cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/2ayaav
title: Révision du genre Ivodea Capuron (Rutaceae), endémique de Madagascar et de l’archipel des Comores

description: This dataset contains the digitized treatments in Plazi based on the original journal article Rabarimanarivo, Marina N., Rakotonirina, Nivo H., Phillipson, Peter B., Lowry Ii, Porter P., Labat, Jean-Noël, Pignal, Marc (2015): Révision du genre Ivodea Capuron (Rutaceae), endémique de Madagascar et de l’archipel des Comores. Adansonia 37 (1): 63-102, DOI: 10.5252/a2015n1a6, URL: http://dx.doi.org/10.5252/a2015n1a6RÉSUMÉUne révision taxonomique du genre Ivodea Capuron est présentée. Trente espèces sont reconnues dont 27 endémiques de Madagascar, deux endémiques des Comores et une commune aux deux archipels. Dix-sept espèces sont nouvellement décrites (I. acuminata Rabarim., Rakoton., Phillipson & Lowry, sp. nov., I. analalavensis Rabarim., Rakoton., Phillipson & Lowry, sp. nov., I. ankeranensis Rabarim., Rakoton., Phillipson & Lowry, sp. nov., I. antilahimenae Rabarim., Rakoton., Phillipson & Lowry, sp. nov., I. aymoniniana Rabarim., Rakoton., Phillipson, Lowry & M.Pignal, sp. nov., I. capuronii Rabarim., Rakoton., Phillipson & Lowry, sp. nov., I. delphinensis Rabarim., Rakoton., Phillipson & Lowry, sp. nov., I. macrocarpa Rabarim., Rakoton., Phillipson & Lowry, sp. nov., I. mahaboensis Rabarim., Rakoton., Phillipson & Lowry, sp. nov., I. mananarensis Rabarim., Rakoton., Phillipson & Lowry, sp. nov., I. mayottensis Labat & M.Pignal, sp. nov., I. moheliensis M.Pignal & Labat, sp. nov., I. occidentalis Rabarim., Rakoton., Phillipson & Lowry, sp. nov., I. petrae Rabarim., Rakoton., Phillipson & Lowry, sp. nov., I. ravelonarivoi Rabarim., Rakoton., Phillipson & Lowry, sp. nov., I. razakamalalae Rabarim., Rakoton., Phillipson & Lowry, sp. nov. et I. toliarensis Rabarim., Rakoton., Phillipson & Lowry, sp. nov.), une nouvelle combinaison est créée (I. decaryana (H. Perrier) Rabarim., Rakoton., Phillipson & Lowry, comb. nov.), et une variété a été élevée au rang d’espèce (I. lanceolata (Capuron) Rabarim., Rakoton., Phillipson & Lowry, comb. et stat.nov.). Les membres du genre se distinguent les uns des autres par les caractères du limbe foliaire (notamment la taille, la forme, la texture et la nervation) et du pétiole (la présence/absence d’une articulation et d’ailes), le type d’indument sur des organes divers, la taille et la position de l’inflorescence et de l’infrutescence, et les caractéristiques de la surface de fruit. Une clé d’identification des espèces est présentée en français et en anglais, avec des cartes de distribution,une évaluation préliminaire du statut de conservation de chaque espèce et des illustrations des espèces nouvellement décrites.
DOI: 10.15468/dl.ptdw9d
title: Occurrence Download

description: A dataset containing 448766 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Abies"
 ]
}

 The dataset includes 448766 records from 1752 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017577-260108223611665/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.30081886
title: <b>Chemoautotrophic carbon fixation in thermokarst lakes on the Tibetan Plateau</b>

description: In this study, we identified chemoautotrophic carbon fixation in thermokarst lakes by collecting water samples along a ~1,100-km permafrost transect on the Tibetan Plateau. Based on biodegradable DOC incubation and <sup>14</sup>C-labeling bicarbonate (NaH<sup>14</sup>CO<sub>3</sub>) assimilation experiment, we examined the DOC dynamics in thermokarst lakes and explored the potential drivers using biogeochemical analysis.
DOI: 10.6084/m9.figshare.30081886.v2
title: <b>Chemoautotrophic carbon fixation in thermokarst lakes on the Tibetan Plateau</b>

description: In this study, we identified chemoautotrophic carbon fixation in thermokarst lakes by collecting water samples along a ~1,100-km permafrost transect on the Tibetan Plateau. Based on biodegradable DOC incubation and <sup>14</sup>C-labeling bicarbonate (NaH<sup>14</sup>CO<sub>3</sub>) assimilation experiment, we examined the DOC dynamics in thermokarst lakes and explored the potential drivers using biogeochemical analysis.
DOI: 10.6084/m9.figshare.30081886.v3
title: <b>Chemoautotrophic carbon fixation in thermokarst lakes on the Tibetan Plateau</b>

description: In this study, we identified chemoautotrophic carbon fixation in thermokarst lakes by collecting water samples along a ~1,100-km permafrost transect on the Tibetan Plateau. Based on biodegradable DOC incubation and <sup>14</sup>C-labeling bicarbonate (NaH<sup>14</sup>CO<sub>3</sub>) assimilation experiment, we examined the DOC dynamics in thermokarst lakes and explored the potential drivers using biogeochemical analysis.
DOI: 10.15468/dl.3d4nj2
title: Occurrence Download

description: A dataset containing 3401 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Hazara University Herbarium"
 ]
}

 The dataset includes 3401 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044759-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17648152
title: Surface colonization, relative abundance and morpho-taxonomical classification of early-stage biofouling communities in the tested prototypes
DOI: 10.5281/zenodo.17648153
title: Surface colonization, relative abundance and morpho-taxonomical classification of early-stage biofouling communities in the tested prototypes
DOI: 10.15468/dl.5db4t4
title: Occurrence Download

description: A dataset containing 231 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hipparchia semele",
 "HasCoordinate is true",
 "Geometry POLYGON ((6.224439 46.56151, 6.224439 48.43216, 8.984551 48.43216, 8.984551 46.56151, 6.224439 46.56151))",
 "Year is greater than or equal to 2020",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 231 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044760-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.46gyxp
title: Occurrence Download

description: A dataset containing 82701 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Themeda triandra",
 "HasCoordinate is true"
 ]
}

 The dataset includes 82701 records from 247 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044709-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ts6drc
title: Occurrence Download

description: A dataset containing 67 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-112.7688 27.59913, -112.6188 27.59913, -112.6188 27.74913, -112.7688 27.74913, -112.7688 27.59913))"
 ]
}

 The dataset includes 67 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044761-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/t953hnpgz7
title: Climate-dominated, LUCC-enhanced water–ecosystem responses in the humid temperate Tumen River Basin

description: The data used in the research included both the processed data and the intermediate data generated.
DOI: 10.17632/t953hnpgz7.1
title: Climate-dominated, LUCC-enhanced water–ecosystem responses in the humid temperate Tumen River Basin

description: The data used in the research included both the processed data and the intermediate data generated.
DOI: 10.5518/4
title: Nepal Energy Gardens Qualitative Dataset and Quantitative Survey Dataset

description: Biofuels and biomass are important sources of renewable energy, yet implementation of bioenergy programmes has attracted considerable controversy for displacing food production, land-grabbing, loss of biodiversity and greenhouse gas emissions. Creation of large industrial biomass and biofuel production has an important role to play in sustainable energy provision, but the real strengths of using plants for energy is that they can be grown in a wide variety of situations and thousands of different species can be used.  These datasets present household survey data and qualitative data- focus group discussions and key informant interviews carried out in three rural villages in mid-hills, Nepal to investigate the possible to establish community-based biofuel production, thereby overcoming environmental and social concerns about biofuels.  A stratified random sampling procedure was used to sample the households for quantitative data to ensure that its representative of the villages where research was conducted. The research participants were drawn from different landholding categories, castes, gender and local development experts to obtain views of different section of the community in three project villages viz. Hamsapur (Gorkha), Lakuri Danda (Dolakha) and Khudi (Lamjung) in the mid-hills region of Nepal. Data collected through qualitative research complements those quantitative data collected through household survey. The qualitative research covered aspects such as forest status, local institutions for forests and biomass uses, communal and social capital, and various issues pertinent to local development and how experience from those can be utilised for community-based biofuel projects such as energy gardens. Data generated through qualitative methods will help to explain the differences in the level of fuel consumption, determining local fuel demand and supply and other local level institutions necessary for creation of energy gardens project.
DOI: 10.17632/jx35gvtp3z
title: Raw Data

description: This dataset is from the article entitled "Wuwei Ganlu Medicales Bath Granules Attenuate Joint Inflammation in Collagen-Induced Arthritis Rats via Modulation of the Toll-Like Receptor 4/Nuclear Factor Kappa-B and NOD-Like Receptor Family Pyrin Domain Containing 3 Signaling Pathways".
DOI: 10.17632/jx35gvtp3z.1
title: Raw Data

description: This dataset is from the article entitled "Wuwei Ganlu Medicales Bath Granules Attenuate Joint Inflammation in Collagen-Induced Arthritis Rats via Modulation of the Toll-Like Receptor 4/Nuclear Factor Kappa-B and NOD-Like Receptor Family Pyrin Domain Containing 3 Signaling Pathways".
DOI: 10.15468/dl.x7bkw7
title: Occurrence Download

description: A dataset containing 46 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Opisthoteuthis mero"
 ]
}

 The dataset includes 46 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044762-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/khnmnp4t7v.3
title: A Comprehensive Multi-Source Dataset for Hybrid NER and Sentiment Analysis in the Uzbek Language

description: This dataset supports the research hypothesis that integrating named entity recognition (NER) and sentiment analysis with emoji-based emotional cues significantly improves the accuracy of Uzbek text interpretation, particularly in social media and informal communication contexts. The data demonstrate that combining linguistic, contextual, and emotional features allows hybrid models (SVM + LSTM + NER) to achieve up to 7–10% higher F1-scores compared to text-only baselines. This confirms that emojis and named entities serve as important auxiliary signals for understanding sentiment polarity and emotional direction in Uzbek language texts.

New in Version 2

Added 3,000 new annotated sentences with entity labels (PER, ORG, LOC).

Expanded emoji coverage from 20% to 30%.

Updated normalization pairs (1,292 → 1,450).

Fixed encoding inconsistencies and added missing metadata columns.

Improved inter-annotator agreement (Cohen’s Kappa = 0.89 → 0.91).

All tables reformatted to standard UTF-8 CSV/XLSX for compatibility.

Dataset Components

sentiment_social_uz_10000_features.xlsx — 10,000 manually annotated Uzbek sentences with polarity, entity, and emoji metadata.

emoji_lexicon_for_model_2000.xlsx — 2,000 individual emoji annotated with polarity and intensity values.

emoji_combo_dataset_for_model_16000.xlsx — 16,000 emoji combinations representing complex or mixed emotions.

emoji_ascii_variants_for_model_104.xlsx — 104 ASCII equivalents of emoji for normalization across platforms.

uz_informal_normalization_dataset_1292.xlsx — 1,292 pairs of informal → normalized Uzbek words for preprocessing.

uzbek_names_for_model_12000.xlsx — 12,000 personal names for Person-type NER training.

Uzb_location_lexicon_for_model_122.xlsx — 122 Uzbek geographic names with English equivalents for Location-type NER.

All data were collected from open sources (Telegram, Facebook, Instagram, blogs, and news portals) and manually cleaned of duplicates, links, and personal information. Annotation was performed by two linguistic experts following unified guidelines for sentiment polarity, emoji polarity, and entity type, with inter-annotator agreement ensuring reliability.

This dataset can be interpreted as a modular training and evaluation resource. Each subfile can be used independently or jointly to train hybrid systems that combine textual, visual (emoji), and named entity features.

Intended Use

Researchers can use this dataset to:

Train hybrid or multimodal sentiment analysis models for Uzbek or other Turkic languages.

Study emoji semantics, code-switching, and informal language normalization.

Explore cross-domain applications in NLP, social media analytics, and affective computing.

In summary, Version 2 represents an expanded and refined dataset demonstrating that integrating emotional and entity-level signals provides a more realistic and culturally sensitive understanding of Uzbek digital communication.
DOI: 10.34740/kaggle/dsv/13790131
title: Core Financial Time-Series Dataset
DOI: 10.15468/dl.8w6w9p
title: Occurrence Download

description: A dataset containing 121 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Thryptomene baeckeacea",
 "HasCoordinate is true"
 ]
}

 The dataset includes 121 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044763-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m2sa8k
title: Occurrence Download

description: A dataset containing 11435 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Genus Salix s.l. in M.G. Popov Herbarium (NSK)"
 ]
}

 The dataset includes 11435 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044764-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/7m6xzkznzc
title: Mendeley Data—Detailed Database (Appendices D1-D5)(NPSs)

description: Deciphering the ecological code of new psychoactive substances in megacity river ecosystems. while the comprehensive dataset of the large-scale Table D are available in the detailed database published at Mendeley
DOI: 10.17632/7m6xzkznzc.2
title: Mendeley Data—Detailed Database (Appendices D1-D5)(NPSs)

description: Deciphering the ecological code of new psychoactive substances in megacity river ecosystems. while the comprehensive dataset of the large-scale Table D are available in the detailed database published at Mendeley
DOI: 10.17632/pkskt3fv3v
title: IDS2025 (Balanced Intrusion Detection Evaluation Dataset)

description: This dataset, titled IDS2025: Balanced Intrusion Detection Evaluation Dataset, is an enhanced and refined version of the original CICIDS2017 dataset, designed specifically for research and development in Intrusion Detection Systems (IDS). It addresses key limitations identified in a detailed analysis of the CICIDS2017 dataset, including severe class imbalance (e.g., Benign traffic dominating at 83.34%), high data volume leading to processing challenges, scattered attack instances across files, and inconsistencies in labeling.

Key Improvements and Features: 

Class Balancing: Minority classes have been relabeled and merged where appropriate (e.g., combining similar attack variants like DoS subtypes) to reduce imbalance, improving model training efficacy and reducing bias toward dominant classes like Benign. The resulting distribution aims for a more equitable representation, with prevalence ratios adjusted from extremes like 0.0009% for rare attacks to more balanced levels.

Data Volume Optimization: Redundant or low-value instances were resampled or removed, resulting in a more manageable size while preserving essential network traffic patterns. The dataset retains approximately [insert approximate total instances, e.g., 2,830,540 based on original, adjusted post-processing] records across merged classes.

Attack Coverage: Includes a comprehensive set of real-world attack scenarios captured from simulated network environments, such as DoS/DDoS (e.g., Hulk, GoldenEye, Slowloris), Brute Force (FTP/SSH), Web Attacks (XSS, SQL Injection), Infiltration, Botnet, PortScan, and Heartbleed. Attacks are now more uniformly distributed across files for easier access and analysis.

Features: Comprises 80 network flow features (e.g., flow duration, packet lengths, flags, protocols like HTTP, HTTPS, SSH), extracted using tools like CICFlowMeter, ensuring compatibility with machine learning frameworks for IDS model development.
File Structure: Organized into daily CSV files (e.g., Monday-WorkingHours.csv to Friday-WorkingHours.csv) with labeled benign and attack traffic, facilitating chronological analysis of network behavior over a 5-day period.

This dataset is ideal for cybersecurity researchers, machine learning practitioners, and IDS developers seeking a benchmark resource for evaluating anomaly detection, classification algorithms, and defensive strategies against modern cyber threats. It supports tasks like binary/multiclass classification, with improved suitability for imbalanced learning techniques.


Cite:

Panigrahi, R., & Borah, S. (2018). A detailed analysis of CICIDS2017 dataset for designing Intrusion Detection Systems. International Journal of Engineering & Technology, 7(3.24), 479-482.

Iman Sharafaldin, Arash Habibi Lashkari, and Ali A. Ghorbani, “Toward Generating a New Intrusion Detection Dataset and Intrusion Traffic Characterization”, 4th International Conference on Information Systems Security and Privacy (ICISSP), Portugal, January 2018.
DOI: 10.17632/pkskt3fv3v.1
title: IDS2025 (Balanced Intrusion Detection Evaluation Dataset)

description: This dataset, titled IDS2025: Balanced Intrusion Detection Evaluation Dataset, is an enhanced and refined version of the original CICIDS2017 dataset, designed specifically for research and development in Intrusion Detection Systems (IDS). It addresses key limitations identified in a detailed analysis of the CICIDS2017 dataset, including severe class imbalance (e.g., Benign traffic dominating at 83.34%), high data volume leading to processing challenges, scattered attack instances across files, and inconsistencies in labeling.

Key Improvements and Features: 

Class Balancing: Minority classes have been relabeled and merged where appropriate (e.g., combining similar attack variants like DoS subtypes) to reduce imbalance, improving model training efficacy and reducing bias toward dominant classes like Benign. The resulting distribution aims for a more equitable representation, with prevalence ratios adjusted from extremes like 0.0009% for rare attacks to more balanced levels.

Data Volume Optimization: Redundant or low-value instances were resampled or removed, resulting in a more manageable size while preserving essential network traffic patterns. The dataset retains approximately [insert approximate total instances, e.g., 2,830,540 based on original, adjusted post-processing] records across merged classes.

Attack Coverage: Includes a comprehensive set of real-world attack scenarios captured from simulated network environments, such as DoS/DDoS (e.g., Hulk, GoldenEye, Slowloris), Brute Force (FTP/SSH), Web Attacks (XSS, SQL Injection), Infiltration, Botnet, PortScan, and Heartbleed. Attacks are now more uniformly distributed across files for easier access and analysis.

Features: Comprises 80 network flow features (e.g., flow duration, packet lengths, flags, protocols like HTTP, HTTPS, SSH), extracted using tools like CICFlowMeter, ensuring compatibility with machine learning frameworks for IDS model development.
File Structure: Organized into daily CSV files (e.g., Monday-WorkingHours.csv to Friday-WorkingHours.csv) with labeled benign and attack traffic, facilitating chronological analysis of network behavior over a 5-day period.

This dataset is ideal for cybersecurity researchers, machine learning practitioners, and IDS developers seeking a benchmark resource for evaluating anomaly detection, classification algorithms, and defensive strategies against modern cyber threats. It supports tasks like binary/multiclass classification, with improved suitability for imbalanced learning techniques.


Cite:

Panigrahi, R., & Borah, S. (2018). A detailed analysis of CICIDS2017 dataset for designing Intrusion Detection Systems. International Journal of Engineering & Technology, 7(3.24), 479-482.

Iman Sharafaldin, Arash Habibi Lashkari, and Ali A. Ghorbani, “Toward Generating a New Intrusion Detection Dataset and Intrusion Traffic Characterization”, 4th International Conference on Information Systems Security and Privacy (ICISSP), Portugal, January 2018.
DOI: 10.17632/c23cbrdnvc
title: GPBAR1-mediated bile acid sensing in cholangiocytes drives IL-23/Th17-dependent inflammation in PSC_Mass Spec data_Figure 1 E-H_pt2

description: MS data related to calibration curves Figure 1 E-H
DOI: 10.17632/c23cbrdnvc.1
title: GPBAR1-mediated bile acid sensing in cholangiocytes drives IL-23/Th17-dependent inflammation in PSC_Mass Spec data_Figure 1 E-H_pt2

description: MS data related to calibration curves Figure 1 E-H
DOI: 10.17632/vw7z46h83c
title: GPBAR1-mediated bile acid sensing in cholangiocytes drives IL-23/Th17-dependent inflammation in PSC_Mass Spec data_Figure S6B + S7

description: MS data related to figure S6B + S7
DOI: 10.17632/vw7z46h83c.1
title: GPBAR1-mediated bile acid sensing in cholangiocytes drives IL-23/Th17-dependent inflammation in PSC_Mass Spec data_Figure S6B + S7

description: MS data related to figure S6B + S7
DOI: 10.17632/wpp8prjv36
title: GPBAR1-mediated bile acid sensing in cholangiocytes drives IL-23/Th17-dependent inflammation in PSC_Mass Spec data_Figure S6C + S8

description: MS data related to figure S6C + S8
DOI: 10.17632/wpp8prjv36.1
title: GPBAR1-mediated bile acid sensing in cholangiocytes drives IL-23/Th17-dependent inflammation in PSC_Mass Spec data_Figure S6C + S8

description: MS data related to figure S6C + S8
DOI: 10.17632/z6fmdbz5dh
title: GPBAR1-mediated bile acid sensing in cholangiocytes drives IL-23/Th17-dependent inflammation in PSC_Mass Spec data_Figure 10 D

description: MS data related to figure 10 D
DOI: 10.17632/z6fmdbz5dh.1
title: GPBAR1-mediated bile acid sensing in cholangiocytes drives IL-23/Th17-dependent inflammation in PSC_Mass Spec data_Figure 10 D

description: MS data related to figure 10 D
DOI: 10.17632/c75ymfvj77
title: GPBAR1-mediated bile acid sensing in cholangiocytes drives IL-23/Th17-dependent inflammation in PSC_Mass Spec data_Figure 10 C

description: MS data related to figure 10 C
DOI: 10.17632/c75ymfvj77.1
title: GPBAR1-mediated bile acid sensing in cholangiocytes drives IL-23/Th17-dependent inflammation in PSC_Mass Spec data_Figure 10 C

description: MS data related to figure 10 C