DatasetKey is one of (Herbario de Plantas Vasculares de la Universidad de Salamanca: SALA, Sistema de Información de la vegetación Ibérica y Macaronésica, Herbario de la Universidad de Sevilla, Colección de plantas vasculares del herbario de la Universitat de València (VAL))",
 "OccurrenceStatus is Present",
 "TaxonKey is Senecio lividus"
 ]
}

 The dataset includes 522 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005943-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6k87hv
title: Occurrence Download

description: A dataset containing 2587781 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Human Observation, Machine Observation)",
 "Continent is Europe",
 "CoordinateUncertaintyInMeters 0.0-649.0",
 "Country is one of (Spain, Norway)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Month is one of (May, June, July, August, September, October)",
 "OccurrenceStatus is Present",
 "TaxonKey is Insecta",
 "Year 1980-2025"
 ]
}

 The dataset includes 2587781 records from 47 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005923-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.b4dvbz
title: Occurrence Download

description: A dataset containing 51 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Fungi (Agaricomycetes, Basidiomycota) of the Yugyd va National Park (Subpolar and Northern Urals, Russia)",
 "TaxonKey is Entoloma"
 ]
}

 The dataset includes 51 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005944-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/icpsr39565
title: Technology-Assisted Qualitative Research: How Does Modality Affect Outcome? [Methods Study], North Carolina, 2014-2018
title: Archival Version

description: To learn about people's experiences, researchers often use one-on-one interviews and group interviews, called focus groups. Researchers can do interviews and focus groups in person or online.
In this study, the research team wanted to learn if people shared more or different information in person versus online. The team did interviews and focus groups with women about safety during pregnancy and compared the information collected in person or online. To collect information online, the team used either online video, chat, a message board, or email. The team then compared differences in the average number of words and what women discussed across the methods.
description: The purpose of this study was to compare data generated from in-depth interviews (IDIs) and focus groups (FGs) across
4 data collection modalities: (1) face-to-face; (2) online synchronous video-based; (3) online synchronous text-based; and (4) online asynchronous text-based.
description: In-depth interviews (IDIs) and focus groups (FGs) provide data on people's thoughts and experiences in their own words. Few studies have examined how data might differ between IDIs and FGs conducted in person versus online. Data may vary in volume, measured by word count, or content, measured by the frequency of thematic codes applied.
In this study, researchers compared the volume and content of data collected through IDIs or FGs conducted in person and through three online modalities. Researchers randomly assigned women to either IDIs or FGs. Next, researchers assigned women to one of four groups:

<strong>In person.</strong> Researchers conducted IDIs and FGs in an office conference room.
<strong>Online video.</strong> Women used their personal computers with webcams to sign in to a private online video chat room and used a telephone conference line for audio.
<strong>Online chat. </strong>Researchers typed questions, and women responded in a private online text chat room in real time.
 <strong> Online message board or email.</strong> For IDIs, the interviewer emailed women three to five questions at a time during a 10-day period. For FGs, the moderator posted three to five questions on an online discussion board each day for 7 to 10 days. Women responded at their convenience. Women in the IDIs and FGs discussed the Zika virus and medical risks during pregnancy.

The study included 171 women in North Carolina who had been pregnant in the previous three years and hoped to become pregnant in the next three.
description: Datasets: 
DS1: Technology-Assisted Qualitative Research: How Does Modality Affect Outcome? [Methods Study], North Carolina, 2014-2018
description: Women over age 18 who had been pregnant between 2013
and 2016 and who were hoping to become pregnant again in the next 3 years, based in North Carolina.
DOI: 10.3886/icpsr39565.v1
title: Technology-Assisted Qualitative Research: How Does Modality Affect Outcome? [Methods Study], North Carolina, 2014-2018
title: Version 1

description: To learn about people's experiences, researchers often use one-on-one interviews and group interviews, called focus groups. Researchers can do interviews and focus groups in person or online.
In this study, the research team wanted to learn if people shared more or different information in person versus online. The team did interviews and focus groups with women about safety during pregnancy and compared the information collected in person or online. To collect information online, the team used either online video, chat, a message board, or email. The team then compared differences in the average number of words and what women discussed across the methods.
description: The purpose of this study was to compare data generated from in-depth interviews (IDIs) and focus groups (FGs) across
4 data collection modalities: (1) face-to-face; (2) online synchronous video-based; (3) online synchronous text-based; and (4) online asynchronous text-based.
description: In-depth interviews (IDIs) and focus groups (FGs) provide data on people's thoughts and experiences in their own words. Few studies have examined how data might differ between IDIs and FGs conducted in person versus online. Data may vary in volume, measured by word count, or content, measured by the frequency of thematic codes applied.
In this study, researchers compared the volume and content of data collected through IDIs or FGs conducted in person and through three online modalities. Researchers randomly assigned women to either IDIs or FGs. Next, researchers assigned women to one of four groups:

<strong>In person.</strong> Researchers conducted IDIs and FGs in an office conference room.
<strong>Online video.</strong> Women used their personal computers with webcams to sign in to a private online video chat room and used a telephone conference line for audio.
<strong>Online chat. </strong>Researchers typed questions, and women responded in a private online text chat room in real time.
 <strong> Online message board or email.</strong> For IDIs, the interviewer emailed women three to five questions at a time during a 10-day period. For FGs, the moderator posted three to five questions on an online discussion board each day for 7 to 10 days. Women responded at their convenience. Women in the IDIs and FGs discussed the Zika virus and medical risks during pregnancy.

The study included 171 women in North Carolina who had been pregnant in the previous three years and hoped to become pregnant in the next three.
description: Datasets: 
DS1: Technology-Assisted Qualitative Research: How Does Modality Affect Outcome? [Methods Study], North Carolina, 2014-2018
description: Women over age 18 who had been pregnant between 2013
and 2016 and who were hoping to become pregnant again in the next 3 years, based in North Carolina.
DOI: 10.4121/6850d59a-275c-4230-8400-1257135a2cf4
title: NMR data underlying the publication: Crystallization of NaCl−NaNO3−H2O in Porous Media During Drying

description: This dataset including the matlab file will plot the figure 5 as given in the article: Crystallization of NaCl−NaNO3−H2O in Porous Media During Drying. The data, is the raw data as comes out of the NMR experiment and using the matlab program the average NaCl and NaNO3 concentrations are calculated during the experiment creating the figure (This program will also run under Octave)
DOI: 10.4121/6850d59a-275c-4230-8400-1257135a2cf4.v1
title: NMR data underlying the publication: Crystallization of NaCl−NaNO3−H2O in Porous Media During Drying

description: This dataset including the matlab file will plot the figure 5 as given in the article: Crystallization of NaCl−NaNO3−H2O in Porous Media During Drying. The data, is the raw data as comes out of the NMR experiment and using the matlab program the average NaCl and NaNO3 concentrations are calculated during the experiment creating the figure (This program will also run under Octave)
DOI: 10.5281/zenodo.17701234
title: Clinical-Grade AI with Minimal Data: Rethinking Model Complexity in Precision Medicine
DOI: 10.5281/zenodo.17701235
title: Clinical-Grade AI with Minimal Data: Rethinking Model Complexity in Precision Medicine
DOI: 10.15468/dl.3c4qxh
title: Occurrence Download

description: A dataset containing 92362 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "PublishingOrg is b4640710-8e03-11d8-b956-b8a03c50a862",
 "TaxonKey is Coleoptera"
 ]
}

 The dataset includes 92362 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005938-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jdkvyt
title: Occurrence Download

description: A dataset containing 40 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Machine Observation, Human Observation, Living Specimen)",
 "TaxonKey is Psammobates geometricus"
 ]
}

 The dataset includes 40 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005947-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.br2875
title: Occurrence Download

description: A dataset containing 75 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Animalia",
 "Geometry POLYGON((14.4274994312284 41.1203531054623, 14.7024261597113 41.1203531054623, 14.7024261597113 41.2537902724291, 14.4274994312284 41.2537902724291, 14.4274994312284 41.1203531054623))",
 "HasCoordinate is true",
 "CoordinateUncertaintyInMeters is less than 300",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2010"
 ]
}

 The dataset includes 75 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005948-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.aryesd
title: Occurrence Download

description: A dataset listing the 46 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-35.78736 -9.54791,-35.7748 -9.57187,-35.76779 -9.58109,-35.76089 -9.59015,-35.75263 -9.59529,-35.7478 -9.60321,-35.74227 -9.60543,-35.7411 -9.60866,-35.73962 -9.61926,-35.73838 -9.62871,-35.73569 -9.64003,-35.73483 -9.64493,-35.73375 -9.65002,-35.73403 -9.65142,-35.73279 -9.65142,-35.73369 -9.64695,-35.73763 -9.62748,-35.73912 -9.61713,-35.7399 -9.60889,-35.74097 -9.60601,-35.74234 -9.60465,-35.74371 -9.60401,-35.74747 -9.60218,-35.75052 -9.59671,-35.75189 -9.59465,-35.75314 -9.59389,-35.75804 -9.59141,-35.76096 -9.58871,-35.76717 -9.58041,-35.77496 -9.5702,-35.77633 -9.56741,-35.78014 -9.5601,-35.78497 -9.55093,-35.78682 -9.54763,-35.78736 -9.54791))",
 "HasGeospatialIssue is false",
 "TaxonKey is Aves"
 ]
}

 The dataset's 46 records were derived from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005939-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/spjfj5
title: Replication Data for: Integrating Machine Behavior into Human Subject Experiments: A User-friendly Toolkit and an Application to Framed Prisoner’s Dilemmas

description: &lt;p&gt;This dataset contains original replication data. See README.* for further details.&lt;/p&gt;

&lt;p&gt;Original abstract:&lt;/p&gt;

&lt;p&gt;&lt;i&gt;Large Language Models (LLMs) have the potential to profoundly transform and enrich experimental economic research. We propose a new software framework, “alter_ego”, which makes it easy to design experiments between LLMs and to integrate LLMs into oTree-based experiments with human subjects. Our toolkit is freely available at github.com/mrpg/ego. To illustrate, we run differently framed prisoner's dilemmas with interacting machines as well as with human-machine interaction. Framing effects in machine-only treatments are strong and similar to those expected from previous human-only experiments, yet less pronounced and qualitatively different if machines interact with human participants.&lt;/i&gt;&lt;/p&gt;
DOI: 10.6084/m9.figshare.30010798
title: Behavioural Response of <i>Sitophilus zeamais</i> to Essential Oil-Derived Compounds

description: This file corresponds to the data presented in the paper entitled "Behavioural Response of <i>Sitophilus zeamais </i>(Coleoptera: Curculionidae) to Essential Oil-Derived Compounds", which recorded the time each insect (<i>Sitophilus zeamais</i>) spent in each of the 4-arm olfactometer zones (A, B and C), for a total of 10 minutes of observation. A, B, and C correspond to the near, central, and far zones, according to their position in relation to the tested essential oil-derived compound.
DOI: 10.6084/m9.figshare.30010798.v1
title: Behavioural Response of <i>Sitophilus zeamais</i> (Coleoptera: Curculionidae) to Essential Oil-Derived Compounds

description: This file corresponds to the data presented in the paper entitled "Behavioural Response of <i>Sitophilus zeamais </i>(Coleoptera: Curculionidae) to Essential Oil-Derived Compounds", which recorded the time each insect (<i>Sitophilus zeamais</i>) spent in each of the 4-arm olfactometer zones (A, B and C), for a total of 10 minutes of observation. A, B, and C correspond to the near, central, and far zones, according to their position in relation to the tested essential oil-derived compound.
DOI: 10.6084/m9.figshare.30010798.v2
title: Behavioural Response of <i>Sitophilus zeamais</i> to Essential Oil-Derived Compounds

description: This file corresponds to the data presented in the paper entitled "Behavioural Response of <i>Sitophilus zeamais </i>(Coleoptera: Curculionidae) to Essential Oil-Derived Compounds", which recorded the time each insect (<i>Sitophilus zeamais</i>) spent in each of the 4-arm olfactometer zones (A, B and C), for a total of 10 minutes of observation. A, B, and C correspond to the near, central, and far zones, according to their position in relation to the tested essential oil-derived compound.
DOI: 10.17635/lancaster/researchdata/740
title: Testing and Combining Transient Spectral Classification Tools on 4MOST-like Blended Spectra Dataset

description: The full set of simulated, 4MOST-like spectra used in the paper. Spectra
 are named as: [Host Morphology][True SN Class]Smag[SN Fibre Mag.]Gmag[Host
 Fibre Mag.]z[Redshift]texp[Exposure Time in Mins].txt. Each spectrum
 contains five columns, wavelength, flux, flux error, flux with no sky
 subtraction, flux error with no sky subtraction. The sample has been split
 across multiple zip files to reduce file size and aid upload/download.
 Each file contains 1000 random spectra from the sample, with the 14th zip
 file containing 443 for a total of 13443 spectra in total. These 13443
 spectra comprise the full sample. Any issue please contact me at:
 a.milligan@lancaster.ac.uk.Description
DOI: 10.5281/zenodo.17701094
title: IIT-Flexterra OFET transistor characterisation sweeps

description: # Transistor Sweep Dataset – File Format Specification

This dataset (DOI: 10.5281/zenodo.17701094) contains raw transistor sweep data acquired in Roman Krahne’s optoelectronics lab at Italian Institute of Technology in 2021.Technician: Dorwal Marchelli.Other data collectors: Simeon Bamford, Simon Mueller-Cleve.PI: Chiara Bartolozzi.Dataset curation: Simeon Bamford.The transistors were OFETs from samples kindly supplied by Flexterra, with thanks to Antonio Facchetti and Xia Yu. Simon-Mueller-Cleve was funded by H2020 "NeuTouch: Neuromorphic Embedded Processing for Touch" grant agreement ID 813713, DOI 10.3030.813713.

# Contents

Several transistors of both P and N-type were swept. Lighting was varied both within and between sweeps. The file headers (as well as the file names themselves) document the transistors used, according to the file format described below. 

Key process parameters are documented in parameters.json file.

Example sweep visualisations for one transistors are also included, in both png and html format - the html can be viewed in any browser and gives interactive 3D visualisation of the IDS-VGS-VDS landscape.

An example script for importing some data is included; however for the latest import scripts please see:

https://github.com/event-driven-robotics/ofet_import

To generate visualsations, consider using: 

https://github.com/event-driven-robotics/ivplot

# File format

Each sweep is stored as a plain-text `.dat` file with this structure.

## 1. File Header

**Line 1:**  ```Scan <label>                 Date: <weekday>, <Mon> <D>, <YYYY> <H>:<M> <AM/PM>```Contains a free-form scan label and the acquisition timestamp.

## 3. Scan Table

Introduced by:```Scan Table----------```

Describes the programmed voltage sweep, e.g.:```<quantity> <start> <stop> <num_points> raster<aux parameters ...>```

## 4. SET Constants Table

Introduced by:```SET Constants Table-------------------```

Contains instrument constants or placeholders (may appear as `...`).

## 5. Channels

Introduced by:```Channels--------```

Typically lists:```Voltage_ChACurrent_ChA```(first column = swept voltage, second column = measured current)

## 6. Measurement Data

Introduced by:```Measurement Data----------------```

Followed by one row per acquired data point:```<voltage> <current>```

Values use scientific notation (`E` format). The number of rows equals the sweep length defined in the Scan Table.
DOI: 10.5281/zenodo.17701093
title: IIT-Flexterra OFET transistor characterisation sweeps

description: # Transistor Sweep Dataset – File Format Specification

This dataset (DOI: 10.5281/zenodo.17701094) contains raw transistor sweep data acquired in Roman Krahne’s optoelectronics lab at Italian Institute of Technology in 2021.Technician: Dorwal Marchelli.Other data collectors: Simeon Bamford, Simon Mueller-Cleve.PI: Chiara Bartolozzi.Dataset curation: Simeon Bamford.The transistors were OFETs from samples kindly supplied by Flexterra, with thanks to Antonio Facchetti and Xia Yu. Simon-Mueller-Cleve was funded by H2020 "NeuTouch: Neuromorphic Embedded Processing for Touch" grant agreement ID 813713, DOI 10.3030.813713.

# Contents

Several transistors of both P and N-type were swept. Lighting was varied both within and between sweeps. The file headers (as well as the file names themselves) document the transistors used, according to the file format described below. 

Key process parameters are documented in parameters.json file.

Example sweep visualisations for one transistors are also included, in both png and html format - the html can be viewed in any browser and gives interactive 3D visualisation of the IDS-VGS-VDS landscape.

An example script for importing some data is included; however for the latest import scripts please see:

https://github.com/event-driven-robotics/ofet_import

To generate visualsations, consider using: 

https://github.com/event-driven-robotics/ivplot

# File format

Each sweep is stored as a plain-text `.dat` file with this structure.

## 1. File Header

**Line 1:**  ```Scan <label>                 Date: <weekday>, <Mon> <D>, <YYYY> <H>:<M> <AM/PM>```Contains a free-form scan label and the acquisition timestamp.

## 3. Scan Table

Introduced by:```Scan Table----------```

Describes the programmed voltage sweep, e.g.:```<quantity> <start> <stop> <num_points> raster<aux parameters ...>```

## 4. SET Constants Table

Introduced by:```SET Constants Table-------------------```

Contains instrument constants or placeholders (may appear as `...`).

## 5. Channels

Introduced by:```Channels--------```

Typically lists:```Voltage_ChACurrent_ChA```(first column = swept voltage, second column = measured current)

## 6. Measurement Data

Introduced by:```Measurement Data----------------```

Followed by one row per acquired data point:```<voltage> <current>```

Values use scientific notation (`E` format). The number of rows equals the sweep length defined in the Scan Table.