cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7910/dvn/fpxycm
title: Data for contextualized demand forecasting explanations

description: The dataset contains data encoded in files, following this convention:
 - features-ranking-SVR-month-materialid.json: ranking of features for specific forecast
 - events-SVR-month-featureid.json: events related to given featureid for a specific reference month on which the forecast was issued
 - events-keywords-SVR-month-featureid.json: most frequent keywords (lemmatized nouns) found in events retrieved for a specific featureid and a reference forecast month
 - ranked-datasets-SVR-month-featureid.json: contains media event keywords used to query for external datasets, and a list of external datasets that match a given featureid and reference forecast month. 
- xai-sampled-external-datasets.csv: manually annotated external datasets entries (match/not match)
 - xai-sampled-media-events.csv: a manually annotated random sample of media events (match/not match)
 - forecast-explanations-media-events.csv: manually annotated media events for 168 forecast explanations (match/not match)
 - forecast-explanations-media-event-keywords.csv: manually annotated media event keywords for 168 forecast explanations (match/not match)
 - forecast-explanations-external-datasets.csv: manually annotated external dataset entries for 168 forecast explanations (match/not match)
DOI: 10.7910/dvn/lvgyyw
title: Replication Data for: Molecular characterization of rotavirus group A strains circulating prior to vaccine introduction in rural coastal Kenya, 2002-2013

description: &lt;p&gt;These data were derived from stool samples collected from children with acute gastroenteritis, who reported to Kilifi County Hospital, with diarrhoea symptoms. The surveillance was conducted between January 2002 to December 2004 and January 2010 to December 2013. The study was aimed at describing the distribution, circulation patterns and diversity of group A rotavirus (RVA) strains circulating in this rural set up. This will ultimately form the basis of estimating the performance of a Rotavirus vaccine that was introduced in mid-2014, in Kenya.&lt;/p&gt;

&lt;p&gt;Sequence data was derived from Rotavirus positive samples identified by enzyme immunoassay method (ELISA) and subsequently sequenced by the di-deoxy Sanger method. After read assembly and sequence clean-up, G (derived from the VP7 glycoprotein) and P (derived from VP4 protease sensitive protein), genotypes were determined by use of NCBI BLAST and RotaC v2 an established online RVA genotyping tool. The data was then analyzed in excel and use of other sequence analysis tools including MEGA v7 for construction of phylogenetic trees.
 &lt;/p&gt;
DOI: 10.7910/dvn/6tu1ax
title: Party positions and the changing gender gap(s) in voting

description: Why, despite increased female support, do social democratic parties (SDPs) in most Western European countries face electoral decline? To study this puzzle, we harness a well-documented regularity – diminishing support for SDPs by manual workers and their increased support for the far right. We contend that this trend is intensified in contexts where the economic positions of SDPs align with market-oriented policies or converge with those of the far right. Additionally, as men are disproportionately represented among manual workers, this shift contributes to the reversal of the gender gap in support for SDPs. Drawing on public opinion data from 18 countries spanning 46 years, along with labor and party position data, our findings substantiate this argument.
DOI: 10.7910/dvn/xqjdzf
title: PDB - 3OPZ - Trans-sialidase from Trypanosoma cruzi in complex with the Fab fragment of a neutralizing monoclonal IgG 13G9: (312K, 39°C, 100 ns) RMSD, SASA, RMSF, Rg, H-bonds

description: PDB - 3OPZ - Trans-sialidase from Trypanosoma cruzi in complex with the Fab fragment of a neutralizing monoclonal IgG 13G9: (312K, 39°C, 100 ns) RMSD, SASA, RMSF, Rg, H-bonds
DOI: 10.7910/dvn/asawcw
title: New Jersey safer state than Texas: A firearm ownership, hospitalization and mortality rate comparison

description: &lt;strong&gt;Introduction:&lt;/strong&gt; Firearm legality and ownership have been contentious topics in American culture, due to the well-documented, yet preventable, health and safety risks. States vary in the amount of firearm ownership, as well as firearm mortality and injury rates.
&lt;br&gt;
&lt;strong&gt;Objectives:&lt;/strong&gt; The primary aim of this project is to compare two states, New Jersey and Texas, on the likelihood of firearm violence occurring to each state's citizens. The variables of gun ownership, firearm mortalities, and firearm injuries are compared and visualized to understand if living in one state is safer than living in the other. 
&lt;br&gt;
&lt;strong&gt;Methods:&lt;/strong&gt; Data analysis focused on connecting and comparing the two states with variables pointing to firearm safety/danger. Line graphs compare the two states and firearm injuries and mortalities over a sixteen-year period as well as number of firearms per state. Scatterplots show a correlation, if any, between number of firearms and injuries/mortalities in the two states.
&lt;br&gt; 
&lt;strong&gt;Results:&lt;/strong&gt; Texas had a consistently higher mortality rate by firearms (excluding suicides) for each year of the seventeen years. Texas also led in firearm injuries from the years 2000-2010, 2012, and 2014-2016, but not in 2011 and 2013. New Jersey consistently has a lower mortality rate (3.5 and under per 100,000) and lower gun ownership (.11 and under per household). Texas’ data has both a higher mortality rate (between 3.8 and 4.8 per 100,000) and a higher gun ownership rate (.34 to .40 per household). With a few exceptions from the years 2011 and 2013, the state data points are clustered to show the relationship between gun ownership and firearm injuries to be high/high for Texas and low/low for New Jersey. 
&lt;br&gt;
&lt;strong&gt;Conclusions:&lt;/strong&gt; From the years 2000-2016 it is, on average, 20% less likely that one will be injured by a firearm and 30% less likely that one will be killed by a firearm if one were to live in New Jersey instead of Texas, causing the conclusion that it is safer to live in New Jersey than in Texas.
description: Excel, null
description: Tableau Public, null
description: The research protocol and report are included for greater understanding and use of the dataset.
DOI: 10.7910/dvn/m4l0ci
title: MUSIK BABATU NEGERI ULAHAHAN

description: https://www.sinta.ristekbrin.go.id/authors/detail?id=6764414&view=overview
MUSIK BABATU NEGERI ULAHAHAN
description: This is a research project of traditional music from Maluku/Indonesia, specifically Seram Island, Maluku Province.
DOI: 10.7910/dvn/argaw7
title: Studies of Girls' Development, Ages 6-17, 1981-1992

description: &lt;b&gt;This study is not yet available for use&lt;/b&gt;&lt;br /&gt;&lt;br /&gt; These studies were conducted by Carol Gilligan and her colleagues at Harvard University. The Harvard Adolescent Project began in 1981-1984 with a longitudinal study of adolescent girls at the Emma Willard School (a girls' boarding/day school, grades 9-12). &lt;br /&gt; &lt;br /&gt; The Emma Willard School Study was designed to explore how adolescent girls of different ages understand and describe themselves, relationships and morality. &lt;br /&gt;&lt;br /
&gt; During 1983-1984, a small study was conducted of 15-year-old girls and boys at the Blake School (a coeducational day school, grades K-12) to understand the ways in which schools can positively affect adolescent development. The Blake School Study was followed by a three-year longitudinal study from 1984-1986, which included both girls and boys at the Middlesex School (a comparable, coeducational school).
&lt;br /&gt;&lt;br /&gt; The Middlesex School Study examined how adolescents think about and make choices and how their experience of choice is related to their sense of self. &lt;br /&gt;&lt;br /&gt; The Boys and Girls Club Study (1985) and Urban Adolescent Community Project (1986) reached more diverse groups of adolescents to investigate ways in which adolescents think about their relationships with adults and their community. &lt;br /&gt;&lt;br /&gt; The Laurel School Study was a cross-sectional, longitudinal study lasting from 1986 to 1990 that examined female adolescent development and education.
&lt;br /&gt;&lt;br /&gt; Concurrently, from 1987 to 1990, the Understanding Adolescence Study (also referred to as The Cambridge Schools Study) interviewed boys and girls attending urban public high schools who were designated "at risk" for either high school dropout and/or early motherhood. &lt;br /&gt; &lt;br /&gt; These studies utilized questionnaires and intensive qualitative interviews on topics ranging from questions on girls' and boys' decisions about morality, relationships, self-images, educational goals,
career possibilities and children. These studies utilized questionnaires and intensive qualitative interviews on topics ranging from questions on girls' and boys' decisions about morality, relationships, self-images, educational goals, career possibilities and children.
&lt;br /&gt;&lt;br /&gt; These studies utilized questionnaires and intensive qualitative interviews on topics ranging from questions on girls' and boys' decisions about morality, relationships, self-images, educational goals, career possibilities and children. &lt;br /&gt;&lt;br /&gt; The Murray Archive holds additional analogue materials for this study (original record paper data in the form of questionnaires, and transcribed interviews; this collection also includes audiotapes from these studies). If you would like to access this material, please apply to use the data. &lt;br/&gt;&lt;br /&gt;&lt;b&gt;Audio Data Availability Note:&lt;/b&gt; This study contains audio data that have been digitized. There are 288 audio files available.
DOI: 10.25549/inscriptifact-ouc110820375
title: Persepolis Fortification Elamite Tablet 2272.101, Fort 2272.101

description: [Text Description:] Administrative text ❧ [Text or Publication Number Note:] Fort 2272.101 ❧ [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:] Non-Alphabetic Cuneiform ❧ [Physical Object Description:] Clay tablet with cuneiform text. ❧ [Physical Object Note:] Upper left, upper right and lower right corners broken off. Damage on obverse, reverse.
DOI: 10.25549/inscriptifact-ouc110820376
title: Persepolis Fortification Elamite Tablet 2272.101, Fort 2272.101

description: [Text Description:] Administrative text ❧ [Text or Publication Number Note:] Fort 2272.101 ❧ [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:] Non-Alphabetic Cuneiform ❧ [Physical Object Description:] Clay tablet with cuneiform text. ❧ [Physical Object Note:] Upper left, upper right and lower right corners broken off. Damage on obverse, reverse.
DOI: 10.25549/inscriptifact-ouc110820318
title: Persepolis Fortification Elamite Tablet 2267.101, Fort 2267.101

description: [Text Description:] Administrative text with seal ❧ [Text or Publication Number Note:] Fort 2267.101 ❧ [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:] Non-Alphabetic Cuneiform ❧ [Physical Object Description:] Clay tablet with cuneiform text. Seal impression on right edge. ❧ [Physical Object Note:] Left side of tablet missing.
DOI: 10.25549/inscriptifact-ouc110814187
title: Copper Scroll

description: [Text Description:] ❧ list of buried treasure ❧ [Text or Publication Number Note:] 3Q15 Copper Scroll ❧ [Excavation Description:] Found during survey of cliffs at Qumran in March 1952 by Roland de Vaux and William Reed. ❧ [Medium:] Metal ❧ [Script Note:] Jewish ❧ [Physical Object Description:] 23 oxydized copper half-cylinder segments with incised letters
DOI: 10.25549/inscriptifact-ouc110814247
title: Copper Scroll

description: [Text Description:] ❧ list of buried treasure ❧ [Text or Publication Number Note:] 3Q15 Copper Scroll ❧ [Excavation Description:] Found during survey of cliffs at Qumran in March 1952 by Roland de Vaux and William Reed. ❧ [Medium:] Metal ❧ [Script Note:] Jewish ❧ [Physical Object Description:] 23 oxydized copper half-cylinder segments with incised letters
DOI: 10.25549/inscriptifact-ouc110814088
title: Copper Scroll

description: [Text Description:] ❧ list of buried treasure ❧ [Text or Publication Number Note:] 3Q15 Copper Scroll ❧ [Excavation Description:] Found during survey of cliffs at Qumran in March 1952 by Roland de Vaux and William Reed. ❧ [Medium:] Metal ❧ [Script Note:] Jewish ❧ [Physical Object Description:] 23 oxydized copper half-cylinder segments with incised letters
DOI: 10.25549/inscriptifact-ouc110814185
title: Copper Scroll

description: [Text Description:] ❧ list of buried treasure ❧ [Text or Publication Number Note:] 3Q15 Copper Scroll ❧ [Excavation Description:] Found during survey of cliffs at Qumran in March 1952 by Roland de Vaux and William Reed. ❧ [Medium:] Metal ❧ [Script Note:] Jewish ❧ [Physical Object Description:] 23 oxydized copper half-cylinder segments with incised letters
DOI: 10.22033/esgf/cmip6.5701
title: MIROC MIROC6 model output prepared for CMIP6 RFMIP piClim-histall

description: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets: These data include all datasets published for 'CMIP6.RFMIP.MIROC.MIROC6.piClim-histall' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'.
 
 The MIROC6 climate model, released in 2017, includes the following components:
 aerosol: SPRINTARS6.0, atmos: CCSR AGCM (T85; 256 x 128 longitude/latitude; 81 levels; top level 0.004 hPa), land: MATSIRO6.0, ocean: COCO4.9 (tripolar primarily 1deg; 360 x 256 longitude/latitude; 63 levels; top grid cell 0-2 m), seaIce: COCO4.9. 
The model was run by the JAMSTEC (Japan Agency for Marine-Earth Science and Technology, Kanagawa 236-0001, Japan), AORI (Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba 277-8564, Japan), NIES (National Institute for Environmental Studies, Ibaraki 305-8506, Japan), and R-CCS (RIKEN Center for Computational Science, Hyogo 650-0047, Japan) (MIROC) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, ocean: 100 km, seaIce: 100 km. 

Project: These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6).

CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ).

The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. - Project website: https://pcmdi.llnl.gov/CMIP6.
DOI: 10.5281/zenodo.15014791
title: Climate TRACE Emissions Inventory

description: Climate TRACE is a non-profit coalition of organizations building a timely, open, and accessible inventory of exactly where greenhouse gas emissions are coming from. Climate TRACE estimates greenhouse gas (GHG) and air pollutant emissions for over 1.8 million sources (from over 660 million assets), and every single country globally.

Each download package includes CSVs of:



Annual country-level emissions by sub-sector and by gas beginning in 2015

Monthly source-level emissions by sub-sector and gas beginning in 2021 and confidence

Emissions source ownership where and when available.


All Climate TRACE data are free and publicly available under a CC-BY 4.0 license to enable action and accountability at the massive scale necessary for global progress. Beginning in March 2025, Climate TRACE is releasing updated data with a 60-day lag during the final week of each month. All previous versions of the Climate TRACE asset- and country-level database will be uploaded to this page.

With the addition of January 2025 data, the Climate TRACE database is now updated to version 4.1.0. Additionally, the database was updated with to include items such as: updating the CH4 global warming potential (GWP) to distinguish between fossil and non-fossil sources; revisions to previous month’s data to incorporate newly available data for multiple sectors; new months of data; updated methodologies . A detailed description of all data updates is available here.

Version 4.0.0 (released in November 2024) will be available here.

We recommend getting familiar with how Climate TRACE data are created and structured by reviewing our FAQs, resources, and guidance:



The Climate TRACE FAQs page is an especially useful resource to quickly learn how we develop the emissions inventory, what data are contained in the inventory, details on units of measurement and coverage, and much more.

The Sectors page summarizes methodological details on dozens of sub-sectors. The data are licensed under the Creative Commons Attribution 4.0 International License; more details can be found on our terms of use page.

Detailed guidance on the data schema, licensing, and citations can be found in the data guide, as well as in the “detailed-data-schema” in the download packages.


If you have any questions, please reach out to us via our contact page.
DOI: 10.5281/zenodo.15262681
title: Climate TRACE Emissions Inventory

description: Climate TRACE is a non-profit coalition of organizations building a timely, open, and accessible inventory of exactly where greenhouse gas emissions are coming from. Climate TRACE estimates greenhouse gas (GHG) and air pollutant emissions for over 1.8 million sources (from over 660 million assets), and every single country globally.

Each download package includes CSVs of:



Annual country-level emissions by sub-sector and by gas beginning in 2015

Monthly source-level emissions by sub-sector and gas beginning in 2021 and confidence

Emissions source ownership where and when available.


All Climate TRACE data are free and publicly available under a CC-BY 4.0 license to enable action and accountability at the massive scale necessary for global progress. Beginning in March 2025, Climate TRACE is releasing updated data with a 60-day lag during the final week of each month. All previous versions of the Climate TRACE asset- and country-level database will be uploaded to this page.

With the addition of February 2025 data, the Climate TRACE database is now updated to version 4.2.0. Additionally, the database was updated with to include items such as: revisions to previous month’s data to incorporate newly available data for multiple sectors; new months of data; updated methodologies . A detailed description of all data updates is available here.

Version 4.1.0 (released in March 2025) will be available here.

We recommend getting familiar with how Climate TRACE data are created and structured by reviewing our FAQs, resources, and guidance:



The Climate TRACE FAQs page is an especially useful resource to quickly learn how we develop the emissions inventory, what data are contained in the inventory, details on units of measurement and coverage, and much more.

The Sectors page summarizes methodological details on dozens of sub-sectors. The data are licensed under the Creative Commons Attribution 4.0 International License; more details can be found on our terms of use page.

Detailed guidance on the data schema, licensing, and citations can be found in the data guide, as well as in the “detailed-data-schema” in the download packages.


If you have any questions, please reach out to us via our contact page.
DOI: 10.5281/zenodo.15312289
title: Climate TRACE Emissions Inventory

description: Climate TRACE is a non-profit coalition of organizations building a timely, open, and accessible inventory of exactly where greenhouse gas emissions are coming from. Climate TRACE estimates greenhouse gas (GHG) and air pollutant emissions for over 1.8 million sources (from over 660 million assets), and every single country globally.

Each download package includes CSVs of:



Annual country-level emissions by sub-sector and by gas beginning in 2015

Monthly source-level emissions by sub-sector and gas beginning in 2021 and confidence

Emissions source ownership where and when available.


All Climate TRACE data are free and publicly available under a CC-BY 4.0 license to enable action and accountability at the massive scale necessary for global progress. Beginning in March 2025, Climate TRACE is releasing updated data with a 60-day lag during the final week of each month. All previous versions of the Climate TRACE asset- and country-level database will be uploaded to this page.

With the addition of March 2025 data, the Climate TRACE database is now updated to version 4.3.0.

Version 4.2.0 (released in April 2025) will be available here. With this version, the database was updated to standardize the use of lowercase ‘t’ for tonnes rather than uppercase ‘T’. Individual sector teams also added 13,757 additional cattle operation emissions sources in France; added 19 oil and gas refining assets and added additional data covering April through June 2024 for refineries in Asia, the Middle East, Africa, Latin America, and parts of Europe; fixed a bug affecting aluminum manufacturing; and added April–June 2024 data for petrochemical steam cracking facilities in Asia and the Middle East. A detailed description of all data updates is available here.

We recommend getting familiar with how Climate TRACE data are created and structured by reviewing our FAQs, resources, and guidance:



The Climate TRACE FAQs page is an especially useful resource to quickly learn how we develop the emissions inventory, what data are contained in the inventory, details on units of measurement and coverage, and much more.

The Sectors page summarizes methodological details on dozens of sub-sectors. The data are licensed under the Creative Commons Attribution 4.0 International License; more details can be found on our terms of use page.

Detailed guidance on the data schema, licensing, and citations can be found in the data guide, as well as in the “detailed-data-schema” in the download packages.


If you have any questions, please reach out to us via our contact page.
DOI: 10.3535/844-ml4-qc4
title: Animalia

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/c8j-hnh-vvy
title: Crinoidea Miller, 1821

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/010-2fx-zxl
title: Cnidaria

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/z3l-jrp-ytn
title: Cnidaria

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/6z2-8ay-3cg
title: Cnidaria

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.