cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6342804
title: Summary of sequence variations in strains of Sars-CoV-2

description: This entry collects JSON files specifying sequence variations of different strains (aka variants) of SARS-CoV-2 based on data retrieved from outbreak.info and/or covariants.org. These JSON files are formatted to match the Feature API of aquaria.ws. File names match the linage names of VOCs and VOIs. In the case of <em>omicron</em> we have added a version (omicron_charge) that highlights charge changing residues in magenta, as well as an extra file (omicron_BA2) for the BA.2/21K sister clade and a file (omicron_BA1_BA2_diff) highlighting the differences between the lineages (coloring variations in only BA.1 red, only BA.2 blue, in both magenta). CovidVariants.pdf lists SARS-CoV-2 proteins together with links that show how to map variations onto the structures.
DOI: 10.6084/m9.figshare.21229083
title: Table S2. Biodiversity change and extinction risk in Plio-Pleistocene Mediterranean bivalves: the families Veneridae, Pectinidae and Lucinidae

description: Time-range distribution of the studied species. rt: range-through distribution
DOI: 10.6084/m9.figshare.21229083.v1
title: Table S2. Biodiversity change and extinction risk in Plio-Pleistocene Mediterranean bivalves: the families Veneridae, Pectinidae and Lucinidae

description: Time-range distribution of the studied species. rt: range-through distribution
DOI: 10.6084/m9.figshare.21229086.v1
title: Table S1. Biodiversity change and extinction risk in Plio-Pleistocene Mediterranean bivalves: the families Veneridae, Pectinidae and Lucinidae

description: Species occurrence and spatial data
DOI: 10.6084/m9.figshare.21229086
title: Table S1. Biodiversity change and extinction risk in Plio-Pleistocene Mediterranean bivalves: the families Veneridae, Pectinidae and Lucinidae

description: Species occurrence and spatial data
DOI: 10.14768/75b44a04-fb39-4a5c-b097-00229d34e5c1
title: An Extremely Elongated Cloud over Arsia Mons Volcano on Mars: II. Mesoscale modeling

description: Enclosed in this dataset are the reference mesoscale simulations supporting the paper Hernandez Bernal et al. JGR planets 2022 studying the formation mechanisms of the AMEC (Arsia Mons Elongated Cloud) on Mars Reference (article): Hernandez Bernal et al. JGR planets 2022
DOI: 10.48366/r219286
title: A comparison on Text Classification Approaches

description: This comparison will explore the different researches on Text Classifications.
DOI: 10.5281/zenodo.7071747
title: Packaging Industry Anomaly DEtection (PIADE) Dataset

description: PIADE dataset contains data from five industrial packaging machines: Machine s_1: from 2020-01-01 14:00:00 to 2021-12-31 13:00:00 Machine s_2: from 2020-06-17 08:00:00 to 2021-12-31 07:00:00 Machine s_3: from 2020-10-07 12:00:00 to 2022-01-01 23:00:00 Machine s_4: from 2020-01-01 01:00:00 to 2022-01-01 23:00:00 Machine s_5: from 2020-01-20 08:00:00 to 2022-01-01 12:00:00 ## Raw Data Each row represents a production interval, with the following schema: interval_start: start of the production interval equipment_ID: equipment identifier alarm: alarm code of the active stop reason, if it occurred type: idle, production, downtime, performance_loss or scheduled_downtime start: start of the production interval end: end of the production interval elapsed: duration of the production interval pi: input packages po: output packages speed: speed (packages per hour) There are 133 different types of alerts, and 429394 rows.<br> ## Sequences (1h) data For each piece of equipment, we define sequences of length = 1 hour and we aggregate raw interval data as follows: 'equipment_ID': machine identifier '#changes': changes in machine state '%downtime': time spent in 'downtime' state '%idle': time spent in 'idle' state '%performance_loss': time spent in 'performance loss' state '%production': time spent in production '%scheduled_downtime': time spent in scheduled downtime 'count_sum': sum of all alarm occurrences 'A_&lt;XXX&gt;': counter of alarm &lt;XXX&gt; occurrences '&lt;state1&gt;/&lt;state2&gt;': number of transitions from &lt;state1&gt; to &lt;state2&gt;
description: The collection of this dataset has been partially supported by the Regione Veneto project VIR2EM (VIrtualization and Remotization for Resilient and Efficient Manufacturing, Virtualizzazione e remotizzazione per una manifattura efficiente e resiliente)
DOI: 10.5281/zenodo.7071746
title: Packaging Industry Anomaly DEtection (PIADE) Dataset

description: PIADE dataset contains data from five industrial packaging machines: Machine s_1: from 2020-01-01 14:00:00 to 2021-12-31 13:00:00 Machine s_2: from 2020-06-17 08:00:00 to 2021-12-31 07:00:00 Machine s_3: from 2020-10-07 12:00:00 to 2022-01-01 23:00:00 Machine s_4: from 2020-01-01 01:00:00 to 2022-01-01 23:00:00 Machine s_5: from 2020-01-20 08:00:00 to 2022-01-01 12:00:00 ## Raw Data Each row represents a production interval, with the following schema: interval_start: start of the production interval equipment_ID: equipment identifier alarm: alarm code of the active stop reason, if it occurred type: idle, production, downtime, performance_loss or scheduled_downtime start: start of the production interval end: end of the production interval elapsed: duration of the production interval pi: input packages po: output packages speed: speed (packages per hour) There are 133 different types of alerts, and 429394 rows.<br> ## Sequences (1h) data For each piece of equipment, we define sequences of length = 1 hour and we aggregate raw interval data as follows: 'equipment_ID': machine identifier '#changes': changes in machine state '%downtime': time spent in 'downtime' state '%idle': time spent in 'idle' state '%performance_loss': time spent in 'performance loss' state '%production': time spent in production '%scheduled_downtime': time spent in scheduled downtime 'count_sum': sum of all alarm occurrences 'A_&lt;XXX&gt;': counter of alarm &lt;XXX&gt; occurrences '&lt;state1&gt;/&lt;state2&gt;': number of transitions from &lt;state1&gt; to &lt;state2&gt;
description: The collection of this dataset has been partially supported by the Regione Veneto project VIR2EM (VIrtualization and Remotization for Resilient and Efficient Manufacturing, Virtualizzazione e remotizzazione per una manifattura efficiente e resiliente)
DOI: 10.5281/zenodo.6861292
title: Implementation and evaluation of a multilingual search pilot in the Europeana digital library (dataset)

description: The dataset contains the data required to reproduce the experiments done in the paper "Implementation and evaluation of a multilingual search pilot in the Europeana digital library", published in the 26th International Conference on Theory and Practice of Digital Libraries (TPDL'22). In that work we implemented a pilot applying query translation to English from the Spanish version of the website in order to surface results that have English metadata associated with them. The dataset is also available at https://rnd-2.eanadev.org/share/crosslingual_SpanishPilot/, and it is organized in three main folders: <strong>sample</strong>: stratified sample of 300 queries queries issued from the Europeana Spanish portal from 1st<br> December 2020 to 28th February 2021. <strong>evaluation.translations: </strong>manual annotation of the quality of the identification of the language of the queries using Google Cloud Translation API, and the quality of the translation obtained using Google plus the CEF translation service (eTranslation). <strong>evaluation.search_retrieval: </strong>manual annotation of the relevancy of the (binary) relevance of the documents that are retrieved by one system but not by the other (current monolingual version vs pilot) in their top ten.
DOI: 10.6084/m9.figshare.21218372.v1
title: Spatial Cooperative Simulation of Land Use-Population-Economy in the Guangdong-Hong Kong-Macao Greater Bay Area, China

description: The fast urbanization has eroded the city boundaries and made the mega-city region. It also brings great challenges to the sustainable development goals, such as excessive exploitation and population explosion. Classical cellular automata (CA) has been widely used to simulate the change of spatial features, i.e., land-use, population, economy, etc., which foster the spatial planning and policy-making. But they focus on one feature thus ignore their inter-wined influences. This study proposes the spatial cooperative simulation (SCS) approach to simulate the land use-population-economy changes in the megacity region. CA is used to forecast the spatial process of one feature. The interactions among multiple features are represented by taking one feature as the dynamic driving factor. The CA model is iteratively trained to capture the cooperative influence of multiple features. The train process will be repeated until the total errors is converged.
DOI: 10.34740/kaggle/dsv/4262947
title: World's Top 10 YouTubers in 2022
DOI: 10.5517/ccdc.csd.cc29b2k9
title: CCDC 2124850: Experimental Crystal Structure Determination

description: Related Article: Odi Th. E. Selan, Mun Hon Cheah, Brendan F. Abrahams, Robert W. Gable, Stephen P. Best|2022|Aust.J.Chem.|75|649|doi:10.1071/CH21309
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.cc29b2lb
title: CCDC 2124851: Experimental Crystal Structure Determination

description: Related Article: Odi Th. E. Selan, Mun Hon Cheah, Brendan F. Abrahams, Robert W. Gable, Stephen P. Best|2022|Aust.J.Chem.|75|649|doi:10.1071/CH21309
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.cc29y2zb
title: CCDC 2143122: Experimental Crystal Structure Determination

description: Related Article: Corinne Vanucci-Bacqué, Christiane André-Barres, Nathalie Saffon-Merceron, Florence Bedos-Belval|2022|Tetrahedron|124|133019|doi:10.1016/j.tet.2022.133019
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.cc29y30d
title: CCDC 2143123: Experimental Crystal Structure Determination

description: Related Article: Corinne Vanucci-Bacqué, Christiane André-Barres, Nathalie Saffon-Merceron, Florence Bedos-Belval|2022|Tetrahedron|124|133019|doi:10.1016/j.tet.2022.133019
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.7123483
title: Webis Health CauseNet 2022

description: An efficient assessment of the health relatedness of text passages is important to mine the web at scale to conduct health sociological analyses or to develop a health search engine. We propose a new efficient and effective termhood score for predicting the health relatedness of phrases and sentences, which achieves 69% recall at over 90% precision on a web dataset with cause–effect statements. It is more effective than state-of-the-art medical entity linkers and as effective but much faster than BERT-based approaches. Using our method, we compile the Webis Health CauseNet 2022, a new resource of 7.8 million health-related cause–effect statements such as “Studies show that stress induces insomnia” in which the cause (‘stress’) and effect (‘insomnia’) are labeled. <pre><code>@InProceedings{schlatt2022health-causenet, author = {Ferdinand Schlatt and Dieter Bettin and Matthias Hagen and Benno Stein and Martin Potthast}, booktitle = {29th International Conference on Computational Linguistics (COLING 2022)}, publisher = {Association for Computational Linguistics}, site = {Gyeongju, Republic of Korea}, title = {{Mining Health-related Cause-Effect Statements with High Precision at Large Scale}}, year = 2022 } </code></pre>
DOI: 10.5281/zenodo.7123482
title: Webis Health CauseNet 2022

description: An efficient assessment of the health relatedness of text passages is important to mine the web at scale to conduct health sociological analyses or to develop a health search engine. We propose a new efficient and effective termhood score for predicting the health relatedness of phrases and sentences, which achieves 69% recall at over 90% precision on a web dataset with cause–effect statements. It is more effective than state-of-the-art medical entity linkers and as effective but much faster than BERT-based approaches. Using our method, we compile the Webis Health CauseNet 2022, a new resource of 7.8 million health-related cause–effect statements such as “Studies show that stress induces insomnia” in which the cause (‘stress’) and effect (‘insomnia’) are labeled. <pre><code>@InProceedings{schlatt2022health-causenet, author = {Ferdinand Schlatt and Dieter Bettin and Matthias Hagen and Benno Stein and Martin Potthast}, booktitle = {29th International Conference on Computational Linguistics (COLING 2022)}, publisher = {Association for Computational Linguistics}, site = {Gyeongju, Republic of Korea}, title = {{Mining Health-related Cause-Effect Statements with High Precision at Large Scale}}, year = 2022 } </code></pre>
DOI: 10.21954/ou.rd.21217607
title: CONNECT - open schooling - Consensus Conference

description: <br> Description Subject: Education <br> Specific: CONNECT - Inclusive Open Schooling with Engaging and Future-oriented science<br> <br> Type: Word Document - Online Consensus Conference<br> Date: 11 Nov 2020 <br> Content Language: Portuguese <br> Title: Formative Itinerary Webinar: Digital Competences for Teaching with open schooling- Intervention Projects <br> <br> Reference: Project CONNECT - Extension course for teachers' professional development about Projects of Intervention <br> Design Method: Participants includes teachers, teachers' educators, policymakers, students, researchers and consultants. A real question is identified by participants (E.g. What are the barriers and drivers in School Education during the pandemic? What is Open Schooling and What will be the benefits and challenges to use open schooling to support schools?) Each participant provides their views, examples, practices. A moderator supports the large number of participants (more than 700) who joined the live stream to facilitate the discussion in the chat. A semi-structured questionnaire is shared with all volunteers participants. Overall results are presented in the Consensus Conference. A facilitator of the event opens the discussion with contributions from the audience and speakers. A summary of results are presented for final comments. <br> Value: These data provide teachers' self-reflective views about projects of intervention, open schooling barriers and drivers during COVID-19 .This data refers to teachers' opinions about open schooling components and strategies. <br> CITATION: Okada A., Soares K. Open Schooling - Consensus Conference - Project of Intervention transcript - Nov 2020 available in ORDO under CC BY SA open license <br> FUNDING European Union’s Horizon 2020 research and innovation programme under grant agreement no. 872814. <br> Ethics This dataset is part of CONNECT project which has received Ethics approval by The Open University, HREC – Human Research and Ethics Committee. The participants provided their informed consent to participate in this study.
DOI: 10.21954/ou.rd.21217607.v1
title: CONNECT - open schooling - Consensus Conference

description: <br> Description Subject: Education <br> Specific: CONNECT - Inclusive Open Schooling with Engaging and Future-oriented science<br> <br> Type: Word Document - Online Consensus Conference<br> Date: 11 Nov 2020 <br> Content Language: Portuguese <br> Title: Formative Itinerary Webinar: Digital Competences for Teaching with open schooling- Intervention Projects <br> <br> Reference: Project CONNECT - Extension course for teachers' professional development about Projects of Intervention <br> Design Method: Participants includes teachers, teachers' educators, policymakers, students, researchers and consultants. A real question is identified by participants (E.g. What are the barriers and drivers in School Education during the pandemic? What is Open Schooling and What will be the benefits and challenges to use open schooling to support schools?) Each participant provides their views, examples, practices. A moderator supports the large number of participants (more than 700) who joined the live stream to facilitate the discussion in the chat. A semi-structured questionnaire is shared with all volunteers participants. Overall results are presented in the Consensus Conference. A facilitator of the event opens the discussion with contributions from the audience and speakers. A summary of results are presented for final comments. <br> Value: These data provide teachers' self-reflective views about projects of intervention, open schooling barriers and drivers during COVID-19 .This data refers to teachers' opinions about open schooling components and strategies. <br> CITATION: Okada A., Soares K. Open Schooling - Consensus Conference - Project of Intervention transcript - Nov 2020 available in ORDO under CC BY SA open license <br> FUNDING European Union’s Horizon 2020 research and innovation programme under grant agreement no. 872814. <br> Ethics This dataset is part of CONNECT project which has received Ethics approval by The Open University, HREC – Human Research and Ethics Committee. The participants provided their informed consent to participate in this study.
DOI: 10.6084/m9.figshare.21220387
title: Additional file 2 of Marine DNA methylation patterns are associated with microbial community composition and inform virus-host dynamics

description: Additional file 2: Supplementary Data 1. Genome information of SHIPPO MAGs. Supplementary Data 2. (DOI link: https://doi.org/10.6084/m9.figshare.17161715 ). Genome files of SHIPPO MAGs.
DOI: 10.6084/m9.figshare.21220387.v1
title: Additional file 2 of Marine DNA methylation patterns are associated with microbial community composition and inform virus-host dynamics

description: Additional file 2: Supplementary Data 1. Genome information of SHIPPO MAGs. Supplementary Data 2. (DOI link: https://doi.org/10.6084/m9.figshare.17161715 ). Genome files of SHIPPO MAGs.
DOI: 10.6084/m9.figshare.21220393
title: Additional file 3 of Marine DNA methylation patterns are associated with microbial community composition and inform virus-host dynamics

description: Additional file 3: Supplementary Data 3. RM system of MAGs from ocean metagenomic studies.
DOI: 10.6084/m9.figshare.21220393.v1
title: Additional file 3 of Marine DNA methylation patterns are associated with microbial community composition and inform virus-host dynamics

description: Additional file 3: Supplementary Data 3. RM system of MAGs from ocean metagenomic studies.
DOI: 10.6084/m9.figshare.21220396
title: Additional file 4 of Marine DNA methylation patterns are associated with microbial community composition and inform virus-host dynamics

description: Additional file 4: Supplementary Data 4. Methylation profiles of 5-mer motifs across MAGs and sampling stations.
DOI: 10.6084/m9.figshare.21220396.v1
title: Additional file 4 of Marine DNA methylation patterns are associated with microbial community composition and inform virus-host dynamics

description: Additional file 4: Supplementary Data 4. Methylation profiles of 5-mer motifs across MAGs and sampling stations.
DOI: 10.34740/kaggle/dsv/4263023
title: Health Workforce Shortage Areas
DOI: 10.34740/kaggle/dsv/4263031
title: AutoXGB
DOI: 10.5281/zenodo.7121000
title: BC4NF_WP5_BAM-summary_30-09-2022

description: This document describes all publication, dissemination, exploitation, and communication activities performed at BAM within the frame of the <strong>BioCombs4Nanofibers</strong> project. (10/2019 – 09/2022). Contact address: Jörn Bonse Bundesanstalt für Materialforschung und -prüfung (BAM) Unter den Eichen 87 D-12205 Berlin, Germany joern.bonse@bam.de
description: This document is related to the Data Management Plan (DMP) of the project BioCombs4Nanofibers that has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 862016.
DOI: 10.5281/zenodo.7121001
title: BC4NF_WP5_BAM-summary_30-09-2022

description: This document describes all publication, dissemination, exploitation, and communication activities performed at BAM within the frame of the <strong>BioCombs4Nanofibers</strong> project. (10/2019 – 09/2022). Contact address: Jörn Bonse Bundesanstalt für Materialforschung und -prüfung (BAM) Unter den Eichen 87 D-12205 Berlin, Germany joern.bonse@bam.de
description: This document is related to the Data Management Plan (DMP) of the project BioCombs4Nanofibers that has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 862016.
DOI: 10.5281/zenodo.2573936
title: Subpixel offsets of Copernicus Sentinel 2 data, related to the displacement field of the Sulawesi Earthquake (2018, Mw 7.5)

description: Sulawesi lies within a complex fault system located between the Australian, Pacific, Philippine and Sunda Plates. The main active structure onshore at the western part of Central Sulawesi is the left-lateral NNW-SSE trending Palu-Koro strike-slip fault that forms the boundary between the North Sula and Makassar blocks. On 28 September 2018, a large tsunamigenic earthquake (Mw 7.5) struck the Minahasa Peninsula, Indonesia. The earthquake caused massive damages near Palu city, including onshore gravitational instabilities and a tsunami.

These data are the result of subpixel image correlation on Copernicus Sentinel-2 data (17 September 2018 and 2 October 2018) to derive the two-dimensional (East-West and North-South) horizontal co-seismic displacement field. In these data, the displacement field is expressed in meters. These results show a dominant senextral strike-slip motion on the onshore part of the Palu-Koro fault. Maximum displacement at the surface reached more than 8 meters at the location of Palu city. Processing is performed with COSI-CORR (Leprince et al., 2007). Data value higher than | 10 | meters should be considered as noise and disregarded. I used a correlation window size of 32 pixels with a sampling step of 16 pixels. A ramp has been removed from (separately) the North-South offsets and from the East-West offsets. The files are rasters of floating point values, served with a header file readable by ENVI software.

Sign conventions:

-North-South offsets: positive values to the North.

- East-West offsets:  positive values to the West.

 

http://www.esa.int/spaceinimages/Images/2018/10/Indonesia_earthquake_displacement_data

<strong>Copyright:</strong> Contains modified Copernicus Sentinel data (2018), processed at the French Geological Survey (BRGM)
DOI: 10.17041/drp/1460808
title: Models and results of transactive energy-based control to stabilize oscillations in integrated wholesale-retail energy markets

description: The resources under this data set represent models and results of work done under Control of Complex Systems Initiative (CCSI) to demonstrate the transactive energy-based control capabilities to stabilize and reduce oscillations that might occur when other control mechanisms are used.