cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/x4xfh2kcdy.3
title: NUTS2 Level Land Use and Land Cover Quantifications under the Shared Socio-Economic Pathways, 2020-2050

description: This dataset provides consistent projections of land use and land cover (LULC) for European NUTS2 regions under the five Shared Socio-Economic Pathways (SSPs) from 2020 to 2050. 

The projections are generated with G-RDEM [1], a recursive-dynamic global Computable General Equilibrium (CGE) model implemented in the open-source platform CGEBox [2]. Designed to capture long-term structural change, G-RDEM simulates economic and land use dynamics directly at the NUTS2 level, avoiding the need for post-model downscaling. European Union (EU) member states follow the 2016 NUTS2 classification [3], while European Free Trade Association (EFTA) countries and EU accession candidates follow the 2008 NUTS2 classification [4]. 

The dataset includes:
• Scenarios: 
 - SSP1
 - SSP2
 - SSP3
 - SSP4
 - SSP5
• Regions: 
 - NUTS2 regions for EU member states, EU accession candidates, and EFTA countries
 - Country level results for Morocco, Algeria, Tunisia, Egypt, the rest of North Africa, Russia, Belarus, and Ukraine
 - Continental aggregates for the rest of the world
• Land cover and corresponding land uses: 
 - Built-up land 
 * No economic land uses
 - Cropland 
 * Apples
 * Bananas/ plantains 
 * Barley 
 * Citrus fruits
 * Cocoa beans
 * Coffee beans
 * Grapes
 * Leguminosae
 * Maize
 * Nuts 
 * Oats 
 * Olives 
 * Other cereals
 * Other crops
 * Other fruits 
 * Other oilseeds 
 * Other roots/ tubers
 * Other vegetables
 * Paddy rice 
 * Palm oil fruit 
 * Plant-based fibres
 * Potatoes 
 * Rape seed 
 * Rye
 * Sorghum
 * Soy bean
 * Sugar cane/ beet
 * Teas
 * Tomatoes
 * Wheat
 * All cropland uses are further differentiated between irrigated and rainfed variants
 - Managed forest 
 * Forestry
 - Other land (rock, ice, desert)
 * No economic land uses
 - Pastureland 
 * Cattle for meat
 * Raw milk
 * Ruminants for meat
 * Wool
 - Savannah/ grassland
 * No economic land uses
 - Shrubland
 * No economic land uses
 - Unmanaged forest
 * No economic land uses
• Units: mio ha
• Temporal coverage: 2020–2050, 2- and 5-year intervals
• Format: CSV and XLSX

The dataset is suitable for applications in climate impact research, ecosystem service assessment, water and biodiversity modelling, land use and land cover planning, and other policy scenario analysis.
DOI: 10.26188/30739082
title: Discovered Process Models from Noisy Logs

description: The dataset consists of three folders:<b>Systems:</b> Three public event logs: <i>Sepsis Cases</i>, <i>RTFMS</i>, and <i>BPIC 2012</i>.<b>Logs:</b> Clean and noisy logs derived from the base systems.<br>From each base log, we created samples of seven sizes (1000, 2000, 4000, 10000, 20000, 40000, 100000 traces) using sampling with replacement, yielding 21 clean logs.<br>Noise was then added using $\snip$ across seven intensity levels (0.1%, 0.2%, 0.4%, 1.0%, 2.0%, 4.0%, 10.0%) and five noise types (absence, insertion, ordering, substitution, mixed). Percentages refer to the number of trace-level injections.<br>Each configuration was repeated five times, producing 3,675 noisy logs and a total of 3,696 logs.<b>Models:</b> Contains discovered models for all clean logs and a random subset of noisy logs (incomplete), using the Alpha, Heuristics, and Inductive miners.
DOI: 10.26188/30739082.v1
title: Discovered Process Models from Noisy Logs

description: The dataset consists of three folders:<b>Systems:</b> Three public event logs: <i>Sepsis Cases</i>, <i>RTFMS</i>, and <i>BPIC 2012</i>.<b>Logs:</b> Clean and noisy logs derived from the base systems.<br>From each base log, we created samples of seven sizes (1000, 2000, 4000, 10000, 20000, 40000, 100000 traces) using sampling with replacement, yielding 21 clean logs.<br>Noise was then added using $\snip$ across seven intensity levels (0.1%, 0.2%, 0.4%, 1.0%, 2.0%, 4.0%, 10.0%) and five noise types (absence, insertion, ordering, substitution, mixed). Percentages refer to the number of trace-level injections.<br>Each configuration was repeated five times, producing 3,675 noisy logs and a total of 3,696 logs.<b>Models:</b> Contains discovered models for all clean logs and a random subset of noisy logs (incomplete), using the Alpha, Heuristics, and Inductive miners.
DOI: 10.17632/gd3syw8wsb
title: Local Time and Seasonal Variations of Protonated Ions in the Martian upper atmosphere: Roles of Solar Insolation and Ion-neutral Chemistry

description: This is the dataset to accompany our publication, "Local Time and Seasonal Variations of Protonated Ions in the Martian upper atmosphere", in journal JGR Planets. The repository contains .csv files. Within the files are the data shown in Figures 1 to 6 of the manuscript. The MAVEN NGIMS data set used in this analysis is publicly available on the NASA Planetary Data System (PDS, see https://doi.org/10.17189/1518931) and the MAVEN Science Data Center (SDC, see https://lasp.colorado.edu/maven/sdc/public/pages/datasets/ngims.html).
DOI: 10.17632/gd3syw8wsb.1
title: Local Time and Seasonal Variations of Protonated Ions in the Martian upper atmosphere: Roles of Solar Insolation and Ion-neutral Chemistry

description: This is the dataset to accompany our publication, "Local Time and Seasonal Variations of Protonated Ions in the Martian upper atmosphere", in journal JGR Planets. The repository contains .csv files. Within the files are the data shown in Figures 1 to 6 of the manuscript. The MAVEN NGIMS data set used in this analysis is publicly available on the NASA Planetary Data System (PDS, see https://doi.org/10.17189/1518931) and the MAVEN Science Data Center (SDC, see https://lasp.colorado.edu/maven/sdc/public/pages/datasets/ngims.html).
DOI: 10.34808/h628-m476
title: Enriched Time-Series Dataset of Polish Forest Composition (2009-2019)

description: This dataset contains processed forest inventory data from Polish State Forests covering the period 2009-2019. The dataset includes both original inventory measurements and derived metrics calculated using established forestry and ecological methods.
Dataset Contents:
Data files:

Original data with standardized classifications (1,260 records)
Annual summary statistics (11 years)
Biodiversity indices (Shannon, Simpson, Pielou's evenness, species richness)
Forest structure metrics (age distribution, weighted mean age)
Composition analysis (coniferous/deciduous ratios, dominant species)
Growth and productivity metrics (MAI, CAI, volume density)
Temporal trends (year-over-year changes)
Species-specific annual metrics (110 records: 10 species × 11 years)

Data Provenance System
Each calculated variable includes a companion column indicating its source:

RAW: Original measurement from inventory
RAW_SUMMED: Aggregated raw values
CALCULATED: Formula-derived from raw data
COUNTED: Direct count from data
DETERMINED: Identified through analysis

Documentation:

Data dictionary: Definitions for 100+ variables
Methodology: Formulas and scientific references for all calculations
Metadata: Explanation of source type categories
README: Dataset overview and usage information

Limitations:

Species are taxonomically aggregated (e.g., "Oak" includes multiple Quercus species)
National-level data without regional breakdowns
Avg_Age field provided only for species-level totals (Total_Area), not for age class breakdowns (110/1,260 records)
Age class midpoints estimated where exact distributions unavailable
DOI: 10.15468/dl.45c6dt
title: Occurrence Download

description: A dataset containing 4875 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Orthoptera",
 "Year 1981-2020"
 ]
}

 The dataset includes 4875 records from 85 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014083-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48459/0k0j-pa33
title: New Dimensions - VESTVIKA, Svalbard
DOI: 10.17632/sn9y2vtmbg
title: Table S1．Information of antibiotic resistance and transmissible elements genes

description: Information of antibiotic resistance and transmissible elements genes
DOI: 10.17632/sn9y2vtmbg.1
title: Table S1．Information of antibiotic resistance and transmissible elements genes

description: Information of antibiotic resistance and transmissible elements genes
DOI: 10.17632/454wknmh4c
title: Dataset: Technological Progress Specific to Investment

description: Definition of data variables

Real output = LN(Gross Domestic Product/ PCE Deflator/ Population) * 100 
Real consumption = LN((Personal Consumption Expenditures/ PCE Deflator) / Population) * 100
Real investment = LN((Private Non-Residential Investment/ PCE Deflator) / Population) * 100
Hours worked = LN((Average Weekly Hours * Employment/ 100)/ Population) * 100 
Inflation = LN(PCE Deflator / PCE Deflator (-1) ) * 100
Real wage = LN(Hourly Compensation / PCE Deflator) * 100 
Policy interest rate = Federal Funds Rate / 4
Relative price of investment = -1 * LN(Price Index of Private Non-Residential Investment/ PCE Deflator) *100 

Source of the original data

Gross Domestic Product: Gross Domestic Product, Table 1.1.5. Gross Domestic Product, NIPA
Source: U.S. Bureau of Economic Analysis

Personal Consumption Expenditures: Personal Consumption Expenditures, Table 1.1.5. Gross Domestic Product, NIPA 
Source: U.S. Bureau of Economic Analysis 

Private Non-Residential Investment: Private Non-Residential Investment, Table 1.1.5 Gross Domestic Product, NIPA 
Source: U.S. Bureau of Economic Analysis

PCE Deflator: Personal Consumption Expenditures, Table 1.1.9. Implicit Price Deflator for Gross Domestic Product 
Source: U.S. Bureau of Economic Analysis 

Price Index of Private Non-Residential Investment: Private Non-Residential Capital Formation, Deflator (PIB), OECD Economic Outlook Database
Source: Organisation for Economic Co-Operation and Development

Population: Population level, Civilian Noninstitutional Population, 16 Years and Over, Labor Force Statistics from the Current Population Survey, Series ID = LNS10000000
Source: U.S. Bureau of Labor Statistics

(Period: 1947 – 1975)
Population: Population level, Civilian Noninstitutional Population, 16 Years and Over, Labor Force Statistics from the Current Population Survey, Series ID = LNU00000000
Source: U.S. Bureau of Labor Statistics

Employment: Employment level, Employed, 16 Years and Over, All Industries, All Occupations, Labor Force Statistics from the Current Population Survey, Series ID = LNS12000000 
Source: U.S. Bureau of Labor Statistics

Average Weekly Hours: Average Weekly Hours, Major Sector Productivity and Costs, Nonfarm Business, Series ID = PRS85006023 
Source : U.S. Bureau of Labor Statistics

Hourly Compensation: Hourly Compensation, Major Sector Productivity and Costs, Nonfarm Business, Series ID = PRS85006103 
Source : U.S. Bureau of Labor Statistics

Federal Funds Rate: Averages of Monthly Figures - Percent 
Source: Board of Governors of the Federal Reserve System
DOI: 10.17632/454wknmh4c.2
title: Dataset: Technological Progress Specific to Investment

description: Definition of data variables

Real output = LN(Gross Domestic Product/ PCE Deflator/ Population) * 100 
Real consumption = LN((Personal Consumption Expenditures/ PCE Deflator) / Population) * 100
Real investment = LN((Private Non-Residential Investment/ PCE Deflator) / Population) * 100
Hours worked = LN((Average Weekly Hours * Employment/ 100)/ Population) * 100 
Inflation = LN(PCE Deflator / PCE Deflator (-1) ) * 100
Real wage = LN(Hourly Compensation / PCE Deflator) * 100 
Policy interest rate = Federal Funds Rate / 4
Relative price of investment = -1 * LN(Price Index of Private Non-Residential Investment/ PCE Deflator) *100 

Source of the original data

Gross Domestic Product: Gross Domestic Product, Table 1.1.5. Gross Domestic Product, NIPA
Source: U.S. Bureau of Economic Analysis

Personal Consumption Expenditures: Personal Consumption Expenditures, Table 1.1.5. Gross Domestic Product, NIPA 
Source: U.S. Bureau of Economic Analysis 

Private Non-Residential Investment: Private Non-Residential Investment, Table 1.1.5 Gross Domestic Product, NIPA 
Source: U.S. Bureau of Economic Analysis

PCE Deflator: Personal Consumption Expenditures, Table 1.1.9. Implicit Price Deflator for Gross Domestic Product 
Source: U.S. Bureau of Economic Analysis 

Price Index of Private Non-Residential Investment: Private Non-Residential Capital Formation, Deflator (PIB), OECD Economic Outlook Database
Source: Organisation for Economic Co-Operation and Development

Population: Population level, Civilian Noninstitutional Population, 16 Years and Over, Labor Force Statistics from the Current Population Survey, Series ID = LNS10000000
Source: U.S. Bureau of Labor Statistics

(Period: 1947 – 1975)
Population: Population level, Civilian Noninstitutional Population, 16 Years and Over, Labor Force Statistics from the Current Population Survey, Series ID = LNU00000000
Source: U.S. Bureau of Labor Statistics

Employment: Employment level, Employed, 16 Years and Over, All Industries, All Occupations, Labor Force Statistics from the Current Population Survey, Series ID = LNS12000000 
Source: U.S. Bureau of Labor Statistics

Average Weekly Hours: Average Weekly Hours, Major Sector Productivity and Costs, Nonfarm Business, Series ID = PRS85006023 
Source : U.S. Bureau of Labor Statistics

Hourly Compensation: Hourly Compensation, Major Sector Productivity and Costs, Nonfarm Business, Series ID = PRS85006103 
Source : U.S. Bureau of Labor Statistics

Federal Funds Rate: Averages of Monthly Figures - Percent 
Source: Board of Governors of the Federal Reserve System
DOI: 10.5281/zenodo.17750566
title: Current Intellectual Structure and Emerging Trends on Nano-Drug Delivery Systems in Traditional Herbal Monomers: A Bibliometric and Visualized Analysis from 2013 to 2025

description: This dataset contains bibliographic and analytical data used for a bibliometric and visualization study on nano-drug delivery systems based on traditional herbal monomers (2013–2025). The data include publication metadata, countries, institutions, keywords, and citation relationships retrieved from the Web of Science Core Collection. Raw Web of Science records are not publicly shared due to database licensing restrictions. The dataset supports the findings of the associated manuscript.
DOI: 10.5281/zenodo.17750565
title: Current Intellectual Structure and Emerging Trends on Nano-Drug Delivery Systems in Traditional Herbal Monomers: A Bibliometric and Visualized Analysis from 2013 to 2025

description: This dataset contains bibliographic and analytical data used for a bibliometric and visualization study on nano-drug delivery systems based on traditional herbal monomers (2013–2025). The data include publication metadata, countries, institutions, keywords, and citation relationships retrieved from the Web of Science Core Collection. Raw Web of Science records are not publicly shared due to database licensing restrictions. The dataset supports the findings of the associated manuscript.
DOI: 10.48459/e69c-xq31
title: New Dimensions - GRUNNVÅGSLETTA, GRUNNVÅGEN, Svalbard
DOI: 10.15468/dl.scwzr5
title: Occurrence Download

description: A dataset containing 20321 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is France",
 "GadmGid is FRA.11.8_1",
 "PublishingOrg is one of (1928bdf0-f5d2-11dc-8c12-b8a03c50a862, 2cd829bb-b713-433d-99cf-64bef11e5b3e)",
 "TaxonKey is Pipistrellus pipistrellus"
 ]
}

 The dataset includes 20321 records from 156 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014082-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34808/6bep-g248
title: Investment expenditures of enterprises in Poland from 2005 to 2024

description: This dataset contains data on investment expenditures of enterprises in Poland on innovation activities from 2005 to 2024. The data is presented for all of Poland and for individual voivodeships. It includes information on enterprises in the service sector, industrial enterprises, and enterprises in general.
DOI: 10.34740/kaggle/dsv/13908686
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.xrperr
title: Occurrence Download

description: A dataset containing 235 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "Country is one of (Namibia, South Africa, Botswana, Madagascar, Zimbabwe, Côte d’Ivoire, Kenya, Zambia, Senegal)",
 "HasCoordinate is true",
 "Month is one of (January, February, March, April, May, June, July, August, September, October, November, December)",
 "TaxonKey is Salvinia molesta",
 "Year 2006-2025"
 ]
}

 The dataset includes 235 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014085-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34808/976g-yy26
title: Results of exposure of Hep G2 cells to ketoprofen solution

description: The data set presents the results of genotoxicity activity (using the Comet Assay) of ketoprofen on human HT29 adenocarcinoma cells.
The results and parameters of the study are presented in the publication Monika Wieczerzak, Jacek Namieśnik & Błażej Kudłak (2019): Genotoxicity of selected pharmaceuticals, their binary mixtures, and varying environmental conditions—study with human adenocarcinoma cancer HT29 cell line, Drug and Chemical ToxicologyTo link to this article: https://doi.org/10.1080/01480545.2018.1529783
Results performed in 2016/17
DOI: 10.34808/kh9n-j694
title: Results of exposure of Hep G2 cells to gemfibrozil solution

description: The data set presents the results of genotoxicity activity (using the Comet Assay) of gemfibrozil on human HT29 adenocarcinoma cells.
The results and parameters of the study are presented in the publication Monika Wieczerzak, Jacek Namieśnik & Błażej Kudłak (2019): Genotoxicity of selected pharmaceuticals, their binary mixtures, and varying environmental conditions—study with human adenocarcinoma cancer HT29 cell line, Drug and Chemical ToxicologyTo link to this article: https://doi.org/10.1080/01480545.2018.1529783
Results performed in 2016/17
DOI: 10.17026/ar/vaqy6f
title: Gemeente Gooise Meren, plangebied Amsterdamsestraatweg 51 te Naarden (terrein 93)
title: Archeologisch bureauonderzoek

description: &lt;p&gt;In het laat paleolithicum tot en met het midden neolithicum bestond het plangebied uit een dekzandlandschap dat geschikt was voor bewoning. Voor deze periode krijgt het plangebied dan ook een middelhoge verwachting. Vanaf het laat neolithicum raakte het plangebied bedekt met een pakket veen wat het plangebied vermoedelijk ongeschikt maakte voor menselijke bewoning. Dit bleef zo tot in de late middeleeuwen, wanneer in de 11e en 12e eeuw het veen werd ontgonnen. Voor deze natte periode krijgt het plangebied een lage verwachting. Voor de late middeleeuwen en nieuwe tijd krijgt het plangebied ook een lage verwachting, aangezien het plangebied enkel in gebruikt is geweest voor agrarische doeleinden zonder dat er een historisch erf in de buurt was. Dit maakt de kans klein dat er archeologische resten aanwezig zijn uit die periode. De aanwezigheid van archeologische resten van laat middeleeuwse ontginningsnederzettingen in de top van het veen kan niet worden uitgesloten, maar die kans wordt, op basis van de ligging en het ontbreken van bewoning in de nieuwe tijd, klein ingeschat. &lt;/p&gt;&lt;p&gt;

Binnen het plangebied kunnen vanaf circa 2 m -NAP nog archeologische resten voorkomen, mits de bodem nog intact is. Dit is waarschijnlijk het geval voor de top van het pleistocene zand. Door middel van een verkennend booronderzoek kan worden vastgesteld of deze top nog intact is en of hier sprake is van bodemvorming. Op basis hiervan kan de kans op archeologische resten worden ingeschat. Geadviseerd wordt om dit onderzoek voorafgaand aan bodemverstoringen groter dan 500 m2 (gemeentelijk beleid) en dieper dan 1,35 m -NAP (buffer 30 cm ten opzichte van ondiepste voorkomen pleistocene zand) uit te voeren. Voorafgaand aan het booronderzoek dienen de eisen waaraan het onderzoek dient te voldoen, te worden vastgelegd in een door de bevoegde overheid goed te keuren Plan van Aanpak (PvA). Bij ondiepere bodemverstoringen wordt geen vervolgonderzoek geadviseerd.&lt;/p&gt;
DOI: 10.34808/2p8z-4366
title: Area specific resistance (at 800 °C - 400 °C) of the Sr1.00Ti0.30Fe0.70O3 cathode sintered at different temperatures

description: In this dataset are presented results of the polarization resistance of differently sintered Sr1.00Ti0.30Fe0.70O3 cathode in symetrical cell. Applied sintering temperatures were 800 °C, 900 °C and 1000 °C. The measurement temperature range was between 800 °C and 400 °C with synthetic air flow (20% O2, 40 ml min-1). Results converted to electrode surfaces area and dived by two electrodes.
DOI: 10.34808/3nz7-ks28
title: Area specific resistance (at 800 °C - 400 °C) of the Sr1.05Ti0.30Fe0.70O3 cathode sintered at different temperatures

description: In this dataset are presented results of the polarization resistance of differently sintered Sr1.05Ti0.30Fe0.70O3 cathode in symetrical cell. Applied sintering temperatures were 800 °C, 900 °C and 1000 °C. The measurement temperature range was between 800 °C and 400 °C with synthetic air flow (20% O2, 40 ml min-1). Results converted to electrode surfaces area and dived by two electrodes.
DOI: 10.15468/dl.b9hhwr
title: Occurrence Download

description: A dataset containing 547 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is FRA.11.8_1",
 "OccurrenceStatus is Present",
 "PublishingOrg is 1928bdf0-f5d2-11dc-8c12-b8a03c50a862",
 "TaxonKey is Barbastella barbastellus"
 ]
}

 The dataset includes 547 records from 62 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014086-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.4121/b182af71-8a77-4454-8593-4ea8e7ee2f92
title: Supplementary benchmark data and experimental setup for "Experimental Studies of Regenerative Wind Farms Featuring Enhanced Vertical Energy Entrainment"

description: <br>This repository contains plotting scripts, representative processed data sets, post-processing scripts, an example set of raw data, CAD models, and experimental footage related to the study titled "Experimental Studies of Regenerative Wind Farms Featuring Enhanced Vertical Energy Entrainment" published in <em>Wind Energy Science</em> by Y. Li, M. Fijen, B. Dsouza, W. Yu, A. Sciacchitano, and C. Ferreira (https://doi.org/10.5194/wes-2025-156).<br>This dataset includes:<br>MATLAB scripts used to generate the figures in the associated publication.Data sets used for plotting.An example raw data set to demonstrate the post-processing workflow.CAD (Computer-Aided Design) models of the experimental setups.Time-lapse footage of the experiments.<br>Further descriptions are available in the file "README.txt".<br>