cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5285/ab8d21568c81491fbb9a300c36884af7
title: ESA Lakes Climate Change Initiative (Lakes_cci): Lake products, Version 2.0

description: This dataset contains the Lakes Essential Climate Variable, which is comprised of processed satellite observations at the global scale, over the period 1992-2020, for over 2000 inland water bodies. This dataset was produced by the European Space Agency (ESA) Lakes Climate Change Initiative (Lakes_cci) project. For more information about the Lakes_cci please visit the project website. This is version 2.0 of the dataset. The five thematic climate variables included in this dataset are: • Lake Water Level (LWL), derived from satellite altimetry, is fundamental to understand the balance between water inputs and water loss and their connection with regional and global climate change. • Lake Water Extent (LWE), modelled from the relation between LWL and high-resolution spatial extent observed at set time-points, describes the areal extent of the water body. This allows the observation of drought in arid environments, expansion in high Asia, or impact of large-scale atmospheric oscillations on lakes in tropical regions for example. . • Lake Surface Water temperature (LSWT), derived from optical and thermal satellite observations, is correlated with regional air temperatures and is informative about vertical mixing regimes, driving biogeochemical cycling and seasonality. • Lake Ice Cover (LIC), determined from optical observations, describes the freeze-up in autumn and break-up of ice in spring, which are proxies for gradually changing climate patterns and seasonality. • Lake Water-Leaving Reflectance (LWLR), derived from optical satellite observations, is a direct indicator of biogeochemical processes and habitats in the visible part of the water column (e.g. seasonal phytoplankton biomass fluctuations), and an indicator of the frequency of extreme events (peak terrestrial run-off, changing mixing conditions). Data generated in the Lakes_cci are derived from multiple satellite sensors including: TOPEX/Poseidon, Jason, ENVISAT, SARAL, Sentinel 2-3, Landsat OLI, ERS, MODIS Terra/Aqua and Metop. Detailed information about the generation and validation of this dataset is available from the Lakes_cci documentation available on the project website.
DOI: 10.5258/soton/d2126
title: Dataset for Raman enhanced four-wave mixing in silicon core fibers

description: This dataset supports the publication "Raman enhanced four-wave mixing in silicon core fibers" published in Optics Letters, including four Excel files and a Readme.txt.
DOI: 10.7303/syn27837434
title: Broad transcriptomic dysregulation across the cerebral cortex in ASD
DOI: 10.21227/hrkm-wt26
title: A READING AND SELF-PRESENTATION SPEECH CHARACTERISTICS DATASET 

description: The following dataset consists of samples of acoustic characteristics of 356 Russian-speaking subjects and measured psychological traits. All the recordings (5701 samples) were processed and acoustic characteristics were calculated.
DOI: 10.5281/zenodo.6367538
title: A WISE view of extreme AGB stars

description: The files in this distribution are related to the paper: "A WISE view of extreme AGB stars", by M.A.T. Groenewegen published in Astronomy & Astrophysics 659, A145 (2022).<br>
DOI: 10.5281/zenodo.5825878
title: A WISE view of extreme AGB stars

description: The files in this distribution are related to the paper: "A WISE view of extreme AGB stars", by M.A.T. Groenewegen published in Astronomy & Astrophysics 659, A145 (2022).<br>
DOI: 10.48370/ofd/wqbmnj
title: Glischrochilus quadripunctatus (Linnaeus, 1758), C-551

description: Coleoptera collection
DOI: 10.5281/zenodo.5517655
title: Spliced isoforms of the cardiac Nav1.5 channel modify channel activation by distinct structural mechanisms: Molecular dynamics coordinate and trajectory files

description: Molecular dynamics files associated with the publication: Spliced isoforms of the cardiac Nav1.5 channel modify channel activation by distinct structural mechanisms
DOI: 10.5281/zenodo.5517654
title: Spliced isoforms of the cardiac Nav1.5 channel modify channel activation by distinct structural mechanisms: Molecular dynamics coordinate and trajectory files

description: Molecular dynamics files associated with the publication: Spliced isoforms of the cardiac Nav1.5 channel modify channel activation by distinct structural mechanisms
DOI: 10.25505/fiz.icsd.cc29zvdk
title: CSD 2144809: Experimental Crystal Structure Determination

description: Related Article: jianbo hu|2022|ICSD Communication|||
DOI: 10.14278/rodare.1457
title: Raw Data: Recycling of rare earth containing waste with peptide-functionalized floating glass bubbles in a phage mimicking approach

description: Raw data for the Publication "Recycling of rare earth containing waste with peptide-functionalized floating glass bubbles in a phage mimicking approach"
DOI: 10.14278/rodare.1456
title: Raw Data: Recycling of rare earth containing waste with peptide-functionalized floating glass bubbles in a phage mimicking approach

description: Raw data for the Publication "Recycling of rare earth containing waste with peptide-functionalized floating glass bubbles in a phage mimicking approach"
DOI: 10.48370/ofd/ouxntf/potfpp
title: Cryptarcha strigata.jpg

description: :unav
DOI: 10.48370/ofd/ouxntf
title: Cryptarcha strigata (Fabricius, 1787), C-552

description: Coleoptera collection
DOI: 10.26180/19358699
title: 3D multiplane dSTORM imaging of whole nuclear lamina

description: Raw data of single molecule photoswitching for 3D multiplane dSTORM of whole COS-7 nuclear lamina. Data from the first z plane, taken at time = 0 h, and the last z plane, taken at time = 1 h, are shown. Movies were captured at 50Hz under high laser power and in the presence of a reducing switching buffer.<br>Also included is the complete SM coordinate list text file to reconstruct the 3D image of the whole COS-7 nuclear lamina.
DOI: 10.26180/19358699.v1
title: 3D multiplane dSTORM imaging of whole nuclear lamina

description: Raw data of single molecule photoswitching for 3D multiplane dSTORM of whole COS-7 nuclear lamina. Data from the first z plane, taken at time = 0 h, and the last z plane, taken at time = 1 h, are shown. Movies were captured at 50Hz under high laser power and in the presence of a reducing switching buffer.<br>Also included is the complete SM coordinate list text file to reconstruct the 3D image of the whole COS-7 nuclear lamina.
DOI: 10.23728/b2share.e9e0a50d2fa44e068ef12d51305e041f
title: Research Data for "On the Composition of the Long Tail of Business Processes: Implications from a Process Mining Study"

description: Fischer, Marcus; Hofmann, Adrian; Imgrund, Florian; Janiesch, Christian; Winkelmann, Axel: On the Composition of the Long Tail of Business Processes: Implications from a Process Mining Study. Information Systems. 2020. https://doi.org/10.1016/j.is.2020.101689 Abstract: "Digital transformation forces companies to rethink their processes to meet current customer needs. Business Process Management (BPM) can provide the means to structure and tackle this change. How-ever, most approaches to BPM face restrictions on the number of processes they can optimize at a time due to complexity and resource restrictions. Investigating this shortcoming, the concept of the long tail of business processes suggests a hybrid approach that entails managing important processes centrally, while incrementally improving the majority of processes at their place of execution. This study scrutinizes this observation as well as corresponding implications. First, we define a system of indicators to automatically prioritize processes based on execution data. Second, we use process mining to analyze processes from multiple companies to investigate the distribution of process value in terms of their process variants. Third, we examine the characteristics of the process variants contained in the short head and the long tail to derive and justify recommendations for their management. Our results suggest that the assumption of a long-tailed distribution holds across companies and indicators and also applies to the overall improvement potential of processes and their variants. Across all cases, process variants in the long tail were characterized by fewer customer contacts, lower execution frequencies, and a larger number of involved stakeholders, making them suitable candidates for distributed improvement." *** Using this data for academic publications is granted explicitly. *** The dataset was created by researchers working at the University of Würzburg.
DOI: 10.48370/ofd/wn0ggk/gmslyt
title: Cryptarcha strigata.jpg

description: :unav
DOI: 10.48370/ofd/wn0ggk
title: Cryptarcha strigata (Fabricius, 1787), C-553

description: Coleoptera collection
DOI: 10.23728/b2share.4d33fde314e84f2cb63f73707518b032
title: Appendix for Mayr et al. “Applications and Challenges of Task Mining: A Literature Review”

description: Dataset for the article: Mayr, Alexander ; Herm, Lukas-Valentin ; Wanner, Jonas ; Janiesch, Christian : Applications and Challenges of Task Mining: A Literature Review. Accepted at: Proceedings of the 30th European Conference on Information Systems. Timișoara 2022. Abstract: Task mining is a technological innovation that combines current developments in process mining and data mining. Using task mining, the interactions of workers with their workstations can be recorded, processed, and linked with the business data of the organization. The approach can provide a holistic picture of the business processes and related tasks. Currently, there is no overview of application scenarios and the challenges of task mining. In our work, we reflect application scenarios as well as technological, legal, and organizational challenges of task mining using a structured literature review. The application areas include discovery of automation potentials, monitoring, as well as optimization of business processes. The challenges include the cleansing, collection, data protection, explainability, merging, organization, processing, and segmentation of task mining data. *** Using this data for academic publications is granted explicitly. *** The dataset was created jointly by researchers working at the University of Würzburg and TU Dortmund University.
DOI: 10.23728/b2share.08b7ff704f724b94a61b4a6cac0fe1e0
title: Supplementary Material for "Process Data Properties Matter: Introducing Gated Convolutional Neural Networks (GCNN) and Key-Value-Predict Attention Networks (KVP) for Next Event Prediction with Deep Learning"

description: Supplementary material for the article: Heinrich, Kai ; Zschech, Patrick ; Janiesch, Christian ; Bonin, Markus: Process Data Properties Matter: Introducing Gated Convolutional Neural Networks (GCNN) and Key-Value-Predict Attention Networks (KVP) for Next Event Prediction with Deep Learning. In: Decision Support Systems, 2021. Abstract: "Predicting next events in predictive process monitoring enables companies to manage and control processes at an early stage and reduce their action distance. In recent years, approaches have steadily moved from classical statistical methods towards the application of deep neural network architectures, which outperform the former and enable analysis without explicit knowledge of the underlying process model. While the focus of prior research is on the long short-term memory network architecture, more deep learning architectures offer promising extensions that have proven useful for other applications of sequential data. In our work, we introduce a gated convolutional neural network and a key-value-predict attention network to the task of next event prediction. In a comprehensive evaluation study on 11 real-life benchmark datasets, we show that these two novel architectures surpass prior work in 34 out of 44 metric-dataset combinations. For our evaluation, we consider the effects of process data properties, such as sparsity, variation, and repetitiveness, and discuss their impact on the prediction quality of the different deep learning architectures. Similarly, we evaluate their classification properties in terms of generalization and handling class imbalance. Our results provide guidance for researchers and practitioners alike on how to select, validate, and comprehensively benchmark (novel) predictive process monitoring models. In particular, we highlight the importance of sufficiently diverse process data properties in event logs and the comprehensive reporting of multiple performance indicators to achieve meaningful results." Data is available under Creative Commons Attribution-ShareAlike (CC-BY-SA) http://creativecommons.org/licenses/by-sa/4.0/ Software code is available under GNU General Public License (GNU GPL v3) http://www.gnu.org/licenses/gpl-3.0.html *** Using this data for academic publications is granted explicitly. *** The dataset was created jointly by researchers working at the Technische Universität Dresden and TU Dortmund University.
DOI: 10.5281/zenodo.6367083
title: Superdiversity dataset

description: The <strong>Superdiversity dataset</strong> includes the <em>Superdiversity Index</em> (SI) calculated on the diversity of the emotional content expressed in texts of different communities. The emotional valences of words used by a community are extracted from Twitter data produced by that specific community.<br> The Superdiversity dataset includes the SI built on <strong>Twitter data</strong> and <strong>lexicon-based Sentiment Analysis</strong>. In addition, the dataset comprises other possible diversity measures calculated from the same data from which the SI is calculated, such as the number of tweets in the community language and the Type-Token Ratio, the number of languages in a community. <em>Note</em> The SI ranges in [0, 1]: a value of 0 means an emotional content very close between the computed valences and a standard emotional lexicon. a value of 0.5 indicates no correlation between the emotional content of words used by the community on Twitter and the standard emotional content. a value of 1 would correspond to the use of terms with the opposite emotional content compared to the standard. Data is computed at different three geographical scales based on the <strong>Classification of Territorial Units for Statistics</strong> (NUTS), i.e., NUTS1, NUTS2, and NUTS3, for two different nations, <strong>Italy</strong> and the <strong>United Kingdom</strong>.
DOI: 10.48370/ofd/ppcakt/hbrdwx
title: Cryptarcha undata.jpg

description: :unav
DOI: 10.48370/ofd/ppcakt
title: Cryptarcha undata (Olivier A.G. 1790), C-554

description: Coleoptera collection
DOI: 10.25919/vpqb-2h51
title: Parkes observations for project P737 semester 2021OCTS_09

description: The aim of this proposal is to carry out tests of the new backend instruments which cannot be carried out during standard maintenance periods. The scheduled time is used to measure beam shapes, determine polarisation calibration solutions and commission the National Facility observing modes for the new wide-band receiver.
DOI: 10.5258/soton/d2065
title: Dataset for "Long range Raman-amplified distributed acoustic sensor based on spontaneous Brillouin scattering for large strain sensing"

description: This dataset supports the publication: Bakhtiari Gorajoobi, Shahab et al (2022) , "Long range Raman-amplified distributed acoustic sensor based on spontaneous Brillouin scattering for large strain sensing", Senors Vol22(5). Data of all figures are given in excel files, and labeled according to the content of the article. Please refer to the README.txt file for detailed description of the dataset.
DOI: 10.25345/c5k649w8m
title: MassIVE MSV000089080 - ADAMTS18+ telocytes maintain a polarized VEGFA signaling domain and fenestrations in intestinal villus blood vessels
title: Blood samples from Adamts18 KO and WT mice gavaged with saline, U-13C glucose or protein solution
DOI: 10.5517/ccdc.csd.cc20859s
title: CCDC 1854894: Experimental Crystal Structure Determination

description: Related Article: Raziullah, Mohit Kumar, Ruchir Kant, Dipankar Koley|2019|Adv.Synth.Catal.|361|3108|doi:10.1002/adsc.201900166
DOI: 10.5517/ccdc.csd.cc26rcmz
title: CCDC 2048251: Experimental Crystal Structure Determination

description: Related Article: Jian-Ping Xu, Wen Zou, Shun-Ze Zhan, Ji Zheng, Kun Wu, Guo-Hui Zhang, Jing-Hong Li, Mian Li, Guo-Hong Ning, Dan Li|2021|Inorg.Chem.Front.|8|3222|doi:10.1039/D1QI00409C
DOI: 10.5517/ccdc.csd.cc26rcw7
title: CCDC 2048259: Experimental Crystal Structure Determination

description: Related Article: Jian-Ping Xu, Wen Zou, Shun-Ze Zhan, Ji Zheng, Kun Wu, Guo-Hui Zhang, Jing-Hong Li, Mian Li, Guo-Hong Ning, Dan Li|2021|Inorg.Chem.Front.|8|3222|doi:10.1039/D1QI00409C
DOI: 10.5517/ccdc.csd.cc26rd1f
title: CCDC 2048264: Experimental Crystal Structure Determination

description: Related Article: Jian-Ping Xu, Wen Zou, Shun-Ze Zhan, Ji Zheng, Kun Wu, Guo-Hui Zhang, Jing-Hong Li, Mian Li, Guo-Hong Ning, Dan Li|2021|Inorg.Chem.Front.|8|3222|doi:10.1039/D1QI00409C
DOI: 10.5281/zenodo.6367595
title: Definition of the terminologies in the SQMM

description: This pdf includes definition of the terminologies in the SQMMs
DOI: 10.5258/soton/d2151
title: HoneyPot Data for PhD Thesis - A Multi-Level Governance Framework for Increasing Awareness and Reducing Cyber Misuse in Next Generation Cross Border Voice Communication Networks & IoT

description: Dataset to support University of Southampton Doctoral Thesis " Multi-Level Governance Framework for Increasing Awareness and Reducing Cyber Misuse in Next Generation Cross Border Voice Communication Networks & IoT. Data is csv files. There are two datasets, one is restricted to researchers, please use this link to request the data. https://library.soton.ac.uk/datarequest
DOI: 10.5281/zenodo.4683711
title: Data to publication: Fibre optic measurements and model uncertainty quantification for Fe-SMA strengthened concrete structures

description: This dataset contains the results of an experimental campaign, presented in the publication "Fibre optic measurements and model uncertainty quantification for Fe-SMA strengthened concrete structures". The publication covers fibre optic measurements inside large-scale specimens subjected to external load. The specimens comprised reinforced concrete slabs, strengthened with reinforcement bars made from iron-based shape memory alloy.
DOI: 10.5281/zenodo.4683710
title: Data to publication: Fibre optic measurements and model uncertainty quantification for Fe-SMA strengthened concrete structures

description: This dataset contains the results of an experimental campaign, presented in the publication "Fibre optic measurements and model uncertainty quantification for Fe-SMA strengthened concrete structures". The publication covers fibre optic measurements inside large-scale specimens subjected to external load. The specimens comprised reinforced concrete slabs, strengthened with reinforcement bars made from iron-based shape memory alloy.
DOI: 10.5281/zenodo.6367510
title: Language intensity classification and Neuronal Networks

description: Kohonen Self-Organizing Maps (SOM) are a particular type of artificial neural network created by Teuvo Kohonen. Their unsupervised learning makes them suitable for application, among other things, to grouping tasks. Occupations have been grouped into this analysis considering the similarity in value of the variables that define this occupation in terms of language proficiency requirements. The 8 variables used were: v1-speaking skills, v2-writing skills, v3-speech clarity, v4-speech recognition, v5-English knowledge, v6-speaking ability, v7-communication with people outsiders, v8-communication with superiors, equals or subordinates. After applying this authomatic classification technique, the SOC occupations are classified according to five distinc groups with decreasing linguistic intensity: Class 1: High linguistic intenisty requirements<br> Class 2: Medium-high linguistic intenisty requirements<br> Class 3: Medium linguistic intenisty requirements<br> Class 4: Medium-low linguistic intenisty requirements<br> Class 5: Low linguistic intenisty requirements
description: For more details on the methodology, see Kohonen, T. (2001). Self-Organizing Maps. Springer Series in Information Sciences. Berlin, Germany: Springer-Verlag. 3th edition. For more details on its use in linguistic skills analysis, see: Molina-Cobo, M.C .; Sorrosal-Forradellas, M.T. and Vidal, A. (2019) Las ocupaciones laborales en funcion de los requisitos de competencias linguisticas: una categorizacion mediante redes neuronales artificiales. Revista RIO, 19, 193-221 and Sorrosal-Forradellas, M.T. Molina-Cobo, M.C and Vidal, A. (2021) Clasificación de ocupaciones mediante redes neuronales artificiales según requisitos lingüísticos In: Vidal and Alarcon (eds.) Lenguaje y Ocupaciones. Editorial URV
description: {"references": ["http://www.publicacions.urv.cat/cataleg/recerca/15-cataleg/recerca/899-ocupaciones-y-lenguaje", "https://www.revista-rio.org/index.php/revista_rio/article/view/323"]}
DOI: 10.5281/zenodo.6367509
title: Language intensity classification and Neuronal Networks

description: Kohonen Self-Organizing Maps (SOM) are a particular type of artificial neural network created by Teuvo Kohonen. Their unsupervised learning makes them suitable for application, among other things, to grouping tasks. Occupations have been grouped into this analysis considering the similarity in value of the variables that define this occupation in terms of language proficiency requirements. The 8 variables used were: v1-speaking skills, v2-writing skills, v3-speech clarity, v4-speech recognition, v5-English knowledge, v6-speaking ability, v7-communication with people outsiders, v8-communication with superiors, equals or subordinates. After applying this authomatic classification technique, the SOC occupations are classified according to five distinc groups with decreasing linguistic intensity: Class 1: High linguistic intenisty requirements<br> Class 2: Medium-high linguistic intenisty requirements<br> Class 3: Medium linguistic intenisty requirements<br> Class 4: Medium-low linguistic intenisty requirements<br> Class 5: Low linguistic intenisty requirements
description: For more details on the methodology, see Kohonen, T. (2001). Self-Organizing Maps. Springer Series in Information Sciences. Berlin, Germany: Springer-Verlag. 3th edition. For more details on its use in linguistic skills analysis, see: Molina-Cobo, M.C .; Sorrosal-Forradellas, M.T. and Vidal, A. (2019) Las ocupaciones laborales en funcion de los requisitos de competencias linguisticas: una categorizacion mediante redes neuronales artificiales. Revista RIO, 19, 193-221 and Sorrosal-Forradellas, M.T. Molina-Cobo, M.C and Vidal, A. (2021) Clasificación de ocupaciones mediante redes neuronales artificiales según requisitos lingüísticos In: Vidal and Alarcon (eds.) Lenguaje y Ocupaciones. Editorial URV
description: {"references": ["http://www.publicacions.urv.cat/cataleg/recerca/15-cataleg/recerca/899-ocupaciones-y-lenguaje", "https://www.revista-rio.org/index.php/revista_rio/article/view/323"]}
DOI: 10.25399/unisadata.19382957
title: Dead on arrival (DOA) among broilers at a poultry abattoir in Mopani District of Limpopo Province, South Africa.

description: The study investigate the trend in the proportions of DOAs and factors associated with DOA’s among chickens slaughtered at a commercial abattoir in the Mopani district in Limpopo, South Africa.<br>
DOI: 10.25399/unisadata.19382957.v1
title: Dead on arrival (DOA) among broilers at a poultry abattoir in Mopani District of Limpopo Province, South Africa.

description: The study investigate the trend in the proportions of DOAs and factors associated with DOA’s among chickens slaughtered at a commercial abattoir in the Mopani district in Limpopo, South Africa.<br>
DOI: 10.48370/ofd/n7cxsb/w2l6yl
title: Cryptarcha undata.jpg

description: :unav
DOI: 10.48370/ofd/n7cxsb
title: Cryptarcha undata (Olivier A.G. 1790), C-555

description: Coleoptera collection
DOI: 10.48370/ofd/na58mz
title: Colydium elongatum (Fabricius,1787), C-556

description: Coleoptera collection