cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.19640816.v2
title: High-resolution Bronze Age palaeoenvironmental change in the Eastern Mediterranean: exploring the links between climate and societies

description: Bronze Age archaeological records from the eastern Mediterranean identify two periods of widespread so-called societal ‘collapse’ between ca. 4.50–ca. 4.20 cal ka BP and ca. 3.50–ca. 2.80 cal ka BP, respectively, which have been linked to a number of proposed causes, including climate change. However, the role of climate change in the ‘collapse’ of eastern Mediterranean Bronze Age societies has been questioned due to the resolution of climate proxy records. In this paper we present a regional synthesis of the highest resolution palaeoclimate records and compare these to archaeological evidence. By recalibrating radiocarbon dates onto a consistent timescale and using pollen, oxygen and carbon isotopes from both marine and terrestrial deposits, we reconstruct aridity at a 50-year resolution. Our results challenge a simple ‘climate destroyed society’ hypothesis. Instead, we find a more complex record of changing aridity and societal response and provide a nuanced perspective on climate versus non-climate causes of Bronze Age societal ‘collapse’ events. Our results have implications for the generation of palaeoclimate records aimed at exploring links between climate and societal change, emphasising the need for high resolution records proximal to archaeological sites.
DOI: 10.5517/ccdc.csd.cc29316p
title: CCDC 2118081: Experimental Crystal Structure Determination

description: Related Article: Miao Yang, Wang Wenjing, Kongzhao Su and Daqiang Yuan|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: 10.5281/zenodo.7220404
title: Detecting anomalies in system logs with a compact convolutional transformer - Data

description: <strong>Detecting anomalies in system logs with a compact convolutional transformer - Data</strong> Preprocessed data and a pre-trained model for the Larisch, Vitay, Hamker (2022) publication. The <em>data</em> directory contains the Blue Gene/L data set, after tokenization, shuffling, and splitting in a training and test set (BGL_masked_Xtrain.npy and BGL_masked_Xtest.npy, respectively) and the corresponding labels.<br> Additionally, the BGL_masked_Xtest_uniq.npy and BGL_masked_Ytest_uniq.npy contains the test data, where samples from the training set are removed. The <em>model</em> directory contains a pre-trained compact convolutional transformer (CCT) model. The CCT is trained on the proposed BGL training data and uses a 4x4 convolutional kernel.
DOI: 10.5281/zenodo.7220403
title: Detecting anomalies in system logs with a compact convolutional transformer - Data

description: <strong>Detecting anomalies in system logs with a compact convolutional transformer - Data</strong> Preprocessed data and a pre-trained model for the Larisch, Vitay, Hamker (2022) publication. The <em>data</em> directory contains the Blue Gene/L data set, after tokenization, shuffling, and splitting in a training and test set (BGL_masked_Xtrain.npy and BGL_masked_Xtest.npy, respectively) and the corresponding labels.<br> Additionally, the BGL_masked_Xtest_uniq.npy and BGL_masked_Ytest_uniq.npy contains the test data, where samples from the training set are removed. The <em>model</em> directory contains a pre-trained compact convolutional transformer (CCT) model. The CCT is trained on the proposed BGL training data and uses a 4x4 convolutional kernel.
DOI: 10.6084/m9.figshare.20348349
title: Data for Wyka et al. "Anatomical acclimation of mature leaves to increased irradiance in sycamore maple (Acer pseudoplatanus L.)"

description: Data are organized into four groups of variables: 1) anatomy, 2) LMA and nitrogen, 3) chlorophyll fluorescence, 4) leaf abscission, each in a separate sheet. Treatment abbreviations: PRE – measurements taken prior to transfer to full sun; CONT – measurements on plants remaining at original growth irradiances, TRANS – measurements on plants that had been transferred to full sun.
DOI: 10.6084/m9.figshare.20348349.v1
title: Data for Wyka et al. "Anatomical acclimation of mature leaves to increased irradiance in sycamore maple (Acer pseudoplatanus L.)"

description: Data are organized into four groups of variables: 1) anatomy, 2) LMA and nitrogen, 3) chlorophyll fluorescence, 4) leaf abscission, each in a separate sheet. Treatment abbreviations: PRE – measurements taken prior to transfer to full sun; CONT – measurements on plants remaining at original growth irradiances, TRANS – measurements on plants that had been transferred to full sun.
DOI: 10.5281/zenodo.7220420
title: PERTEMUAN 7, 18 OKTOBER 2022, SIKLUS AKUNTANSI PERUSAHAAN JASA, UNIVERSITAS GRESIK

description: <strong>Capaian Pembelajaran Mata Kuliah (CPMK)</strong> Mahasiswa diharapkan mampu memahami dan menyajikan laporan keuangan perusahaan jasa.
description: PERTEMUAN 7, 18 OKTOBER 2022, SIKLUS AKUNTANSI PERUSAHAAN JASA, UNIVERSITAS GRESIK
DOI: 10.5281/zenodo.7220419
title: PERTEMUAN 7, 18 OKTOBER 2022, SIKLUS AKUNTANSI PERUSAHAAN JASA, UNIVERSITAS GRESIK

description: <strong>Capaian Pembelajaran Mata Kuliah (CPMK)</strong> Mahasiswa diharapkan mampu memahami dan menyajikan laporan keuangan perusahaan jasa.
description: PERTEMUAN 7, 18 OKTOBER 2022, SIKLUS AKUNTANSI PERUSAHAAN JASA, UNIVERSITAS GRESIK
DOI: 10.6084/m9.figshare.5113960
title: Populus nigra chorology

description: Distribution map of black poplar (<i>Populus nigra</i>)<br><br>These maps were produced by combining numerous and heterogeneous data collected from atlas monographs providing complete species distribution maps, from national to regional atlases, occurrence geo-databases, scientific and grey literature.<br>The maps were created using ESRI shapefiles (*.shp, *.shx, *.dbf, *.prj files) archived in the ZIP file. Species range is mapped with polygon features (name suffix "plg"), which define continuous areas of occupancy of the species, and with point features (name suffix "pnt"), which identify more fragmented and isolated populations. If synanthropic occurrences are reported outside the species natural range, additional point and/or polygon shapefiles are also present (suffix "syn"). <br>Polygon borders delimiting species ranges are generalized across the mainland and sea boundaries. This offers the possibility to mask sea areas or to clip and extract the terrestrial range parts using GIS data layers of the users' choice. An additional version of polygon ranges are clipped with a coastline (name suffix "clip"), which have been derived from Natural Earth dataset "Admin 0 - Countries" 1:50M version 4.1.0 (https://www.naturalearthdata.com). <br><br>Please cite as:<br>Caudullo, G., Welk, E., San-Miguel-Ayanz, J., 2017. Chorological maps for the main European woody species. Data in Brief 12, 662-666. DOI: doi.org/10.1016/j.dib.2017.05.007 <br><br>Additional information and used references are on 'supplementary materials' document:<br>https://doi.org/10.6084/m9.figshare.5091901<br><br>Chorological maps are part of the "European Atlas of Forest Tree Species" project:<br>https://w3id.org/mtv/FISE-Comm/v01
DOI: 10.34740/kaggle/dsv/4345945
title: YouTube Daily
DOI: 10.5519/qd.c22k1v3l
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (30 records)
DOI: 10.5519/qd.r9om0ufx
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (52 records)
DOI: 10.5519/qd.rg4ywqks
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (52 records)
DOI: 10.5519/qd.l8elgg2k
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (30 records)
DOI: 10.6084/m9.figshare.21253596
title: Wellcome Clinical Trial Compliance Monitoring 2022

description: Report summarising Wellcome clinical trial compliance monitoring analysis for 2018-2022, alongside the raw data used to compile this report. <br> The data were analysed and the report written in September 2022.
DOI: 10.6084/m9.figshare.21253596.v1
title: Wellcome Clinical Trial Compliance Monitoring 2022

description: Report summarising Wellcome clinical trial compliance monitoring analysis for 2018-2022, alongside the raw data used to compile this report. <br> The data were analysed and the report written in September 2022.
DOI: 10.5281/zenodo.6420518
title: An analysis of the current overlay journals

description: Research data to accommodate the preprint Overlay journals: a study of the current landscape (arXiv: insert link). Detailed metadata under development.
DOI: 10.25625/o01vgg
title: [188]

description: Spectral and structural data for phenol-acetophenone complexes
DOI: 10.5281/zenodo.6617002
title: An analysis of the current overlay journals

description: Research data to accommodate the article "Overlay journals: a study of the current landscape" (https://doi.org/10.1177/09610006221125208) Identifying the sample of overlay journals was an explorative process (occurring during April 2021 to February 2022). The sample of investigated overlay journals were identified by using the websites of Episciences.org (2021), Scholastica (2021), Free Journal Network (2021), Open Journals (2021), PubPub (2022), and Wikipedia (2021). In total, this study identified 34 overlay journals. Please see the paper for more details about the excluded journal types. The journal ISSN numbers, manuscript source repositories, first overlay volumes, article volumes, publication languages, peer-review type, licence for published articles, author costs, publisher types, submission policy, and preprint availability policy were observed by inspecting journal editorial policies and submission guidelines found from journal websites. The overlay journals’ ISSN numbers were identified by examining journal websites and cross-checking this information with the Ulrich’s periodicals database (Ulrichsweb, 2021). Journals that published review reports, either with reviewers’ names or anonymously, were classified as operating with open peer-review. Publisher types defined by Laakso and Björk (2013) were used to categorise the findings concerning the publishers. If the journal website did not include publisher information, the editorial board was interpreted to publish the journal. The Organisation for Economic Co-operation and Development (OECD) field of science classification was used to categorise the journals into different domains of science. The journals’ primary OECD field of sciences were defined by the authors through examining the journal websites. Whether the journals were indexed in the Directory of Open Access Journals (DOAJ), Scopus, or Clarivate Analytics’ Web of Science Core collection’s journal master list was examined by searching the services with journal ISSN numbers and journal titles. The identified overlay journals were examined from the viewpoint of both qualitative and quantitative journal metrics. The qualitative metrics comprised the Nordic expert panel rankings of scientific journals, namely the Finnish Publication Forum, the Danish Bibliometric Research Indicator and the Norwegian Register for Scientific Journals, Series and Publishers. Searches were conducted from the web portals of the above services with both ISSN numbers and journal titles. Clarivate Analytics’ Journal Citation Reports database was searched with the use of both ISSN numbers and journal titles to identify whether the journals had a Journal Citation Indicator (JCI), Two-Year Impact Factor (IF) and an Impact Factor ranking (IF rank). The examined Journal Impact Factors and Impact Factor rankings were for the year 2020 (as released in 2021).
DOI: 10.5281/zenodo.6420517
title: An analysis of the current overlay journals

description: Research data to accommodate the article "Overlay journals: a study of the current landscape" (https://doi.org/10.1177/09610006221125208) Identifying the sample of overlay journals was an explorative process (occurring during April 2021 to February 2022). The sample of investigated overlay journals were identified by using the websites of Episciences.org (2021), Scholastica (2021), Free Journal Network (2021), Open Journals (2021), PubPub (2022), and Wikipedia (2021). In total, this study identified 34 overlay journals. Please see the paper for more details about the excluded journal types. The journal ISSN numbers, manuscript source repositories, first overlay volumes, article volumes, publication languages, peer-review type, licence for published articles, author costs, publisher types, submission policy, and preprint availability policy were observed by inspecting journal editorial policies and submission guidelines found from journal websites. The overlay journals’ ISSN numbers were identified by examining journal websites and cross-checking this information with the Ulrich’s periodicals database (Ulrichsweb, 2021). Journals that published review reports, either with reviewers’ names or anonymously, were classified as operating with open peer-review. Publisher types defined by Laakso and Björk (2013) were used to categorise the findings concerning the publishers. If the journal website did not include publisher information, the editorial board was interpreted to publish the journal. The Organisation for Economic Co-operation and Development (OECD) field of science classification was used to categorise the journals into different domains of science. The journals’ primary OECD field of sciences were defined by the authors through examining the journal websites. Whether the journals were indexed in the Directory of Open Access Journals (DOAJ), Scopus, or Clarivate Analytics’ Web of Science Core collection’s journal master list was examined by searching the services with journal ISSN numbers and journal titles. The identified overlay journals were examined from the viewpoint of both qualitative and quantitative journal metrics. The qualitative metrics comprised the Nordic expert panel rankings of scientific journals, namely the Finnish Publication Forum, the Danish Bibliometric Research Indicator and the Norwegian Register for Scientific Journals, Series and Publishers. Searches were conducted from the web portals of the above services with both ISSN numbers and journal titles. Clarivate Analytics’ Journal Citation Reports database was searched with the use of both ISSN numbers and journal titles to identify whether the journals had a Journal Citation Indicator (JCI), Two-Year Impact Factor (IF) and an Impact Factor ranking (IF rank). The examined Journal Impact Factors and Impact Factor rankings were for the year 2020 (as released in 2021).
DOI: 10.5255/ukda-sn-855975
title: Skills Acquisition and Employability Through Volunteering by Displaced Youth in Uganda, 2019-2022

description: This archive contains the full dataset of the project "Skills acquisition and employability through volunteering by displaced youth in Uganda", also known as Refugee Youth Volunteering Uganda (RYVU), an interdisciplinary research project funded by the UK’s Global Challenges Research Fund (GCRF) and Economic and Social Research Council (ESRC). The archive includes the project's quantitative and qualitative data collected in four locations in Uganda (Kampala city, and the refugee settlements of Bidibidi, Nakivale and Rwamwanja).
DOI: 10.15156/bio/sh000001.07fu
title: SH000001.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh000002.07fu
title: SH000002.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh000003.07fu
title: SH000003.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh000004.07fu
title: SH000004.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh000005.07fu
title: SH000005.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh000006.07fu
title: SH000006.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh000007.07fu
title: SH000007.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.