cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.xakr9g
title: Occurrence Download

description: A dataset containing 237 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Pinus fenzeliana)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 237 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064525-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tv2azq
title: Occurrence Download

description: A dataset containing 7764 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "VerbatimScientificName is Ficus microcarpa"
 ]
}

 The dataset includes 7764 records from 105 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064526-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8abbd2
title: Occurrence Download

description: A dataset containing 4591 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is WII Herbarium Dataset"
 ]
}

 The dataset includes 4591 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064524-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.12757/bbk.bopf2025q1.01
title: Bundesbank Online Panel - Firms (BOP-F)

description: Self-administered questionnaire: Web-based
description: The sample for the survey is drawn from the universe of firms based in Germany with a taxable turnover of more than €22,000 or at least one employer subject to social security contributions which includes roughly 1 million firms.
description: The drawing is a proportional random sample according to industry, region and size class, so that the selection probability is equal for all firms.
DOI: 10.15468/dl.zw7msh
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Tinamiformes)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((-150 0,-120 0,-120 30,-150 30,-150 0))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064528-250920141307145/datasets/export for details.
DOI: 10.15468/dl.y2ma78
title: Occurrence Download

description: A dataset containing 101 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Vaccinium constablaei",
 "BasisOfRecord is one of (Specimen, Human Observation, Occurrence evidence, Material sample, Living Specimen)",
 "HasCoordinate is true",
 "Country is one of (Canada, United States of America)"
 ]
}

 The dataset includes 101 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011828-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/vm34mn
title: Swiss National Vespoidea Databank

description: This dataset includes records of the Aculeata pro parte (Vespoidea: Formicidae, Mutillidae, Sapygidae, Scoliidae, Tiphiidae, Vespidae) from Switzerland and the adjacent area. Data sources include museum and private collections, the literature, field observations provided by a large network of volunteer collaborators, environmental impact studies, national inventories and academic work. The period covered by the data extends from 1855 to the present day. All data provided have been subject to a validation procedure.
DOI: 10.15468/dl.h647vz
title: Occurrence Download

description: A dataset listing the 1 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is Inventaires Aéro Biodiversité - RUN - Aéroport La Réunion Roland Garros-Inventaires Aéro Biodiversité - RUN - Point d'EPOC 5"
 ]
}

 The dataset's 1 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011816-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21227/fm2x-ye76
title: "Dataset for herb-symptom associations prediction (HIT & TCMIO)"

description: "The HIT dataset integrates TCM-related information from multiple sources, including: (1) ingredient-target and herb-ingredient associations from the HIT2.0 database, and (2) symptom-target and herb-symptom associations from the SymMap database. The TCMIO dataset has a similar composition to HIT, except that its ingredient-target and herb-ingredient associations come from the TCMIO database."
DOI: 10.7795/550.20260123a
title: Ergänzung zu: Anleitung zur Nutzung des DCC-Schemas für die Erstellung eines digitalen Kalibrierscheins für Strömungsmessgrößen : Expertenbericht DKD-E 11-1, Anhang A

description: Dieser DCC ist Teil des DKD-Expertenberichts DKD-E 11-1 Anleitung zur Nutzung des DCC-Schemas für die Erstellung eines digitalen Kalibrierscheins für Strömungsmessgrößen, Ausgabe 01/2026, Physikalisch-Technische Bundesanstalt, Braunschweig und Berlin. DOI: https://doi.org/10.7795/550.20260123 Dies ist KEIN echter Kalibrierschein!
DOI: 10.15468/dl.yrj2n8
title: Occurrence Download

description: A dataset containing 186 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Musgravea stenostachya",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 186 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011833-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/8p82c8
title: Swiss National Diplopoda Databank

description: This dataset concerns the Diplopoda (Orders Callipodida, Chordeumatida, Glomerida, Julida, Polydesmida, Polyxenida) from Switzerland. Data sources include Swiss museum collections, scientific publications, recent specimens collected in environmental impact studies or by Ariane Pedroli for her PhD Thesis on this group. The period covered by the data is from 1846 to the present day. All data provided have been subjected to a validation procedure.
DOI: 10.5281/zenodo.11179787
title: Adiac

description: This dataset is part of the TSML dataset archive maintained by University of Southampton and University of Bradford researchers. Please cite a relevant or the latest full archive release if you use the datasets. See http://www.timeseriesclassification.com/ for information on the group and alternative download sources.

This dataset was originally part of the University of California, Riverside (UCR) time series classification archive.

The Automatic Diatom Identification and Classification (ADIAC) project was a pilot study concerning automatic identification of diatoms (unicellular algae) on the basis of images. The data was donated by Andrei Jalba, a PhD student on the project, which finished in the early 2000s. The outlines are extracted from thresholded images. Presumably the time series are generated as distance to a reference point (the centre being the obvious candidate). The data is very sinusoidal.

Donator: A. Jalba
DOI: 10.5281/zenodo.11179788
title: Adiac

description: This dataset is part of the TSML dataset archive maintained by University of Southampton and University of Bradford researchers. Please cite a relevant or the latest full archive release if you use the datasets. See http://www.timeseriesclassification.com/ for information on the group and alternative download sources.

This dataset was originally part of the University of California, Riverside (UCR) time series classification archive.

The Automatic Diatom Identification and Classification (ADIAC) project was a pilot study concerning automatic identification of diatoms (unicellular algae) on the basis of images. The data was donated by Andrei Jalba, a PhD student on the project, which finished in the early 2000s. The outlines are extracted from thresholded images. Presumably the time series are generated as distance to a reference point (the centre being the obvious candidate). The data is very sinusoidal.

Donator: A. Jalba
DOI: 10.5281/zenodo.11184892
title: ACSF1

description: This dataset is part of the UCR Archive maintained by University of Southampton researchers. Please cite a relevant or the latest full archive release if you use the datasets. See http://www.timeseriesclassification.com/.

The dataset is compiled from ACS-F1, the first version of the database of appliance consumption signatures. The dataset contains the power consumption of typical appliances. The recordings are characterized by long idle periods and some high bursts of energy consumption when the appliance is active.

The classes correspond to 10 categories of home appliances: 

mobile phones (via chargers), coffee machines, computer stations (including monitor), fridges and freezers, Hi-Fi systems (CD players), lamp (CFL), laptops (via chargers), microwave ovens, printers, and televisions (LCD or LED). There is nothing to infer from the order of examples in the train and test set.

Data created by Gisler, Christophe, et al. [1] and https://icosys.ch/acs-f1. Data edited by Patrick Schafer and Ulf Leser (see [2]).

[1] Gisler, Christophe, et al. "Appliance consumption signature database and recognition test protocols." Systems, Signal Processing and their Applications (WoSSPA), 2013 8th International Workshop on. IEEE, 2013.   [2] Schafer, Patrick, and Ulf Leser. "Fast and accurate time series classification with weasel." Proceedings of the 2017 ACM on Conference on Information and Knowledge Management. ACM, 2017.

Donator: P. Schafer
DOI: 10.5281/zenodo.11184893
title: ACSF1

description: This dataset is part of the UCR Archive maintained by University of Southampton researchers. Please cite a relevant or the latest full archive release if you use the datasets. See http://www.timeseriesclassification.com/.

The dataset is compiled from ACS-F1, the first version of the database of appliance consumption signatures. The dataset contains the power consumption of typical appliances. The recordings are characterized by long idle periods and some high bursts of energy consumption when the appliance is active.

The classes correspond to 10 categories of home appliances: 

mobile phones (via chargers), coffee machines, computer stations (including monitor), fridges and freezers, Hi-Fi systems (CD players), lamp (CFL), laptops (via chargers), microwave ovens, printers, and televisions (LCD or LED). There is nothing to infer from the order of examples in the train and test set.

Data created by Gisler, Christophe, et al. [1] and https://icosys.ch/acs-f1. Data edited by Patrick Schafer and Ulf Leser (see [2]).

[1] Gisler, Christophe, et al. "Appliance consumption signature database and recognition test protocols." Systems, Signal Processing and their Applications (WoSSPA), 2013 8th International Workshop on. IEEE, 2013.   [2] Schafer, Patrick, and Ulf Leser. "Fast and accurate time series classification with weasel." Proceedings of the 2017 ACM on Conference on Information and Knowledge Management. ACM, 2017.

Donator: P. Schafer
DOI: 10.5281/zenodo.18483878
title: Data set of strain-rate, one-second peak absolute acceleration and strain rate values

description: The data stored here is the observations of strain-rate, one-second peak absolute acceleration and strain rate values in the paper of ‘Experimental Evaluation of DAS under Strong Shaking and Interpretation of Observed Strain Signals via Internal Cable Modeling’, by Katakami et al.
DOI: 10.15468/dl.rgmaqk
title: Occurrence Download

description: A dataset containing 52 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Vaccinium ashei",
 "BasisOfRecord is one of (Specimen, Human Observation, Occurrence evidence, Material sample, Living Specimen)",
 "HasCoordinate is true",
 "Country is one of (Canada, United States of America)"
 ]
}

 The dataset includes 52 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011835-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18483877
title: Data set of strain-rate, one-second peak absolute acceleration and strain rate values

description: The data stored here is the observations of strain-rate, one-second peak absolute acceleration and strain rate values in the paper of ‘Experimental Evaluation of DAS under Strong Shaking and Interpretation of Observed Strain Signals via Internal Cable Modeling’, by Katakami et al.
DOI: 10.5281/zenodo.11185163
title: ArrowHead

description: This dataset is part of the UCR Archive maintained by University of Southampton researchers. Please cite a relevant or the latest full archive release if you use the datasets. See http://www.timeseriesclassification.com/.

The arrowhead data consists of outlines of the images of arrowheads. The shapes of the projectile points are converted into a time series using the angle-based method. The classification of projectile points is an important topic in anthropology. The classes are based on shape distinctions  such as the presence and location of a notch in the arrow. The problem in the repository is a length normalised version of that used in Ye09shapelets. The three classes are called "Avonlea", "Clovis" and "Mix".

http://alumni.cs.ucr.edu/~lexiangy/shapelet.html

http://alumni.cs.ucr.edu/~lexiangy/Shapelet/Proj_Point_Review.pdf

Donator: L. Ye, E. Keogh
DOI: 10.5281/zenodo.11185162
title: ArrowHead

description: This dataset is part of the UCR Archive maintained by University of Southampton researchers. Please cite a relevant or the latest full archive release if you use the datasets. See http://www.timeseriesclassification.com/.

The arrowhead data consists of outlines of the images of arrowheads. The shapes of the projectile points are converted into a time series using the angle-based method. The classification of projectile points is an important topic in anthropology. The classes are based on shape distinctions  such as the presence and location of a notch in the arrow. The problem in the repository is a length normalised version of that used in Ye09shapelets. The three classes are called "Avonlea", "Clovis" and "Mix".

http://alumni.cs.ucr.edu/~lexiangy/shapelet.html

http://alumni.cs.ucr.edu/~lexiangy/Shapelet/Proj_Point_Review.pdf

Donator: L. Ye, E. Keogh
DOI: 10.5281/zenodo.11185190
title: Beef

description: This dataset is part of the UCR Archive maintained by University of Southampton researchers. Please cite a relevant or the latest full archive release if you use the datasets. See http://www.timeseriesclassification.com/.

Food spectrographs are used in chemometrics to classify food types, a task that has obvious applications in food safety and quality assurance. The beef dataset consists of four classes of beef spectrograms, from pure beef and beef adulterated with varying degrees of offal. 

Further information can be found in the original paper [1]. The data was first used in the time series classification literature in [2].

[1] Jowder et al. Detection of Adulteration in Cooked Meat Products by Mid-Infrared Spectroscopy, J. Agricultural and Food Chemistry, 50 (6), 2002.

[2] Bagnall et al. Transformation Based Ensembles for Time Series Classification, SDM 2012.

Donator: K. Kemsley, A. Bagnall
DOI: 10.5281/zenodo.11185189
title: Beef

description: This dataset is part of the UCR Archive maintained by University of Southampton researchers. Please cite a relevant or the latest full archive release if you use the datasets. See http://www.timeseriesclassification.com/.

Food spectrographs are used in chemometrics to classify food types, a task that has obvious applications in food safety and quality assurance. The beef dataset consists of four classes of beef spectrograms, from pure beef and beef adulterated with varying degrees of offal. 

Further information can be found in the original paper [1]. The data was first used in the time series classification literature in [2].

[1] Jowder et al. Detection of Adulteration in Cooked Meat Products by Mid-Infrared Spectroscopy, J. Agricultural and Food Chemistry, 50 (6), 2002.

[2] Bagnall et al. Transformation Based Ensembles for Time Series Classification, SDM 2012.

Donator: K. Kemsley, A. Bagnall
DOI: 10.5281/zenodo.11185217
title: BeetleFly

description: This dataset is part of the UCR Archive maintained by University of Southampton researchers. Please cite a relevant or the latest full archive release if you use the datasets. See http://www.timeseriesclassification.com/.

MPEG-7 CE Shape-1 Part B is a database of binary images developed for testing MPEG-7 shape descriptors, and is available free online. It is used for testing contour/image and skeleton-based descriptors. Classes of images vary broadly, and include classes that are similar in shape to one another. There are 20 instances of each class, and 60 classes in total. We have extracted the outlines of these images and mapped them into 1-D series of distances to the centre. Beetle/Fly is the problem of distinguishing between an outline of a beetle and a fly

Donator: J. Hills, A. Bagnall
DOI: 10.5281/zenodo.11185218
title: BeetleFly

description: This dataset is part of the UCR Archive maintained by University of Southampton researchers. Please cite a relevant or the latest full archive release if you use the datasets. See http://www.timeseriesclassification.com/.

MPEG-7 CE Shape-1 Part B is a database of binary images developed for testing MPEG-7 shape descriptors, and is available free online. It is used for testing contour/image and skeleton-based descriptors. Classes of images vary broadly, and include classes that are similar in shape to one another. There are 20 instances of each class, and 60 classes in total. We have extracted the outlines of these images and mapped them into 1-D series of distances to the centre. Beetle/Fly is the problem of distinguishing between an outline of a beetle and a fly

Donator: J. Hills, A. Bagnall
DOI: 10.5281/zenodo.11185258
title: BirdChicken

description: This dataset is part of the UCR Archive maintained by University of Southampton researchers. Please cite a relevant or the latest full archive release if you use the datasets. See http://www.timeseriesclassification.com/.

MPEG-7 CE Shape-1 Part B is a database of binary images developed for testing MPEG-7 shape descriptors, and is available free online. It is used for testing contour/image and skeleton-based descriptors. Classes of images vary broadly, and include classes that are similar in shape to one another. There are 20 instances of each class, and 60 classes in total. We have extracted the outlines of these images and mapped them into 1-D series of distances to the centre. Bird/Chicken is the problem of distinguishing between an outline of a bird and a chicken

Donator: J. Hills, A. Bagnall
DOI: 10.5281/zenodo.11185259
title: BirdChicken

description: This dataset is part of the UCR Archive maintained by University of Southampton researchers. Please cite a relevant or the latest full archive release if you use the datasets. See http://www.timeseriesclassification.com/.

MPEG-7 CE Shape-1 Part B is a database of binary images developed for testing MPEG-7 shape descriptors, and is available free online. It is used for testing contour/image and skeleton-based descriptors. Classes of images vary broadly, and include classes that are similar in shape to one another. There are 20 instances of each class, and 60 classes in total. We have extracted the outlines of these images and mapped them into 1-D series of distances to the centre. Bird/Chicken is the problem of distinguishing between an outline of a bird and a chicken

Donator: J. Hills, A. Bagnall
DOI: 10.5281/zenodo.11185290
title: BME

description: This dataset is part of the UCR Archive maintained by University of Southampton researchers. Please cite a relevant or the latest full archive release if you use the datasets. See http://www.timeseriesclassification.com/.

BME (Begin-Middle-End) is a synthetic univariate data set with three classes:  one class is characterized by a small positive bell arising at the initial period (Begin), one does not have any bell (Middle), one has a positive bell arising at the final period (End).  

All series are constituted by a central plate. The central plates may be positive or negative. The discriminant is the presence or absence of a positive peak, or at the beginning of series or at the end.



Class 1: Begin

Class 2: Middle

Class 3: End   


Data source: University Joseph Fourier (Grenoble I), Laboratoire d informatique de Grenoble(LIG), Equipe AMA

Donator: Joseph Fourier University
DOI: 10.5281/zenodo.11185291
title: BME

description: This dataset is part of the UCR Archive maintained by University of Southampton researchers. Please cite a relevant or the latest full archive release if you use the datasets. See http://www.timeseriesclassification.com/.

BME (Begin-Middle-End) is a synthetic univariate data set with three classes:  one class is characterized by a small positive bell arising at the initial period (Begin), one does not have any bell (Middle), one has a positive bell arising at the final period (End).  

All series are constituted by a central plate. The central plates may be positive or negative. The discriminant is the presence or absence of a positive peak, or at the beginning of series or at the end.



Class 1: Begin

Class 2: Middle

Class 3: End   


Data source: University Joseph Fourier (Grenoble I), Laboratoire d informatique de Grenoble(LIG), Equipe AMA

Donator: Joseph Fourier University
DOI: 10.5281/zenodo.11185321
title: Car

description: This dataset is part of the UCR Archive maintained by University of Southampton researchers. Please cite a relevant or the latest full archive release if you use the datasets. See http://www.timeseriesclassification.com/.

The data is outlines of four different types of cars extracted from traffic videos using the motion information. The images were mapped onto a 1-D series.The vehicles were classified into one of the four class: sedan, pickup, minivan or SUV. Further details are available in [1].

[1] Thakoor, Ninad, and Gao, Jean. "Shape classifier based on generalized probabilistic descent method with hidden Markov descriptor." Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1. Vol. 1. IEEE, 2005. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.60.161&rep=rep1&type=pdf90.18%

Donator: J. Gao
DOI: 10.5281/zenodo.11185322
title: Car

description: This dataset is part of the UCR Archive maintained by University of Southampton researchers. Please cite a relevant or the latest full archive release if you use the datasets. See http://www.timeseriesclassification.com/.

The data is outlines of four different types of cars extracted from traffic videos using the motion information. The images were mapped onto a 1-D series.The vehicles were classified into one of the four class: sedan, pickup, minivan or SUV. Further details are available in [1].

[1] Thakoor, Ninad, and Gao, Jean. "Shape classifier based on generalized probabilistic descent method with hidden Markov descriptor." Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1. Vol. 1. IEEE, 2005. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.60.161&rep=rep1&type=pdf90.18%

Donator: J. Gao