cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10067451
title: Rigid and hinged very large floating structure (VLFS) dataset - Kelvin Hydrodynamics Laboratory

description: This dataset corresponds to the measurements performed at the Kelvin Hydrodynamics Laboratory at the University of Strathclyde, in August 2022, to assess the motion performance and internal loading of a rigid and hinged very large floating structure (VLFS) under regular waves. The VLFS was constructed with three pontoons and two hinges. The hinges were replaced with aluminium steel bars to built the rigid VLFS. The dimensions of each pontoon of the VLFS were 580 mm x 580 mm x 52 mm. Each pontoon was built with 2 mm layer of carbon fibre and a 50 mm layer of PVC foam.
The VLFS was tested in regular waves at two incidences: 0 degrees and 30 degrees. For 0 degree incidence, the wave frequencies tested ranged from 0.4 to1.6 Hz in intervals of 0.1 Hz. Four wave heights were tested, h=5, 10, 20 and 40 mm. For 30 degree incidence, the same range of frequencies were tested, but only one wave height, h=5 mm. Preliminary results for some of the data at 0 degrees incidence can be found in the conference paper: https://doi.org/10.36688/ewtec-2023-389.  Further analysis of this dataset and additional results are in preparation for a journal manuscript.
The following files are included as part of the dataset:

Motion files (Matlab files).
Strain gauge and wave height files (Matlab files).
Data description file - Description of files.
Test matrix - Test cases summarised with nomenclature used in files.
Matlab script to sort out position of motion spheres as depicted in Figure 1.
Video of the hinged VLFS subject to a train of regular waves at f=0.8 Hz, i.e. when the wavelength is of similar length to the length of the platform, i.e. f=0.8 Hz.

The motion files contain the time series information recorded for each of the motion detection spheres. Because the motion raw data is not labelled sequentially, it is necessary to run the Matlab file included in the data repository to sort out the information of the spheres.
The strain gauge files contain the raw strain gauge data (8 channels) and the wave gauge data with the file number describing the corresponding test in the test matrix.
The VLFS was equipped with 36 motion detection spheres and 8 strain gauges. The diagram and notation of each sphere is depicted in Figure 1. Figure 1 is available in the Data description document.
DOI: 10.13120/34939086-0b2e-42f2-b78c-6e9be5c01c6e
title: Contaminants: Hydrocarbons (PAH) - Benzo(a)pyrene (measurements counts), v2023
title: Contaminants: Hydrocarbons (PAH) - Benzo(a)pyrene (measurements counts), v2023

description: This product displays for Benzo(a)pyrene, positions with values counts that have been measured per matrix and are present in EMODnet validated datasets. The product displays positions for all available years and per year.
DOI: 10.13120/ba4280dc-1e5b-4b36-9853-b99135093ec7
title: Contaminants: Hydrocarbons (PAH) - Naphthalene (measurements counts), v2023
title: Contaminants: Hydrocarbons (PAH) - Naphthalene (measurements counts), v2023

description: This product displays for Naphthalene, positions with values counts that have been measured per matrix and are present in EMODnet validated datasets. The product displays positions for all available years and per year.
DOI: 10.25403/upresearchdata.24358654
title: Analysis of themes generated for the development of a co-production model for human settlements in South Africa

description: The data contained here in comprises atlas.ti data as well as the combined report and tables which indicate how the themes were generated.Data was collected through interviews. All 24 interviews were conducted online, via Microsoft Teams. The recordings of the interviews were sent to a professional transcription service provider and where the sound was not clear, the researcher was able to fill in the gaps due to familiarity with the subject matter. The transcriptions were given a unique identifier once loaded on ATLAS.ti. The unique identifiers are NGO 1-12 and MinTech 1-9.The results were obtained from inductive thematic analysis. The qualitative analysis utilised by the researcher entailed a six-phase thematic analytical process, which includes familiarising yourself with the data, generating initial codes, searching for themes, reviewing the themes, defining and naming the themes, and producing the report.<br>
DOI: 10.25403/upresearchdata.24358654.v1
title: Analysis of themes generated for the development of a co-production model for human settlements in South Africa

description: The data contained here in comprises atlas.ti data as well as the combined report and tables which indicate how the themes were generated.Data was collected through interviews. All 24 interviews were conducted online, via Microsoft Teams. The recordings of the interviews were sent to a professional transcription service provider and where the sound was not clear, the researcher was able to fill in the gaps due to familiarity with the subject matter. The transcriptions were given a unique identifier once loaded on ATLAS.ti. The unique identifiers are NGO 1-12 and MinTech 1-9.The results were obtained from inductive thematic analysis. The qualitative analysis utilised by the researcher entailed a six-phase thematic analytical process, which includes familiarising yourself with the data, generating initial codes, searching for themes, reviewing the themes, defining and naming the themes, and producing the report.<br>
DOI: 10.13120/8e577af5-20f5-43b9-85cb-c8de0175e495
title: Contaminants: Pesticides and biocides - DDT-DDE-DDD (median values), v2023
title: Contaminants: Pesticides and biocides - DDT-DDE-DDD (median values), v2023

description: This product displays for DDT, DDE, and DDD, median values of the last 6 available years that have been measured per matrix and are present in EMODnet validated datasets. The median values ranges are derived from the following percentiles: 0-25%, 25-75%, 75-90%, &gt;90%. Only "good data" are used, namely data with Quality Flag=1, 2, 6, Q (SeaDataNet Quality Flag schema). For water, only surface values are used (0-15 m), for sediment and biota data at all depths are used.
DOI: 10.13120/62be8610-65e4-42ee-a0d3-0bd129fbb0d3
title: Contaminants: Pesticides and biocides - Hexachlorobenzene (median values), v2023
title: Contaminants: Pesticides and biocides - Hexachlorobenzene (median values), v2023

description: This product displays for Hexachlorobenzene, median values of the last 6 available years that have been measured per matrix and are present in EMODnet validated datasets. The median values ranges are derived from the following percentiles: 0-25%, 25-75%, 75-90%, &gt;90%. Only "good data" are used, namely data with Quality Flag=1, 2, 6, Q (SeaDataNet Quality Flag schema). For water, only surface values are used (0-15 m), for sediment and biota data at all depths are used.
DOI: 10.13120/bd32ec5e-ca2a-4c9c-b7e5-ff2a18a0f0e2
title: Contaminants: Antifoulants - Tributyltin (median values), v2023
title: Contaminants: Antifoulants - Tributyltin (median values), v2023

description: This product displays for Tributyltin, median values of the last 6 available years that have been measured per matrix and are present in EMODnet validated datasets. The median values ranges are derived from the following percentiles: 0-25%, 25-75%, 75-90%, &gt;90%. Only "good data" are used, namely data with Quality Flag=1, 2, 6, Q (SeaDataNet Quality Flag schema). For water, only surface values are used (0-15 m), for sediment and biota data at all depths are used.
DOI: 10.6084/m9.figshare.24153333
title: The Dataset used for exploring benefits and practices of applying analytics in software startups

description: This dataset has been used to synthesize the results of the video data on analytics in startups
DOI: 10.6084/m9.figshare.24153333.v3
title: The Dataset used for exploring benefits and practices of applying analytics in software startups

description: This dataset has been used to synthesize the results of the video data on analytics in startups
DOI: 10.6084/m9.figshare.24153333.v2
title: The Dataset for the paper submission to ICSOB 2023

description: This dataset has been used to synthesize the results of the video data on analytics in startups
DOI: 10.13120/c75e059c-6b0f-468a-aadc-d7eee35d6e50
title: Contaminants: Antifoulants - Triphenyltin (median values), v2023
title: Contaminants: Antifoulants - Triphenyltin (median values), v2023

description: This product displays for Triphenyltin, median values of the last 6 available years that have been measured per matrix and are present in EMODnet validated datasets. The median values ranges are derived from the following percentiles: 0-25%, 25-75%, 75-90%, &gt;90%. Only "good data" are used, namely data with Quality Flag=1, 2, 6, Q (SeaDataNet Quality Flag schema). For water, only surface values are used (0-15 m), for sediment and biota data at all depths are used.
DOI: 10.13120/a5a0770a-b457-4dca-a157-79eb4617352a
title: Contaminants: Heavy metals - Mercury (median values), v2023
title: Contaminants: Heavy metals - Mercury (median values), v2023

description: This product displays for Mercury, median values of the last 6 available years that have been measured per matrix and are present in EMODnet validated datasets. The median values ranges are derived from the following percentiles: 0-25%, 25-75%, 75-90%, &gt;90%. Only "good data" are used, namely data with Quality Flag=1, 2, 6, Q (SeaDataNet Quality Flag schema). For water, only surface values are used (0-15 m), for sediment and biota data at all depths are used.
DOI: 10.13120/ca8f35f8-66ba-48f5-badc-a6dae21fd967
title: Contaminants: Heavy metals - Cadmium (median values), v2023
title: Contaminants: Heavy metals - Cadmium (median values), v2023

description: This product displays for Cadmium, median values of the last 6 available years that have been measured per matrix and are present in EMODnet validated datasets. The median values ranges are derived from the following percentiles: 0-25%, 25-75%, 75-90%, &gt;90%. Only "good data" are used, namely data with Quality Flag=1, 2, 6, Q (SeaDataNet Quality Flag schema). For water, only surface values are used (0-15 m), for sediment and biota data at all depths are used.
DOI: 10.13120/f42c4021-a315-45ab-9ae8-d4c633d62815
title: Contaminants: Heavy metals - Lead (median values), v2023
title: Contaminants: Heavy metals - Lead (median values), v2023

description: This product displays for Lead, median values of the last 6 available years that have been measured per matrix and are present in EMODnet validated datasets. The median values ranges are derived from the following percentiles: 0-25%, 25-75%, 75-90%, &gt;90%. Only "good data" are used, namely data with Quality Flag=1, 2, 6, Q (SeaDataNet Quality Flag schema). For water, only surface values are used (0-15 m), for sediment and biota data at all depths are used.
DOI: 10.13120/329036eb-dfce-4f73-bf3f-e10f7d14ab3b
title: Contaminants: Heavy metals - Nickel (median values), v2023
title: Contaminants: Heavy metals - Nickel (median values), v2023

description: This product displays for Nickel, median values of the last 6 available years that have been measured per matrix and are present in EMODnet validated datasets. The median values ranges are derived from the following percentiles: 0-25%, 25-75%, 75-90%, &gt;90%. Only "good data" are used, namely data with Quality Flag=1, 2, 6, Q (SeaDataNet Quality Flag schema). For water, only surface values are used (0-15 m), for sediment and biota data at all depths are used.
DOI: 10.13120/25a1dd23-8d4a-4b72-8a6b-9351fae92aee
title: Contaminants: Hydrocarbons (PAH) - Anthracene (median values), v2023
title: Contaminants: Hydrocarbons (PAH) - Anthracene (median values), v2023

description: This product displays for Anthracene, median values of the last 6 available years that have been measured per matrix and are present in EMODnet validated datasets. The median values ranges are derived from the following percentiles: 0-25%, 25-75%, 75-90%, &gt;90%. Only "good data" are used, namely data with Quality Flag=1, 2, 6, Q (SeaDataNet Quality Flag schema). For water, only surface values are used (0-15 m), for sediment and biota data at all depths are used.
DOI: 10.14473/csda/ohlwnl
title: Naše společnost 2018 - únor

description: Výzkum provedl výzkumný tým CVVM Sociologického ústavu AV ČR, v.v.i., v rámci výzkumu „Naše společnost 2018". Sběr dat provedla tazatelská síť CVVM.
DOI: 10.13120/926a693e-cdc3-42d8-9f27-e28792432305
title: Contaminants: Hydrocarbons (PAH) - Fluoranthene (median values), v2023
title: Contaminants: Hydrocarbons (PAH) - Fluoranthene (median values), v2023

description: This product displays for Fluoranthene, median values of the last 6 available years that have been measured per matrix and are present in EMODnet validated datasets. The median values ranges are derived from the following percentiles: 0-25%, 25-75%, 75-90%, &gt;90%. Only "good data" are used, namely data with Quality Flag=1, 2, 6, Q (SeaDataNet Quality Flag schema). For water, only surface values are used (0-15 m), for sediment and biota data at all depths are used.
DOI: 10.6084/m9.figshare.24552340
title: All data used in the manuscript from Small increases in ambient temperature reduce offspring body mass in an equatorial mammal

description: Human-induced climate change is leading to temperature rises, along with increases in the frequency and intensity of heatwaves. Many animals respond to high temperatures through behavioural thermoregulation, for example by resting in the shade, but this may impose opportunity costs by reducing foraging time (therefore energy supply), and so may be most effective when food is abundant. However, the heat dissipation limit theory (HDL) proposes that even when energy supply is plentiful, high temperatures can still have negative effects. This is because dissipating excess heat becomes harder, which limits processes that generate heat such as lactation. We tested predictions from HDL on a wild, equatorial population of banded mongooses (<i>Mungos mungo</i>). In support of HDL, higher ambient temperatures led to lighter pups, and increasing food availability made little difference to pup weight under hotter conditions. This suggests that direct physiological constraints rather than opportunity costs of behavioural thermoregulation explain the negative impact of high temperatures on pup growth. Our results indicate that climate change may be particularly important for equatorial species, which often experience high temperatures year-round so cannot time reproduction to coincide with cooler conditions.
DOI: 10.13120/3e72d77f-c922-45f6-97cb-69c2fea166fb
title: Contaminants: Hydrocarbons (PAH) - Benzo(a)pyrene (median values), v2023
title: Contaminants: Hydrocarbons (PAH) - Benzo(a)pyrene (median values), v2023

description: This product displays for Benzo(a)pyrene, median values of the last 6 available years that have been measured per matrix and are present in EMODnet validated datasets. The median values ranges are derived from the following percentiles: 0-25%, 25-75%, 75-90%, &gt;90%. Only "good data" are used, namely data with Quality Flag=1, 2, 6, Q (SeaDataNet Quality Flag schema). For water, only surface values are used (0-15 m), for sediment and biota data at all depths are used.
DOI: 10.13120/6ebbafcb-79fa-4751-b0b6-585938ee0e5a
title: Contaminants: Hydrocarbons (PAH) - Naphthalene (median values), v2023
title: Contaminants: Hydrocarbons (PAH) - Naphthalene (median values), v2023

description: This product displays for Naphthalene, median values of the last 6 available years that have been measured per matrix and are present in EMODnet validated datasets. The median values ranges are derived from the following percentiles: 0-25%, 25-75%, 75-90%, &gt;90%. Only "good data" are used, namely data with Quality Flag=1, 2, 6, Q (SeaDataNet Quality Flag schema). For water, only surface values are used (0-15 m), for sediment and biota data at all depths are used.
DOI: 10.5281/zenodo.10118739
title: Valorization of plastic wastes into value-add biochar production through co-pyrolysis with biomass residues
DOI: 10.5281/zenodo.10118738
title: Valorization of plastic wastes into value-add biochar production through co-pyrolysis with biomass residues
DOI: 10.5285/834dc665-1ae6-464d-8c29-265a9be5229a
title: Arctic Melt Pond Fraction and Binary Classification, 2021-2022

description: This dataset provides daily, 8-day, and monthly Arctic melt pond fractions and binary classification, from 2021-05-01 to 2022-08-31. Level-2 MODerate resolution Imaging Spectroradiometer (MODIS) top-of-the-atmosphere (TOA) reflectances for bands 1-4 were obtained, to which two machine learning algorithms such as multi-layer neural networks and logistic regression were applied to map melt pond fraction and binary melt pond/ice classification. This work was funded by NERC standard grant NE/R017123/1.
description: Level-2 MODIS top-of-the-atmosphere (TOA) reflectances for bands 1-5 were used for the melt pond fraction and binary classification. Additionally, MODIS bands 5, 13, 16 and 19 were used to remove cloud shadows. The MOD35 data product was also used for cloud masking and MOD29 ice surface temperature product was used to flag refrozen melt ponds. Two machine learning algorithms were applied to the TOA band reflectances to map melt pond fraction and binary melt pond/ice/ocean classification. These included a Multi-Neural Network (MNN) and Multinomial Logistic Regression (MLR). Results were validated against high-resolution WorldView imagery, ship observations and other high resolution unclassified spy satellite data.
description: Matlab R2019a ENVI 5.5 ArcGIS 10.0 Python 3
description: The accuracy assessment for melt pond binary classification and fraction is further evaluated against WV imagery, showing mean overall accuracy (85.5%), average mean difference (0.09), and mean RMSE (0.18). In addition to cross-validation with WV, retrieved melt pond data are validated against melt pond fractions from satellite and ship-based observations, showing mean correlation coefficients, root-mean-square-error (RMSE) and mean differences of 0.41, 0.12, and 0.05, respectively.
DOI: 10.14473/csda/fdgzym
title: Naše společnost 2018 - leden

description: Výzkum provedl výzkumný tým CVVM Sociologického ústavu AV ČR, v.v.i., v rámci výzkumu „Naše společnost 2018". Sběr dat provedla tazatelská síť CVVM.
DOI: 10.5063/f1bg2mgv
title: AgEvidence US: Agro-environmental responses of conservation agricultural practices published from 1980 to 2020

description: AgEvidence US is a database of the multiple benefits and trade-offs associated with conservation agricultural practices in the United States Midwest. The purpose of these data are to provide organizations, policy makers, scientists, and other interested parties with all the available evidence related to the diversity and magnitude of agro-environmental impacts that occur following the implementation of conservation practices. The conservation practices we focused on include winter cover crops, conservation tillage, strategic nutrient management, early season pest management, and crop rotation in corn and soybean systems. Data were extracted from peer-reviewed literature published between 1980 and 2020 with experimental field sites located in at least one of the following states: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, North Dakota, Nebraska, Ohio, South Dakota, and Wisconsin. Our dataset includes all response variables reported in each paper where there are isolated comparisons of a conservation practice (e.g. soil nitrate content following winter fallow and following winter cover crop). With this approach, we were able to capture the state-of-knowledge for a wide diversity of response variables and identify where we lack knowledge.
DOI: 10.3886/e195061v1-143002
title: Observed Instagram Use & Satisfaction With Life

description: Over 70% of Americans use social media platforms, like Instagram. With this high prevalence, researchers have investigated the relationship between social media use and psychological well-being. Extant research has yielded mixed results, however, as most measures of social media use are self-reported and focus on amount of use. Even when studies account for type of social media use, such as active or passive use, there remains much to be captured. To address this, we asked participants to report their satisfaction with life and then recorded their actual Instagram activity for 10 minutes after posting a “selfie” portrait to their account. Importantly, we coded the observed Instagram activity into the following four clusters of experiences: communications received, communications sent, monitoring self-related content, exploring other-related content. We found that greater life satisfaction was associated with higher frequency of receiving communications and viewing other-related content. Life satisfaction was not associated with frequency of sending communications and self-monitoring. Surprisingly, none of the clusters of Instagram experiences were negatively associated with life satisfaction. Our findings highlight the importance of objective data and moving beyond the active/passive dichotomy of social media use to consider additional experiences.
description: Response Rates: In total, 80 participants completed the online survey and had their Instagram use monitored for 10 minutes. The final analytical sample includes 70 participants, 11 individuals were excluded from analysis because they did not follow directions during the experiment (e.g., did not spend the full 10 minutes using the Instagram app).
description: Presence of Common Scales: Participants completed the 5-item Satisfaction with Life Scale, abbreviated SWLS (45). Example items: “In most ways, my life is close to my ideal” and “I am satisfied with my life”. Participants responded to each item using a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree). The mean of each participant’s responses was calculated, with higher scores indicating greater satisfaction with life (M = 4.75, SD = 1.15).
description: Convenience sample of undergraduate college students who self-selected into the research study.
description: Emerging adult iPhone and Instagram users, ages 18-26 attending a four-year university.
description: coded video observation; web-based survey;
DOI: 10.5281/zenodo.10103841
title: The OREGANO knowledge graph for computational drug repurposing

description: The files here are data files from the OREGANO project, which consists of building a holistic knowledge graph on drugs, including natural compounds. Here is the list of files:
 
- OREGANO_V2.tsv : The triplet file used for link prediction. 3 columns : Subjet ; Predicate ; Object
- oreganov2.1_metadata_complet.ttl : The OREGANO knowledge graph in turtle format with the names and cross-references of the various integrated entities.
 
The following files contain the cross-references of OREGANO entities according to their type. They are all organised as follows: the external sources are the titles of the columns and each line begins with the identifier of the entity in OREGANO :
- TARGET.tsv: Cross-reference table of the 22,096 targets.- PHENOTYPES.tsv: Cross-reference table of the 11,605 phenotypes.- DISEASES.tsv:  Cross-reference table of the 18,333 diseases.- PATHWAYS.tsv: Cross-reference table of the 2,129 pathways.- GENES.tsv: Cross-reference table of the 35,794 genes.- COMPOUND.tsv:  Cross-reference table of the 90,868 compounds.- INDICATIONS.tsv: Cross-reference table of the 2,714 indications.- SIDE_EFFECT.tsv: Cross-reference table of the 6,060 side-effects.- ACTIVITY.tsv: Names of the 78 activities.- EFFECT.tsv: Names of the 171 effects.
The OREGANO knowledge graph is composed of 11 types of nodes and 19 types of links. The current version of the graph contains 88,937 nodes and 824,231 links.
A SPARQL endpoint has been provided to enable users to retrieve and explore the knowledge graph at OREGANO SPARQL endpoint .
 
The integration files and the knowledge graph are available on the GitHub of the OREGANO project in the Integration folder: Gitub repository .