cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5285/94c9eaa3-a178-4de4-8905-dbfab03b69a0
title: Gridded Standardized Precipitation Index (SPI) using gamma distribution with standard period 1961-2010 for Great Britain [SPIgamma61-10]

description: 1km and 5km gridded Standardised Precipitation Index (SPI) data for Great Britain, which is a drought index based on the probability of precipitation for a given accumulation period as defined by McKee et al. (1993). SPI is calculated for different accumulation periods: 1, 3, 6, 12, 18, 24 months. Each of these is in turn calculated for each of the twelve calendar months. Note that values in monthly (and for longer accumulation periods also annual) time series of the data therefore are likely to be autocorrelated. The standard period which was used to fit the gamma distribution is 1961-2010. The dataset covers the period from 1961 to 2012.
description: SPI is calculated as originally defined in [1]. SPI is based on the cumulative probability of a given rainfall amount occurring at a location. The historic rainfall data of the station is fitted to a statistical distribution. For this dataset, the statistical distribution used is the gamma distribution, which has been extensively used and is recommended as a default choice for Europe by [2]. The L-moments method was used to estimate the gamma distribution parameters, as the maximum likehood method was failing to fit a realistic distribution in some isolated cases (more details on the choice of methodology in [3]). To calculate SPI, the R package SCI was used [4], but modified to use L-moments (instead of Maximum Likelihood). The input data used is the monthly rainfall grids from CEH-Gridded Estimates of Areal Rainfall [CEH-GEAR] ([5], [6]) 

[1] McKee, T. B., Doesken, N. J., Kleist, J. (1993). The Relationship of Drought Frequency and Duration to Time Scales. Eighth Conference on Applied Climatology, 17-22 January 1993, Anaheim, California. 

[2] Stagge, J. H., Tallaksen, L. M., Gudmundsson, L., Van Loon, A. F. and Stahl, K. (2015), Candidate Distributions for Climatological Drought Indices (SPI and SPEI). Int. J. Climatol. doi: 10.1002/joc.4267

[3] Tanguy et al. (2015), in preparation. 

[4] Gudmundsson, L. & Stagge, J. H. (2014). Package 'SCI': Standardized Climate Indices such as SPI, SRI or SPEI. Repository CRAN, http://cran.r-project.org/web/packages/SCI/SCI.pdf 

[5] Tanguy, M., Dixon, H., Prosdocimi, I., Morris, D. G., Keller, V. D. J. (2014). Gridded estimates of daily and monthly areal rainfall for the United Kingdom (1890-2012) [CEH-GEAR]. NERC-Environmental Information Data Centre doi:10.5285/5dc179dc-f692-49ba-9326-a6893a503f6e 

[6] Keller,V. D. J., Tanguy, M. , Prosdocimi, I. , Terry, J. A. , Hitt, O., Cole, S. J. , Fry, M., Morris, D. G., Dixon, H. (2015) CEH-GEAR: 1km resolution daily and monthly areal rainfall estimates for the UK for hydrological use. Earth Syst. Sci. Data Discuss., 8, 83-112, www.earth-syst-sci-data-discuss.net/8/83/2015/ doi:10.5194/essdd-8-83-2015.
DOI: 10.6084/m9.figshare.29344775
title: MirtronDB_version2

description: MirtronDB_version2 database dump.<br><br><b>MirtronDB v2</b> is an updated version of MirtronDB that includes articles published between <b>2017 and 2025</b>. The sequences were <b>manually obtained from PubMed</b>, compared with <b>version 1</b> to retain only <b>newly identified mirtrons</b>, and then uploaded to the database using the command "<i>\copy feature FROM 'MirtronDB2_feature_17.csv' WITH (FORMAT csv, HEADER true, DELIMITER ',', QUOTE '"');</i>".
DOI: 10.6084/m9.figshare.29344775.v6
title: MirtronDB_version2

description: MirtronDB_version2 database dump.<br><br><b>MirtronDB v2</b> is an updated version of MirtronDB that includes articles published between <b>2017 and 2025</b>. The sequences were <b>manually obtained from PubMed</b>, compared with <b>version 1</b> to retain only <b>newly identified mirtrons</b>, and then uploaded to the database using the command "<i>\copy feature FROM 'MirtronDB2_feature_17.csv' WITH (FORMAT csv, HEADER true, DELIMITER ',', QUOTE '"');</i>".
DOI: 10.6084/m9.figshare.29344775.v7
title: MirtronDB_version2

description: MirtronDB_version2 database dump.<br><br><b>MirtronDB v2</b> is an updated version of MirtronDB that includes articles published between <b>2017 and 2025</b>. The sequences were <b>manually obtained from PubMed</b>, compared with <b>version 1</b> to retain only <b>newly identified mirtrons</b>, and then uploaded to the database using the command "<i>\copy feature FROM 'MirtronDB2_feature_17.csv' WITH (FORMAT csv, HEADER true, DELIMITER ',', QUOTE '"');</i>".
DOI: 10.5285/abe4dd7c-a340-4595-a57f-8c1446ff7656
title: Hourly physical and nutrient monitoring data for The Cut, Berkshire (2010-2012)

description: This data set comprises of hourly physical and nutrient monitoring data of The Cut at Bray Marina (National grid reference SU915786), from May 2010 to February 2012.  Parameters measured are total phosphorus, total reactive phosphorus, ammonium, conductivity, temperature, dissolved oxygen, pH and total chlorophyll.  The accompanying hourly averaged flow data (from the EA flow gauging station at Binfield, approximately 10 km upstream of the monitoring site) are also supplied. The monitoring programme was funded by the EPSRC, through the LIMPIDS project.
description: Total and total reactive phosphorus data was produced in the field using a Hach Lange Phosphax Sigma auto-analyser.  The other parameters were monitored using a YSI 6600 sonde.  The monitoring site installation, telemetry / data collection and maintenance / calibration of the YSI probe was conducted by the Environment Agency's National Water Quality Instrumentation Service.  The hourly phosphorus data was produced by CEH. Data processing was carried out jointly by CEH and University of Reading. Full details of the field procedures and laboratory groundtruthing samples are outlined in the accompanying papers (see Additional Information Source, under Description tab).
DOI: 10.5281/zenodo.18506948
title: Drivers of viral diversity and sharing in marine mammals (supporting data)

description: Supporting data and code for the paper entitled "Drivers of viral diversity and sharing in marine mammals".

Data



Contigs resulting from pipeline (as described in Materials and Methods):



final_min_length_0vertebrate_viral_hits.csv: vertebrate viral contigs

final_min_length_0non_vertebrate_viral_hits.csv: non-vertebrate viral contigs

final_min_length_0all_viral_hits.csv: all contigs combined

diamond_hits_vert_viruses.csv: vertebrate viral contigs with closest result from diamond BLASTX against nr and match statistics








Metadata:



final_min_length_0all_viral_hits.csv: details of samples and additional variables for each sequencing pool



vOTUs:



cluster_by_genus_len{150/250/400}.csv: vOTUs derived by clustering at all ID thresholds (see Materials and Methods) for three different contig length cutoffs

vOTU_representative_sequences.csv: longest sequence from each vOTU (min. length 250nt, clustering threshold 95%), with taxonomy assignment and top hit from diamond BLASTX vs. nr

vOTU_representative_sequences.fasta: longest sequence from each vOTU (min length 250nt, clustering threshold 95%) in fasta format

pairwise_identity_within_vOTUs.csv: pariwise identity values for all sequences clustered into each vOTU (min length 250nt, clustering threshold 95%)





 

Code





Demographics_CommunityComposition_models.Rmd: Code to run GLM of demographic and taxonomic variables against viral richness, PERMANOVA of viral community composition and Mantel test of community composition versus host phylogenetic distance

Sharing.Rmd: Code to derive vOTUs from raw contigs, build unipartite virus-host network and run GLMs of network node degree against demographic and taxonomic variables
DOI: 10.5281/zenodo.17100058
title: Drivers of viral diversity and sharing in marine mammals (supporting data)

description: Supporting data and code for the paper entitled "Drivers of viral diversity and sharing in marine mammals".

Data



Contigs resulting from pipeline (as described in Materials and Methods):



final_min_length_0vertebrate_viral_hits.csv: vertebrate viral contigs

final_min_length_0non_vertebrate_viral_hits.csv: non-vertebrate viral contigs

final_min_length_0all_viral_hits.csv: all contigs combined

diamond_hits_vert_viruses.csv: vertebrate viral contigs with closest result from diamond BLASTX against nr and match statistics








Metadata:



final_min_length_0all_viral_hits.csv: details of samples and additional variables for each sequencing pool



vOTUs:



cluster_by_genus_len{150/250/400}.csv: vOTUs derived by clustering at all ID thresholds (see Materials and Methods) for three different contig length cutoffs

vOTU_representative_sequences.csv: longest sequence from each vOTU (min. length 250nt, clustering threshold 95%), with taxonomy assignment and top hit from diamond BLASTX vs. nr

vOTU_representative_sequences.fasta: longest sequence from each vOTU (min length 250nt, clustering threshold 95%) in fasta format

pairwise_identity_within_vOTUs.csv: pariwise identity values for all sequences clustered into each vOTU (min length 250nt, clustering threshold 95%)





 

Code





Demographics_CommunityComposition_models.Rmd: Code to run GLM of demographic and taxonomic variables against viral richness, PERMANOVA of viral community composition and Mantel test of community composition versus host phylogenetic distance

Sharing.Rmd: Code to derive vOTUs from raw contigs, build unipartite virus-host network and run GLMs of network node degree against demographic and taxonomic variables
DOI: 10.5281/zenodo.17753339
title: Chiral phonons in polar LiNbO3 - supplementary data

description: These are the supplementary data to the linked publication.

Experimental data are included as .txt files containing the raw data corresponding to the figures in the publication. 

Input and output files of density functional theory (DFT) calculations of phonon energies and eigenvectors of LiNbO3 are located in the folder "DFT".

This folder contains files with the following extensions:

.abi - Input files for the Abinit DFT software package. 

.xml - PAW atomic datasets, used as additional input for DFT calculations. 

.nc - NetCDF files containing the phonon eigenvectors, energies, and Born effective charges.

.m - MATLAB scripts for plotting the phonon chirality.

.ddb.out - Abinit derivative database file containing the results of the DFT calculations.

.json - JSON file containing phonon energies and eigenvectors.

.abi, .xml, .m, .ddb.out, and .json files can be viewed in a standard text editor.

Data within the .nc files can be extracted using NetCDF (v. 4, www.unidata.ucar.edu/software/netcdf). The .nc files are labeled as "disperson," containing data for a high symmetry path through reciprocal space; and "surface_hk0_fine" and "surface_hk0", containing a grid of points in the hk0 plane (in hexagonal coordinates) with fine and coarse resolution, respectively.

The DFT calculations can be replicated using the linbo.abi and .xml files and the Abinit software package (v. 10, www.abinit.org). Post-processing of the derivative database was performed using the anaddb utility of Abinit and the post.*.abi files.

The chirality of the phonons can be plotted using the included MATLAB scripts (v. 2025b, www.mathworks.com/products/matlab.html) over the high-symmetry points or on the hk0 surface.

The phonon modes can be visualized by uploading the .json file to phononwebsite (henriquemiranda.github.io/phononwebsite/phonon.html).
DOI: 10.5281/zenodo.17753338
title: Chiral phonons in polar LiNbO3 - supplementary data

description: These are the supplementary data to the linked publication.

Experimental data are included as .txt files containing the raw data corresponding to the figures in the publication. 

Input and output files of density functional theory (DFT) calculations of phonon energies and eigenvectors of LiNbO3 are located in the folder "DFT".

This folder contains files with the following extensions:

.abi - Input files for the Abinit DFT software package. 

.xml - PAW atomic datasets, used as additional input for DFT calculations. 

.nc - NetCDF files containing the phonon eigenvectors, energies, and Born effective charges.

.m - MATLAB scripts for plotting the phonon chirality.

.ddb.out - Abinit derivative database file containing the results of the DFT calculations.

.json - JSON file containing phonon energies and eigenvectors.

.abi, .xml, .m, .ddb.out, and .json files can be viewed in a standard text editor.

Data within the .nc files can be extracted using NetCDF (v. 4, www.unidata.ucar.edu/software/netcdf). The .nc files are labeled as "disperson," containing data for a high symmetry path through reciprocal space; and "surface_hk0_fine" and "surface_hk0", containing a grid of points in the hk0 plane (in hexagonal coordinates) with fine and coarse resolution, respectively.

The DFT calculations can be replicated using the linbo.abi and .xml files and the Abinit software package (v. 10, www.abinit.org). Post-processing of the derivative database was performed using the anaddb utility of Abinit and the post.*.abi files.

The chirality of the phonons can be plotted using the included MATLAB scripts (v. 2025b, www.mathworks.com/products/matlab.html) over the high-symmetry points or on the hk0 surface.

The phonon modes can be visualized by uploading the .json file to phononwebsite (henriquemiranda.github.io/phononwebsite/phonon.html).
DOI: 10.5285/bad1514f-119e-44a4-8e1e-442735bb9797
title: Future flows climate data

description: Future Flows Climate (FF-HadRM3-PPE) is an eleven-member ensemble climate projection for Great Britain at a 1-km resolution spanning from 1950 to 2098. It was specifically developed for hydrological application and contain daily time series of Available Precipitation, which is the precipiated water available to hydrological processes after delays due to snow and ice storage are accounted for; and monthly reference Potential Evapotranspiration calculated using the FAO56 method. Future Flows Climate is derived from the Hadley Centre's Regional climate projection ensemble HadRM3-PPE based on 11 different variants of the regional climate model run under the SRES A1B emission scenario. HadRM3-PPE is underpinning the UKCP09 products. Bias correction and spatial downscaling were applied to the total precpitation and air temperature variables before Future Flows Climate APr and PE were generated. The development of Future Flows Climate was made during the partnership project 'Future Flows and Groundwater Levels' funded by the Environment Agency for England and Wales, Defra, UK Water Research Industry, NERC (Centre for Ecology & Hydrology and British Geological Survey) and Wallingford HydroSolutions.
description: A modified version of the 11-member HadRM3-PPE ensemble projection assuming SRES-A1B emissions scenario developed for hydrological application in March 2012. It cover land areas of Great Britain at a 1-km resolution and contains 11 sets of 1951-2098 equally likely time series for two data types daily Available Precipitation (incorporating delays due to water storage as snow and ice) and monthly Potential Evapotranspiritation time series. Future Flows Climate used a monthly bias-correction and downscaling procedure based on the Gamma distribution (precipitation) and linear model (temperature). Potential Evapotranspiration is calculated using the FAO56 formulation with monthly bias-corrected downscaled temperature and HadRM3-PPE original time series for the other variables. As Future Flows Climate datasets are derived from climate model outputs they do not replicate the historical weather but are possible realisations of the climate. Despite the use of bias-correction and downscaling procedures Future Flows Climate might still contain some differences with observed climate and cannot be compared directly with gauged values. SC090016/PN2, SC090016/PN3 SC090016/PN5 project technical notes provide details on the methods used and results.
DOI: 10.5285/f3723162-4fed-4d9d-92c6-dd17412fa37b
title: Future flows hydrology data

description: Future Flows Hydrology (FF-HydMod-PPE) is an 11-member ensemble projections of river flow and groundwater levels time series for 283 catchments and 24 boreholes in Great Britain. It is derived from Future Flows Climate, an 11-member 1-km bias-corrected and downscaled climate projection products based on the SRES A1B emission scenario. River Flows data are at a daily time step: Groundwater Levels data are at a monthly time step. Future Flows Hydrology span from 1951 to 2098. The development of Future Flows Hydrology was made during the partnership project 'Future Flows and Groundwater Levels' funded by the Environment Agency for England and Wales, Defra, UK Water Research Industry, NERC (Centre for Ecology & Hydrology and British Geological Survey) and Wallingford HydroSolutions.
description: An 11-member ensemble of daily river flow and monthly groundwater levels for 283 river catchments and 24 boreholes across Great Britain simulated in March 2012. Future Flows Hydrology time series are generated using conceptual hydrological models driven by Future Flows Climate and span the period 1951-2098. Each ensemble set contains 11 members all equally likely that together accounts for climate variability, climate modelling uncertainty and climate forcing under the SRES A1B emissions scenario. As Future Flows Hydrology datasets are driven by forcing from climate model outputs they do not replicate the historical weather but are possible realisations of river flow and groundwater levels time series. Despite the use of bias-corrected Future Flows Climate as input and local hydrological models Future Flows Hydrology dataset might still contain hydrological and climate modelling errors and cannot be compared directly with gauged values. SC090016/PN5, SC090016/PN6, SC090016/PN7 and SC090016/PN9 project technical notes provide details on the methods used and results.
DOI: 10.5281/zenodo.18507102
title: GEOMETRIK NAQSHLARNING RAMZLARDA IFODALANISHI

description: Ushbu ishda geometrik naqshlarning arxitekturadagi ramziy ifodasi va ularning semantik ahamiyati yoritilgan. Geometrik shakllar — doira, kvadrat, ko‘pburchak va yulduzsimon kompozitsiyalar — me’moriy bezaklarda ilohiy tartib, muvozanat va abadiylik g‘oyalarini ifodalaydi. Ayniqsa, islom arxitekturasida geometrik naqshlar ramz sifatida keng qo‘llanilib, binolarga nafaqat estetik, balki ma’naviy mazmun ham bag‘ishlaydi. Tadqiqot geometrik naqshlarni arxitekturani badiiy va falsafiy makon sifatida anglashda muhim vosita ekanini ko‘rsatadi.
DOI: 10.5281/zenodo.18507101
title: GEOMETRIK NAQSHLARNING RAMZLARDA IFODALANISHI

description: Ushbu ishda geometrik naqshlarning arxitekturadagi ramziy ifodasi va ularning semantik ahamiyati yoritilgan. Geometrik shakllar — doira, kvadrat, ko‘pburchak va yulduzsimon kompozitsiyalar — me’moriy bezaklarda ilohiy tartib, muvozanat va abadiylik g‘oyalarini ifodalaydi. Ayniqsa, islom arxitekturasida geometrik naqshlar ramz sifatida keng qo‘llanilib, binolarga nafaqat estetik, balki ma’naviy mazmun ham bag‘ishlaydi. Tadqiqot geometrik naqshlarni arxitekturani badiiy va falsafiy makon sifatida anglashda muhim vosita ekanini ko‘rsatadi.
DOI: 10.5285/7af4c236-5148-4d3d-815c-b6451aee67a5
title: High resolution nutrient chemistry of the River Frome, Dorset, UK (2004-2006)

description: This data resource consists of a nutrient concentration time series for the River Frome at East Stoke, Dorset, gathered between January 2004 and February 2006. Total phosphorus concentration data was gathered for the full duration of the project. Soluble reactive phosphorus, total oxidisable nitrogen and dissolved reactive silicon concentration was only gathered from Jan 2005 until Feb 2006. Sampling interval varied throughout the monitoring period, from a minimum of two samples to day, to eight per day during storm events (with an average of three samples per day throughout the duration of the monitoring period). Samples were taken from the main flow of the river using an automatic water sampler, and analysed using standard colorometric methods, at the CEH Dorset laboratories. Further details of the field and laboratory procedures are outlined in Bowes MJ, Smith JT, Neal C. The value of high resolution nutrient monitoring: a case study of the River Frome, Dorset, UK. Journal of Hydrology 2009; 378: 82-96.
description: The sampling and chemical analysis was carried out by Mike Bowes (CEH). Samples were collected from approximately 1 m depth from the main flow of the River Frome at East Stoke, using Epic water samplers. Samples were filtered through a 0.45 µm filter immediately on return to the laboratory, prior to soluble reactive phosphorus, dissolved reactive silicon and total oxidisable nitrogen analysis. Chemical analysis was carried out at the nutrient laboratories at CEH Dorset, using the standard colorometric techniques outlined in the key reference (Bowes et al., 2009). Phosphorus concentration data are presented in µg l-1. Nitrate and dissolved reactive silicon concentrations are given in mg l-1. All batches were analysed alongside quality control standards. 

See Bowes, M.J., Smith, J.T., & Neal, C. (2009). The value of high-resolution nutrient monitoring: A case study of the River Frome, Dorset, UK. Journal of Hydrology, 378(1-2), 82–96 https://doi.org/10.1016/j.jhydrol.2009.09.015
DOI: 10.15468/dl.4y4dff
title: Occurrence Download

description: A dataset containing 77880 records in GBIF matching the query:

 SELECT gbifid, datasetkey, specieskey, kingdom, phylum, class, "order", family, genus, species, scientificname, decimallatitude, decimallongitude, eventdate, institutioncode, "year" AS obs_year, basisofrecord, coordinateuncertaintyinmeters, issue
 FROM occurrence
 WHERE
 decimallatitude IS NOT NULL
 AND decimallongitude IS NOT NULL
 AND NOT ARRAY_CONTAINS(issue, 'ZERO_COORDINATE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_OUT_OF_RANGE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_INVALID')
 AND NOT ARRAY_CONTAINS(issue, 'COUNTRY_COORDINATE_MISMATCH')
 AND "year" &gt;= 2015
 AND "year" &lt;= 2026
 AND coordinateuncertaintyinmeters IS NOT NULL
 AND coordinateuncertaintyinmeters &gt; 0
 AND coordinateuncertaintyinmeters &lt;= 200.0
 AND decimallatitude &gt;= -37.42857426825602
 AND decimallatitude &lt;= -33.06103686093294
 AND decimallongitude &gt;= 116.8884474107165
 AND decimallongitude &lt;= 126.64106794692027
 AND GBIF_Within('POLYGON ((126.641068 -37.428574, 126.641068 -33.061037, 116.888447 -33.061037, 116.888447 -37.428574, 126.641068 -37.428574))', decimallatitude, decimallongitude) = TRUE
 

 The dataset's 77880 records were derived from 32 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016565-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.