cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25318/1610008601-eng
title: Ratios of finished goods and total inventory owned to shipments in non-durable and durable goods industries

description: This table contains 42 series, with data for years 1970 - 1984 (not all combinations necessarily have data for all years), and is no longer being released. This table contains data described by the following dimensions (Not all combinations are available): Geography (12 items: Canada; Newfoundland and Labrador; Prince Edward Island; Nova Scotia; ...); Principal statistics (3 items: Shipments; Ratio of finished goods to shipments; Ratio of total inventory owned to shipments); Type of industry (3 items: All manufacturing industries; Non-durable industries; Durable industries).
DOI: 10.6084/m9.figshare.28396166
title: Data and Code for "Pseudo-linear Summation explains Neural Geometry of Multi-finger Movements in Human Premotor Cortex", Nishal P. Shah, Donald Avansino, Foram Kamdar, Claire Nicolas, Anastasia Kapitonava, Carlos Vargas-Irwin, Leigh R. Hochberg, Chethan Pandarinath, Krishna V Shenoy, Francis R Willett, Jaimie M. Henderson

description: <b>Abstract</b>How does the motor cortex combine simple movements (such as single finger flexion/extension) into complex movements (such as hand gestures, or playing the piano)? To address this question, motor cortical activity was recorded using intracortical multi-electrode arrays in two male people with tetraplegia as they attempted single, pairwise and higher-order finger movements. Neural activity for simultaneous movements was largely aligned with linear summation of corresponding single finger movement activities, with two violations. First, the neural activity exhibited normalization, preventing a large magnitude with an increasing number of moving fingers. Second, the neural tuning direction of weakly represented fingers changed significantly as a result of the movement of more strongly represented fingers. These deviations from linearity resulted in non-linear methods outperforming linear methods for neural decoding. Simultaneous finger movements are thus represented by the combination of individual finger movements by pseudo-linear summation.<br>Please refer to README for details.
DOI: 10.25318/1610008601-fra
title: Rapports des produits finis et des stocks possédés aux livraisons en des groupes de biens non durables et de biens durables

description: Ce tableau contient 42 séries, avec des données pour les années 1970 - 1984 (il n'y a pas nécessairement de données pour toutes les années pour l'ensemble des combinaisons), et sa mise à jour n'a plus lieu. Ce tableau contient des données telles que décrites par les dimensions suivantes (Les combinaisons ne sont pas toutes disponibles) : Géographie (12 éléments : Canada;Terre-Neuve-et-Labrador;Île-du-Prince-Édouard;Nouvelle-Écosse; ...) ; Les statistiques principales (3 éléments : Livraisons; Rapports des produits finis aux livraisons; Rapports des stocks possédés aux livraisons) ; Type d'industrie (3 éléments : Toutes les industries manufacturières; Industries biens non durables; Industries biens durables).
DOI: 10.15468/dl.ahc96z
title: Occurrence Download

description: A dataset containing 32557058 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "PublishingCountry is Colombia",
 {
 "and" : [
 "Country is Colombia",
 {
 "not" : {
 "Issue" : [
 "is Country coordinate mismatch"
 ]
 }
 }
 ]
 }
 ]
 },
 "StateProvince is one of (antioquia, magdalena, valle del cauca, caldas, cundinamarca, meta, santander, risaralda, tolima, nariño, casanare, la guajira, bolívar, boyacá, chocó, quindío, cauca, huila, putumayo, distrito capital de bogotá, caquetá, amazonas, cesar, córdoba, vaupés, sucre, guainía, bogotá, d.c., guaviare, atlántico, vichada, norte de santander, arauca, archipiélago de san andrés, providencia y santa catalina, san andrés providencia y santa catalina, guainia/vichada, choco, bolivar, narino, boyaca, caqueta, valle, valle de cauca, cordoba, amazônas, guajira, cauca department, bogota d.c., san andrés y providencia, isla de providencia, vaupes, departamento archipiélago de san andrés, providencia y santa catalina, putumayo department, bogota, district capital, san andres y providencia, santander department, distrito capital, bogotá, choco department, quindio, choco dept., archipiélago de san andrés, providencia y santa ca, bogotá d.c., valle del cauca department, magdalena department, bolivar department, san andres and providencia, narino department)"
 ]
}

 The dataset includes 32557058 records from 3747 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000482-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q2r6qx
title: Occurrence Download

description: A dataset containing 387554 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Convolvulus arvensis L.",
 "HasCoordinate is true"
 ]
}

 The dataset includes 387554 records from 1771 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0099644-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g3z9b8
title: Occurrence Download

description: A dataset containing 2281975 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "GadmGid is JPN",
 "TaxonKey is Aves",
 "Year 2000-2024"
 ]
}

 The dataset includes 2281975 records from 38 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001948-241125135418005/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wzt33y
title: Occurrence Download

description: A dataset containing 2698 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Raphia P.Beauv.",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2698 records from 151 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001996-241125135418005/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.aynn7q
title: Occurrence Download

description: A dataset containing 135 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is one of (Hanceola sinensis (Hemsl.) Kudô)"
 ]
}

 The dataset includes 135 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001997-241125135418005/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2tdx7m
title: Occurrence Download

description: A dataset containing 3907 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is one of (Loropetalum chinense (R.Br.) Oliv.)"
 ]
}

 The dataset includes 3907 records from 74 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001999-241125135418005/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.b8qdxs
title: Occurrence Download

description: A dataset containing 907 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Attalea allenii H.E.Moore",
 "HasCoordinate is true"
 ]
}

 The dataset includes 907 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002000-241125135418005/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sk8b5f
title: Occurrence Download

description: A dataset containing 2698 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Raphia P.Beauv.",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2698 records from 151 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001998-241125135418005/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.detxf9
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is one of (Hanceola suffruticosa Y.P.Chen, A.J.Paton & C.L.Xiang)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002003-241125135418005/datasets/export for details.
DOI: 10.15468/dl.zjuvrb
title: Occurrence Download

description: A dataset containing 4000 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Anoura geoffroyi Gray, 1838"
 ]
}

 The dataset includes 4000 records from 145 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002001-241125135418005/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17617/4.eu
title: Amyloid beta and its naturally occurring N-terminal variants are potent activators of human and mouse formyl peptide receptor 1

description: This contains the data of Figures 2D, S1A and S1C
Busch, L.; Taleb, Z. a.; Tsai, Y.-L.; Nguyen, V. T. T.; Lu, Q.; Synatschke, C. V.; Endres, K.; Bufe, B.
Amyloid beta and its naturally occurring N-terminal variants are potent activators of human and mouse 
formyl peptide receptor 1. 
Journal of Biological Chemistry, 2022, 298 (12), 102642. doi.org/10.1016/j.jbc.2022.102642
No other data was generated at the MPIP.
DOI: 10.15468/dl.ugptx6
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is one of (Loropetalum flavum Aver., P.K.Endress & K.S.Nguyen)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002004-241125135418005/datasets/export for details.
DOI: 10.15468/dl.hccjap
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is one of (Hanceola tuberifera Y.Z.Sun ex G.Y.Wu)"
 ]
}

 The dataset includes 3 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002005-241125135418005/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d8f8yg
title: Occurrence Download

description: A dataset containing 7477 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Aedes aegypti (Linnaeus, 1762)",
 "Country is Brazil",
 "Year is greater than or equal to 1500"
 ]
}

 The dataset includes 7477 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002007-241125135418005/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sf6nth
title: Occurrence Download

description: A dataset containing 2698 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Raphia P.Beauv.",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2698 records from 151 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002006-241125135418005/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10141592
title: CIC-IDS-2017 V2
title: CIC-IDS-2017 Version 2

description: The CIC-IDS-V2 is an extended version of the original CIC-IDS 2017 dataset. The dataset is normalised and 1 new class called "Comb" is added which is a combination of synthesised data of multiple non-benign classes.

To cite the dataset, please reference the original paper with DOI: 10.1109/SmartNets61466.2024.10577645. The paper is published in IEEE SmartNets and can be accessed here.

Citation info:

Madhubalan, Akshayraj & Gautam, Amit & Tiwary, Priya. (2024). Blender-GAN: Multi-Target Conditional Generative Adversarial Network for Novel Class Synthetic Data Generation. 1-7. 10.1109/SmartNets61466.2024.10577645. 

This dataset was made by Abluva Inc, a Palo Alto based, research-driven Data Protection firm. Our data protection platform empowers customers to secure data through advanced security mechanisms such as Fine Grained Access control and sophisticated depersonalization algorithms (e.g. Pseudonymization, Anonymization and Randomization). Abluva's Data Protection solutions facilitate data democratization within and outside the organizations, mitigating the concerns related to theft and compliance. The innovative intrusion detection algorithm by Abluva employs patented technologies for an intricately balanced approach that excludes normal access deviations, ensuring intrusion detection without disrupting the business operations. Abluva’s Solution enables organizations to extract further value from their data by enabling secure Knowledge Graphs and deploying Secure Data as a Service among other novel uses of data. Committed to providing a safe and secure environment, Abluva empowers organizations to unlock the full potential of their data.
DOI: 10.5281/zenodo.10141593
title: CIC-IDS-2017 V2
title: CIC-IDS-2017 Version 2

description: The CIC-IDS-V2 is an extended version of the original CIC-IDS 2017 dataset. The dataset is normalised and 1 new class called "Comb" is added which is a combination of synthesised data of multiple non-benign classes.

To cite the dataset, please reference the original paper with DOI: 10.1109/SmartNets61466.2024.10577645. The paper is published in IEEE SmartNets and can be accessed here.

Citation info:

Madhubalan, Akshayraj & Gautam, Amit & Tiwary, Priya. (2024). Blender-GAN: Multi-Target Conditional Generative Adversarial Network for Novel Class Synthetic Data Generation. 1-7. 10.1109/SmartNets61466.2024.10577645. 

This dataset was made by Abluva Inc, a Palo Alto based, research-driven Data Protection firm. Our data protection platform empowers customers to secure data through advanced security mechanisms such as Fine Grained Access control and sophisticated depersonalization algorithms (e.g. Pseudonymization, Anonymization and Randomization). Abluva's Data Protection solutions facilitate data democratization within and outside the organizations, mitigating the concerns related to theft and compliance. The innovative intrusion detection algorithm by Abluva employs patented technologies for an intricately balanced approach that excludes normal access deviations, ensuring intrusion detection without disrupting the business operations. Abluva’s Solution enables organizations to extract further value from their data by enabling secure Knowledge Graphs and deploying Secure Data as a Service among other novel uses of data. Committed to providing a safe and secure environment, Abluva empowers organizations to unlock the full potential of their data.
DOI: 10.15468/dl.rg2rx9
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is one of (Hanceola yuanyangensis Y.S.Chen, C.L.Xiang & H.L.Zheng)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002009-241125135418005/datasets/export for details.
DOI: 10.15468/dl.3u9xf7
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is one of (Loropetalum lanceum Hand.-Mazz.)"
 ]
}

 The dataset includes 5 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002008-241125135418005/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10149294
title: CSE-CIC-IDS2018 V2
title: CSE-CIC-IDS2018 Version 2

description: This is the updated version CSE-CIC-IDS 2018 dataset. The data is normalised and 1 new class "Comb" which is a combination of existing attacks is added. 

To cite the dataset, please reference the original paper with DOI: 10.1109/SmartNets61466.2024.10577645. The paper is published in IEEE SmartNets and can be accessed here.

Citation info:

Madhubalan, Akshayraj & Gautam, Amit & Tiwary, Priya. (2024). Blender-GAN: Multi-Target Conditional Generative Adversarial Network for Novel Class Synthetic Data Generation. 1-7. 10.1109/SmartNets61466.2024.10577645. 

This dataset was made by Abluva Inc, a Palo Alto based, research-driven Data Protection firm. Our data protection platform empowers customers to secure data through advanced security mechanisms such as Fine Grained Access control and sophisticated depersonalization algorithms (e.g. Pseudonymization, Anonymization and Randomization). Abluva's Data Protection solutions facilitate data democratization within and outside the organizations, mitigating the concerns related to theft and compliance. The innovative intrusion detection algorithm by Abluva employs patented technologies for an intricately balanced approach that excludes normal access deviations, ensuring intrusion detection without disrupting the business operations. Abluva’s Solution enables organizations to extract further value from their data by enabling secure Knowledge Graphs and deploying Secure Data as a Service among other novel uses of data. Committed to providing a safe and secure environment, Abluva empowers organizations to unlock the full potential of their data.
DOI: 10.5281/zenodo.10149295
title: CSE-CIC-IDS2018 V2
title: CSE-CIC-IDS2018 Version 2

description: This is the updated version CSE-CIC-IDS 2018 dataset. The data is normalised and 1 new class "Comb" which is a combination of existing attacks is added. 

To cite the dataset, please reference the original paper with DOI: 10.1109/SmartNets61466.2024.10577645. The paper is published in IEEE SmartNets and can be accessed here.

Citation info:

Madhubalan, Akshayraj & Gautam, Amit & Tiwary, Priya. (2024). Blender-GAN: Multi-Target Conditional Generative Adversarial Network for Novel Class Synthetic Data Generation. 1-7. 10.1109/SmartNets61466.2024.10577645. 

This dataset was made by Abluva Inc, a Palo Alto based, research-driven Data Protection firm. Our data protection platform empowers customers to secure data through advanced security mechanisms such as Fine Grained Access control and sophisticated depersonalization algorithms (e.g. Pseudonymization, Anonymization and Randomization). Abluva's Data Protection solutions facilitate data democratization within and outside the organizations, mitigating the concerns related to theft and compliance. The innovative intrusion detection algorithm by Abluva employs patented technologies for an intricately balanced approach that excludes normal access deviations, ensuring intrusion detection without disrupting the business operations. Abluva’s Solution enables organizations to extract further value from their data by enabling secure Knowledge Graphs and deploying Secure Data as a Service among other novel uses of data. Committed to providing a safe and secure environment, Abluva empowers organizations to unlock the full potential of their data.
DOI: 10.5281/zenodo.10141422
title: UNSW-NB15 V3
title: UNSW-NB15 Version 3

description: The dataset is an extended version of UNSW-NB 15. It has 1 additional class synthesised  and the data is normalised for ease of use.

To cite the dataset, please reference the original paper with DOI: 10.1109/SmartNets61466.2024.10577645. The paper is published in IEEE SmartNets and can be accessed here.

Citation info:

Madhubalan, Akshayraj & Gautam, Amit & Tiwary, Priya. (2024). Blender-GAN: Multi-Target Conditional Generative Adversarial Network for Novel Class Synthetic Data Generation. 1-7. 10.1109/SmartNets61466.2024.10577645. 

This dataset was made by Abluva Inc, a Palo Alto based, research-driven Data Protection firm. Our data protection platform empowers customers to secure data through advanced security mechanisms such as Fine Grained Access control and sophisticated depersonalization algorithms (e.g. Pseudonymization, Anonymization and Randomization). Abluva's Data Protection solutions facilitate data democratization within and outside the organizations, mitigating the concerns related to theft and compliance. The innovative intrusion detection algorithm by Abluva employs patented technologies for an intricately balanced approach that excludes normal access deviations, ensuring intrusion detection without disrupting the business operations. Abluva’s Solution enables organizations to extract further value from their data by enabling secure Knowledge Graphs and deploying Secure Data as a Service among other novel uses of data. Committed to providing a safe and secure environment, Abluva empowers organizations to unlock the full potential of their data.
DOI: 10.5281/zenodo.10141617
title: UNSW-NB15 V3
title: UNSW-NB15 Version 3

description: The dataset is an extended version of UNSW-NB 15. It has 1 additional class synthesised  and the data is normalised for ease of use.

To cite the dataset, please reference the original paper with DOI: 10.1109/SmartNets61466.2024.10577645. The paper is published in IEEE SmartNets and can be accessed here.

Citation info:

Madhubalan, Akshayraj & Gautam, Amit & Tiwary, Priya. (2024). Blender-GAN: Multi-Target Conditional Generative Adversarial Network for Novel Class Synthetic Data Generation. 1-7. 10.1109/SmartNets61466.2024.10577645. 

This dataset was made by Abluva Inc, a Palo Alto based, research-driven Data Protection firm. Our data protection platform empowers customers to secure data through advanced security mechanisms such as Fine Grained Access control and sophisticated depersonalization algorithms (e.g. Pseudonymization, Anonymization and Randomization). Abluva's Data Protection solutions facilitate data democratization within and outside the organizations, mitigating the concerns related to theft and compliance. The innovative intrusion detection algorithm by Abluva employs patented technologies for an intricately balanced approach that excludes normal access deviations, ensuring intrusion detection without disrupting the business operations. Abluva’s Solution enables organizations to extract further value from their data by enabling secure Knowledge Graphs and deploying Secure Data as a Service among other novel uses of data. Committed to providing a safe and secure environment, Abluva empowers organizations to unlock the full potential of their data.