cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.17914049
title: Dataset: Jellyfish observations of Greece (2021)

description: Raw data from the project of Jellyfish observations in Greece. <br><br>These data are more interesting because of the 2021 jellyfish bloom in Aegean of the species Pelagia noctiluca.
DOI: 10.34740/kaggle/dsv/3010872
title: AutoXGB
DOI: 10.5281/zenodo.5824401
title: Document_Internet

description: Document_Internet
DOI: 10.5281/zenodo.5824400
title: Document_Internet

description: Document_Internet
DOI: 10.5281/zenodo.5792219
title: TESTAR State Model

description: TESTAR extracted State Model dataset with TESTAR tool using CODEO desktop application as System Under Test (SUT). This State Model has been generated to be used as an example to be automatically generated and introduced locally in DECODER PKM, from H2020 DECODER Project. TESTAR tool is an open source tool (www.testar.org) for automated testing through graphical user interface (GUI) currently being developed by the Universitat Politecnica de Valencia and the Open University of the Netherlands. CODEO (https://www.sysgo.com/codeo) is an Eclipse-based IDE that facilitates embedded applications development, by providing all the components software engineers need. The architecture configurations can be esaily done through the CODEO graphical tools. PKM is the Persistent Knowledge Monitor developed as main infrastructure from H2020 DECODER Project (www.decoder-project.eu) under grant agreement number 824231. As TESTAR explores automatically the SUT, it will use the Document Object Model (DOM) information extracted from MyThaiStar SUT, to generate and save a TESTAR State Model in the OrientDB graph database. This model contains information about the Widgets, States and Actions, that were found in the SUT. - ArtefactStateModel_codeo_74_1dwbc1338198529501_2021-12-14_13h38m39s.zip: For DECODER project purposes, the knowledge extracted with TESTAR in the generation of the State Model has been summarized and referenced in an artifact JSON file to be adapted to PKM input requirements.
DOI: 10.5281/zenodo.5792218
title: TESTAR State Model

description: TESTAR extracted State Model dataset with TESTAR tool using CODEO desktop application as System Under Test (SUT). This State Model has been generated to be used as an example to be automatically generated and introduced locally in DECODER PKM, from H2020 DECODER Project. TESTAR tool is an open source tool (www.testar.org) for automated testing through graphical user interface (GUI) currently being developed by the Universitat Politecnica de Valencia and the Open University of the Netherlands. CODEO (https://www.sysgo.com/codeo) is an Eclipse-based IDE that facilitates embedded applications development, by providing all the components software engineers need. The architecture configurations can be esaily done through the CODEO graphical tools. PKM is the Persistent Knowledge Monitor developed as main infrastructure from H2020 DECODER Project (www.decoder-project.eu) under grant agreement number 824231. As TESTAR explores automatically the SUT, it will use the Document Object Model (DOM) information extracted from MyThaiStar SUT, to generate and save a TESTAR State Model in the OrientDB graph database. This model contains information about the Widgets, States and Actions, that were found in the SUT. - ArtefactStateModel_codeo_74_1dwbc1338198529501_2021-12-14_13h38m39s.zip: For DECODER project purposes, the knowledge extracted with TESTAR in the generation of the State Model has been summarized and referenced in an artifact JSON file to be adapted to PKM input requirements.
DOI: 10.5281/zenodo.5815935
title: TESTAR PKM Connector

description: TESTAR functionality (Java source code) has been developed to translate TESTAR objects artifacts into collections of documents, that can be assimilated by the PKM through its API. TESTAR tool is an open source tool (www.testar.org) for automated testing through graphical user interface (GUI) currently being developed by the Universitat Politecnica de Valencia and the Open University of the Netherlands. PKM is the Persistent Knowledge Monitor developed as main infrastructure from H2020 DECODER Project (www.decoder-project.eu) under grant agreement number 824231. As TESTAR explores automatically the SUT, it will use the Document Object Model (DOM) information extracted from MyThaiStar SUT, to generate and save a TESTAR State Model in the OrientDB graph database. This model contains information about the Widgets, States and Actions, that were found in the SUT. - Artefact.zip: Java classes used to manage the creation of JSON artifacts. - json.zip: Java classes used to create JSON artifacts (Logs, State Model, State Model Difference and Test Results).
DOI: 10.5281/zenodo.5815934
title: TESTAR PKM Connector

description: TESTAR functionality (Java source code) has been developed to translate TESTAR objects artifacts into collections of documents, that can be assimilated by the PKM through its API. TESTAR tool is an open source tool (www.testar.org) for automated testing through graphical user interface (GUI) currently being developed by the Universitat Politecnica de Valencia and the Open University of the Netherlands. PKM is the Persistent Knowledge Monitor developed as main infrastructure from H2020 DECODER Project (www.decoder-project.eu) under grant agreement number 824231. As TESTAR explores automatically the SUT, it will use the Document Object Model (DOM) information extracted from MyThaiStar SUT, to generate and save a TESTAR State Model in the OrientDB graph database. This model contains information about the Widgets, States and Actions, that were found in the SUT. - Artefact.zip: Java classes used to manage the creation of JSON artifacts. - json.zip: Java classes used to create JSON artifacts (Logs, State Model, State Model Difference and Test Results).
DOI: 10.5281/zenodo.5822752
title: TESTAR Model-Difference report

description: Two TESTAR State Models, extracted from different versions of the same application, are compared to create this HTML file with textual and visual information about new and disappeared States and Actions. TESTAR tool is an open source tool (www.testar.org) for automated testing through graphical user interface (GUI) currently being developed by the Universitat Politecnica de Valencia and the Open University of the Netherlands. PKM is the Persistent Knowledge Monitor developed as main infrastructure from H2020 DECODER Project (www.decoder-project.eu) under grant agreement number 824231. As TESTAR explores automatically the SUT, it will use the Document Object Model (DOM) information extracted from MyThaiStar SUT, to generate and save a TESTAR State Model in the OrientDB graph database. This model contains information about the Widgets, States and Actions, that were found in the SUT. - DifferenceReport.zip: HTML report that contains information about how the GUI of a SUT has been changed between two versions.
DOI: 10.5281/zenodo.5822751
title: TESTAR Model-Difference report

description: Two TESTAR State Models, extracted from different versions of the same application, are compared to create this HTML file with textual and visual information about new and disappeared States and Actions. TESTAR tool is an open source tool (www.testar.org) for automated testing through graphical user interface (GUI) currently being developed by the Universitat Politecnica de Valencia and the Open University of the Netherlands. PKM is the Persistent Knowledge Monitor developed as main infrastructure from H2020 DECODER Project (www.decoder-project.eu) under grant agreement number 824231. As TESTAR explores automatically the SUT, it will use the Document Object Model (DOM) information extracted from MyThaiStar SUT, to generate and save a TESTAR State Model in the OrientDB graph database. This model contains information about the Widgets, States and Actions, that were found in the SUT. - DifferenceReport.zip: HTML report that contains information about how the GUI of a SUT has been changed between two versions.
DOI: 10.5281/zenodo.5824423
title: Floristic survey of vascular plants of a poorly known area in the Brazilian Atlantic Forest (Flona do Rio Preto, Espírito Santo)

description: The Atlantic Forest is one of the most threatened biomes in the world. Despite that, this biome still includes many areas that are poorly known floristically, including several protected areas such as the "Floresta Nacional do Rio Preto" ("Flona do Rio Preto"), located in the Brazilian state of Espírito Santo. This study used a published vascular plant species list for this protected area from the "Catálogo de Plantas das Unidades de Conservação do Brasil" as the basis to synthesize the species richness, endemism, conservation, and new species occurrences found in the "Flona do Rio Preto". The published list of vascular plants was based on field expeditions conducted between 2018-2020 and data obtained from herbarium collections available in online databases. Overall, 722 species were documented for the "Flona do Rio Preto", 711 of which are native to Brazil, and 349 are endemic to the Atlantic Forest. In addition, 60 species are geographically disjunct between the Atlantic and the Amazon forests. Most of the documented species are woody, and more than 50% of these are trees. Twenty-three species are threatened (CR, EN, and VU), while five are Data Deficient (DD). Thirty-two species are new records for the state of Espírito Santo. Our results expand the knowledge of the flora of the Atlantic Forest and provide support for the development of new conservation policies for this protected area.
description: Supplemental Material
DOI: 10.5281/zenodo.5815128
title: Floristic survey of vascular plants of a poorly known area in the Brazilian Atlantic Forest (Flona do Rio Preto, Espírito Santo)

description: The Atlantic Forest is one of the most threatened biomes in the world. Despite that, this biome still includes many areas that are poorly known floristically, including several protected areas such as the "Floresta Nacional do Rio Preto" ("Flona do Rio Preto"), located in the Brazilian state of Espírito Santo. This study used a published vascular plant species list for this protected area from the "Catálogo de Plantas das Unidades de Conservação do Brasil" as the basis to synthesize the species richness, endemism, conservation, and new species occurrences found in the "Flona do Rio Preto". The published list of vascular plants was based on field expeditions conducted between 2018-2020 and data obtained from herbarium collections available in online databases. Overall, 722 species were documented for the "Flona do Rio Preto", 711 of which are native to Brazil, and 349 are endemic to the Atlantic Forest. In addition, 60 species are geographically disjunct between the Atlantic and the Amazon forests. Most of the documented species are woody, and more than 50% of these are trees. Twenty-three species are threatened (CR, EN, and VU), while five are Data Deficient (DD). Thirty-two species are new records for the state of Espírito Santo. Our results expand the knowledge of the flora of the Atlantic Forest and provide support for the development of new conservation policies for this protected area.
description: Supplemental Material
DOI: 10.5517/ccdc.csd.cc29cqfv
title: CCDC 2126427: Experimental Crystal Structure Determination

description: Related Article: Masrat Bashir, Imtiyaz Yousuf|2022|Inorg.Chim.Acta|532|120757|doi:10.1016/j.ica.2021.120757
DOI: 10.5281/zenodo.5824414
title: Flood timing data for the paper "Climate Leads to Reversed Latitudinal Changes in Chinese Flood Peak Timing"

description: Annual maximum flood peak timing data used in the paper <em>Climate Leads to Reversed Latitudinal Changes in Chinese Flood Peak Timing.</em>
DOI: 10.34740/kaggle/dsv/3011033
title: Omicron daily cases by country (COVID-19 variant)
DOI: 10.5281/zenodo.5813444
title: EURAKNOS Communication and Dissemination Activities

description: Excel tables containing a record of EURAKNOS Communication and Dissemination activities
DOI: 10.5281/zenodo.5813443
title: EURAKNOS Communication and Dissemination Activities

description: Excel tables containing a record of EURAKNOS Communication and Dissemination activities
DOI: 10.5281/zenodo.5813411
title: TN interviews Task 2.4

description: ZIP archive of all Task 2.4 interviews
DOI: 10.5281/zenodo.5813405
title: TN interviews Task 2.3

description: ZIP archive of all Task 2.3 interviews
DOI: 10.5281/zenodo.5813410
title: TN interviews Task 2.4

description: ZIP archive of all Task 2.4 interviews
DOI: 10.5281/zenodo.5813402
title: TN interviews Task 2.2

description: ZIP archive of all Task 2.2 interviews
DOI: 10.5281/zenodo.5813404
title: TN interviews Task 2.3

description: ZIP archive of all Task 2.3 interviews
DOI: 10.5281/zenodo.5813396
title: TN interviews Task 2.1

description: ZIP archive of all Task 2.1 interviews
DOI: 10.5281/zenodo.5813401
title: TN interviews Task 2.2

description: ZIP archive of all Task 2.2 interviews
DOI: 10.5281/zenodo.5813395
title: TN interviews Task 2.1

description: ZIP archive of all Task 2.1 interviews
DOI: 10.5281/zenodo.5813339
title: WP2 Task 2.2 results of desktop study of TNs

description: WP2 Task 2.2 results of desktop study of TNs
DOI: 10.5281/zenodo.5813338
title: WP2 Task 2.2 results of desktop study of TNs

description: WP2 Task 2.2 results of desktop study of TNs
DOI: 10.26050/wdcc/momergombsemep
title: MOM-ERGOM western Baltic Sea simulations with tagging of atmospheric nitrogen deposition by EMEP

description: Project: HBM-ERGOM western Baltic Sea simulations with tagging of atmospheric nitrogen deposition within the MeRamo project - The MeRamo project (Unterstützung der mit der Umsetzung der EU Meeresstrategie-Rahmenrichtlinie befassten Behörden mittels eines assimilativen Ökosystems) was funded within the German national budget for the EU Copernicus Programme (BMVI Grand 50EW1601). The aim of the project was to link EU Copernicus services -- namely Sentinel remote sensing data -- with a marine biogeochemical model system (HBM-ERGOM). Additionally, the contribution of nitrogen from atmospheric deposition to the marine nitrogen budget was to assess. Two scientific questions were derived for the second project focus: - What contribution does atmospheric nitrogen deposition in total and atmospheric deposition of nitrogen from shipping and agricultural activities have to the nitrogen budget in the marine surface layer of the western Baltic Sea? - What is the impact of the spatial resolution of nitrogen deposition data on the biogeochemical model predictions in highly structured coastal areas in the western Baltic Sea region? To deal with these questions, the model system HBM-ERGOM was extended by a nutrient tagging/tracing approach and model simulations with tagged atmospheric nitrogen compounds were performed at the North-German Supercomputing Alliance (HLRN, project id: mvk00054, zulassung.hlrn.de/kurzbeschreibungen/mvk00054.pdf). Three different nitrogen deposition data sets were used for the model simulations. Two spatial highly resolved deposition data sets were provided by the EU BONUS Project SHEBA (Karl et al., 2019, doi:10.5194/acp-2018-1317) and one deposition data set was provided by the Norwegian Meteorological Institut (MetNo, 2016) for the European Evaluation and Modelling Programme (EMEP). The year 2012 was simulated. The North Sea and Baltic Sea were covered by the model domain but only results for the western Baltic Sea are provided here. The latter data were presented in Neumann et al. (2018, doi:10.5194/os-2018-71). Summary: A marine physical biogeochemical model simulation was performed with the model MOM-ERGOM for the years 2003 to 2014 covering the Baltic Sea. Previously, MOM-ERGOM had been initialized for several decades without tagging until 1999 and, then, from 2000 to 2002 with tagging (see below). The model output has been validated with measurement data of the "IOW Baltic Monitoring and long-term data program" (https://www.io-warnemuende.de/iowdb.html; IOW: Leibniz Institute for Baltic Sea Research Warnemünde) and from the HELCOM database (http://ocean.ices.dk/helcom/Helcom.aspx; HELCOM: Helsinki Commission). A publication is in preparation.
DOI: 10.5281/zenodo.5676286
title: Individual multilocus genotypes of adults and seed progeny from eight natural populations of Campanula glomerata

description: Individual multilocus genotypes based on 15 microsatellite loci of adults and seed progeny from eight natural populations of <em>Campanula glomerata</em>. For more details see Van Rossum et al. (2022) in Frontiers in Conservation Science
description: {"references": ["Van Rossum et al. (2022), Assessing population genetic status for designing plant translocations, Frontiers in Conservation Science. doi: 10.3389/fcosc.2022.829332"]}
DOI: 10.5281/zenodo.5676272
title: Fitness measures of seed progeny from seven natural populations of Campanula glomerata.

description: Fitness (rosette diameter in cm) and HL for seed progeny of seven wild populations of <em>Campanula glomerata </em>from southern Belgium and north-eastern France. For details see Van Rossum et al. (2022) in Frontiers in Conservation Science.
description: {"references": ["Van Rossum et al. (2022), Assessing population genetic status for designing plant translocations, Frontiers in Conservation Science. doi: 10.3389/fcosc.2022.829332"]}
DOI: 10.5281/zenodo.5676285
title: Individual multilocus genotypes of adults and seed progeny from eight natural populations of Campanula glomerata

description: Individual multilocus genotypes based on 15 microsatellite loci of adults and seed progeny from eight natural populations of <em>Campanula glomerata</em>. For more details see Van Rossum et al. (2022) in Frontiers in Conservation Science
description: {"references": ["Van Rossum et al. (2022), Assessing population genetic status for designing plant translocations, Frontiers in Conservation Science. doi: 10.3389/fcosc.2022.829332"]}
DOI: 10.5281/zenodo.5676271
title: Fitness measures of seed progeny from seven natural populations of Campanula glomerata.

description: Fitness (rosette diameter in cm) and HL for seed progeny of seven wild populations of <em>Campanula glomerata </em>from southern Belgium and north-eastern France. For details see Van Rossum et al. (2022) in Frontiers in Conservation Science.
description: {"references": ["Van Rossum et al. (2022), Assessing population genetic status for designing plant translocations, Frontiers in Conservation Science. doi: 10.3389/fcosc.2022.829332"]}
DOI: 10.5281/zenodo.5824485
title: Data Bundle for PyPSA-Eur-Sec: A Sector-Coupled Open Optimisation Model of the European Energy System

description: While small data files used in PyPSA-Eur-Sec are included directly in the git repository, larger ones are collected in this data bundle. The data bundle’s size is around 680 MB. <strong>Licenses</strong> Different licenses apply to the various components of this data bundle (mostly attribution). For details see https://pypsa-eur-sec.readthedocs.io/en/latest/installation.html#data-requirements <strong>Changelog 0.2.0</strong> add hydrogen salt cavern storage potential (h2_salt_caverns_GWh_per_sqkm.geojson)
DOI: 10.5281/zenodo.5824567
title: MICCAI 2021 MSSEG-2 challenge demographics data

description: This dataset will include all demographics and dataset constitution information for the MICCAI 2021 challenge.
DOI: 10.5281/zenodo.5824513
title: Data for article "Synthesis of Four-Membered BN3 Heterocycles by the Borylation of Triazenes"

description: This upload contains raw data (NMR, X-Ray, Elemental Analysis, Fluorescence) files for the article: A. A. Suleymanov, R. Scopelliti, K. Severin, "Synthesis of Four-Membered BN3 Heterocycles by the Borylation of Triazenes" <em>Inorg. Chem. </em><strong>2022</strong>, DOI: 10.1021/acs.inorgchem.1c03309
DOI: 10.5281/zenodo.5824512
title: Data for article "Synthesis of Four-Membered BN3 Heterocycles by the Borylation of Triazenes"

description: This upload contains raw data (NMR, X-Ray, Elemental Analysis, Fluorescence) files for the article: A. A. Suleymanov, R. Scopelliti, K. Severin, "Synthesis of Four-Membered BN3 Heterocycles by the Borylation of Triazenes" <em>Inorg. Chem. </em><strong>2022</strong>, DOI: 10.1021/acs.inorgchem.1c03309
DOI: 10.5517/ccdc.csd.cc29h375
title: CCDC 2129676: Experimental Crystal Structure Determination

description: Related Article: S.S. Kurup, S. Nasser, C.L. Ward, S. Groysman|2022|Acta Crystallogr.,Sect.E:Cryst.Commun.|78|92|doi:10.1107/S2056989021013438
DOI: 10.5517/ccdc.csd.cc29h3sq
title: CCDC 2129693: Experimental Crystal Structure Determination

description: Related Article: S. Daoui, S. Kansiz, F.A. Aktas, N. Dege, E. Saif, N. Benchat, K. Karrouchi|2022|Acta Crystallogr.,Sect.E:Cryst.Commun.|78|88|doi:10.1107/S205698902101344X
DOI: 10.15161/oar.it/74390
title: CovidStat project data

description: This record contains the daily updated data of the CovidStat project. CovidStat is a project carried out by the CovidStat Working Group at INFN, whose creation was promoted within the Italian National Institute of Nuclear Physics with the aim of making a statistical analysis of the data provided daily by the Civil Protection on the spread of the pandemic in Italy. CovidStat data can interactively be browsed at https://covid19.infn.it.
description: The software to process this Root TTree is in the related identifier. Be sure to use the right corresponding version, based on the data in which Root TTree was generated.
DOI: 10.3886/e144261
title: COVID-19 research profiling data about author, bio entity, and institution

description: The outbreak of COVID-19 has a severe impact on our families, communities, and businesses. White House released the COVID-19 literature dataset (called CORD-19 dataset) which has grown exponentially into a gigantic collection of over 500,000 articles. Researchers, practitioners, and administrators need data to help them digest this enormous amount of knowledge to address vairous scientific questions related to COVID-19. This data combine CORD-19 dataset, author information from Semantic Scholar, tweets information from Altmetric, bio entities from Pubtator and Clinical Trails data. This data is managed by the University of Texas at Austin and is also hosted at COVID-19 Portal (https://aihealth.ischool.utexas.edu/COVID19/#/).
DOI: 10.3886/e144261v2
title: COVID-19 research profiling data about author, bio entity, and institution

description: The outbreak of COVID-19 has a severe impact on our families, communities, and businesses. White House released the COVID-19 literature dataset (called CORD-19 dataset) which has grown exponentially into a gigantic collection of over 500,000 articles. Researchers, practitioners, and administrators need data to help them digest this enormous amount of knowledge to address vairous scientific questions related to COVID-19. This data combine CORD-19 dataset, author information from Semantic Scholar, tweets information from Altmetric, bio entities from Pubtator and Clinical Trails data. This data is managed by the University of Texas at Austin and is also hosted at COVID-19 Portal (https://aihealth.ischool.utexas.edu/COVID19/#/).
DOI: 10.12751/g-node.tltp1x
title: Inflammatory profile in chronic subdural haematoma, the post-operative course and response to dexamethasone

description: Original cytokine data for analysis