cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.14284/569
title: AlgaeTraits: a trait database for (European) seaweeds

description: The macroalgae traits project started in 2014 as one of the pilot projects for collecting traits under EMODnet Biology. During this pilot project, Sofie Vranken (UGent) started compiling several traits for European marine algal genera in a database. This was in collaboration with Olivier De Clerck (UGent). In 2017, Sofie and Olivier reaeched out to Marine Robuchon and Line Le Gall of MNHN in Paris, since they had the idea to develop a similar traits database on species level, as the traits might slightly differ between the species in the same genus. The spreadsheets at the genus level and species level were compared and inconsistencies were fixed. The trait information for European macroalgae was uploaded to Aphia/WoRMS in spring 2020.
description: The dataset contains the following traits for European Macroalgae Biogeography : Distribution Ecology : Blooming Ecology: Environment Ecology : Habitat Ecology : Substrate Ecology: Thallus seasonality Ecology : Tolerance to pollutants Ecology : Zonation Morphofunctional growth form : Calcification Morphofunctional growth form : Thallus life span Morphofunctional growth form : Thallus shape Morphofunctional growth form : Thallus vertical space used Reproductive biology: Arrangement gametophytes Reproductive biology : Asexual reproduction Reproductive biology : Dispersion mode Reproductive biology : Fertility period Reproductive biology: Form gametes Reproductive biology : Generation time Reproductive biology: Life cycle Reproductive biology : Life phase resemblance Reproductive biology : Spawning method
DOI: 10.5517/ccdc.csd.cc2b84nf
title: CCDC 2152784: Experimental Crystal Structure Determination

description: Related Article: Divyesh S. Shelar, Gauri S. Malankar, M. Manikandan, Malay Patra, Ray J. Butcher, Sudesh T. Manjare|2022|New J.Chem.|46|17610|doi:10.1039/D2NJ02956A
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: 10.5281/zenodo.7118558
title: MicrolibDataset

description: Dataset associated with microlib project, including 87 microstructures to which SliceGAN was applied to generate 3D volumes.
DOI: 10.5281/zenodo.7118727
title: Students' perceptions on different sources of self-feedback

description: Feedback is crucial for improving student learning. In this regard, overcoming the transmissive conception of feedback, in favour of its dialogic function, introduces new reflections concerning the internal generative feedback process. In this regard, Nicol (2020; 2021) outlines the concept of self-feedback, i.e. the continuous comparative process that students produce from various external information and sources triggering internal feedback. Our research aims to explore students' perceptions concerning the activation of internal/self-feedback, investigating which sources are most effective from their point of view and researching the relationships between different individual characteristics. The results show that students' individual differences and contextual cultural factors might play a crucial role in creating ideal environments to enable the generation of self-feedback. Finally, students consider the teacher to be most effective in activating self-feedback, and many have never experienced self-feedback or automated feedback situations. This record contains the open dataset adopted in the study, jointly with the R script used with the data.
DOI: 10.34820/fk2/10upki/worgpx
title: tabelmap1coursestudent.sql

description: student-course map
DOI: 10.34820/fk2/10upki/3yw1cj
title: tabelmap1courselecturer.sql

description: lecturer-course map
DOI: 10.34820/fk2/10upki
title: Dataset for university course timetabling model in joint course program

description: This dataset consists of two data: (1) lecturer-course map and (2) student-course map. Number of courses is 10. Number of lecturers is 50. Number of students is 200. Number of timeslots is 24. This data is simulation generated data.
DOI: 10.6084/m9.figshare.21220796
title: Chloranthus genome annotation files

description: The annotation files (gff, CDS, and proteins) .
DOI: 10.6084/m9.figshare.21220796.v1
title: Chloranthus genome annotation files

description: The annotation files (gff, CDS, and proteins) .
DOI: 10.5281/zenodo.7115599
title: Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities

description: Data for the benchmarks problems of the paper "Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities"
DOI: 10.11583/dtu.20237436.v2
title: Total Basin Run Off (ESA POLAR+ 4D Greenland Experimental Dataset)

description: The total monthly runoff (2014-2021), both surface and basal, of five drainage basins in Greenland; NEGIS, Northern Lakes, Southern Lakes, Store, and Watson. The run off is estimated by summing the Surface Melt, Firn Retention, Supraglacial Change and Subglacial Runoff into monthly basin scale estimates.<br> 1. Surface water was computed from the chosen RCM on a monthly basis by summing the surface melt and the liquid precipitation (rain fall).<br> 2. Firn Retention is computed by subtracting the RCM runoff from the RCM surface melt in the snow/firn-covered part of the drainage basins<br> 3. Supraglacial change volume estimates were determined via the following methodology by Lancaster University.<br> Supraglacial lake extent were delineated using RT algorithm to classify water within S2 images. Lake depths were calculated using a radiative transfer model (section 2.2.6.1 ATBD). Lake depth was determined using Sentinel 2 red band imagery (Band 4). Total lake volume was calculated by multiplying lake depths by lake area for each individual lake polygon and summing over the basin area.<br> Volume uncertainty was determined via comparison with ICESat-2 transects. The uncertainty is represented by the maximum percentage difference between lake depths integrated over ICESat-2 transects and the corresponding S2 derived lake depth transect. For the red band, it was found that lake volumes were being underestimated by up to 33.5%.<br> Some of the meltwater in the supraglacial lakes will not leave the ice sheet at the end of the melt season but remain frozen over the winter. It is very difficult to estimate how much. In this experimental dataset we assume that it is 25% of the observed September water volume that is frozen and stored during winter.<br> 4. Subglacial meltwater flux maps were computed Greenland-wide, and integrated over the drainage basins of interest to produce monthly estimates of basal runoff.<br> Please read the README_TotalRunOff.txt
DOI: 10.11583/dtu.20237436.v1
title: Total Basin Run Off (ESA POLAR+ 4D Greenland Experimental Dataset)

description: The total monthly runoff (2017-2021), both surface and basal, of five drainage basins in Greenland; NEGIS, Northern Lakes, Southern Lakes, Store, and Watson. The run off is estimated by summing the Surface Melt, Firn Retention, Supraglacial Change and Subglacial Runoff into monthly basin scale estimates.<br> 1. Surface water was computed from the chosen RCM on a monthly basis by summing the surface melt and the liquid precipitation (rain fall).<br> 2. Firn Retention is computed by subtracting the RCM runoff from the RCM surface melt in the snow/firn-covered part of the drainage basins<br> 3. Supraglacial change volume estimates were determined via the following methodology by Lancaster University.<br> Supraglacial lake extent were delineated using RT algorithm to classify water within S2 images. Lake depths were calculated using a radiative transfer model (section 2.2.6.1 ATBD). Lake depth was determined using Sentinel 2 red band imagery (Band 4). Total lake volume was calculated by multiplying lake depths by lake area for each individual lake polygon and summing over the basin area.<br> Volume uncertainty was determined via comparison with ICESat-2 transects. The uncertainty is represented by the maximum percentage difference between lake depths integrated over ICESat-2 transects and the corresponding S2 derived lake depth transect. For the red band, it was found that lake volumes were being underestimated by up to 33.5%.<br> Some of the meltwater in the supraglacial lakes will not leave the ice sheet at the end of the melt season but remain frozen over the winter. It is very difficult to estimate how much. In this experimental dataset we assume that it is 25% of the observed September water volume that is frozen and stored during winter.<br> 4. Subglacial meltwater flux maps were computed Greenland-wide, and integrated over the drainage basins of interest to produce monthly estimates of basal runoff.<br> Please read the README_TotalRunOff.txt
DOI: 10.5281/zenodo.7116834
title: Wikidata ALPINE-based WINE & SPINE embedding

description: 100-dimensional Wikidata graph embedding obtained using degree-based WINE and SPINE.
DOI: 10.5281/zenodo.7116835
title: Wikidata ALPINE-based WINE & SPINE embedding

description: 100-dimensional Wikidata graph embedding obtained using degree-based WINE and SPINE.
DOI: 10.5281/zenodo.7117686
title: Wikidata ALPINE-based WINE & SPINE embedding

description: 100-dimensional Wikidata graph embedding obtained using degree-based WINE and SPINE.
DOI: 10.34943/7c3cd2f6-552c-4d83-bbfc-564f57c2279e
title: Strait of Georgia East Junction Box Deployed 2022-09-27

description: The S30005 was deployed on 2022-09-27 at Strait of Georgia East. Strait of Georgia East refers to an eastern area of the Strait of Georgia. This device is a Junction Box. Junction Boxes supply power and communications to deployed instruments. Junction boxes have a number of serial and ethernet ports, including 400V ethernet ports that enable connections to other junction boxes and high-voltage instruments. Junction boxes can convert high voltages to lower voltages (15V, 24V or 48V) required by many instruments. It was deployed on a fixed platform. Data from this deployment were archived and made available through Ocean Networks Canada's Oceans 3.0 digital infrastructure, with quality assurance and derived data products following established practices.
DOI: 10.14469/hpc/11235
title: Can Ganymede’s magnetopause help us probe its subsurface ocean? (JGR: Space Physics)

description: Data published in Figures 2-6 in a manuscript submitted to Journal of Geophysical Research: Space Physics in September 2022, concerning magnetopause-produced induction in Ganymede's subsurface ocean.
DOI: 10.6084/m9.figshare.14222474
title: Phloem feeding herbivores affect floral development and reproduction in the Mediterranean honey-suckle (Lonicera etrusca Santi)

description: Data set assessing the effects of phloem-feeding herbivores on the development of floral structures, pollen morphology, pollen quantity produced per anther, nectar production, floral morphology and pollination.
DOI: 10.6084/m9.figshare.14222474.v1
title: Phloem feeding herbivores affect floral development and reproduction in the Mediterranean honey-suckle (Lonicera etrusca Santi)

description: Data set assessing the effects of phloem-feeding herbivores on the development of floral structures, pollen morphology, pollen quantity produced per anther, nectar production, floral morphology and pollination.
DOI: 10.5281/zenodo.5787492
title: Library of multivariate time series

description: A database of many different types of multivariate time series, each with between 5-25 processes and between 100-2500 observations.
DOI: 10.5281/zenodo.7113159
title: Library of multivariate time series

description: A database of many different types of multivariate time series, each with between 5-25 processes and between 100-2500 observations. The database contains a serialized Python dictionary of 1053 datasets, where the key for the dictionary is the dataset name, and each value is another dictionary of:data (an MxT numpy array of processes-by-observations) and labels (a list of descriptive labels for the dataset).
DOI: 10.5281/zenodo.7118947
title: Library of multivariate time series

description: A database of many different types of multivariate time series, each with between 5-25 processes and between 100-2500 observations. The database contains a serialized Python dictionary of 1053 datasets, where the key for the dictionary is the dataset name, and each value is another dictionary of: "data", an MxT numpy array of processes-by-observations; and "labels", a list of descriptive labels for the dataset.
description: Version 1.1 fixed an issue where some of the datasets were transposed.
DOI: 10.5281/zenodo.5787491
title: Library of multivariate time series

description: A database of many different types of multivariate time series, each with between 5-25 processes and between 100-2500 observations. The database contains a serialized Python dictionary of 1053 datasets, where the key for the dictionary is the dataset name, and each value is another dictionary of: "data", an MxT numpy array of processes-by-observations; and "labels", a list of descriptive labels for the dataset.
description: Version 1.1 fixed an issue where some of the datasets were transposed.
DOI: 10.5281/zenodo.7113213
title: Library of multivariate time series

description: A database of many different types of multivariate time series, each with between 5-25 processes and between 100-2500 observations. The database contains a serialized Python dictionary of 1053 datasets, where the key for the dictionary is the dataset name, and each value is another dictionary of:data (an MxT numpy array of processes-by-observations) and labels (a list of descriptive labels for the dataset).
description: Version 1.0 has updated labels and removed low-dimensional time series
DOI: 10.34808/mhx2-sq43
title: SEM results of melamine sponges impregnated by DES

description: SEM results of melamine sponges impregnated by DES (3 um magnification). The set includes raw data from SEM analysis of pure melamine sponge and melamine sponges impregnated by:- Eucalyptol:Menthol (1:1)- Eucalyptol:Menthol (1:2)- Eucalyptol:Menthol (1:3)- Eucalyptol:Menthol (1:4)- Eucalyptol:Menthol (1:5)- Thymol:Menthol (1:1)
DOI: 10.6084/m9.figshare.21220949
title: Dataset Cumulative CO2 Emissions of International Transport

description: This dataset considers the year 1783, when the first steamship was built, as the first year of the international transport CO2 emissions. The global cumulative CO2 emissions including international transport are converted to the 1875 baseline, similar to the Global Warming baseline (1850-1900).
DOI: 10.5285/e85a9312-8531-4261-a2f6-1c58f40cfc71
title: Antarctic krill (Euphausia superba) biomass density estimates derived from acoustic backscatter data collected in the Western Core Box survey, South Georgia, South Atlantic: 1996 - 2019

description: This dataset contains processed acoustic backscatter data that reflect integrated density estimates for Antarctic krill (Euphausia superba). The acoustic backscatter data are from the Western Core Box (WCB), comprising 8 acoustic transects that span the shelf-break at South Georgia. The data were obtained from a time series of 22 cruises carried out between 1996/97 and 2019/20. Data were collected using either a Simrad EK500 or EK60 echo sounder by biological oceanographers working at the British Antarctic Survey under the Ecosystems scientific research programme and predecessor Discovery 2010 and Dynamo research programmes. Funding was provided by the NERC/BAS Antarctic, Logistic, Infrastructure (ALI) Science and predecessor Long Term Monitoring Science research programmes.
description: Acoustic surveys targeting Antarctic krill (Euphausia superba) within the Western Core Box (WCB; an area covering 132 km by 80 km) to the northwest of South Georgia have been described previously (Trathan et al., 2003; Reid et al., 2010; Fielding et al., 2014). Here we extend the time series from 1997 to 2020, using only acoustic surveys that took place within a fixed time window (1 December to 16 February), given that known intra-annual variation in the timing of peak summer biomass can affect estimates of krill mean density at South Georgia (Saunders et al., 2007; Reid et al., 2010). The WCB includes on-shelf and off-shelf areas sometimes used by predators foraging from Bird Island. During each survey, acoustic data were collected along eight transects, although in some years not all transects could be completed. Also, the location of some transects changed after the first few years. Acoustic data were depth integrated to 250 m (or to 2 m above the sea floor if shallower) with a horizontal average integration distance of 500 m. Estimate of krill density in each acoustic sampling interval were derived using the 3 frequency (38, 120 and 200 kHz) identification model and the ASAM TS model (Fielding et al., 2011; 2014; 2016).
DOI: 10.5517/ccdc.csd.cc2cl909
title: CCDC 2192320: Experimental Crystal Structure Determination

description: Related Article: Xinyue Wang, Bingbing Zhang, Daqing Yang, Ying Wang|2022|Dalton Trans.|51|14059|doi:10.1039/D2DT02573F
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: 10.5517/ccdc.csd.cc2cyz0b
title: CCDC 2203542: Experimental Crystal Structure Determination

description: Related Article: Bernd Koop, Roland Fröhlich, Constantin G. Daniliuc, Hans J. Schäfer|2022|CSD Communication|||
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: 10.5517/ccdc.csd.cc2cz0v7
title: CCDC 2203599: Experimental Crystal Structure Determination

description: Related Article: Daniel Witthaut, Roland Fröhlich, Constantin G. Daniliuc, Hans J. Schäfer|2022|CSD Communication|||
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: 10.5517/ccdc.csd.cc2cz1cs
title: CCDC 2203615: Experimental Crystal Structure Determination

description: Related Article: Phu Qui Nguyen, Roland Fröhlich, Constantin G. Daniliuc, Hans J. Schäfer|2022|CSD Communication|||
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: 10.5517/ccdc.csd.cc2cz2ct
title: CCDC 2203646: Experimental Crystal Structure Determination

description: Related Article: Phu Qui Nguyen, Roland Fröhlich, Constantin G. Daniliuc, Hans J. Schäfer|2022|CSD Communication|||
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: 10.5517/ccdc.csd.cc2cz2l1
title: CCDC 2203653: Experimental Crystal Structure Determination

description: Related Article: Bernd Koop, Roland Fröhlich, Constantin G. Daniliuc, Hans J. Schäfer|2022|CSD Communication|||
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: 10.6084/m9.figshare.21213146
title: Swipe_ATMS_CMORPH_2016_2019.csv

description: Include the H8 data, MW data and CMORPH data of CIs between 2016-2019
DOI: 10.6084/m9.figshare.21213146.v1
title: Swipe_ATMS_CMORPH_2016_2019.csv

description: Include the H8 data, MW data and CMORPH data of CIs between 2016-2019
DOI: 10.57745/u44b7l/3raxen
title: rpg_complete_2020_d91.zip

description: :unav
DOI: 10.57745/u44b7l/avtnf3
title: rpg_complete_2020_d94.zip

description: :unav
DOI: 10.57745/u44b7l/hkq4on
title: rpg_complete_2020_d95.zip

description: :unav
DOI: 10.57745/u44b7l/rmnvxe
title: rpg_complete_2020_d78.zip

description: :unav
DOI: 10.57745/u44b7l/sllwke
title: rpg_complete_2020_d77.zip

description: :unav
DOI: 10.57745/gn4f3m
title: rpg_complete_2020_d93.zip

description: :unav
DOI: 10.57745/1oo0r7/0awrft
title: rpg_complete_2020_d34.zip

description: :unav
DOI: 10.57745/1oo0r7/bhwx6s
title: rpg_complete_2020_d30.zip

description: :unav
DOI: 10.57745/1oo0r7/dhb91t
title: rpg_complete_2020_d48.zip

description: :unav
DOI: 10.57745/1oo0r7/z4i8rp
title: rpg_complete_2020_d66.zip

description: :unav
DOI: 10.57745/iylsck
title: rpg_complete_2020_d11.zip

description: :unav
DOI: 10.26180/21221012
title: Data from "Temporal repeatability of behaviour in a lizard: implications for behavioural syndrome studies"

description: Data amd code from "Temporal repeatability of behaviour in a lizard: implications for behavioural syndrome studies"
DOI: 10.26180/21221012.v1
title: Data from "Temporal repeatability of behaviour in a lizard: implications for behavioural syndrome studies"

description: Data amd code from "Temporal repeatability of behaviour in a lizard: implications for behavioural syndrome studies"
DOI: 10.5281/zenodo.7081522
title: MUHAI Benchmark : Task 1 (Short story generation with Knowledge Graphs)

description: <strong>Meaning and Understanding in Human-Centric AI (MUHAI) Benchmark<br> Task 1 (Short story generation with Knowledge Graphs and Language Models)</strong> The dataset can be used to test understandability of text generated through the combination of knowledge graphs and language models without using knowledge graph embeddings.<br> <br> The task here is to generate 5-sentence stories from a set of <em>subject-predicate-object</em> triples that are extracted from a knowledge graph. Two steps need to be performed: 1. Language model fine-tuning (SVO triple extraction + model fine-tuning)<br> 2. Story generation (knowledge enrichment + text generation) <br> <br> The submission includes the following data: Original ROC stories corpus (100 stories) ROC stories encoded with relevant triples (extracted through SpaCy, 2 versions, with and without coreference resolution) Stories generated by the pre-trained model (GPT2-simple) Stories generated by the fine-tuned model (DICE + ConceptNet + DBpedia ) Stories generated by the fine-tuned model (DICE + ConceptNet + DBpedia + WordNet ) Stories generated by the GPT-2-keyword-generation (an open-source software that uses GPT-2 to generate text pertaining to the specified keywords) Model results Evaluation metrics description User-evaluation questionnaire Code : https://github.com/kmitd/muhai-dice_story
description: {"references": ["Yang, X., & Tiddi, I. (2020, January). Creative storytelling with language models and knowledge graphs. In CIKM (Workshops).", "Blin, I. (2022). Building Narrative Structures from Knowledge Graphs. In European Semantic Web Conference (pp. 234-251). Springer, Cham."]}