cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3535/j1k-qw9-ly0
title: Kadua affinis Cham. & Schltdl.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/a3a-ktw-aa0
title: Cystopteris fragilis (L.) Bernh.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/fw5-f04-xv9
title: Crepidomanes humile (G. Forst.) Bosch

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/h0x-x0r-3ez
title: Cystopteris fragilis (L.) Bernh.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/pay-hpq-jd2
title: Aethionema diastrophis Bunge

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/e8s-eyf-la7
title: Mucura globulifera (Poir.) L. A. Triana & Sundue

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/w00-kqh-tm6
title: Doryopteris triphylla (Lam.) Christ

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/h0f-88f-rye
title: Didymochlaena truncatula (Sw.) J. Sm.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/52e-r3k-fg8
title: Didymochlaena truncatula (Sw.) J. Sm.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/zbr-40q-je0
title: Miconia rariflora (Humb. & Bonpl.) Michelang.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/ass-lqx-08j
title: Miconia dependens (D. Don) Judd & Majure

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/cnf-k9c-44j
title: Didymochlaena truncatula (Sw.) J. Sm.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/wn7-79s-p9r
title: Cyathea microdonta (Desv.) Domin

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/y27-f5m-hry
title: Miconia alaticaulis Michelang.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/lfv-t1k-yv4
title: Megalastrum grande (C. Presl) A. R. Sm. & R. C. Moran

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/re1-jvk-07z
title: Cyathea microdonta (Desv.) Domin

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/bq4-g0v-9v7
title: Janusia mediterranea (Vell.) W. R. Anderson

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/ghs-1p7-5sx
title: Miconia dependens (D. Don) Judd & Majure

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/vaw-3ky-ajf
title: Janusia mediterranea (Vell.) W. R. Anderson

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/254-q6h-60g
title: Miconia rariflora (Humb. & Bonpl.) Michelang.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/ehe-fjk-8ec
title: Cyathea microdonta (Desv.) Domin

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/dpy-8xa-33s
title: Janusia mediterranea (Vell.) W. R. Anderson

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/25c-2jd-3fs
title: Megalastrum grande (C. Presl) A. R. Sm. & R. C. Moran

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/hqj-2xa-pdm
title: Janusia mediterranea (Vell.) W. R. Anderson

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/6ms-z69-q7n
title: Cyathea microdonta (Desv.) Domin

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/mws-1qc-64b
title: Carolus chlorocarpus (A. Juss.) W. R. Anderson

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/60b-513-bt2
title: Janusia janusioides (A. Juss.) W. R. Anderson

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/lxs-qy0-yhz
title: Cyathea microdonta (Desv.) Domin

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/d1p-xqh-snx
title: Lophanthera longifolia (Kunth) Griseb.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/wvn-4te-5py
title: Cyathea aurea Klotzsch

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/kel-gxa-9p4
title: Asplenium mucronatum C. Presl

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/ytp-nas-yj3
title: Megalastrum grande (C. Presl) A. R. Sm. & R. C. Moran

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/301-ngb-2p1
title: Cyathea microdonta (Desv.) Domin

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/mlj-c3l-x6c
title: Diplazium expansum Willd.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/6xx-1r9-rne
title: Cyclosorus interruptus (Willd.) H. Itô

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/29z-3mf-vzr
title: Cyclosorus interruptus (Willd.) H. Itô

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/bva-p34-xnm
title: Megalastrum grande (C. Presl) A. R. Sm. & R. C. Moran

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.15468/dl.k3a8wg
title: Occurrence Download

description: A dataset containing 323 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acacia melanoxylon",
 "Country is Ecuador",
 "HasCoordinate is true"
 ]
}

 The dataset includes 323 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074657-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3535/3er-bgx-t9p
title: Megalastrum grande (C. Presl) A. R. Sm. & R. C. Moran

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/hp6-skc-e4x
title: Miconia dependens (D. Don) Judd & Majure

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/al8-kca-f3p
title: Cyclosorus interruptus (Willd.) H. Itô

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/b4d-d2f-q8f
title: Miconia dependens (D. Don) Judd & Majure

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/s8f-28w-5rj
title: Miconia dependens (D. Don) Judd & Majure

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/yrh-e5j-5tx
title: Miconia dependens (D. Don) Judd & Majure

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/61w-dy0-qbt
title: Miconia crenata (Vahl) Michelang.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/zrg-0vk-ah3
title: Miconia crenata (Vahl) Michelang.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.15468/dl.kvhm2q
title: Occurrence Download

description: A dataset containing 28596 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "DatasetKey is EOD – eBird Observation Dataset",
 "Geometry POLYGON((-128.54691 21.06412,-56.28743 21.06412,-56.28743 51.05918,-128.54691 51.05918,-128.54691 21.06412))",
 "HasGeospatialIssue is false",
 "Month is one of (June, July, August, September)",
 "TaxonKey is Perisoreus canadensis",
 "Year 2022-2024"
 ]
}

 The dataset includes 28596 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009809-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25505/fiz.icsd.cc4qdz6
title: CSD 140708: Experimental Crystal Structure Determination

description: Related Article: Yan Xu, Jianjiang Lu, N.K.Goh|1999|J.Mater.Chem.|9|1599|doi:10.1039/a901592b
description: An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cc43nyt
title: CCDC 122696: Experimental Crystal Structure Determination

description: Related Article: M.Doi, T.Ishida, A.Terashima, T.Taniguchi, M.Sasaki, C.Tanaka|1998|Anal.Sci.|14|1191|doi:10.2116/analsci.14.1191
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.15156/bio/sh1399342.10fu
title: SH1399342.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1399346.10fu
title: SH1399346.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1399347.10fu
title: SH1399347.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1399350.10fu
title: SH1399350.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1399351.10fu
title: SH1399351.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.5281/zenodo.15647142
title: Catalan and Spanish Lexical Simplification and Complexity Prediction Dataset

description: This is the Spanish and the Catalan part of the MLSP dataset on Lexical Simplification and Lexical Complexity Prediction. They were used in the MLSP (Multilingual Lexical Simplification Pipeline) shared task, held at the BEA (Innovative use of NLP for Building Educational Applications). 

The target selection and data collection process of the datasets for Spanish and Catalan was largely parallel, but there were some differences due to the availability of source texts and annotators. The initial goal was to select 600 target words per language in 200 contexts, with 3 targets per context. An additional 10 contexts (and 30 words) were required for pilot annotations. Due to the sparseness of resources, we had to relax the goal for Catalan to 160 contexts. For each target a minimum of 10 annotations was required which were collected through on-line forms. The annotation process collected two pieces of data for each target word: i) a rating on Lexical Complexity on a 5-point Likert scale (from "very easy" to "very hard") and ii) up to 3 lexical substitutes for the target that fit in the given context. Annotators were asked to simply repeat the target word if they could not find a suitable alternative.

The Catalan dataset consists of 160 context sentences containing 475 target word tokens (454 distinct types). Sentences were selected from the Educational news section of the TeCla corpus4 (Armengol-Estapé et al., 2021) of news texts. The Spanish dataset consists of 625 target words in 210 contexts from texts on educational books on finance.

More details on the creation and compositoin of the datasets can be found in: 



Saggion, Horacio, et al. ‘Lexical Complexity Prediction and Lexical Simplification for Catalan and Spanish: Resource Creation, Quality Assessment, and Ethical Considerations’. Proceedings of the Third Workshop on Text Simplification, Accessibility and Readability (TSAR 2024), edited by Matthew Shardlow et al., Association for Computational Linguistics, 2024, pp. 82–94, https://aclanthology.org/2024.tsar-1.9.


The description of the BEA MLSP Shared task is described in: 



Shardlow, Matthew, et al. ‘The BEA 2024 Shared Task on the Multilingual Lexical Simplification Pipeline’. Proceedings of the 19th Workshop on Innovative Use of NLP for Building Educational Applications (BEA), 2024.

Shardlow, Matthew, et al. ‘An Extensible Massively Multilingual Lexical Simplification Pipeline Dataset Using the MultiLS Framework’. Proceedings of the 3rd Workshop on Tools and Resources for People with Reading Difficulties (READI), 2024.
DOI: 10.5281/zenodo.15647143
title: Catalan and Spanish Lexical Simplification and Complexity Prediction Dataset

description: This is the Spanish and the Catalan part of the MLSP dataset on Lexical Simplification and Lexical Complexity Prediction. They were used in the MLSP (Multilingual Lexical Simplification Pipeline) shared task, held at the BEA (Innovative use of NLP for Building Educational Applications). 

The target selection and data collection process of the datasets for Spanish and Catalan was largely parallel, but there were some differences due to the availability of source texts and annotators. The initial goal was to select 600 target words per language in 200 contexts, with 3 targets per context. An additional 10 contexts (and 30 words) were required for pilot annotations. Due to the sparseness of resources, we had to relax the goal for Catalan to 160 contexts. For each target a minimum of 10 annotations was required which were collected through on-line forms. The annotation process collected two pieces of data for each target word: i) a rating on Lexical Complexity on a 5-point Likert scale (from "very easy" to "very hard") and ii) up to 3 lexical substitutes for the target that fit in the given context. Annotators were asked to simply repeat the target word if they could not find a suitable alternative.

The Catalan dataset consists of 160 context sentences containing 475 target word tokens (454 distinct types). Sentences were selected from the Educational news section of the TeCla corpus4 (Armengol-Estapé et al., 2021) of news texts. The Spanish dataset consists of 625 target words in 210 contexts from texts on educational books on finance.

More details on the creation and compositoin of the datasets can be found in: 



Saggion, Horacio, et al. ‘Lexical Complexity Prediction and Lexical Simplification for Catalan and Spanish: Resource Creation, Quality Assessment, and Ethical Considerations’. Proceedings of the Third Workshop on Text Simplification, Accessibility and Readability (TSAR 2024), edited by Matthew Shardlow et al., Association for Computational Linguistics, 2024, pp. 82–94, https://aclanthology.org/2024.tsar-1.9.


The description of the BEA MLSP Shared task is described in: 



Shardlow, Matthew, et al. ‘The BEA 2024 Shared Task on the Multilingual Lexical Simplification Pipeline’. Proceedings of the 19th Workshop on Innovative Use of NLP for Building Educational Applications (BEA), 2024.

Shardlow, Matthew, et al. ‘An Extensible Massively Multilingual Lexical Simplification Pipeline Dataset Using the MultiLS Framework’. Proceedings of the 3rd Workshop on Tools and Resources for People with Reading Difficulties (READI), 2024.
DOI: 10.15156/bio/sh1399353.10fu
title: SH1399353.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1399355.10fu
title: SH1399355.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1399357.10fu
title: SH1399357.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.