cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57754/fdat.mqb3c-rmj69
title: German Adjective-Noun Phrase Dataset for Compositionality Tests (deu-adj-n)

description:  If you want to use this dataset for research purposes, please refer to the following sources:
                 - Daniël de Kok, Sebastian Pütz. 2019. Stylebook for the Tübingen treebank of dependency-parsed German (TüBa-D/DP).
                 - Corina Dima, Daniël de Kok, Neele Witte, Erhard Hinrichs. 2019. No word is an island — a transformation weighting model for semantic composition. Transactions of the Association for Computational Linguistics.
The dataset is distributed under the Creative Commons Attribution NonCommercial (CC-BY-NC) license.
The 119,434 German adjective-noun phrases in this dataset (splits: 83,603 train, 23,887 test, 11,944 dev instances) were extracted automatically from the TüBa-D/DP treebank. The treebank is composed of three different parts: 1) articles from the German newspaper taz; 2)  the German Wikipedia dump from January 20, 2018; 3) German proceedings from the EuroParl corpus (Koehn, 2005; Tiedemann, 2012). The treebank consists of 64.9M sentences and 1.3B tokens. The train/test/dev files have the following format, single parts are separated by space: adjective noun adj-noun phrase, where the adjective and the noun of the phrase are separated by the string _adj_n_ (e.g. kritisch Film kritisch_adj_n_Film).
The phrases were extracted with the part-of-speech tag information provided by the treebank. For results of different composition models on this dataset see Dima et al. (2019), No word is an island — a transformation weighting model for semantic composition.
The embeddings for all words and phrases in this dataset are stored in the word2vec format in twe-adj-n.bin. This format can be loaded by several packages (e.g. the gensim package of Řehůřek, Radim and Petr Sojka (2010)).
The embeddings for the adjectives, nouns and phrases were trained jointly on the lemmatized version of the TüBa-D/DP treebank, using the word2vec package (Mikolov et al. 2013).
The word embeddings were trained with the skipgram model with negative sampling, a symmetric window of 10 as context size, 25 negative samples per positive training instance and a sample probability threshold of 0.0001.
The resulting embeddings have a dimension of 200 and the vocabulary contains 476,137 words in total. The minimum frequency cut-off was set to 50 for all words.1
description: Research carried out in work package A03 of the SFB 833.
DOI: 10.57754/fdat.0yjbq-rze07
title: English Adjective-Noun Phrase Dataset for Compositionality Tests (eng-adj-n)

description:  If you want to use this dataset for research purposes, please refer to the following sources:
                 - Roland  Schäfer. 2015. Processing  and  querying large  web  corpora  with  the  COW14  architecture. In Proceedings of Challenges in the Management of Large Corpora 3 (CMLC-3),  Lancaster. UCREL, IDS.
                 - Roland Schäfer and Felix Bildhauer. 2012. Building Large Corpora from the Web Using a New Efficient  Tool  Chain. In Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12),  pages 486–493, Istanbul, Turkey. European Language Resources Association (ELRA).
                 - Corina Dima, Daniël de Kok, Neele Witte, Erhard Hinrichs. 2019. No word is an island — a transformation weighting model for semantic composition. Transactions of the Association for Computational Linguistics.
The dataset is distributed under the Creative Commons Attribution NonCommercial (CC-BY-NC) license.
This dataset contains 238,975 English adjective-noun phrases (split into 167,292 train, 47,803 test, 23,880 dev instances) that were automatically extracted from the ENCOW16AX treebank (Schäfer  and  Bildhauer, 2012;  Schäfer,  2015).
The phrases were extracted with the help of the part-of-speech tag information provided by the treebank.
The train/test/dev files have the following format, single parts separated by tab: adjective noun adj-noun phrase, where the adjective and the noun are separated by the string _adj_n_ (e.g. good networking good_adj_n_networking).
For results of different composition models on this dataset see Dima et al. (2019) ), No word is an island — a transformation weighting model for semantic composition.
The word embeddings were trained on ENCOW16AX, which contains crawled web data from different sources. The training corpus was filtered to only contain sentences with a document quality of a or b to avoid noisy data.
To ensure that trained word embeddings for enough adjective-noun phrases are available, the embeddings were trained on word forms, instead of lemmas. The final training corpus for the word embeddings contains 89.0M sentences and 2.2B  tokens.
The embeddings for the adjectives, nouns and phrases were trained jointly, with the word2vec package (Mikolov et al. 2013), using the skipgram model with negative sampling, a symmetric window of 10 as context size, 25 negative samples per positive training instance and a sample probability threshold of 0.0001. The resulting embeddings have a dimension of 200 and the vocabulary size is 478,372.
The minimum frequency cut-off was set to 50 for all words and phrases.
The embeddings are stored in the binary format of word2vec in encow-adj-n.bin. This format can be loaded by several packages (e.g. the gensim package of Řehůřek, Radim and Petr Sojka (2010)).1
description: Research carried out in work package A03 of the SFB 833.
DOI: 10.57754/fdat.myevg-4a328
title: English Adverb-Adjective Phrase Dataset for Compositionality Tests (eng-adv-adj)

description:  If you want to use this dataset for research purposes, please refer to the following sources:
                 - Roland  Schäfer. 2015. Processing  and  querying large  web  corpora  with  the  COW14  architecture. In Proceedings of Challenges in the Management of Large Corpora 3 (CMLC-3),  Lancaster. UCREL, IDS.
                 - Roland Schäfer and Felix Bildhauer. 2012. Building Large Corpora from the Web Using a New Efficient  Tool  Chain. In Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12),  pages 486–493, Istanbul, Turkey. European Language Resources Association (ELRA).
                 - Corina Dima, Daniël de Kok, Neele Witte, Erhard Hinrichs. 2019. No word is an island — a transformation weighting model for semantic composition. Transactions of the Association for Computational Linguistics.
The dataset is distributed under the Creative Commons Attribution NonCommercial (CC-BY-NC) license.
This dataset contains 238,975 English adjective-noun phrases (split into 167,292 train, 47,803 test, 23,880 dev instances) that were automatically extracted from the ENCOW16AX treebank (Schäfer  and  Bildhauer, 2012;  Schäfer,  2015).
The phrases were extracted with the help of the part-of-speech tag information provided by the treebank.
The train/test/dev files have the following format, single parts separated by tab: adjective noun adj-noun phrase, where the adjective and the noun are separated by the string _adj_n_ (e.g. good networking good_adj_n_networking).
For results of different composition models on this dataset see Dima et al. (2019) ), No word is an island — a transformation weighting model for semantic composition.
The word embeddings were trained on ENCOW16AX, which contains crawled web data from different sources. The training corpus was filtered to only contain sentences with a document quality of a or b to avoid noisy data.
To ensure that trained word embeddings for enough adjective-noun phrases are available, the embeddings were trained on word forms, instead of lemmas. The final training corpus for the word embeddings contains 89.0M sentences and 2.2B  tokens.
The embeddings for the adjectives, nouns and phrases were trained jointly, with the word2vec package (Mikolov et al. 2013), using the skipgram model with negative sampling, a symmetric window of 10 as context size, 25 negative samples per positive training instance and a sample probability threshold of 0.0001. The resulting embeddings have a dimension of 200 and the vocabulary size is 478,372.
The minimum frequency cut-off was set to 50 for all words and phrases.
The embeddings are stored in the binary format of word2vec in encow-adj-n.bin. This format can be loaded by several packages (e.g. the gensim package of Řehůřek, Radim and Petr Sojka (2010)).
DOI: 10.15468/dl.z8wec6
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.281916 -32.665678, 148.281916 -32.667924, 148.284161 -32.667924, 148.284161 -32.665678, 148.281916 -32.665678))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055852-240626123714530/datasets/export for details.
DOI: 10.15468/dl.64sxbr
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((145.196188 -37.202192, 145.196188 -37.211176, 145.205171 -37.211176, 145.205171 -37.202192, 145.196188 -37.202192))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055853-240626123714530/datasets/export for details.
DOI: 10.15468/dl.vk8mxw
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Aristichthys nobilis (Richardson, 1845)"
 ]
}

 The dataset includes 16 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055855-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ypukaw
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Viverricula indica (É.Geoffroy Saint-Hilaire, 1803)",
 "Year 1970-2024"
 ]
}

 The dataset includes 7 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055856-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.26517871
title: Cell protect ability-24h MTT.xlsx

description: In order to assess the ability of PtNCs and MM-PtNCs to maintain HK-2 cell growth under high ROS conditions, a MTT assay was conducted and here is the raw data for result analysis.
DOI: 10.6084/m9.figshare.26517871.v2
title: Cell protect ability-24h MTT.xlsx

description: In order to assess the ability of PtNCs and MM-PtNCs to maintain HK-2 cell growth under high ROS conditions, a MTT assay was conducted and here is the raw data for result analysis.
DOI: 10.6084/m9.figshare.26517871.v1
title: Cell protect ability-24h MTT.xlsx

description: In order to assess the ability of PtNCs and MM-PtNCs to maintain HK-2 cell growth under high ROS conditions, a MTT assay was conducted and here is the raw data for result analysis.
DOI: 10.15468/dl.nqt8va
title: Occurrence Download

description: A dataset containing 33128 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Material sample, Specimen)",
 "TaxonKey is Canis lupus Linnaeus, 1758"
 ]
}

 The dataset includes 33128 records from 212 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055854-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u6bxcw
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.382977 -32.665678, 148.382977 -32.672416, 148.385222 -32.672416, 148.385222 -32.665678, 148.382977 -32.665678))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055857-240626123714530/datasets/export for details.
DOI: 10.15468/dl.593qtu
title: Occurrence Download

description: A dataset containing 171 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((142.867294 -37.206684, 142.867294 -37.211176, 142.876277 -37.211176, 142.876277 -37.206684, 142.867294 -37.206684))"
 ]
}

 The dataset includes 171 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055858-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13268651
title: Supplementary Material: Effectiveness of Performance Visualizations for Declarative Model Transformations

description: We performed a case study to evaluate whether our performance visualizations developed for the declarative transformation language Henshin are suitable for performing a root cause analysis. Our study consisted of four parts. 1) Participants completed a questionnaire that collected data on their demographics and knowledge of model transformations. 2) The participants watched a video explaining the basics of models, Henshin, and our performance visualizations. 3) The study participants solved four different tasks one after the other. Guided by a questionnaire, they carried out a root cause analysis. 4) Finally, in a short interview session, we asked the participants about their assessment of the comprehensibility and usefulness of the visualizations.

In total, 18 participants took part in our study. Our results show that most participants could correctly read and interpret the information provided by the visualizations. The majority of our participants could propose a performance optimization based on the visualizations that optimized the execution of a transformation.

This data set contains our study material, which is necessary to repeat the study, our raw and processed data.
description: This work was partially funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - 358569332 and partially supported by the Wallenberg AI, Autonomous Systems and Software Program (WASP) funded by the Knut and Alice Wallenberg Foundation.
DOI: 10.5281/zenodo.13268652
title: Supplementary Material: Effectiveness of Performance Visualizations for Declarative Model Transformations

description: We performed a case study to evaluate whether our performance visualizations developed for the declarative transformation language Henshin are suitable for performing a root cause analysis. Our study consisted of four parts. 1) Participants completed a questionnaire that collected data on their demographics and knowledge of model transformations. 2) The participants watched a video explaining the basics of models, Henshin, and our performance visualizations. 3) The study participants solved four different tasks one after the other. Guided by a questionnaire, they carried out a root cause analysis. 4) Finally, in a short interview session, we asked the participants about their assessment of the comprehensibility and usefulness of the visualizations.

In total, 18 participants took part in our study. Our results show that most participants could correctly read and interpret the information provided by the visualizations. The majority of our participants could propose a performance optimization based on the visualizations that optimized the execution of a transformation.

This data set contains our study material, which is necessary to repeat the study, our raw and processed data.
description: This work was partially funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - 358569332 and partially supported by the Wallenberg AI, Autonomous Systems and Software Program (WASP) funded by the Knut and Alice Wallenberg Foundation.
DOI: 10.34740/kaggle/dsv/9130287
title: AutoXGB
DOI: 10.34740/kaggle/dsv/9130288
title: OnlineFree
DOI: 10.15468/6m9vxa
title: Gymnosperms preserved at Natural History Museum, TU, Nepal

description: A total of 71 gymnosperm specimens are preserved at NHM, TU, Nepal either in formalin or dry herbarium specimen. These specimen belonged to three classes, three order, seven families and fifteen genera. Juniperus, Pinus, Ephedra and Araucaria has the maximum number of preserved specimens. These specimens were collected in between 1969 and 2003 by different collectors from different parts of Nepal. Ephedra was collected from the highest elevation (3962.4 m). Besides this, NHM, TU, Nepal has conserved Cupressus sp., Juniperus incurva, Pinus wallichiana, Podocarpus nerifolius, Taxus wallichiana and T. squamata in the living form within it's premises.
DOI: 10.15468/dl.khqgjt
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.450351 -32.665678, 148.450351 -32.672416, 148.452596 -32.672416, 148.452596 -32.665678, 148.450351 -32.665678))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055861-240626123714530/datasets/export for details.
DOI: 10.15468/dl.qakkaa
title: Occurrence Download

description: A dataset containing 25 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((143.213147 -37.206684, 143.213147 -37.211176, 143.224376 -37.211176, 143.224376 -37.206684, 143.213147 -37.206684))"
 ]
}

 The dataset includes 25 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055862-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gwsk46
title: Occurrence Download

description: A dataset containing 79 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Schizothorax prenanti (Tchang, 1930)"
 ]
}

 The dataset includes 79 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055863-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/5jwk6b
title: Pisces specimen from NHM, Nepal

description: This dataset includes the Pisces species preserved in Natural History Museum, Nepal. The pisces collection includes 420 specimen of 164 species, collected from India and Nepal.
DOI: 10.34740/kaggle/dsv/9038224
title: ISIC 2024 Challenge SelfClean Scores
DOI: 10.15468/dx9c4a
title: Mammal specimen from NHM, Nepal

description: The mammal collection in the Natural History Museum of Kathmandu, Nepal consists of 227 mammal species, which includes trophy horns, mounted skin, skeletons, and whole specimens. The specimens have been brought from different sources such as donations from various people and organizations like the Central Zoo of Nepal.
DOI: 10.15468/dl.fbskyd
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.919723 -32.665678, 148.919723 -32.667924, 148.921968 -32.667924, 148.921968 -32.665678, 148.919723 -32.665678))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055864-240626123714530/datasets/export for details.
DOI: 10.15468/dl.9kdk7b
title: Occurrence Download

description: A dataset containing 17033 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((145.429751 -37.206684, 145.429751 -37.211176, 145.431997 -37.211176, 145.431997 -37.206684, 145.429751 -37.206684))"
 ]
}

 The dataset includes 17033 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055865-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ct38cb
title: Occurrence Download

description: A dataset containing 15 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Schizothorax davidi (Sauvage, 1880)"
 ]
}

 The dataset includes 15 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055866-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bvkwds
title: Occurrence Download

description: A dataset containing 22 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.074683 -32.665678, 149.074683 -32.667924, 149.079174 -32.667924, 149.079174 -32.676907, 149.085912 -32.676907, 149.085912 -32.674662, 149.08142 -32.674662, 149.08142 -32.665678, 149.074683 -32.665678))"
 ]
}

 The dataset includes 22 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055867-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tupvj3
title: Occurrence Download

description: A dataset containing 174 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((143.422007 -37.204438, 143.422007 -37.206684, 143.424252 -37.206684, 143.424252 -37.204438, 143.422007 -37.204438)), ((143.424252 -37.206684, 143.424252 -37.215667, 143.428744 -37.215667, 143.428744 -37.222405, 143.43099 -37.222405, 143.43099 -37.220159, 143.435481 -37.220159, 143.435481 -37.213421, 143.43099 -37.213421, 143.43099 -37.206684, 143.424252 -37.206684)))"
 ]
}

 The dataset includes 174 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055868-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6dgcyy
title: Occurrence Download

description: A dataset containing 875 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "TaxonKey is Athene noctua (Scopoli, 1769)",
 "Year 1000-1920"
 ]
}

 The dataset includes 875 records from 61 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055869-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5bt5v7
title: Occurrence Download

description: A dataset containing 113419 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Triturus cristatus (Laurenti, 1768)",
 "HasCoordinate is true",
 "Year is greater than or equal to 2011",
 "Year is less than or equal to 2024"
 ]
}

 The dataset includes 113419 records from 608 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055845-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bz5h9c
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((149.202693 -32.665678, 149.202693 -32.674662, 149.204939 -32.674662, 149.204939 -32.672416, 149.209431 -32.672416, 149.209431 -32.667924, 149.204939 -32.667924, 149.204939 -32.665678, 149.202693 -32.665678)), ((149.204939 -32.674662, 149.204939 -32.676907, 149.209431 -32.676907, 149.209431 -32.674662, 149.204939 -32.674662)), ((149.209431 -32.667924, 149.216168 -32.667924, 149.216168 -32.665678, 149.209431 -32.665678, 149.209431 -32.667924)))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055870-240626123714530/datasets/export for details.