cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.18187851
title: Bulk BCR repertoire dataset of blood samples from individuals responding to a SARS-CoV-2 mRNA vaccine.

description: This data file contain all BCR sequences from the bulk BCR repertoire dataset generated and analysed in the associated manuscript. The file conforms to tab-delimited output formats from the IMGT/HighVQuest web-server, subsequently processed via the BRepertoire webserver (https://brepertoire.cs.ucl.ac.uk/). Please refer to the BRepertoire webserver Help pages for further description - below columns of specific interest pertaining to the experimental design as well as the analysis investigated in the manuscript are highlighted:



"UseAsRef":  In each donor one sequence from each clone was selected (labelled 'TRUE') as the representative sequences for the analysis of VDJ sequence features without biases from clonal expansion. All other sequences from the same clone are labelled 'NA'.

"CloneID": Clone identifier labelling clone information. Clonotype clustering was performed following procedure detailed in the manuscript.

"NumInClone": Clone size (number of sequences in the clone)

"IsCrossClass", "Cross_Class": whether the clone contains sequences of multiple antibody classes (i.e. isotypes). 'Cross_Class' list all the classes observed in the clone, 'IsCrossClass' is a binary indicator whether multiple antibody classes were observed in the clone.

"IsCrossSubclass", "Cross_Subclass": same as above but at the antibody subclass level

"NumInClone_Sample", "UseAsRef_Sample", "IsCrossSample", "Cross_Sample": 'Sample' here refers to timepoints. These columns indicate statistics of the clonotype with respect to observations across multiple timepoints.

"PatientID", "Timepoint": Donor and timepoint information. Note the counting of timepoints do not conform to the nomenclature used in the manuscript - use 'Timepoint2' instead.

"Timepoint2": Timepoint nomenclature used in this manuscript.
DOI: 10.15468/dl.33pwrn
title: Occurrence Download

description: A dataset containing 208 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is one of (Melhania stipulosa, Ornithogalum munzurense, Galium petrae, Galium pseudocapitatum, Galium schlumbergeri, Galium tuncelianum, Orobanche ducellieri, Scholtzia calcicola, Galium olivetorum, Galium penduliflorum, Galium pralognense, Galium huber-morathii, Galium pamphylicum, Galium pisoderium, Thamnea gracilis, Galium circae, Hypoxis zeyheri, Ornithogalum saginatum, Ornithogalum dolichopharynx, Ornithogalum microcarpum, Lathyrus hirticarpus, Galium pestalozzae, Galium setuliferum, Duranta xalapensis, Galium rigidifolium, Apodolirion bolusii, Ornithogalum gulnariense, Orobanche cohenii, Galium globuliferum, Galium lasiocarpum, Erythrina johnsoniae, Ornithogalum joschtiae, Ornithogalum zebrinellum, Veronica ozturkii, Veronica antalyensis, Galium penicillatum, Thamnea depressa, Galium ceratocarpon, Orobanche denudata, Ornithogalum verae, Ornithogalum nivale, Scholtzia tenuissima, Galium isauricum, Galium retzii, Heterotheca sandersii, Petrorhagia syriaca, Veronica allahuekberensis, Galium talaveranum, Petrorhagia sarbaghiae, Ornithogalum yildirimlii, Ornithogalum insulare, Orobanche cyrenaica, Orobanche chironii, Veronica stamatiadae, Ornithogalum capillaris, Lathyrus golanensis, Lathyrus brachyodon, Galium ehrenbergii, Galium inconspicuum, Galium membranaceum, Apodolirion cedarbergense, Nonea dumanii, Galium basalticum, Aubrieta birolmutlui, Bertya pomaderrioides, Drosera gracilis, Galium acuminatum, Lamium tschorochense, Orobanche caucasica, Galium conforme, Galium insulare, Galium babadaghense, Ornithogalum namaquanulum, Ornithogalum rotatum, Ornithogalum naviculum, Scholtzia quindecim, Lathyrus tukhtensis, Galium scopulorum, Alepidea acutidens, Galium jarynae, Galium kerneri, Veronica ersin-yucelii, Galium thracicum, Orobanche turcica, Ornithogalum monophyllum, Lathyrus layardii, Lathyrus turcicus, Galium baytopianum, Veronica cetikiana, Ornithogalum pendens, Galium ovitdaghense, Ornithogalum alpigenum)",
 "Year is greater than or equal to 1950"
 ]
}

 The dataset includes 208 records from 34 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003418-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17257401
title: Data for: Arbuscular mycorrhizal responsiveness of a Canary Island endemic (Artemisia thuscula Cav.): implications for nursery propagation and restoration
DOI: 10.5281/zenodo.17638164
title: Data for: Arbuscular mycorrhizal field colonization and nursery responsiveness of the Canary endemic Artemisia thuscula along contrasting volcanic island soils

description: Dataset for “Arbuscular mycorrhizal field colonization and nursery responsiveness of the Canary endemic Artemisia thuscula along contrasting volcanic island soils”

This dataset accompanies the Short Communication submitted to Applied Soil Ecology (2025). It provides summarized data supporting the analyses and figures presented in the manuscript.

The study assessed arbuscular mycorrhizal (AM) colonization and edaphic/foliar context of three Artemisia taxa (A. thuscula, A. ramosa, A. reptans) from contrasting volcanic environments in Tenerife (Canary Islands), and evaluated the early responsiveness of A. thuscula seedlings to controlled AM inoculation in nursery conditions.

Contents:

Table 1: Soil properties (mean, 95% confidence intervals, CI) for three Artemisia taxa (A. thuscula Cav., A. ramosa C. Sm. ex Link, A. reptans C. Sm.) across contrasting sites in Tenerife, Canary Islands.

Table 2: Nursery leaf nutrient concentrations of Artemisia thuscula Cav. seedlings.

Table S1: Foliar nutrient concentrations of field plants.

Table S2: Nursery substrate properties and seedling growth responses (control vs. AM-inoculated).

Fig. 1. Field AM colonization and edaphic filters in Canary Island Artemisia.

Figure 2: Gardner–Altman estimation plot of growth responses to AM inoculation of Artemisia thuscula Cav. (biomass, length and stem diameter).

Figure 1S: Gardner–Altman estimation plots of growth responses to AM inoculation of Artemisia annua L.

README: Metadata and explanation of variables.

CODEBOOK: Variable names, units and descriptions.

File format: All data tables are provided in ODT (LibreOffice) format compatible with common spreadsheet software. Mean values and 95 % CIs were calculated from three replicates per site or treatment.

License: Creative Commons Attribution 4.0 International (CC-BY 4.0).

Recommended citation:Garzón-Molina, M.S., Jaizme-Vega, M.C., & González-González, M. (2025). Dataset for “Arbuscular mycorrhizal field colonization and nursery responsiveness of the Canary endemic Artemisia thuscula along contrasting volcanic island soils”. Zenodo. https://doi.org/10.5281/zenodo.17638164

Keywords: Arbuscular mycorrhiza · Volcanic soils · Endemic shrubs · Nursery performance · Restoration ecology · Canary Islands · Macaronesia
DOI: 10.5281/zenodo.15494240
title: FoodLAND - Datasets of randomised controlled trials of farm innovations implemented in Morocco, Tanzania, and Uganda

description: This submission derives from Task 5.9 "Innovation validation across the network" of the H2020 project FoodLAND "Food and Local, Agricultural and Nutritional Diversity" (2020-2025). T5.9 had two objectives: (1) assessing the impact of different dissemination strategies (information provision or financial incentivisation) on the adoption of selected FoodLAND innovations by smallholder farmers; (2) assessing the impact of these innovations, if adopted and used, on various indicators of farm performance and household wellbeing. To achieve these closely related goals, T5.9 implemented Randomised Controlled Trials (RCTs) in three so-called Food Hubs: Meknès (Morocco), where a phone application for precision irrigation and protection was considered; Mvomero (Tanzania), where the focus was on two new bean varieties characterised by higher zinc and iron content; and Kajjansi-Masaka (Uganda), where fish farmers were introduced to the integration between aquaculture and vegetable farming. The RCTs were conducted between May 2023 (initial survey) and early January 2025 (post-implementation/final survey), depending on the country and specific local conditions. A detailed description of the methodological approach and the data collection tools is provided in deliverable D5.20 "Protocol to implement the randomised controlled trials of the innovations." This submission consists of three datasets, one per Food Hub, plus the report D5.21 "Dataset of RCTs of innovation results, linked to socioeconomic and demographic factors." The datasets are provided in Excel Workbook format. Each dataset consists of eight (Morocco and Tanzania) or 13 (Uganda) worksheets, plus the metadata and the sheet descriptions. The sheets are the following: baseline survey (base_survey), baseline crop production (base_crop_prod), baseline crop inputs (base_crop_input), planned crop production (plan_crop), baseline fish production – Uganda only (base_fish_prod), baseline fish inputs – Uganda only (base_fish_input), planned fish production – Uganda only (plan_fish), post-training survey (post_survey), final survey (final_survey), final crop production (final_crop_prod), final crop inputs (final_crop_input), final fish production – Uganda only (final_fish_prod), final fish inputs – Uganda only (final_fish_input). Each variable is assigned a short name, e.g., “treatment,” and a long name that conveys information about the country and the worksheet, e.g., “u_post_surv_treatment.” The unique ID of the farmer, “unique_id,” appears with the same name in all the worksheets to facilitate merging during the analysis; all the variable names include 32 characters or less.

Update 2025-05-23: The Ugandan dataset was reviewed based on new observations, some errors were corrected in the Moroccan dataset, and the report D5.21 was updated accordingly.
DOI: 10.5281/zenodo.18089199
title: A digitized dataset of legacy geophysical logs from deep boreholes within the "Irpinia Near Fault Observatory Area" (INFO - Southern Apennines, Italy)

description: The dataset includes geophysical logs digitized from seven deep boreholes (ACERNO_001, CONTURSI_001, CONTURSI_001BIS, MONTE FORCUSO_001, SAN FELE_001, SAN GREGORIO MAGNO_001_001BIS, TAURASI_001), collected in the Southern Apennines (Irpinia region, Italy) for commercial exploration during the '80s. These wells have been specifically selected within the "Irpinia Near Fault Observatory area (INFO)". The source data are currently available in the Italian repository VIDEPI (videpi.com) in PDF format, scanned from the original paper copies, and include stratigraphic information, geophysical well logs and other ancillary data. Such a format often makes the data difficult to find and access, as well as making them not interoperable and reusable, as recommended by the FAIR policy. This policy characterizes the EPOS infrastructure (https://www.epos-eu.org/dataportal), funder of this digitalization project accomplished by UniPG, in collaboration with ISPRA, as part of the activities carried out in the framework of EPOS-JRU Italy, to make deep borehole data publicly available in a digital version. The new digitized data will enable users to reuse them to allow quantitative analyses and improve interpretability, as well as to better integrate them into the geological and geophysical studies related to the NFO IRPINIA (https://meet.ingv.it/progetto/wp-linee-di-ricerca/wp4-irpinia-near-fault-observatory-nfo, https://isnet.unina.it).
DOI: 10.5281/zenodo.14284426
title: FoodLAND - Dataset on producers' socio-economic conditions, operational and technological states, and behavioural experimental results

description: This submission derives from Work Package 3 "Producers' behaviours, agrobiodiversity, and food diversity" of the H2020 project FoodLAND "Food and Local, Agricultural and Nutritional Diversity" (2020-2025). It consists of two datasets, and two survey questionnaires used to gather these data (English version). The datasets include information about small crop and fish farmers, respectively, sampled in so-called Food Hubs (i.e., local production regions) in Morocco, Kenya, Tanzania, Tunisia, and Uganda. The crop farmers' data were collected in two Food Hubs in each country, while the fish farmers' data were collected in one Food Hub in each of Kenya and Uganda, plus a limited number of observations in Tanzania, in all the cases using standardised survey questionnaires. In one location in each of Morocco, Kenya, Tanzania and Tunisia, lab-in-the-field experiments were run with crop farmers, while in one location in Uganda the same experiments were run with fish farmers. The experimental protocols have been submitted separately. The datasets are provided as Excel Workbooks, while the questionnaires are provided in PDF format. Each dataset includes one sheet about "Conditions" (one row per farmer: 4,529 observations for crop farmers and 927 for fish farmers), one sheet about "Production" (one row per farmer and per up to three crops: 10,668 observations for crop farmers and 1,245 for fish farmers), and one sheet with the results of the behavioural experiments (one row per farmer: 1,987 observations for crop farmers and 406 for fish farmers).
DOI: 10.5281/zenodo.17570007
title: Hotspots of multidimensional biodiversity are overlooked by protected areas

description: This folder contains data and R code to reproduce the analyses and results presented in the manuscript entitled "Hotspots of multidimensional biodiversity are overlooked by protected areas".
DOI: 10.25549/satjrnl-m1148
title: Satiricheskoe Obozrenie, no. 2 (1906)

description: [description (english with transliteration)] Satiricheskoe Obozrenie [Satirical Survey], no. 2, 1906. Weekly. Published by I.N. Glagolev. Edited by N.K. Di-Sen'i. St. Petersburg. Тypography: "Severnaia pechatnIa." Literary-artistic journal of social-political satire, theater, and art -- Rudzinskii, no. 93; BPIR, no. 7157.
DOI: 10.15468/dl.npfrat
title: Occurrence Download

description: A dataset containing 20076173 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Mexico",
 "Geometry POLYGON((-112.86558 32.30454,-117.36677 32.79534,-115.95898 30.21438,-114.17577 28.90043,-114.78581 27.53956,-112.48641 26.50718,-111.92329 25.05246,-110.42164 23.50388,-109.38926 23.31617,-110.22925 24.30476,-111.12085 26.3226,-113.04484 28.76278,-113.79566 29.41975,-114.87497 30.49907,-114.64034 31.67223,-113.3264 31.10911,-112.05938 28.85664,-110.22925 27.49577,-109.19686 26.3226,-108.58682 25.52485,-107.50751 24.30476,-106.85053 23.69472,-105.67737 22.38077,-104.64499 20.92605,-104.03494 19.70596,-102.62714 18.48587,-101.17242 17.50041,-100.18696 16.70266,-97.69986 15.95184,-96.29206 15.81106,-95.35353 16.28032,-93.7111 16.28032,-92.33902 14.40606,-92.15132 15.43845,-90.52425 16.71436,-91.41585 17.69982,-88.08407 18.49757,-87.47402 19.85844,-86.7232 21.5478,-87.80251 21.64165,-89.96113 21.21931,-90.47732 19.24839,-91.55663 18.35679,-93.71525 18.30986,-95.7331 18.96683,-97.37964 21.13781,-97.88004 22.58633,-97.22162 25.90474,-95.24638 31.33009,-112.86558 32.30454))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 20076173 records from 425 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003392-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fze9ru
title: Occurrence Download

description: A dataset containing 383 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is one of (Ornithogalum nurdaniae, Lathyrus campestris, Galium peplidifolium, Alepidea longipetiolata, Galium glaucophyllum, Galium oreophilum, Galium parvulum, Galium pastorale, Galium atlanticum, Galium consanguineum, Galium cotinoides, Ornithogalum beyazoglui, Ornithogalum bicornutum, Ornithogalum anatolicum, Galium dincii, Scholtzia peltigera, Orobanche humbertii, Galium cornigerum, Aubrieta vulcanica, Lamium demirizii, Ornithogalum alatum, Ornithogalum campanulatum, Ornithogalum mekselinae, Lathyrus apenninus, Galium pterocarpum, Galium tortumense, Scholtzia truncata, Galium campanelliferum, Lathyrus pygmaeus, Lamium galactophyllum, Scholtzia laciniata, Lathyrus karsianus, Lathyrus bitlisicus, Galium haussknechtii, Veronica samuelssonii, Galium brunneum, Galium citraceum, Galium shinasii, Lathyrus sericeus, Orobanche singarensis, Orobanche tarapacana, Ornithogalum sumbulianum, Ornithogalum synadelphicum, Pentameris glacialis, Scholtzia trilocularis, Aubrieta albanica, Ornithogalum alatepense, Petrorhagia laconica, Frankenia hamata, Galium huteri, Galium nigricans, Galium numidicum, Galium samium, Galium tubiflorum, Ornithogalum plurifolium, Frankenia pallida, Galium afropusillum, Galium aladaghense, Phiambolia similis, Bornmuellera kiyakii, Pentameris ellisii, Galium bingoelense, Ornithogalum lychnite, Lathyrus stenophyllus, Galium festivum, Galium hypoxylon, Bornmuellera dieckii, Ornithogalum baurii, Lathyrus cilicicus, Lathyrus basalticus, Alepidea cirsiifolia, Orobanche serratocalyx, Ornithogalum pullatum, Ornithogalum graecum, Ornithogalum pluttulum, Arum euxinum, Galium leptum, Galium werdermannii, Orobanche tetuanensis, Ornithogalum atticum, Ornithogalum vasakii, Ornithogalum samariae, Ornithogalum anamurense, Frankenia decurrens, Galium jemense, Galium sieheanum, Nonea anomala, Galium trojanum, Scholtzia uniflora, Aubrieta ekimii, Nonea karsensis, Galium amorginum, Galium bornmuelleri, Lamium ponticum, Hypoxis tetramera, Ornithogalum polyphyllum)",
 "Year is greater than or equal to 1950"
 ]
}

 The dataset includes 383 records from 35 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003421-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kc422e
title: Occurrence Download

description: A dataset containing 1277 records in GBIF matching the query:

SELECT
 GBIF_ISEA3HCode(
 8, 
 decimalLatitude,
 decimalLongitude,
 COALESCE(coordinateUncertaintyInMeters, 1000)
 ) AS geogrid_id,
 CASE 
 WHEN classKey IN ('359') THEN 'Mammals'
 WHEN classKey IN ('212') THEN 'Birds'
 WHEN familyKey IN ('1103', '1104', '494', '495', '1105', '496', '497', '1106', '498', '499', '1107', '537', '538', '1153', '547', '1162', '548', '549', '550', '1163', '1164', '1165', '1166', '1167', '1305', '1067', '1306', '1307', '1308', '1068', '1069', '587', '1310', '588', '589', '1311', '1312', '1313', '590', '708', '890', '774', '889', '773', '772', '888', '765', '879') THEN 'Bony Fish'
 WHEN classKey IN ('131') THEN 'Amphibians'
 WHEN classKey IN ('216') THEN 'Insects'
 WHEN classKey IN ('11418114', '11569602', '11592253', '11493978') THEN 'Reptiles'
 WHEN phylumKey IN ('52') THEN 'Molluscs'
 WHEN classKey IN ('367') THEN 'Arachnids'
 WHEN classKey IN ('220', '196') THEN 'Flowering Plants'
 WHEN classKey IN ('194', '244', '228', '282') THEN 'Gymnosperms'
 WHEN orderKey IN ('392') THEN 'Ferns'
 WHEN phylumKey IN ('35') THEN 'Mosses'
 WHEN phylumKey IN ('95') THEN 'Sac Fungi'
 WHEN phylumKey IN ('34') THEN 'Basidiomycota'
 END AS taxonomic_group,
 COUNT(DISTINCT speciesKey) AS species_count
FROM occurrence
WHERE countryCode = 'TR'
 AND hasCoordinate = TRUE
 AND hasGeospatialIssues = FALSE
 AND coordinateUncertaintyInMeters &lt;= 2000
 AND occurrenceStatus = 'PRESENT'
 AND speciesKey IS NOT NULL
 AND basisOfRecord != 'FOSSIL_SPECIMEN'
 AND taxonRank = 'SPECIES'
 AND (
 classKey IN ('359', '212', '131', '216', '11418114', '11569602', '11592253', '11493978', '367', '220', '196', '194', '244', '228', '282')
 OR familyKey IN ('1103', '1104', '494', '495', '1105', '496', '497', '1106', '498', '499', '1107', '537', '538', '1153', '547', '1162', '548', '549', '550', '1163', '1164', '1165', '1166', '1167', '1305', '1067', '1306', '1307', '1308', '1068', '1069', '587', '1310', '588', '589', '1311', '1312', '1313', '590', '708', '890', '774', '889', '773', '772', '888', '765', '879')
 OR phylumKey IN ('52', '35', '95', '34')
 OR orderKey IN ('392')
 )
GROUP BY geogrid_id, taxonomic_group;


 The dataset's 1277 records were derived from 151 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003413-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18393536
title: A Multidetector Fluorescence Flow Cell with Software-Based Calibration for High Optical Density Analysis - Experimental data

description: This repository contains the processed datasets and raw instrument exports supporting the manuscript “A Multidetector Fluorescence Flow Cell with Software-Based Calibration for High Optical Density Analysis” (manuscript in preparation; citation data will be updated pending publication).

The study evaluates inner-filter-effect correction using two fixed fluorescence detection points (F0, F1) in a custom flow cell under (i) static sample loading and (ii) continuous-flow gradient conditions.

Contents

1) Processed datasets (Excel)



Weitner and Sakic-Multidetector Fluorescence Flow Cell-STATIC.xlsx: static (manual) sample loading dataset including fluorescein concentration series, extracted fluorescence signals (F0, F1), calibrated/corrected signal (F_IFE-CORR), and summary performance metrics (e.g., R2, LOD%, mErr%) used in the manuscript figures and analysis.

Weitner and Sakic-Multidetector Fluorescence Flow Cell-FLOW.xlsx: continuous-flow gradient dataset including time-point series across the usable gradient window (2–98% B), extracted fluorescence signals (F0, F1), calibrated/corrected signal (F_IFE-CORR), and summary performance metrics used in the manuscript.


2) Raw instrument exports (ASCII)These files are provided to enable full reprocessing from primary instrument outputs.

(a) ÄKTA start exports (gradient method + run log)



Method export (UNICORN start 1.1): tabulated parameter list for the programmed gradient, including flow rate, mixer/delay volume parameters, and gradient segment definitions (0–100% B).

Raw run data export: time/volume series, including UV (mAU), gradient concentration (%B), system flow, pressure, and run log annotations.


(b) Ocean Optics exports (spectral time series)



ASCII spectral time-series exports recorded during gradient runs, including acquisition metadata (spectrometer ID, trigger mode, scans-to-average, integration time, pixel count) followed by wavelength-resolved spectra. These files provide the raw fluorescence spectra from which F0/F1 intensities were extracted.


Notes on gradient verification / correction

The effective gradient delivered to the flow cell was verified using on-line UV absorbance at 280 nm from the ÄKTA UV detector (0.2 cm path length). Due to known non-linearity at the gradient endpoints (valve duty-cycle limits and mixer dispersion), only the central 2–98% B region was used for inner-filter-effect evaluation; the initial and final 2% were excluded. The measured UV trace was used to construct a corrected gradient axis for downstream analysis by mapping the recorded signal onto an ideal linear gradient.

Reuse

Users can reproduce the manuscript plots directly from the Excel files or recompute fluorescence extraction and calibration from the raw ASCII exports.