cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.16779467
title: Annual Bibliometric Data on Target-Setting in Wildfire and Flood Risk Management

description: This dataset contains annual bibliographic records related to publications focusing on target-setting in Flood and Wildfire Risk Management. It includes metadata extracted via the KATI tool from the Web Of Science Database. Each entry includes bibliographic information on the annual publication activities. 

Creator: Juliane SchlierkampORCID: https://orcid.org/0000-0002-6574-4022Affiliation: Fraunhofer INTEmail: juliane.schlierkamp@int.fraunhofer.de

Date of Data Collection: August 6, 2025

Geographic Coverage: Global (with focus on country of publication origin)

Source: Data retrieved using the KATI based on Web Of Science

Query (Flood): "flood AND target* AND (policy OR governance OR strategy)"

Query (Wildfire): "flood AND target* AND (policy OR governance OR strategy)"

Language: English

File Format: CSV (Comma-Separated Values)

Variables Included:



Year

Count Publications Flood

Count Publications Wildfire


Related Publications:[1] Berchtold et al. (2025). “Towards wildfire risk reduction targets for Europe – opportunities and challenges” Journal of Hazard Research. [DOI]

Version: 1.0
DOI: 10.5281/zenodo.16779468
title: Annual Bibliometric Data on Target-Setting in Wildfire and Flood Risk Management

description: This dataset contains annual bibliographic records related to publications focusing on target-setting in Flood and Wildfire Risk Management. It includes metadata extracted via the KATI tool from the Web Of Science Database. Each entry includes bibliographic information on the annual publication activities. 

Creator: Juliane SchlierkampORCID: https://orcid.org/0000-0002-6574-4022Affiliation: Fraunhofer INTEmail: juliane.schlierkamp@int.fraunhofer.de

Date of Data Collection: August 6, 2025

Geographic Coverage: Global (with focus on country of publication origin)

Source: Data retrieved using the KATI based on Web Of Science

Query (Flood): "flood AND target* AND (policy OR governance OR strategy)"

Query (Wildfire): "flood AND target* AND (policy OR governance OR strategy)"

Language: English

File Format: CSV (Comma-Separated Values)

Variables Included:



Year

Count Publications Flood

Count Publications Wildfire


Related Publications:[1] Berchtold et al. (2025). “Towards wildfire risk reduction targets for Europe – opportunities and challenges” Journal of Hazard Research. [DOI]

Version: 1.0
DOI: 10.15468/dl.w3knvu
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Xolmis velatus)",
 "Country is one of (American Samoa, Australia, Christmas Island, Cocos (Keeling) Islands, Cook Islands, Fiji, French Polynesia, Guam, Heard Island and McDonald Islands, Kiribati, Marshall Islands, Micronesia (Federated States of), Nauru, New Caledonia, New Zealand, Niue, Norfolk Island, Northern Mariana Islands, Palau, Papua New Guinea, Pitcairn, Samoa, Solomon Islands, Tokelau, Tonga, Tuvalu, United States Minor Outlying Islands, Vanuatu, Wallis and Futuna)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028893-250802193616735/datasets/export for details.
DOI: 10.15468/dl.a9byr3
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Xolmis velatus)",
 "Country is one of (Åland Islands, Albania, Andorra, Austria, Belarus, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, Czechia, Denmark, Estonia, Faroe Islands, Finland, France, Germany, Gibraltar, Greece, Guernsey, Holy See, Hungary, Iceland, Ireland, Isle of Man, Italy, Jersey, Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Moldova, Republic of, Monaco, Montenegro, Netherlands, North Macedonia, Norway, Poland, Portugal, Romania, Russian Federation, San Marino, Serbia, Slovakia, Slovenia, Spain, Svalbard and Jan Mayen, Sweden, Switzerland, Ukraine, United Kingdom of Great Britain and Northern Ireland)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028892-250802193616735/datasets/export for details.
DOI: 10.15468/dl.y6nn8q
title: Occurrence Download

description: A dataset containing 18 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is BOLD:AAD8586"
 ]
}

 The dataset includes 18 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028894-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.s9459z
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Xolmis velatus)",
 "Country is one of (Algeria, Angola, Benin, Botswana, British Indian Ocean Territory, Burkina Faso, Burundi, Cabo Verde, Cameroon, Central African Republic, Chad, Comoros, Congo, Congo, Democratic Republic of the, Côte d’Ivoire, Djibouti, Egypt, Equatorial Guinea, Eritrea, Eswatini, Ethiopia, French Southern Territories, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, Liberia, Libya, Madagascar, Malawi, Mali, Mauritania, Mauritius, Mayotte, Morocco, Mozambique, Namibia, Niger, Nigeria, Réunion, Rwanda, Saint Helena, Ascension and Tristan da Cunha, Sao Tome and Principe, Senegal, Seychelles, Sierra Leone, Somalia, South Africa, South Sudan, Sudan, Tanzania, United Republic of, Togo, Tunisia, Uganda, Western Sahara, Zambia, Zimbabwe)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028895-250802193616735/datasets/export for details.
DOI: 10.6084/m9.figshare.29860856
title: <b>Rapid Lithological Mapping Using Multi-Source Remote Sensing Data Fusion and Automatic Sample Generation Strategy</b>

description: The advancement of remote sensing technology aids geologists in obtaining lithological maps more quickly, comprehensively, and accurately. However, key challenges in lithological mapping include the limited spectral information from individual sensors and the difficulties in visually interpreting lithological samples. In this study, we integrated 241 scenes of optical data and 106 scenes of radar data on the Google Earth Engine (GEE) platform, proposing a rapid lithological identification framework that combines an automatic lithological sample data generation strategy with multi-source data. Using various machine learning algorithms, we evaluated the classification capabilities of heterogeneous predictive factors, feature optimization algorithms, and object-based algorithms. Results indicate that: (1) Combining optical and radar data improves prediction accuracy, with terrain data further enhancing mapping capabilities; (2) Terrain factors contribute most to classification, but SWIR and TIR bands of optical data are critical for lithological identification; (3) The feature optimization algorithm reduces feature redundancy and efficiency issues from multi-source data, achieving 96.51% accuracy with the optimal feature model, an improvement of 0.1%-2.02% over original features; (4) Object-based algorithms show significant potential in mapping areas with large rock outcrops. This study offers new insights for medium- to large-scale lithological maps and provides essential data support for geological work.
DOI: 10.6084/m9.figshare.29860856.v1
title: <b>Rapid Lithological Mapping Using Multi-Source Remote Sensing Data Fusion and Automatic Sample Generation Strategy</b>

description: The advancement of remote sensing technology aids geologists in obtaining lithological maps more quickly, comprehensively, and accurately. However, key challenges in lithological mapping include the limited spectral information from individual sensors and the difficulties in visually interpreting lithological samples. In this study, we integrated 241 scenes of optical data and 106 scenes of radar data on the Google Earth Engine (GEE) platform, proposing a rapid lithological identification framework that combines an automatic lithological sample data generation strategy with multi-source data. Using various machine learning algorithms, we evaluated the classification capabilities of heterogeneous predictive factors, feature optimization algorithms, and object-based algorithms. Results indicate that: (1) Combining optical and radar data improves prediction accuracy, with terrain data further enhancing mapping capabilities; (2) Terrain factors contribute most to classification, but SWIR and TIR bands of optical data are critical for lithological identification; (3) The feature optimization algorithm reduces feature redundancy and efficiency issues from multi-source data, achieving 96.51% accuracy with the optimal feature model, an improvement of 0.1%-2.02% over original features; (4) Object-based algorithms show significant potential in mapping areas with large rock outcrops. This study offers new insights for medium- to large-scale lithological maps and provides essential data support for geological work.
DOI: 10.21227/mfp8-tm97
title: "Dataset for Analysis of Child-Abusive Memes"

description: "This dataset is a collection of child-abusive memes to analyze such content and model to flag child-abusive contnet. "
DOI: 10.60797/rulb.2025.68.11.1
title: Пятьдесят наиболее часто используемых иероглифов в именах новорождённых за 2021 г

description: Russian Linguistic Bulletin, Выпуск 8 (68) 2025
DOI: 10.60797/rulb.2025.68.9.1
title: Тексты песен «Ох, Катенька-Катюшенька» в записи 2001 и 2008 годов

description: Russian Linguistic Bulletin, Выпуск 8 (68) 2025
DOI: 10.60797/rulb.2025.68.9.2
title: Тексты песен «Ох, Катенька-Катюшенька» из с. Степанёнки Кезского района Удмуртии в многомикрофонной записи 2001 года

description: Russian Linguistic Bulletin, Выпуск 8 (68) 2025
DOI: 10.60797/rulb.2025.68.9.3
title: Тексты песен «Ох, Катенька-Катюшенька» и «Ох, роспечальное моё сердечко» из с. Карсовай Балезинского района Удмуртии

description: Russian Linguistic Bulletin, Выпуск 8 (68) 2025
DOI: 10.5281/zenodo.16779475
title: Pubmed part1

description: ## Estrategia de búsqueda








("Achillea"[Mesh] OR "Achillea millefolium"[tiab] OR "Achillea"[tiab] OR yarrow[tiab] OR "common yarrow"[tiab] OR milenrama*[tiab] OR milfoil[tiab] ) AND ( "Anti-Inflammatory Agents"[Mesh] OR anti-inflammatory*[tiab] OR antiinflammatory*[tiab] OR inflammation[tiab] OR "Analgesics"[Mesh] OR analgesic*[tiab] OR analgesia[tiab] OR pain[tiab] ) AND ( randomized controlled trial[pt] OR controlled clinical trial[pt] OR randomized[tiab] OR randomised[tiab] OR randomly[tiab] OR placebo[tiab] OR trial[tiab] ) NOT ( animals[mh] NOT humans[mh] )






## FiltrosNinguno

## ResultadosTotal: 13Exportado: CSV (full record)
DOI: 10.5281/zenodo.16779476
title: Pubmed part1

description: ## Estrategia de búsqueda








("Achillea"[Mesh] OR "Achillea millefolium"[tiab] OR "Achillea"[tiab] OR yarrow[tiab] OR "common yarrow"[tiab] OR milenrama*[tiab] OR milfoil[tiab] ) AND ( "Anti-Inflammatory Agents"[Mesh] OR anti-inflammatory*[tiab] OR antiinflammatory*[tiab] OR inflammation[tiab] OR "Analgesics"[Mesh] OR analgesic*[tiab] OR analgesia[tiab] OR pain[tiab] ) AND ( randomized controlled trial[pt] OR controlled clinical trial[pt] OR randomized[tiab] OR randomised[tiab] OR randomly[tiab] OR placebo[tiab] OR trial[tiab] ) NOT ( animals[mh] NOT humans[mh] )






## FiltrosNinguno

## ResultadosTotal: 13Exportado: CSV (full record)
DOI: 10.15468/dl.c8s5c4
title: Occurrence Download

description: A dataset containing 15674 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Sphenopsis melanotis)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "License is one of (CC-BY 4.0, CC0 1.0)"
 ]
}

 The dataset includes 15674 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028896-250802193616735/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.29860595
title: <b>Open-source solution for evaluation and benchmarking of large language models for public health</b>

description: This folder contains the datasets used to produce the manuscript with the same title.
DOI: 10.6084/m9.figshare.29860595.v1
title: <b>Open-source solution for evaluation and benchmarking of large language models for public health</b>

description: This folder contains the datasets used to produce the manuscript with the same title.
DOI: 10.6084/m9.figshare.29860595.v2
title: <b>Open-source solution for evaluation and benchmarking of large language models for public health</b>

description: This folder contains the datasets used to produce the manuscript with the same title.
DOI: 10.57903/uj/w1n7ae
title: Ahobilam - research data

description: The dataset contains selected materials gathered during field trips to Ahobilam (Andhra Pradesh, India) and queries in Europe, working notes and visual materials that refer to the topic of Ahobilam being a sacred site involved in variously conceptualised connections and relations with other religious centers of South India.
DOI: 10.15468/dl.m98uxe
title: Occurrence Download

description: A dataset containing 75 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Xyrichtys pavo"
 ]
}

 The dataset includes 75 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028897-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/12709678
title: Bitcoin BTC, 7 Exchanges, 1m Full Historical Data
DOI: 10.15468/dl.tkn9g7
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Arundinicola leucocephala)",
 "Country is one of (Bermuda, Canada, Greenland, Saint Pierre and Miquelon, United States of America)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028901-250802193616735/datasets/export for details.
DOI: 10.15468/dl.ru2m4j
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Diasporus quidditus)",
 "Country is one of (Algeria, Angola, Benin, Botswana, British Indian Ocean Territory, Burkina Faso, Burundi, Cabo Verde, Cameroon, Central African Republic, Chad, Comoros, Congo, Congo, Democratic Republic of the, Côte d’Ivoire, Djibouti, Egypt, Equatorial Guinea, Eritrea, Eswatini, Ethiopia, French Southern Territories, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, Liberia, Libya, Madagascar, Malawi, Mali, Mauritania, Mauritius, Mayotte, Morocco, Mozambique, Namibia, Niger, Nigeria, Réunion, Rwanda, Saint Helena, Ascension and Tristan da Cunha, Sao Tome and Principe, Senegal, Seychelles, Sierra Leone, Somalia, South Africa, South Sudan, Sudan, Tanzania, United Republic of, Togo, Tunisia, Uganda, Western Sahara, Zambia, Zimbabwe)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081306-250717081556266/datasets/export for details.
DOI: 10.5281/zenodo.16642325
title: Dupljaja loess palaeosol sequence, Serbia (Age model, Mass accumulation rate, Grain size, Magnetic susceptibility, End members)

description: Here you can find produced data related to the loess palaeosol section Dupljaja in southern Banat region of Serbia. Please cite doi number if you use this data.
DOI: 10.5281/zenodo.16642326
title: Dupljaja loess palaeosol sequence, Serbia (Age model, Mass accumulation rate, Grain size, Magnetic susceptibility, End members)

description: Here you can find produced data related to the loess palaeosol section Dupljaja in southern Banat region of Serbia. Please cite doi number if you use this data.
DOI: 10.25549/inscriptifact-ouc110598372
title: Persepolis Fortification Anepigraphic Tablet 0845.102, PFAnep 0845.102

description: [Text Description:] Administrative text with seals PFUTS 0037s; PFUTS 0038s; PFUTS 0039s. ❧ [Text or Publication Number Note:] PFAnep 0845.102, PFUT 0845-102 ❧ [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-Text ❧ [Physical Object Description:] Clay tablet with seal impressions PFUTS 0037s on obverse; PFUTS 0038s on reverse; PFUTS 0039s on left edge.
DOI: 10.5255/ukda-sn-8208-1
title: Harmonised Height, Weight and BMI in Five Longitudinal Cohort Studies: Avon Longitudinal Study of Parents and Children: Special Licence Access
title: CLOSER Workpackage 1: Harmonised Height, Weight and BMI in Five Longitudinal Cohort Studies
title: CLOSER Workpackage 1; ALSPAC

description: The &lt;I&gt;Harmonised Height, Weight and BMI in Five Longitudinal Cohort Studies: Avon Longitudinal Study of Parents and Children&lt;/I&gt; provides the harmonised data on height, weight and BMI for the ALSPAC.&lt;br&gt;
&lt;br&gt;
The harmonised anthropometric measures for the NCDS, BCS70 and the MCS are held under SN 8207, and for the NSHD are available under Special Licence access, SN 8209.&lt;br&gt;
&lt;br&gt;
 The Cohort and Longitudinal Studies Enhancement Resources (CLOSER) project aims to maximise the use, value and impact of longitudinal research. It brings together eight leading longitudinal studies, the British Library and the UK Data Service, to stimulate interdisciplinary research, develop shared resources, provide training, and share expertise. Resources available from CLOSER include harmonised datasets (developed to facilitate cross-study comparisons) and CLOSER Discovery (a search engine that enables researchers to search and browse questionnaires and data from different longitudinal studies). CLOSER’s website also includes a range of training materials focused on longitudinal studies and data. CLOSER is funded by the Economic and Social Research Council (ESRC) and the Medical Research Council (MRC) and is based at the UCL Institute of Education.&lt;br&gt;
&lt;br&gt;
The CLOSER Workpackage 1 provides the harmonisation of anthropometric measures between the National Survey of Health and Development (NSHD), National Child Development Study (NCDS), 1970 British Cohort Study (BCS70), Avon Longitudinal Study of Parents and Children (ALSPAC), and the Millennium Cohort Study (MCS).&lt;br&gt;
&lt;br&gt;
Further information about CLOSER can be found at &lt;a href="www.closer.ac.uk" target="_blank"&gt;www.closer.ac.uk&lt;/a&gt;.&lt;br&gt;
&lt;br&gt;
DOI: 10.5255/ukda-sn-8251-1
title: Quarterly Survey of Financial Assets and Liabilities, 2014-2016: Secure Access
title: FALS

description: The &lt;i&gt;Quarterly Survey of Financial Assets and Liabilities&lt;/i&gt; (FALS) collects information on the financial assets and liabilities held by companies, with the exception of financial institutions. (Financial Institutions are organisations such as banks and building societies and these provide data directly to the Bank of England). The data are mainly used in constructing the financial accounts for the non-financial corporations’ sector of the UK National Accounts and as an input into the compilation of the capital account of the UK Balance of Payments (the difference between imports and exports).&lt;br&gt;
&lt;br&gt;
DOI: 10.5255/ukda-sn-8209-1
title: Harmonised Height, Weight and BMI in Five Longitudinal Cohort Studies: MRC National Survey of Health and Development: Special Licence Access
title: CLOSER Workpackage 1: Harmonised Height, Weight and BMI in Five Longitudinal Cohort Studies
title: CLOSER Workpackage 1; NSHD

description: The &lt;I&gt;Harmonised Height, Weight and BMI in Five Longitudinal Cohort Studies: MRC National Survey of Health and Development&lt;/I&gt; includes the harmonised data on height, weight and BMI for the NSHD.&lt;br&gt;
&lt;br&gt;
The harmonised anthropometric measures for the NCDS, BCS70, and the MCS are held under SN 8207, and data for the ALSPAC are available under Special Licence access, SN 8208.&lt;br&gt;
&lt;br&gt;
 The Cohort and Longitudinal Studies Enhancement Resources (CLOSER) project aims to maximise the use, value and impact of longitudinal research. It brings together eight leading longitudinal studies, the British Library and the UK Data Service, to stimulate interdisciplinary research, develop shared resources, provide training, and share expertise. Resources available from CLOSER include harmonised datasets (developed to facilitate cross-study comparisons) and CLOSER Discovery (a search engine that enables researchers to search and browse questionnaires and data from different longitudinal studies). CLOSER’s website also includes a range of training materials focused on longitudinal studies and data. CLOSER is funded by the Economic and Social Research Council (ESRC) and the Medical Research Council (MRC) and is based at the UCL Institute of Education.&lt;br&gt;
&lt;br&gt;
The CLOSER Workpackage 1 provides the harmonisation of anthropometric measures between the National Survey of Health and Development (NSHD), National Child Development Study (NCDS), 1970 British Cohort Study (BCS70), Avon Longitudinal Study of Parents and Children (ALSPAC), and the Millennium Cohort Study (MCS).&lt;br&gt;
&lt;br&gt;
Further information about CLOSER can be found at &lt;a href="www.closer.ac.uk" target="_blank"&gt;www.closer.ac.uk&lt;/a&gt;.&lt;br&gt;
&lt;br&gt;
DOI: 10.25549/inscriptifact-ouc110599653
title: Persepolis Fortification Elamite Tablet 1161, PF 1161

description: [Text Description:] Administrative text with seals PFS 0114, PFS 0105 ❧ [Text or Publication Number Note:] PF 1161 ❧ [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 impressions PFS 0114 reverse; PFS 0105 left edge.
DOI: 10.25549/inscriptifact-ouc110600575
title: Persepolis Fortification Aramaic Text 412, PFAT 412

description: [Text Description:] Administrative text with seals PFATS 0393 ❧ [Text or Publication Number Note:] PFAT 412, Bowman 412 ❧ [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 0393 on obverse, upper edge, reverse, bottom edge, flat edge.