cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.14458/hcu.res.2012.5
title: นโยบายการคุ้มครองสิทธิมนุษยชนชายแดนไทย - พม่า : กรณีผู้อพยพภัยสงคราม
DOI: 10.14458/tsu.res.2011.11
title: การปรับปรุงสายพันธุ์แบคทีเรียผลิตเซลลูเลสและสภาวะที่เหมาะสมต่อการผลิตเซลลูเลสจากเชื้อสายพันธุ์กลาย
DOI: 10.5281/zenodo.1320158
title: Kglove Dbpedia Inverse Predicate Object Frequency Embeddings

description: This dataset contains the vectors from computing KGloVe embeddings from a inverse predicate object frequency weighted DBpedia 2016-04 graph.

For each entity in the graph, the text file in the zip archive contains a line with the entity name and the embedded vector.

The parameter settings for the embedding are as specified in the paper:

Michael Cochez, Petar Ristoski, Simone Paolo Ponzetto, and Heiko Paulheim. 2017. Global RDF Vector Space Embeddings. In The Semantic Web – ISWC 2017: 16th International Semantic Web Conference, Vienna, Austria, October 21–25, 2017, Proceedings, Part I.
DOI: 10.5281/zenodo.1320159
title: Kglove Dbpedia Inverse Predicate Object Frequency Embeddings

description: This dataset contains the vectors from computing KGloVe embeddings from a inverse predicate object frequency weighted DBpedia 2016-04 graph.

For each entity in the graph, the text file in the zip archive contains a line with the entity name and the embedded vector.

The parameter settings for the embedding are as specified in the paper:

Michael Cochez, Petar Ristoski, Simone Paolo Ponzetto, and Heiko Paulheim. 2017. Global RDF Vector Space Embeddings. In The Semantic Web – ISWC 2017: 16th International Semantic Web Conference, Vienna, Austria, October 21–25, 2017, Proceedings, Part I.
DOI: 10.5281/zenodo.1320179
title: Acc-Lists For Glassgo &gt;=1.5.1

description: Accession lists are compatible with GLASSgo version &gt;= 1.5.1 (Publikation: https://www.frontiersin.org/articles/10.3389/fgene.2018.00124/full).
DOI: 10.5281/zenodo.1320180
title: Acc-Lists For Glassgo &gt;=1.5.1

description: Accession lists are compatible with GLASSgo version &gt;= 1.5.1 (Publikation: https://www.frontiersin.org/articles/10.3389/fgene.2018.00124/full).
DOI: 10.5281/zenodo.1321253
title: Esem18 Maintenance Communities Dataset

description: This dataset contains data in the paper: The Birth, Growth, Death and Rejuvenation of Software Maintenance Communities (ESEM 2018).
DOI: 10.25828/fg8x-je72
title: IDASA Opinion Survey 1998
DOI: 10.5281/zenodo.1321252
title: Esem18 Maintenance Communities Dataset

description: This dataset contains data in the paper: The Birth, Growth, Death and Rejuvenation of Software Maintenance Communities (ESEM 2018).
DOI: 10.5281/zenodo.1321351
title: Dados Suplementares Do Artigo Submetido Para Avaliação Pelos Pares Ao Xix Enancib:  Análise Da Produção Científica Do Periódico Jasis&T Sob A Ótica Dos Três Paradigmas Da Ciência Da Informação  Este Documento Apresenta Dois Quadros. Um Primeiro Que Relaciona Os Termos Extraídos Do Texto De Referência  E Suas Passagens Correspondentes Que Foram Fruto Da Porção Qualitativa E Indutiva Do Estudo; E Um Segundo, Que Apresenta A Lista De Termos Em Ordem Alfabética E Suas Respectivas Traduções Para A Língua Inglesa Utilizadas Na Etapa Quantitativa De Levantamento Junto Ao Periódico Jasis&T.

description: Este documento apresenta dois quadros. Um primeiro que relaciona os termos extraídos do texto de referência[1] e suas passagens correspondentes referente à porção qualitativa e indutiva do estudo; e um segundo, que apresenta a lista de termos em ordem alfabética e suas respectivas traduções para a língua inglesa utilizadas na etapa quantitativa de levantamento junto ao periódico JASIS&T.

[1] BARRETO, A. de A. Uma história da ciência da informação. In. TOUTAIN, L. M. B. B. <strong>Para entender a Ciência da Informação</strong> (Org.). Salvador: EDUFBA, 2007, p. 13-34. Disponível em: &lt;https://repositorio.ufba.br/ri/bitstream/ufba/145/1/Para%20entender%20a%20ciencia%20da%20informacao.pdf&gt;. Acesso em: 5 abr. 2018.
DOI: 10.5281/zenodo.1321352
title: Dados Suplementares Do Artigo Submetido Para Avaliação Pelos Pares Ao Xix Enancib:  Análise Da Produção Científica Do Periódico Jasis&T Sob A Ótica Dos Três Paradigmas Da Ciência Da Informação  Este Documento Apresenta Dois Quadros. Um Primeiro Que Relaciona Os Termos Extraídos Do Texto De Referência  E Suas Passagens Correspondentes Que Foram Fruto Da Porção Qualitativa E Indutiva Do Estudo; E Um Segundo, Que Apresenta A Lista De Termos Em Ordem Alfabética E Suas Respectivas Traduções Para A Língua Inglesa Utilizadas Na Etapa Quantitativa De Levantamento Junto Ao Periódico Jasis&T.

description: Este documento apresenta dois quadros. Um primeiro que relaciona os termos extraídos do texto de referência[1] e suas passagens correspondentes referente à porção qualitativa e indutiva do estudo; e um segundo, que apresenta a lista de termos em ordem alfabética e suas respectivas traduções para a língua inglesa utilizadas na etapa quantitativa de levantamento junto ao periódico JASIS&T.

[1] BARRETO, A. de A. Uma história da ciência da informação. In. TOUTAIN, L. M. B. B. <strong>Para entender a Ciência da Informação</strong> (Org.). Salvador: EDUFBA, 2007, p. 13-34. Disponível em: &lt;https://repositorio.ufba.br/ri/bitstream/ufba/145/1/Para%20entender%20a%20ciencia%20da%20informacao.pdf&gt;. Acesso em: 5 abr. 2018.
DOI: 10.5281/zenodo.1321006
title: Circulation Type Classifications For Surface Temperature And Precipitation Optimized For Italy

description: The four files are two couple of files for two circulation type classifications (pct9 and san9) optimized for Italy, in order to stratify precipitation and surface temperature respectively.

"pct9.cla" and "san.cla" are the circulation type daily series between 1979 and 2015 computed on mean sea level pressure (MSLP) and geopotential height at 500 hPa (500HGT) respectively. Meteorological fields are extracted by the NCEP-NCAR Reanalysis 2 dataset.

"pct-nc.txt" and "san9-nc.txt" are the centroid values of MSLP and 500HGT respectively, computed on 9 classes over a spatial domain of 7 X 7 grid points across Italy.

These files are created through the COST733 software package (DOI: 10.1002/joc.3920). 

The pct9 and san9 classifications were selected as the best performing for the stratifacation of precipitation and surface temperature respectively across Italian peninsula, through a sensitivity analysis detailed in a specific study (DOI: 10.1002/joc.5219). In summary several circulation type classifications were computed with different classification methods, number of types and classification variables (i.e. predictands). Then such classifications were compared through the use of proper statistical indexes in order to assess the stratification of the ground-level precipitation and the surface air temperature across Italian peninsula.

These two classifications could be evaluated also for other meteorological or environmental variables.
description: {"references": ["Vallorani R., Bartolini, G., Betti, G., Crisci A., Gozzini B., Grifoni D., Iannuccilli M., Messeri A., Messeri G., Morabito M., and Maracchi G.: Circulation type classifications for temperature and precipitation stratification in Italy, Int. J. Climatol., DOI: 10.1002/joc.5219, 2017.", "Philipp, A., Beck, C., Huth, R., and Jacobeit, J.: Development and comparison of circulation type classifications using the COST 733 dataset and software, Int. J. Climatol., 36, 2673-2691, DOI: 10.1002/joc.3920, 2014."]}
DOI: 10.5281/zenodo.1321007
title: Circulation Type Classifications For Surface Temperature And Precipitation Optimized For Italy

description: The four files are two couple of files for two circulation type classifications (pct9 and san9) optimized for Italy, in order to stratify precipitation and surface temperature respectively.

"pct9.cla" and "san.cla" are the circulation type daily series between 1979 and 2015 computed on mean sea level pressure (MSLP) and geopotential height at 500 hPa (500HGT) respectively. Meteorological fields are extracted by the NCEP-NCAR Reanalysis 2 dataset.

"pct-nc.txt" and "san9-nc.txt" are the centroid values of MSLP and 500HGT respectively, computed on 9 classes over a spatial domain of 7 X 7 grid points across Italy.

These files are created through the COST733 software package (DOI: 10.1002/joc.3920). 

The pct9 and san9 classifications were selected as the best performing for the stratifacation of precipitation and surface temperature respectively across Italian peninsula, through a sensitivity analysis detailed in a specific study (DOI: 10.1002/joc.5219). In summary several circulation type classifications were computed with different classification methods, number of types and classification variables (i.e. predictands). Then such classifications were compared through the use of proper statistical indexes in order to assess the stratification of the ground-level precipitation and the surface air temperature across Italian peninsula.

These two classifications could be evaluated also for other meteorological or environmental variables.
description: {"references": ["Vallorani R., Bartolini, G., Betti, G., Crisci A., Gozzini B., Grifoni D., Iannuccilli M., Messeri A., Messeri G., Morabito M., and Maracchi G.: Circulation type classifications for temperature and precipitation stratification in Italy, Int. J. Climatol., DOI: 10.1002/joc.5219, 2017.", "Philipp, A., Beck, C., Huth, R., and Jacobeit, J.: Development and comparison of circulation type classifications using the COST 733 dataset and software, Int. J. Climatol., 36, 2673-2691, DOI: 10.1002/joc.3920, 2014."]}
DOI: 10.5255/ukda-sn-8346-1
title: English Longitudinal Study of Ageing: Wave 8, 2016-2017, Primary Data: Special Licence Access
DOI: 10.5281/zenodo.1320164
title: Kglove Dbpedia Object Frequency Embeddings

description: This dataset contains the vectors from computing KGloVe embeddings from a object frequency weighted DBpedia 2016-04 graph.

For each entity in the graph, the text file in the zip archive contains a line with the entity name and the embedded vector.

The parameter settings for the embedding are as specified in the paper:

Michael Cochez, Petar Ristoski, Simone Paolo Ponzetto, and Heiko Paulheim. 2017. Global RDF Vector Space Embeddings. In The Semantic Web – ISWC 2017: 16th International Semantic Web Conference, Vienna, Austria, October 21–25, 2017, Proceedings, Part I.
DOI: 10.5281/zenodo.1320165
title: Kglove Dbpedia Object Frequency Embeddings

description: This dataset contains the vectors from computing KGloVe embeddings from a object frequency weighted DBpedia 2016-04 graph.

For each entity in the graph, the text file in the zip archive contains a line with the entity name and the embedded vector.

The parameter settings for the embedding are as specified in the paper:

Michael Cochez, Petar Ristoski, Simone Paolo Ponzetto, and Heiko Paulheim. 2017. Global RDF Vector Space Embeddings. In The Semantic Web – ISWC 2017: 16th International Semantic Web Conference, Vienna, Austria, October 21–25, 2017, Proceedings, Part I.
DOI: 10.5281/zenodo.1320167
title: Kglove Dbpedia Page Rank Frequency Embeddings

description: This dataset contains the vectors from computing KGloVe embeddings from a Page Rank frequency weighted DBpedia 2016-04 graph.

For each entity in the graph, the text file in the zip archive contains a line with the entity name and the embedded vector.

The parameter settings for the embedding are as specified in the paper:

Michael Cochez, Petar Ristoski, Simone Paolo Ponzetto, and Heiko Paulheim. 2017. Global RDF Vector Space Embeddings. In The Semantic Web – ISWC 2017: 16th International Semantic Web Conference, Vienna, Austria, October 21–25, 2017, Proceedings, Part I.
DOI: 10.5281/zenodo.1321257
title: Nonhuman Primate Reaching With Multichannel Sensorimotor Cortex Electrophysiology: Broadband For Indy_20161027_03

description: This dataset supplements https://doi.org/10.5281/zenodo.583331 .<br>
<br>
<strong>General description.</strong> These data consist of extracellular neural recordings ("broadband") from primate subject "Indy", session identifier "indy_20161027_03".

<strong>Filtering. </strong>The data are sampled at 24414.0625 Hz and are unfiltered, except for an anti-aliasing filter built-in to the recording amplifier: a 4th order low-pass with a roll-off of 24 dB per octave at 7.5 kHz, operating at the sampling rate.

<strong>File format.</strong> The data are contained in an HDF5 formatted file, organized according to the Neurodata Without Borders (NWB) version 1.0.6 specification.

<strong>Datasets. </strong>A few of the relevant dataset paths are listed here for convenience. In the below, <em>n</em> refers to the number of recording channels and <em>k</em> refers to the number of samples.


	"/acquisition/timeseries/broadband/data" - k x n
	
		The broadband neural recordings.
	
	
	"/acquisition/timeseries/broadband/data/conversion" (scalar attribute)
	
		When multiplied by each sample converts the data into units of volts.
	
	
	"/acquisition/timeseries/broadband/timestamps" - k x 1
	
		Timestamps for each sample, seconds.
	
	
	"/general/extracellular_ephys/electrode_map" - n x 3
	
		The relative coordinates of each electrode contact (x, y, z), meters.
	
	


Please refer to the master dataset for further information.
description: This research was supported by the Congressionally Directed Medical Research Program (W81XWH-14-1-0510). JEO was supported by fellowship #2978 from the Paralyzed Veterans of America. JGM was supported by a fellowship from the Swartz Foundation.
DOI: 10.5281/zenodo.1311717
title: 360D

description: <strong>A dataset of omnidirectional (360 - spherical panoramas)  images with their corresponding ground truth depths.</strong>


The 360 dataset provides 360 color images of indoor scenes along with their corresponding ground truth depth annotations. This dataset is composed from renders of other publicly available textured 3D datasets of indoor scenes. Specifically, it contains renders from two Computer Generated (CG) datasets, SunCG, SceneNet, and two realistic ones, acquired by scanning indoor building, Stanford2D3D, and Matterport3D. The 360 renders are produced by utilizing a path-tracing renderer and placing a spherical camera and a uniform light source at the same position in the scene. 


More information can be found  @ http://vcl.iti.gr/360-dataset/
description: Recent work on depth estimation up to now has only focused on projective images ignoring 360 content which is now increasingly and more easily produced. However, we show that monocular depth estimation models trained on traditional images produce sub-optimal results on omnidirectional images, showcasing the need for training directly on 360 datasets, which however, are hard to acquire. In this work, we circumvent the challenges associated to acquiring high quality 360 datasets with ground truth depth annotations, by re-using recently released large scale 3D datasets and re-purposing them to 360 via rendering. This dataset, which is considerably larger than similar projective datasets, is publicly offered to the community to enable future research in this direction. We use this dataset to learn in an end-to-end fashion the task of depth estimation from 360 images. We show promising results in our synthesized data as well as in unseen realistic images.
DOI: 10.5281/zenodo.1311718
title: 360D

description: <strong>A dataset of omnidirectional (360 - spherical panoramas)  images with their corresponding ground truth depths.</strong>


The 360 dataset provides 360 color images of indoor scenes along with their corresponding ground truth depth annotations. This dataset is composed from renders of other publicly available textured 3D datasets of indoor scenes. Specifically, it contains renders from two Computer Generated (CG) datasets, SunCG, SceneNet, and two realistic ones, acquired by scanning indoor building, Stanford2D3D, and Matterport3D. The 360 renders are produced by utilizing a path-tracing renderer and placing a spherical camera and a uniform light source at the same position in the scene. 


More information can be found  @ http://vcl.iti.gr/360-dataset/
description: Recent work on depth estimation up to now has only focused on projective images ignoring 360 content which is now increasingly and more easily produced. However, we show that monocular depth estimation models trained on traditional images produce sub-optimal results on omnidirectional images, showcasing the need for training directly on 360 datasets, which however, are hard to acquire. In this work, we circumvent the challenges associated to acquiring high quality 360 datasets with ground truth depth annotations, by re-using recently released large scale 3D datasets and re-purposing them to 360 via rendering. This dataset, which is considerably larger than similar projective datasets, is publicly offered to the community to enable future research in this direction. We use this dataset to learn in an end-to-end fashion the task
of depth estimation from 360 images. We show promising results in our synthesized data as well as in unseen realistic images.
DOI: 10.5281/zenodo.1320166
title: Kglove Dbpedia Page Rank Frequency Embeddings

description: This dataset contains the vectors from computing KGloVe embeddings from a Page Rank frequency weighted DBpedia 2016-04 graph.

For each entity in the graph, the text file in the zip archive contains a line with the entity name and the embedded vector.

The parameter settings for the embedding are as specified in the paper:

Michael Cochez, Petar Ristoski, Simone Paolo Ponzetto, and Heiko Paulheim. 2017. Global RDF Vector Space Embeddings. In The Semantic Web – ISWC 2017: 16th International Semantic Web Conference, Vienna, Austria, October 21–25, 2017, Proceedings, Part I.
DOI: 10.6092/unibo/amsacta/5975
title: CATCH-EyoU Work Package 2 Dataset 2.1a - Full Consortium Collection of Literature: Derived Dataset

description: The dataset contains a textual corpus of references in academic literature concerning Europe, youth engagement and active citizenship. The references were searched, catalogued and summarized by CATCH-EyoU researchers in the fields of Cultural Studies, Education, History, Media and Communication, Philosophy, Political Science, Psychology and Sociology. The analyzed literature consists of 779 selected texts. The dataset represents an integration of the CATCH-EyoU Work Package 2 Dataset 2.1a: Full Consortium Collection of Literature Matrix available at https://doi.org/10.5281/zenodo.1313202. It relies on the following information: specific identifying information about the text itself (title/author/year/publisher); and abstract or summarizing information either taken directly from the text or summarized by the researcher. With respect to the CATCH-EyoU Work Package 2 Dataset 2.1a: Full Consortium Collection of Literature Matrix, the current dataset adds further information relative to each record, namely: identification number for each record; leading disciplinary field according to which the text was searched by the researchers. These integrations were used in specific lexicometric content analysis and the dataset allows its replication or further textual analyses.
DOI: 10.5281/zenodo.1320007
title: Rdf2Vec Dbpedia Inverse Predicate Frequency Embeddings

description: This dataset contains the vectors from computing RDF2vec embeddings from a inverse predicate frequency weighted DBpedia 2016-04 graph.

For each entity in the graph, the text file in the zip archive contains a line with the entity name and the embedded vector.

The parameter settings for the embedding are as specified in the paper:

Michael Cochez, Petar Ristoski, Simone Paolo Ponzetto, and Heiko Paulheim. 2017. Biased graph walks for RDF graph embeddings. In Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics (WIMS '17). ACM, New York, NY, USA, Article 21, 12 pages. DOI: https://doi.org/10.1145/3102254.3102279
DOI: 10.5281/zenodo.1320006
title: Rdf2Vec Dbpedia Inverse Predicate Frequency Embeddings

description: This dataset contains the vectors from computing RDF2vec embeddings from a inverse predicate frequency weighted DBpedia 2016-04 graph.

For each entity in the graph, the text file in the zip archive contains a line with the entity name and the embedded vector.

The parameter settings for the embedding are as specified in the paper:

Michael Cochez, Petar Ristoski, Simone Paolo Ponzetto, and Heiko Paulheim. 2017. Biased graph walks for RDF graph embeddings. In Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics (WIMS '17). ACM, New York, NY, USA, Article 21, 12 pages. DOI: https://doi.org/10.1145/3102254.3102279
DOI: 10.5281/zenodo.1320014
title: Rdf2Vec Dbpedia Object Frequency Embeddings

description: This dataset contains the vectors from computing RDF2vec embeddings from a object frequency weighted DBpedia 2016-04 graph.

For each entity in the graph, the text file in the zip archive contains a line with the entity name and the embedded vector.

The parameter settings for the embedding are as specified in the paper:

Michael Cochez, Petar Ristoski, Simone Paolo Ponzetto, and Heiko Paulheim. 2017. Biased graph walks for RDF graph embeddings. In Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics (WIMS '17). ACM, New York, NY, USA, Article 21, 12 pages. DOI: https://doi.org/10.1145/3102254.3102279
DOI: 10.5281/zenodo.1320015
title: Rdf2Vec Dbpedia Object Frequency Embeddings

description: This dataset contains the vectors from computing RDF2vec embeddings from a object frequency weighted DBpedia 2016-04 graph.

For each entity in the graph, the text file in the zip archive contains a line with the entity name and the embedded vector.

The parameter settings for the embedding are as specified in the paper:

Michael Cochez, Petar Ristoski, Simone Paolo Ponzetto, and Heiko Paulheim. 2017. Biased graph walks for RDF graph embeddings. In Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics (WIMS '17). ACM, New York, NY, USA, Article 21, 12 pages. DOI: https://doi.org/10.1145/3102254.3102279
DOI: 10.5525/gla.researchdata.616
title: Resolution-enhanced full-field imaging by centroid estimation of biphotons

description: The acquired frames from the EMCCD camera of the slanted-edge target and of the real-world objects are contained in their respective folders. Each dataset comprises of two subfolders: one for spatially correlated biphotons illumination ('Q') and one for spatially uncorrelated illumination ('C'). In order to save space, the files are saved in a custom file format ('.nia' extension). Each file contains 100 binary frames and can be opened using LabVIEW (2016 onward), using the provided sample programme.
DOI: 10.7910/dvn/lq2zzx/oqiq2k
title: READ ME Run data stored here.pdf
DOI: 10.7910/dvn/lq2zzx/pzivhx
title: strain data, lab book pages.zip
DOI: 10.5255/ukda-sn-851653
title: School, physical activity and well-being, 2012-2014
DOI: 10.5281/zenodo.1320462
title: Dataset from research: Origin, characteristics, predominance and conceptual networks of eponyms in bibliometric literature

description: Dataset in a xlsx file used by Juan-Carlos Valderrama-Zurián & collaborators in the research “Origin, characteristics, predominance and conceptual networks of eponyms in bibliometric literature”.
DOI: 10.5281/zenodo.1320463
title: Dataset from research: Eponyms in bibliometric literature: origin, characteristics, predominance, conceptual networks and arguments for and against its use

description: Dataset in a xlsx file used by Juan-Carlos Valderrama-Zurián & collaborators in the research “Eponyms in bibliometric literature: origin, characteristics, predominance, conceptual networks and arguments for and against its use”.