cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5255/ukda-sn-5181-1
title: International Energy Agency Carbon Dioxide (CO2) Emissions from Fuel Combustion, 1960-2015
title: IEA CO2 Emissions from Fuel Combustion

description: The International Energy Agency (IEA) datasets published by the Energy Statistics Division (ESD) contain annual and quarterly time series data from 1960 onwards on energy production, trade, stocks, transformation, consumption, prices and taxes as well as on greenhouse gas emissions for over the 30 OECD Member countries and over 100 non-OECD countries world-wide.&lt;br&gt;
&lt;br&gt;
In OECD Member countries the data are collected by official bodies (most often the national statistics office in each country) from firms, government agencies and industry organisations and are then reported to the IEA using questionnaires to ensure international comparability. In non-OECD countries the data are collected directly from government and industry contacts and from national publications.&lt;br&gt;
&lt;br&gt;
The &lt;i&gt;International Energy Agency (IEA) Carbon Dioxide (CO2) Emissions from Fuel Combustion&lt;/i&gt; database provides a comparative analysis of CO2 emissions from fossil fuel combustion, a major source of anthropogenic emissions. The data are designed to assist in understanding the evolution of these emissions on a country, regional and worldwide basis. Data are included for 30 Organisation for Economic Co-operation and Development (OECD) countries and for more than 100 non-OECD countries and regions. In general, OECD data are available from 1960 and non-OECD data from 1971 onwards. Emissions have been calculated using the IEA energy databases (see also SNs 5182-5189) and the default methods and emissions factors from the &lt;i&gt;Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories&lt;/i&gt;. &lt;br&gt;
&lt;br&gt;
These data were first provided by the UK Data Service in June 2005 and are updated annually. The UK Data Service web site includes further information on its &lt;i&gt;IEA CO2 Emissions from Fuel Combustion&lt;/i&gt; holdings, including a &lt;a href="http://ukdataservice.ac.uk//use-data/guides/dataset/iea.aspx" title="IEA CO2 Emissions from Fuel Combustion dataset user guide"&gt;dataset user guide&lt;/a&gt;  and details of &lt;a href=" http://dx.doi.org/10.5257/iea/co2/2010" title="IEA CO2 Emissions from Fuel Combustion latest database updates"&gt;latest database updates&lt;/a&gt;.&lt;br&gt;
&lt;br&gt;
&lt;b&gt;Citation:&lt;/b&gt; The bibliographic citation for the database is: International Energy Agency (&lt;i&gt;{YYYY}&lt;/i&gt;): CO2 Emissions from Fuel Combustion (&lt;i&gt;{Ed. YYYY}&lt;/i&gt;). UK Data Service. DOI: &lt;i&gt;{edition specific doi - e.g. &lt;a href="http://dx.doi.org/10.5257/iea/co2/2010"&gt;http://dx.doi.org/10.5257/iea/co2/2010&lt;/a&gt;}&lt;/i&gt;. &lt;br&gt;
&lt;br&gt;
&lt;b&gt;Alternative DOIs:&lt;/b&gt; &lt;a href="http://www.oecd-ilibrary.org/energy/data/iea-co2-emissions-from-fuel-combustion-statistics_co2-data-en" title="10.1787/co2-data-en"&gt;10.1787/co2-data-en&lt;/a&gt; (to access via OECD.Stat subscription).&lt;br&gt;
DOI: 10.5255/ukda-sn-5182-1
title: International Energy Agency Coal Information, 1960-2015
title: IEA Coal Information

description: The International Energy Agency (IEA) datasets published by the Energy Statistics Division (ESD) contain annual and quarterly time series data from 1960 onwards on energy production, trade, stocks, transformation, consumption, prices and taxes as well as on greenhouse gas emissions for over the 30 OECD Member countries and over 100 non-OECD countries world-wide.&lt;br&gt;
&lt;br&gt;
In OECD Member countries the data are collected by official bodies (most often the national statistics office in each country) from firms, government agencies and industry organisations and are then reported to the IEA using questionnaires to ensure international comparability. In non-OECD countries the data are collected directly from government and industry contacts and from national publications.&lt;br&gt;
&lt;br&gt;
The &lt;i&gt;International Energy Agency (IEA) Coal Information&lt;/i&gt; database contains a complete time series of coal statistics corresponding to the data shown in Part II of the annual IEA publication &lt;i&gt;Coal Information&lt;/i&gt;. Selected tables from Part I of the publication are also included, as well as a database of worldwide coal statistics covering production, trade, use in transformation (electricity and heat production) and final consumption in industry and other sectors. The &lt;i&gt;Coal Information&lt;/i&gt; database contains a time series of annual coal data for Organisation for Economic Co-operation and Development (OECD) and non-OECD countries from 1960 onwards. The &lt;i&gt;Coal Information&lt;/i&gt; data is structured into four databases and a set of selected tables. The database is updated by the IEA in July each year.&lt;br&gt;
&lt;br&gt;
These data were first provided by the UK Data Service in June 2005 and are updated annually. The UK Data Service web site includes further information on its &lt;i&gt;IEA Coal Information&lt;/i&gt; holdings, including a &lt;a href="http://ukdataservice.ac.uk//use-data/guides/dataset/iea.aspx" title="IEA Coal Information dataset user guide"&gt; dataset user guide&lt;/a&gt; and details of &lt;a href="http://dx.doi.org/10.5257/iea/coal/2011" title="IEA Coal Information latest database updates"&gt;latest database updates&lt;/a&gt;.&lt;br&gt;
&lt;br&gt;
&lt;b&gt;Citation:&lt;/b&gt; The bibliographic citation for the database is:  International Energy Agency ({YYYY}): Coal Information, YYYY-YYYY (Data downloaded: DD Month YYYY}). UK Data Service. DOI: &lt;I&gt;{edition specific doi - e.g. http://dx.doi.org/10.5257/iea/coal/2015}.&lt;/i&gt; &lt;br&gt;
&lt;br&gt;
&lt;b&gt;Alternative DOIs:&lt;/b&gt; &lt;a href="http://www.oecd-ilibrary.org/energy/data/iea-coal-information-statistics_coal-data-en" title="10.1787/coal-data-en"&gt;10.1787/coal-data-en&lt;/a&gt; (to access via OECD.Stat subscription).&lt;br&gt;
&lt;br&gt;
DOI: 10.25549/inscriptifact-ouc110601474
title: Persepolis Fortification Aramaic Text 435, PFAT 435

description: [Text Description:] Administrative text with seals PFATS 0028s ❧ [Text or Publication Number Note:] PFAT 435, Bowman 435 ❧ [Excavation Description:] Found during Oriental Institute's excavations in Spring, 1933, near the northeastern corner of the stone platform of Persepolis, in two small rooms of a bastion in the fortification wall ❧ [Medium:] Clay ❧ [Script Note:] Aramaic ❧ [Physical Object Description:] Clay tablet with ink inscription. Seal impression PFATS 0028s on reverse. ❧ [Physical Object Note:] Damage on round edge.
DOI: 10.5255/ukda-sn-5183-1
title: International Energy Agency Electricity Information, 1960-2015
title: IEA Electricity Information

description: The International Energy Agency (IEA) datasets published by the Energy Statistics Division (ESD) contain annual, and a small amount of quarterly and monthly time series data from 1960 onwards. The database covers energy production, trade, stocks, transformation, consumption, prices and taxes as well as on greenhouse gas emissions for over the 30 OECD Member countries and over 100 non-OECD countries world-wide.&lt;br&gt;
&lt;br&gt;
In OECD Member countries the data are collected by official bodies (most often the national statistics office in each country) from firms, government agencies and industry organisations and are then reported to the IEA using questionnaires to ensure international comparability. In non-OECD countries the data are collected directly from government and industry contacts and from national publications.&lt;br&gt;
&lt;br&gt;
The International Energy Agency (IEA) Electricity Information database contains a time series of electricity statistics of OECD countries for supply, consumption, trade, capacity and price, and some projection data corresponding to the data shown in Part II of the annual IEA publication Electricity Information. Where available, all tables from Part I of the publication are also included. Data are based on submissions from national administrations to the Secretariat. The database contains a time series of annual electricity and heat data for Organisation for Economic Co-operation and Development (OECD) countries from 1960 onwards. The Electricity Information database is structured into eight tables. This database is updated by the IEA in September each year.&lt;br&gt;
&lt;br&gt;
These data were first provided by the UK Data Service in June 2005 and are updated annually. The UK Data Service web site includes further information on its &lt;i&gt;IEA Electricity Information&lt;/i&gt; holdings, including a &lt;a href=" http://ukdataservice.ac.uk//use-data/guides/dataset/iea.aspx" title="IEA Electricity Information dataset user guide"&gt;dataset user guide&lt;/a&gt; and details of &lt;a href="http://dx.doi.org/10.5257/iea/elec/2011" title=" IEA Electricity Information latest database updates"&gt;latest database updates&lt;/a&gt;.&lt;br&gt;
&lt;br&gt;
&lt;b&gt;Citation:&lt;/b&gt; The bibliographic citation for the database is: International Energy Agency (&lt;i&gt;{YYYY}&lt;/i&gt;): Electricity Information (&lt;i&gt;{Ed. YYYY}&lt;/i&gt;). UK Data Service. DOI: &lt;i&gt;{edition specific doi - e.g. &lt;a href="http://dx.doi.org/10.5257/iea/elec/2011"&gt;http://dx.doi.org/10.5257/iea/elec/2011&lt;/a&gt;}&lt;/i&gt;. &lt;br&gt;
&lt;br&gt;
&lt;b&gt;Alternative DOIs:&lt;/b&gt; &lt;a href="http://www.oecd-ilibrary.org/energy/data/iea-electricity-information-statistics_elect-data-en" title="10.1787/elect-data-en"&gt;10.1787/elect-data-en&lt;/a&gt; (to access via OECD.Stat subscription).&lt;br&gt;
&lt;br&gt;
DOI: 10.5255/ukda-sn-5184-1
title: International Energy Agency Energy Prices and Taxes, 1978-2016
title: IEA Energy Prices and Taxes

description: The International Energy Agency (IEA) datasets published by the Energy Statistics Division (ESD) contain annual and quarterly time series data from 1960 onwards on energy production, trade, stocks, transformation, consumption, prices and taxes as well as on greenhouse gas emissions for over the 30 OECD Member countries and over 100 non-OECD countries world-wide.&lt;br&gt;
&lt;br&gt;
In OECD Member countries the data are collected by official bodies (most often the national statistics office in each country) from firms, government agencies and industry organisations and are then reported to the IEA using questionnaires to ensure international comparability. In non-OECD countries the data are collected directly from government and industry contacts and from national publications.&lt;br&gt;
&lt;br&gt;
The &lt;i&gt;International Energy Agency (IEA) Energy Prices and Taxes&lt;/i&gt; database contains a major international compilation of energy prices at all market levels: import prices, industry prices and consumer prices. The statistics cover import costs and export prices of main petroleum products, natural gas and coal in Organisation for Economic Co-operation and Development (OECD) countries. End-user prices and taxes for selected petroleum, gas and coal products as well as for electricity are provided for industry, electricity generation and households for OECD countries and a selection of non-OECD countries. Full notes on sources and methods and a description of price mechanisms in each country are included. Time series availability varies with each data series. In general, end-user prices and taxes start in 1978, import costs in 1980 and spot prices in 1982. This database is updated by the IEA in January, April, July and October of each year.&lt;br&gt;
&lt;br&gt;
These data were first provided by the UK Data Service in June 2005 and are updated annually. The UK Data Service web site includes further information on its &lt;i&gt;IEA Energy Prices and Taxes&lt;/i&gt; holdings, including a &lt;a href=" http://ukdataservice.ac.uk//use-data/guides/dataset/iea.aspx" title="IEA Energy Prices and Taxes dataset user guide"&gt;dataset user guide&lt;/a&gt; and details of &lt;a href="http://dx.doi.org/10.5257/iea/ept/2011q3" title="IEA Energy Prices and Taxes latest database updates"&gt;latest database updates&lt;/a&gt;.&lt;br&gt;
&lt;br&gt;
&lt;b&gt;Citation:&lt;/b&gt; The bibliographic citation for the database is: International Energy Agency (&lt;i&gt;{YYYY}&lt;/i&gt;): Energy Prices and Taxes (&lt;i&gt;{Ed. YYYY-QQ}&lt;/i&gt;). UK Data Service. DOI: &lt;i&gt;{edition specific doi - e.g. &lt;a href="http://dx.doi.org/10.5257/iea/ept/2011q3"&gt;http://dx.doi.org/10.5257/iea/ept/2011q3&lt;/a&gt;}&lt;/i&gt;. &lt;br&gt;
&lt;br&gt;
&lt;b&gt;Alternative DOIs:&lt;/b&gt; &lt;a href="http://www.oecd-ilibrary.org/energy/data/iea-energy-prices-and-taxes-statistics_eneprice-data-en" title="10.1787/eneprice-data-en"&gt;10.1787/eneprice-data-en&lt;/a&gt; (to access via OECD.Stat subscription).&lt;br&gt;
DOI: 10.15468/dl.yrr4zp
title: Occurrence Download

description: A dataset containing 1420 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Benin",
 "OccurrenceStatus is Present",
 "TaxonKey is Phyllanthus amarus Schumach. & Thonn."
 ]
}

 The dataset includes 1420 records from 58 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010082-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25345/c52805b2d
title: MassIVE MSV000097686 - TIE-UP-SIN: A Novel Method for Enhanced Identification of Protein-Protein Interactions
title: Proteins are indispensable biomolecules playing vital roles in nearly every aspect of cellular function. They participate in processes such as enzymatic catalysis, signaling pathways, cell responses, pathogenicity as well as structural components of cells. Their structural and functional diversity are the foundation of biological complexity and adaptability. As many proteins function collaboratively through interactions with others, identifying protein-protein interactions (PPIs) is fundamental to understanding the complicated networks and pathways governing cellular activities. Numerous methods exist to study PPIs, including two-hybrid screening, co-immunoprecipitation, mass spectrometry (MS), and computational approaches. While each technique has its strengths, limitations such as high false-positive rates, technical complexity, and low efficiency can hinder precise identification of specific interaction partners. We present TIE-UP-SIN (Targeted Interactome Experiment for Unknown Proteins by Stable Isotope Normalization), a novel simple and straight forward approach for in vivo PPI identification. It combines stable isotope labeling, reversible crosslinking, and affinity purification with highly sensitive mass spectrometry analysis. Stable isotope labeling improves MS data by enhancing quantification accuracy and reproducibility while reducing the number of false discoveries. Rapid, cost-effective reversible crosslinking captures transient interactions for stringent purification, ensuring maximum specificity. The effectiveness of TIE-UP-SIN is showcased by identifying key interaction partners of the essential Bacillus subtilis sigma factor RpoD (SigA) under control and ethanol stress conditions, highlighting its reliability and affordability for in vivo protein-protein interaction studies.
DOI: 10.21415/n146-p733
title: CHILDES Japanese-English CSLAD Corpus
DOI: 10.25935/2f8g-c505
title: Cassini RPWS Jupiter Encounter Calibrated Dataset

description: This dataset contains calibrated Cassini-RPWS-HFR Jupiter fly-by data from 6 months of Jupiter encounter: 2000-275 (Oct 1st) 00:00 to 2001-090 (Mar 31st) 24:00. The spectral range covers 3.5 kHz to 16 MHz.
DOI: 10.25935/5jfx-dh49
title: Cassini/RPWS/HFR LESIA/Kronos N3d Data Collection

description: This collection is composed of Cassini/RPWS/HFR (Radio and Plasma Waves Science / High Frequency Receiver) hourly N3d (Level 3d) files.
DOI: 10.25935/6d16-bm97
title: Cassini/RPWS/HFR LESIA/Kronos Northern and Southern SKR Phase Systems

description: This collection is composed of the Southern and Northern SKR phase systems derived from Cassini/RPWS/HFR (Radio and Plasma Waves Science / High Frequency Receiver) measurements, as described in Lamy (2011).
DOI: 10.25935/9zab-fp47
title: Cassini/RPWS/HFR LESIA/Kronos N3e Data Collection

description: This collection is composed of Cassini/RPWS/HFR (Radio and Plasma Waves Science / High Frequency Receiver) hourly N3e (Level 3e) files.
DOI: 10.25935/b9nf-9558
title: Cassini/RPWS/HFR LESIA/Kronos QTN Data Collection V1.0

description: This collection is composed of Cassini RPWS Quasi Thermal Noise (QTN) data set contains thermal plasma parameters derived by QTN spectroscopy analysis applied on data acquired with the High Frequency Receiver (HFR) during the perikrones of the entire mission.
DOI: 10.25935/f8ns-0911
title: Cassini/RPWS/HFR LESIA/Kronos N3b Data Collection
DOI: 10.25935/h98j-ma66
title: Cassini RPWS Jupiter Encounter Calibrated Dataset

description: This dataset contains calibrated Cassini-RPWS-HFR Jupiter fly-by data from 6 months of Jupiter encounter: 2000-275 (Oct 1st) 00:00 to 2001-090 (Mar 31st) 24:00. The spectral range covers 3.5 kHz to 16 MHz. The data is available in CDF format. Processing routines are provided in IDL and Python.
DOI: 10.25935/xs9j-nd90
title: Cassini/RPWS/HFR LESIA/Kronos N2 Dataset

description: This collection is composed of Cassini/RPWS/NHFR (Radio and Plasma Waves Science / High Frequency Receiver) hourly N2 (Level 2) files.
DOI: 10.25935/zkxb-6c84
title: Cassini/RPWS/HFR LESIA/Kronos SKR Dataset

description: This collection is composed of Cassini/RPWS daily SKR derived files, as described in Lamy et al. (2008).
DOI: 10.13026/30k0-av04
title: MIMIC-III-Ext-Synthetic-Clinical-Trial-Questions

description: Large-language models (LLMs) show promise for extracting information from
clinical notes. Deploying these models at scale can be challenging due to high
computational costs, regulatory constraints, and privacy concerns. To address
these challenges, synthetic data distillation can be used to fine-tune
smaller, open-source LLMs that achieve performance similar to the teacher
model. These smaller models can be run on less expensive local hardware or at
a vastly reduced cost in cloud deployments.

In our recent study [1], we used Llama-3.1-70B-Instruct to generate synthetic
training examples in the form of question-answer pairs along with supporting
information. We manually reviewed 1000 of these examples and release them
here. These examples can then be used to fine-tune smaller versions of Llama
to improve their ability to extract clinical information from notes.
DOI: 10.13026/rqxd-sz93
title: MIMIC-III-Ext-Synthetic-Clinical-Trial-Questions

description: Large-language models (LLMs) show promise for extracting information from
clinical notes. Deploying these models at scale can be challenging due to high
computational costs, regulatory constraints, and privacy concerns. To address
these challenges, synthetic data distillation can be used to fine-tune
smaller, open-source LLMs that achieve performance similar to the teacher
model. These smaller models can be run on less expensive local hardware or at
a vastly reduced cost in cloud deployments.

In our recent study [1], we used Llama-3.1-70B-Instruct to generate synthetic
training examples in the form of question-answer pairs along with supporting
information. We manually reviewed 1000 of these examples and release them
here. These examples can then be used to fine-tune smaller versions of Llama
to improve their ability to extract clinical information from notes.
DOI: 10.15468/dl.3m8g96
title: Occurrence Download

description: A dataset containing 536939 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is University of California Museum of Paleontology"
 ]
}

 The dataset includes 536939 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009974-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14974654
title: Time-Series of Shoreline Marine Debris Highlights Impact of Urbanization on Coastal Pollution Pathways, Nha Trang, Vietnam

description: This dataset includes marine debris shoreline surveys conducted every 4-8 days from October 2022 to January 2023 (Raw dataset: Marine Debris Counts). Transects were walked on each beach and debris counted in typically 3x3 meter quadrants.  Microplastics were measured in surface sand or sediment at each site (dataset Microplastic10-9-2022.xlsx).  Type of shoreline debris was noted on select sampling days (dataset ShorelineDebrisType). Environmental drivers (e.g., wind, waves, tides, and precipitation) were collected to compare against marine debris data (EnvironmentalDriverData_with_MeanDebrisConcentrations.xlsx).
DOI: 10.5281/zenodo.14974655
title: Time-Series of Shoreline Marine Debris Highlights Impact of Urbanization on Coastal Pollution Pathways, Nha Trang, Vietnam

description: This dataset includes marine debris shoreline surveys conducted every 4-8 days from October 2022 to January 2023 (Raw dataset: Marine Debris Counts). Transects were walked on each beach and debris counted in typically 3x3 meter quadrants.  Microplastics were measured in surface sand or sediment at each site (dataset Microplastic10-9-2022.xlsx).  Type of shoreline debris was noted on select sampling days (dataset ShorelineDebrisType). Environmental drivers (e.g., wind, waves, tides, and precipitation) were collected to compare against marine debris data (EnvironmentalDriverData_with_MeanDebrisConcentrations.xlsx).
DOI: 10.15468/dl.89657g
title: Occurrence Download

description: A dataset containing 2648 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Podocarpus oleifolius D.Don"
 ]
}

 The dataset includes 2648 records from 160 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009978-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28840718
title: Preference score for each bee species

description: Pollen preference score attributed to each bee species according to their interactions, protein-lipid ratio preference and K-Na content.
DOI: 10.5517/ccdc.csd.cc2k6lr4
title: CCDC 2359836: Experimental Crystal Structure Determination

description: Related Article: Paru Jamwal, Yumnam Nganthoinganbi, Ming-Kang Tsai, Ramani Gurubrahamam|2025|J.Org.Chem.|90|4545|doi:10.1021/acs.joc.4c02951
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2k9xph
title: CCDC 2363027: Experimental Crystal Structure Determination

description: Related Article: Soumen Biswas, Ramon Trevino, Seth O. Fremin, Luis Mario Sanchez-Palestino, Babu Raj Dhungana, Arka Porey, William B. Hughes, Hadi D. Arman, Oleg V. Larionov, Michael P. Doyle|2025|J.Am.Chem.Soc.|147|12308|doi:10.1021/jacs.5c02500
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.