cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4601264
title: VedaWeb 1.0 - TEI files

description: VedaWeb - TEI Files These TEI files contain different versions of the Rigveda in Sanskrit, annotated and translated. Each version has a different CC licence. Please see the &lt;teiHeader&gt; in vedaweb_corpus.tei for more details
DOI: 10.5281/zenodo.4601263
title: VedaWeb 1.0 - TEI files

description: VedaWeb - TEI Files These TEI files contain different versions of the Rigveda in Sanskrit, annotated and translated. Each version has a different CC licence. Please see the &lt;teiHeader&gt; in vedaweb_corpus.tei for more details
DOI: 10.15468/bpvhgf
title: Two new species of Neotrichoporoides Girault (Hymenoptera, Eulophidae) from China and a key to Chinese species

description: This dataset contains the digitized treatments in Plazi based on the original journal article Li, Wen-Jian, Li, Cheng-De (2021): Two new species of Neotrichoporoides Girault (Hymenoptera, Eulophidae) from China and a key to Chinese species. ZooKeys 1023: 61-79, DOI: http://dx.doi.org/10.3897/zookeys.1023.61580, URL: http://dx.doi.org/10.3897/zookeys.1023.61580
DOI: 10.15468/xs3gn8
title: A new species of Leptopelis (Anura, Arthroleptidae) from the south-eastern slope of the Ethiopian Highlands, with notes on the Leptopelis gramineus species complex and the revalidation of a previously synonymised species

description: This dataset contains the digitized treatments in Plazi based on the original journal article Tiutenko, Arthur, Zinenko, Oleksandr (2021): A new species of Leptopelis (Anura, Arthroleptidae) from the south-eastern slope of the Ethiopian Highlands, with notes on the Leptopelis gramineus species complex and the revalidation of a previously synonymised species. ZooKeys 1023: 119-150, DOI: http://dx.doi.org/10.3897/zookeys.1023.53404, URL: http://dx.doi.org/10.3897/zookeys.1023.53404
DOI: 10.15468/7ngdmf
title: Two new species of the genus Deltomerodes Deuve, 1992 (Coleoptera, Carabidae, Patrobini) from Xizang, China

description: This dataset contains the digitized treatments in Plazi based on the original journal article Yan, Weifeng, Shi, Hongliang, Liang, Hongbin, Shi, Juan (2021): Two new species of the genus Deltomerodes Deuve, 1992 (Coleoptera, Carabidae, Patrobini) from Xizang, China. ZooKeys 1023: 151-169, DOI: http://dx.doi.org/10.3897/zookeys.1023.61553, URL: http://dx.doi.org/10.3897/zookeys.1023.61553
DOI: 10.15468/gea6jg
title: A review of Copelatus diving beetles from the Solomon Islands, reporting the discovery of six new species (Coleoptera, Dytiscidae, Copelatinae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Hajek, Jiri, Shaverdo, Helena, Hendrich, Lars, Balke, Michael (2021): A review of Copelatus diving beetles from the Solomon Islands, reporting the discovery of six new species (Coleoptera, Dytiscidae, Copelatinae). ZooKeys 1023: 81-118, DOI: http://dx.doi.org/10.3897/zookeys.1023.61478, URL: http://dx.doi.org/10.3897/zookeys.1023.61478
DOI: 10.15468/uafm2s
title: DNA barcoding and morphology reveal a new cryptic species of Nagiella (Lepidoptera, Crambidae, Spilomelinae) from Japan

description: This dataset contains the digitized treatments in Plazi based on the original journal article Matsui, Yuki, Naka, Hideshi, Jinbo, Utsugi (2021): DNA barcoding and morphology reveal a new cryptic species of Nagiella (Lepidoptera, Crambidae, Spilomelinae) from Japan. ZooKeys 1023: 171-192, DOI: http://dx.doi.org/10.3897/zookeys.1023.60934, URL: http://dx.doi.org/10.3897/zookeys.1023.60934
DOI: 10.5517/ccdc.csd.cc21vhw9
title: CCDC 1902311: Experimental Crystal Structure Determination

description: Related Article: Arvind Kumar Gupta, Andreas Orthaber|2019|Dalton Trans.|48|16518|doi:10.1039/C9DT03697K
DOI: 10.5517/ccdc.csd.cc25ktp8
title: CCDC 2013130: Experimental Crystal Structure Determination

description: Related Article: Chong Zhao, Fupin Liu, Lai Feng, Mingzhe Nie, Yuxi Lu, Jie Zhang, Chunru Wang, Taishan Wang|2021|Nanoscale|13|4880|doi:10.1039/D0NR08931A
DOI: 10.5281/zenodo.4539697
title: Crowd4SDG-VisualCit COVID-19 behavioral indicators

description: This dataset contains the VisualCit data for social distance and face masks derived from social media image analysis. From Twitter crawls with COVID-10 keywords, images are filtered ewith ML classifiers in order to retrieve images of people in public places which are photos. With crowdsourcing additional information is added about COVID-19 related behavioral aspects, with the goal of deriving indicators for decision makers to assess the ongoing situation. In this analysis we focus on the percentages of people wearing masks and maintaining social distances. Reference paper: V. Negri, D. Scuratti, S. Agresti, D. Rooein, G. Scalia, J.L. Fernandez Marquez, A. Ravi Shankar, M. Carman and B. Pernici, Image-based Social Sensing: Combining AI and the Crowd to Mine Policy-Adherence Indicators from Twitter, ICSE - Track Software Engineering in Society, May 2021 https://arxiv.org/abs/2010.03021 Abstract Social Media provides a trove of information that, if aggregated and analysed appropriately can provide important statistical indicators to policy makers. In some situations these indicators are not available through other mechanisms. For example, given the ongoing COVID-19 outbreak, it is essential for governments to have access to reliable data on policy-adherence with regards to mask wearing, social distancing, and other hard-to-measure quantities. In this paper we investigate whether it is possible to obtain such data by aggregating information from images posted to social media. The paper presents VisualCit, a pipeline for image-based social sensing combining recent advances in image recognition technology with geocoding and crowdsourcing techniques. Our aim is to discover in which countries, and to what extent, people are following COVID-19 related policy directives.<br> We compared the results with the indicators produced within the CovidDataHub behavior tracker initiative. Preliminary results shows that social media images can produce reliable indicators for policy makers.
description: The metadata for the files in this dataset are described in the file crowd4SDG-VisualCit-COVID-19-metadata.docx in the dataset below.
description: {"references": ["V. Negri, D. Scuratti, S. Agresti, D. Rooein, G. Scalia, J.L. Fernandez-Marquez, A. Ravi Shankar, M. Carman and B.Pernici, Image-based Social Sensing: Combining AI and the Crowd to Mine Policy-Adherence Indicators from Twitter, ICSE - Track Software Engineering in Society, May 2021 http://hdl.handle.net/11311/1161146"]}
DOI: 10.5281/zenodo.4539696
title: Crowd4SDG-VisualCit COVID-19 behavioral indicators

description: This dataset contains the VisualCit data for social distance and face masks derived from social media image analysis. From Twitter crawls with COVID-10 keywords, images are filtered ewith ML classifiers in order to retrieve images of people in public places which are photos. With crowdsourcing additional information is added about COVID-19 related behavioral aspects, with the goal of deriving indicators for decision makers to assess the ongoing situation. In this analysis we focus on the percentages of people wearing masks and maintaining social distances. Reference paper: V. Negri, D. Scuratti, S. Agresti, D. Rooein, G. Scalia, J.L. Fernandez Marquez, A. Ravi Shankar, M. Carman and B. Pernici, Image-based Social Sensing: Combining AI and the Crowd to Mine Policy-Adherence Indicators from Twitter, ICSE - Track Software Engineering in Society, May 2021 https://arxiv.org/abs/2010.03021 Abstract Social Media provides a trove of information that, if aggregated and analysed appropriately can provide important statistical indicators to policy makers. In some situations these indicators are not available through other mechanisms. For example, given the ongoing COVID-19 outbreak, it is essential for governments to have access to reliable data on policy-adherence with regards to mask wearing, social distancing, and other hard-to-measure quantities. In this paper we investigate whether it is possible to obtain such data by aggregating information from images posted to social media. The paper presents VisualCit, a pipeline for image-based social sensing combining recent advances in image recognition technology with geocoding and crowdsourcing techniques. Our aim is to discover in which countries, and to what extent, people are following COVID-19 related policy directives.<br> We compared the results with the indicators produced within the CovidDataHub behavior tracker initiative. Preliminary results shows that social media images can produce reliable indicators for policy makers.
description: The metadata for the files in this dataset are described in the file crowd4SDG-VisualCit-COVID-19-metadata.docx in the dataset below.
description: {"references": ["V. Negri, D. Scuratti, S. Agresti, D. Rooein, G. Scalia, J.L. Fernandez-Marquez, A. Ravi Shankar, M. Carman and B.Pernici, Image-based Social Sensing: Combining AI and the Crowd to Mine Policy-Adherence Indicators from Twitter, ICSE - Track Software Engineering in Society, May 2021 http://hdl.handle.net/11311/1161146"]}
DOI: 10.5281/zenodo.4601456
title: Ooh Na Na

description: This is a gzipped three-column TSV file that has 138,749,325 prefixes, identifiers, and names for lots of biomedical entities, drawing from the OBO Foundry, ontologies in the Ontology Lookup Service, and many other nomenclature consortia that just haven't made it to the prime-time of standardized goodness. Ultimately, this dataset helps answer the question: what's my name? It's really a lot of work to get this stuff, so I tried to make it easy. It was generated with the following code in the shell: <pre>pip install pyobo obo database names</pre> More information on how and why this resource was made is available at https://cthoyt.com/2020/04/18/ooh-na-na.html.
description: The 1.2.0 version includes the addition of PubChem, ChEBML, and NPASS
DOI: 10.15468/czdx5p
title: Systematic revision of Platevindex Baker, 1938 (Gastropoda: Euthyneura: Onchidiidae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Goulding, Tricia C., Bourke, Adam J., Comendador, Joseph, Khalil, Munawar, Quang, Ngo Xuan, Tan, Shau Hwai, Tan, Siong Kiat, Dayrat, Benoît (2021): Systematic revision of Platevindex Baker, 1938 (Gastropoda: Euthyneura: Onchidiidae). European Journal of Taxonomy 737 (1): 1-133, DOI: https://doi.org/10.5852/ejt.2021.737.1259, URL: http://dx.doi.org/10.5852/ejt.2021.737.1259
DOI: 10.5281/zenodo.4596590
title: NGS Data (09.03.21) IL

description: NGS data (MACROGEN) received on 09.03.21
DOI: 10.5281/zenodo.4596589
title: NGS Data (09.03.21) IL

description: NGS data (MACROGEN) received on 09.03.21
DOI: 10.5281/zenodo.4601476
title: Data Library

description: Age and sex-standardized prevalence of ten diseases and the use of different procedures, which treat the diseases at NUTS3 level. Switzerland Age and sex-standardized prevalence of ten diseases and the use of different procedures, which treat the diseases at NUTS3 level. Italy Codebook (in progress)
description: Aleksandra Torbica & Benedetta Pongiglione collaborated for dataset COMED_WP4&5_DS_1_IT.xlsx
DOI: 10.5281/zenodo.4601475
title: Data Library

description: Age and sex-standardized prevalence of ten diseases and the use of different procedures, which treat the diseases at NUTS3 level. Switzerland Age and sex-standardized prevalence of ten diseases and the use of different procedures, which treat the diseases at NUTS3 level. Italy Codebook (in progress)
description: Aleksandra Torbica & Benedetta Pongiglione collaborated for dataset COMED_WP4&5_DS_1_IT.xlsx
DOI: 10.5281/zenodo.4601406
title: Campylobacter dataset with simulated inter and intra genus contaminations

description: This dataset serves for the detection of inter and intra genus contaminations in Campylobacter. Its design follows the concepts presented in https://doi.org/10.1186/s13059-019-1914-x: Illumina reads from complete Campylobacter genomes were simulated and artificially mixed at different concentrations and genomic distances. The mixed reads were assembled using shovill.<br> <br> This dataset contains the following files: simulated_reads.tar: The simulated reads for 248 Campylobacter samples assemblies.tar.gz: Shovill assembly of all read data genome_info_Ca.tsv: Description of the original complete Campylobacter genomes metadata_Ca.tsv: Mixing information for all provided samples Details: We downloaded all complete Campylobacter genomes from NCBI refseq. Next, we computed the MLST ST using mlst (https://github.com/tseemann/mlst) and excluded all samples without an ST, resulting in a final dataset of 218 samples. We then determined the genetic similarity between these samples by computing pairwise MLST allele distances (usinghttps://github.com/tseemann/cgmlst-dists). For each sample, we attempted to find a close, intermediate and distant matching sample following the proposed definition of https://doi.org/10.1186/s13059-019-1914-x: close (same ST, 0 AD), intermediate (2-6 AD), distant (7 AD). We selected two C. coli and six C. jejuni samples with at least one close, intermediate and distant matching sample. For each species we selected genomes with maximal overall genomic diversity and simulated reads from the selected genomes using ART_Illumina v2.5.8 (see FDA for details). Next, we combined reads from the eight samples and their respective matching samples using the script select_reads.pl (http://github.com/apightling/contamination), in order to create simulated contaminated datasets. Additionally, we created inter-genus contaminants by mixing reads of the eight Campylobacter spp. samples with reads from any of the other three genera (Listeria, Salmonella, Escherichia) of the analogous FDA dataset (https://doi.org/10.6084/m9.figshare.c.4282706.v1).
DOI: 10.5281/zenodo.4601405
title: Campylobacter dataset with simulated inter and intra genus contaminations

description: This dataset serves for the detection of inter and intra genus contaminations in Campylobacter. Its design follows the concepts presented in https://doi.org/10.1186/s13059-019-1914-x: Illumina reads from complete Campylobacter genomes were simulated and artificially mixed at different concentrations and genomic distances. The mixed reads were assembled using shovill.<br> <br> This dataset contains the following files: simulated_reads.tar: The simulated reads for 248 Campylobacter samples assemblies.tar.gz: Shovill assembly of all read data genome_info_Ca.tsv: Description of the original complete Campylobacter genomes metadata_Ca.tsv: Mixing information for all provided samples Details: We downloaded all complete Campylobacter genomes from NCBI refseq. Next, we computed the MLST ST using mlst (https://github.com/tseemann/mlst) and excluded all samples without an ST, resulting in a final dataset of 218 samples. We then determined the genetic similarity between these samples by computing pairwise MLST allele distances (usinghttps://github.com/tseemann/cgmlst-dists). For each sample, we attempted to find a close, intermediate and distant matching sample following the proposed definition of https://doi.org/10.1186/s13059-019-1914-x: close (same ST, 0 AD), intermediate (2-6 AD), distant (7 AD). We selected two C. coli and six C. jejuni samples with at least one close, intermediate and distant matching sample. For each species we selected genomes with maximal overall genomic diversity and simulated reads from the selected genomes using ART_Illumina v2.5.8 (see FDA for details). Next, we combined reads from the eight samples and their respective matching samples using the script select_reads.pl (http://github.com/apightling/contamination), in order to create simulated contaminated datasets. Additionally, we created inter-genus contaminants by mixing reads of the eight Campylobacter spp. samples with reads from any of the other three genera (Listeria, Salmonella, Escherichia) of the analogous FDA dataset (https://doi.org/10.6084/m9.figshare.c.4282706.v1).
DOI: 10.6084/m9.figshare.12180789
title: Sex difference in embryonic microglia in quail

description: Dataset associated with the Delage and Cornil Dev Neurobiol. 2020 paper titled:
DOI: 10.12686/a9
title: Mars Seismic Catalogue, InSight Mission; V4 2020-10-01

description: The NASA InSight mission installed a single seismic station on the surface of Mars in 2019. The Marsquake Service (MQS) is an official service of the InSight ground services. MQS is tasked with detecting and characterising marsquakes, and curating the catalogue. Waveform data is publicly released on a 3 month schedule. Starting on 2 January, 2020, an updated MQS catalogue is released with each new waveform dataset. This is Data Release 4.
DOI: 10.6084/m9.figshare.14207963
title: labeled_profile

description: Labeled author profiles on Google Scholar about whether they are mis-configured
DOI: 10.6084/m9.figshare.14207963.v1
title: labeled_profile

description: Labeled author profiles on Google Scholar about whether they are mis-configured
DOI: 10.6084/m9.figshare.14207984
title: CM1 Namelist

description: CM1 namelist<br>
DOI: 10.5281/zenodo.4601139
title: Differentially Private Event Logs for Process Mining: Supplementary Material

description: In this archive, we provide supplementary material for our paper entitled "Mine Me but Don’t Single Me Out: DifferentiallyPrivate Event Logs for Process Mining". We list the selected event logs and their characteristics and descriptive statistics. Also, this archive contains the anonymized event logs as the result of the experiments. The source code is available on GitHub.
DOI: 10.5281/zenodo.4601138
title: Differentially Private Event Logs for Process Mining: Supplementary Material

description: In this archive, we provide supplementary material for our paper entitled "Mine Me but Don’t Single Me Out: DifferentiallyPrivate Event Logs for Process Mining". We list the selected event logs and their characteristics and descriptive statistics. Also, this archive contains the anonymized event logs as the result of the experiments. The source code is available on GitHub.
DOI: 10.6084/m9.figshare.14208011
title: Ensemble Averaging Script

description: Ensemble Averaging Script<br>
DOI: 10.21232/i6n36jz7
title: Phenology Leaf Spectra Cedar Creek Biodiversity Experiment 2014

description: null
DOI: 10.6084/m9.figshare.14207702.v1
title: Panel Data: Measuring Fiscal and Monetary Policy Impacts on Aggregate Economic Growth (1977-2016)

description: The dataset has been originally extracted from the "World Development Indicators" database made publicly available by the World Bank (https://databank.worldbank.org). The author's actions include filtering the data and organizing the data for statistical analysis. The filtered data saved in the source can be accessed from the referenced link. The dataset includes 40 years of longitudinal data on 76 macroeconomic variables for 100 countries.<br>
DOI: 10.6084/m9.figshare.14207702
title: Panel Data: Measuring Fiscal and Monetary Policy Impacts on Aggregate Economic Growth (1977-2016)

description: The dataset has been originally extracted from the "World Development Indicators" database made publicly available by the World Bank (https://databank.worldbank.org). The author's actions include filtering the data and organizing the data for statistical analysis. The filtered data saved in the source can be accessed from the referenced link. The dataset includes 40 years of longitudinal data on 76 macroeconomic variables for 100 countries.<br>
DOI: 10.6084/m9.figshare.14207702.v2
title: Panel Data: Measuring Fiscal and Monetary Policy Impacts on Aggregate Economic Growth (1977-2016)

description: The dataset has been originally extracted from the "World Development Indicators" database made publicly available by the World Bank (https://databank.worldbank.org). The author's actions include filtering the data and organizing the data for statistical analysis. The filtered data saved in the source can be accessed from the referenced link. The dataset includes 40 years of longitudinal data on 76 macroeconomic variables for 100 countries.<br>
DOI: 10.5281/zenodo.4601503
title: Natural & Ultra-Processed Foods (NUPF) database

description: The Natural & Ultra-Processed Foods (NUPF) database includes 40 images of food stimuli photographed on a grey background. Twenty images depict a natural food item (such as an apple) or lightly processed item (such as cheese) and twenty images depict an ultra-processed item (e.g., a chocolate bar). Ratings were obtained from two sets of participants. The first group (n = 70) rated the stimuli on approachability (approach/avoid), desirability, popularity, and healthiness. The second group (n = 90) rated the same items on valence, arousal, and recognizability. Participant details can be found in Table 1 (which can be found in the NUPFdatabase.zip). Natural foods are typically considered healthier than ultra-processed foods, therefore tentative category labels regarding healthiness are included as well. The NUPF database includes the minimum, maximum, and mean ratings per food item. Also information regarding the weight of the portion, calories per portion, and calorie density (calories per 100 or 1 gram) are included. The NUPFdatabase.zip includes: - 40 High resolution images (divided into healthy and unhealthy categories) - 40 low resolution (websize) images (divided into healthy and unhealthy categories) - Mean ratings on valence, arousal, approach/avoid, desirability, popularity, perceived healthiness, and recognizability - Table 1 with details regarding the raters (i.e., participants who rated the images) - A readme file regarding info about the rating file
DOI: 10.1184/r1/13870256
title: DOM XSS Web Vulnerability Dataset

description: This dataset relates to a large scale web crawl performed over the Alexa 10K in 2019. For each website, the Javascript code is analyzed with taint tracking, a dynamic analysis technique, to determine if DOM XSS (Document Object Model Cross Site Scripting) vulnerabilities are present. <br>From taint tracking, we generate two datasets: a dataset of "unconfirmed" functions, labeled with the result of this taint analysis, and a dataset of "confirmed" functions, labeled with the result of a proof-of-concept DOM XSS exploit.<br>Both datasets were used to train a variety of machine learning models, and the resulting models are also included for reference.
DOI: 10.5281/zenodo.4338881
title: HDT Bitmap Triple Indices Experimental Results

description: <strong>Queries</strong><br> These are the queries which have been deployed in the Bitmap Triple indices experiments. The directories contain the queries as sparql text file, the appropriate time measurements and the resulting boxplots. <strong>Explanation of the Query Notation</strong> Filter Queries: qi_j i: level of difficulty j: number of applied filters Class Queries (query directory is labeled as 'categoryQueries'): qi_j i: level of difficulty j: number of incremental join operations Hybrid Queries: qi_j i: level of difficulty of the underlying Class Query and the number of incremental join operations j: number of applied filters <strong>CSV-Files Naming Convention</strong> "CP": reachable classes operation, count results are returned "Verbose": class queries, results are returned as strings "ApplyFilters": filter queries, results are returned as strings "AvailableFilters": computation of all available filters, count results are returned "Hybrid": hybrid queries, results are returned as strings