Scientific DataPub Date : 2026-09-21DOI: 10.1038/s41597-026-08289-7
Reuben Docea, Rayan Younis, Yonghao Long, Maxime Fleury, Jinjing Xu, Chenyang Li, André Schulze, Ann Wierick, Johannes Bender, Micha Pfeiffer, Qi Dou, Martin Wagner, Stefanie Speidel
{"title":"The Dresden Dataset for 4D Reconstruction of Non-Rigid Abdominal Surgical Scenes.","authors":"Reuben Docea, Rayan Younis, Yonghao Long, Maxime Fleury, Jinjing Xu, Chenyang Li, André Schulze, Ann Wierick, Johannes Bender, Micha Pfeiffer, Qi Dou, Martin Wagner, Stefanie Speidel","doi":"10.1038/s41597-026-08289-7","DOIUrl":"10.1038/s41597-026-08289-7","url":null,"abstract":"<p><p>The D4D Dataset provides paired endoscopic video and high-quality structured-light geometry for evaluating 3D reconstruction of deforming abdominal soft tissue in realistic surgical conditions. Data were acquired from six porcine cadavers using a da Vinci Xi stereo endoscope and a Zivid structured-light camera, registered via optical tracking and manually curated iterative alignment methods. Three session types (whole deformations, incremental deformations, and moved-camera sessions) probe algorithm robustness to non-rigid motion, deformation magnitude, and out-of-view updates. Each clip provides rectified stereo images, per-frame instrument masks, stereo depth, start/end structured-light point clouds, curated camera poses and camera intrinsics. In postprocessing, ICP and semi-automatic registration techniques are used to register data, and instrument masks are created. The dataset enables quantitative geometric evaluation in both visible and occluded regions, alongside photometric view-synthesis baselines. Comprising over 300,000 frames and 369 point clouds across 98 curated sessions, this resource can serve as a comprehensive benchmark for developing and evaluating non-rigid SLAM, 4D reconstruction, and depth estimation methods.</p>","PeriodicalId":21597,"journal":{"name":"Scientific Data","volume":"13 1","pages":""},"PeriodicalIF":7.2,"publicationDate":"2026-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13594231/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149017967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Scientific DataPub Date : 2026-09-19DOI: 10.1038/s41597-026-08356-z
Shah Saki, Giulia Sofia, Bandana Kar, Emmanouil Anagnostou
{"title":"A spatiotemporally harmonized dataset of utility-reported power outages and NWS VTEC weather warnings for the contiguous United States (2015-2024).","authors":"Shah Saki, Giulia Sofia, Bandana Kar, Emmanouil Anagnostou","doi":"10.1038/s41597-026-08356-z","DOIUrl":"10.1038/s41597-026-08356-z","url":null,"abstract":"<p><p>Power grids across the United States are increasingly exposed to weather-related disruption, yet reproducible analyses are limited by differences in the spatial and temporal structure of outage and meteorological records. This Data Descriptor presents a harmonized, event-based archive linking county-level customer power-outage records from the U.S. Department of Energy EAGLE-I platform with National Weather Service watches, warnings and advisories encoded through the Valid Time Event Code system. The archive spans the contiguous United States from 2015 through 2024. The primary released file contains hourly indexed, positive processed outage observations that overlap at least one VTEC warning and include event identifiers, matched warning types, and source-record availability diagnostics. Companion files provide the consolidated warning archive, daily county-level EAGLE-I source-record availability and sensitivity summaries evaluating missing-record treatment, temporal aggregation, and recovery persistence. Technical validation quantifies the consequences of preprocessing assumptions and documents spatial, temporal and warning-matching consistency. The dataset supports reproducible analysis of spatiotemporal co-occurrence between reported power disruptions and operational weather warnings while explicitly retaining limitations associated with the underlying outage record.</p>","PeriodicalId":21597,"journal":{"name":"Scientific Data","volume":"13 1","pages":""},"PeriodicalIF":7.2,"publicationDate":"2026-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13642956/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149114698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Scientific DataPub Date : 2026-09-19DOI: 10.1038/s41597-026-08335-4
Jan Schwalbach, Lukas Hetzer, Sven-Oliver Proksch, Christian Rauh, Miklós Sebők
{"title":"The ParlLawSpeech Parliamentary Text Data Collection > 3 Million Parliamentary Bills, Laws, and Speeches from 8 Legislatures.","authors":"Jan Schwalbach, Lukas Hetzer, Sven-Oliver Proksch, Christian Rauh, Miklós Sebők","doi":"10.1038/s41597-026-08335-4","DOIUrl":"10.1038/s41597-026-08335-4","url":null,"abstract":"<p><p>Parliamentary texts are central sources for studying democratic representation, policy-making, and institutional decision-making, and they also constitute a highly valuable domain for natural language processing research. Despite their importance, access to comprehensive, clean, and machine-readable parliamentary corpora remains limited. This paper introduces the ParlLawSpeech (PLS) collection, a large-scale, curated corpus comprising more than three million documents from eight European parliaments, each covering over two decades. PLS extends existing parliamentary text resources in two key ways. First, it integrates full texts and metadata not only for parliamentary speeches but also for legislative bills and finally adopted laws. Second, it provides systematic data linkage across these document types, enabling researchers to trace the full parliamentary decision-making process from draft legislation through debate to adoption. Covering seven national parliaments and the European Parliament, PLS offers a uniquely rich resource for political science and advanced NLP research.</p>","PeriodicalId":21597,"journal":{"name":"Scientific Data","volume":"13 1","pages":""},"PeriodicalIF":7.2,"publicationDate":"2026-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13589736/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149008782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Scientific DataPub Date : 2026-09-18DOI: 10.1038/s41597-026-08326-5
Jonas Bömer, Elias Marks, Facundo Ramón Ispizua Yamati, Cyrill Stachniss, Stefan Paulus, Anne-Katrin Mahlein
{"title":"A Dataset of Temporally Consistent Instance Annotations for 4D Plant Phenotyping.","authors":"Jonas Bömer, Elias Marks, Facundo Ramón Ispizua Yamati, Cyrill Stachniss, Stefan Paulus, Anne-Katrin Mahlein","doi":"10.1038/s41597-026-08326-5","DOIUrl":"10.1038/s41597-026-08326-5","url":null,"abstract":"<p><p>Spatio-temporal 4D plant phenotyping requires high-quality datasets with precise and temporally consistent annotations. However, such datasets are currently limited due to the substantial effort required for data acquisition and manual annotation. To address this limitation, we present Sugar4D, a publicly available 4D plant phenotyping dataset of sugar beet acquired using a terrestrial LiDAR scanner. The dataset comprises 768 point clouds from 48 individual plants representing twelve genotypes, recorded semiweekly across 16 consecutive time points during the growing season. All point clouds are provided with temporally consistent, pointwise instance annotations at the organ level, enabling the tracking of individual leaves over time. Sugar4D includes 6778 annotated leaves corresponding to 675 unique leaf instances. In addition to the annotated point cloud data, we provide 58 plant- and five leaf-related morphological parameters for each plant and leaf at each time point, validated using a 3D-printed plant reference model and invasive manual reference measurements. Sugar4D supports the development and evaluation of methods for plant instance segmentation, temporal registration, organ tracking, and spatio-temporal morphological analysis.</p>","PeriodicalId":21597,"journal":{"name":"Scientific Data","volume":"13 1","pages":""},"PeriodicalIF":7.2,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13588776/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149002663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"SARD: A Large-Scale Synthetic Arabic OCR Dataset for Book-Style Text Recognition.","authors":"Yasser Alhabashi, Omer Nacar, Serry Sibaee, Adel Ammar, Wadii Boulila","doi":"10.1038/s41597-026-07780-5","DOIUrl":"10.1038/s41597-026-07780-5","url":null,"abstract":"<p><p>Arabic Optical Character Recognition (OCR) plays a critical role in converting extensive Arabic print media into digital formats. The development of modern OCR models, particularly advanced vision-language models, is hindered by the lack of large, diverse, and well-structured datasets that accurately replicate real-world book layouts. Most existing Arabic OCR datasets focus on isolated words or lines and are limited in scale, typographic diversity, or structural complexity representative of books. To address this limitation, this paper introduces SARD (Large-Scale Synthetic Arabic OCR Dataset). SARD is a synthetically generated dataset specifically designed to simulate book-style documents, comprising 2,621,075 document images and 794.6 million words rendered in six fonts: Sakkal Majalla, Arial, Calibri, Scheherazade New, Amiri, and Traditional Arabic. Unlike datasets derived from scanned documents, SARD is free from real-world noise and distortions, providing a clean and controlled environment for model training. Its synthetic nature enables exceptional scalability and precise control over layout and content variation. This study describes the dataset's composition, generation process, and technical validation, and presents benchmark results for several traditional and deep-learning OCR models to highlight the challenges and opportunities associated with the dataset. SARD serves as a valuable resource for developing and evaluating robust OCR and vision-language models that can process diverse Arabic book-style texts.</p>","PeriodicalId":21597,"journal":{"name":"Scientific Data","volume":"13 1","pages":""},"PeriodicalIF":7.2,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13588801/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149002672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Scientific DataPub Date : 2026-09-16DOI: 10.1038/s41597-026-08088-0
Inès N Otosaka, Andrew Shepherd, Charles Amory, Martin Horwath, Erik R Ivins, Michalea D King, Sophie Nowicki, Anthony J Payne, Eric Rignot, Louise Sandberg Sørensen, Nicole-Jeanne Schlegel, Karen M Simon, Benjamin E Smith, Tyler C Sutterley, Michiel R van den Broeke, Isabella Velicogna, Geruo A, Cécile Agosta, Pavel Ditmar, Thorben Döhne, Marcus E Engdahl, Xavier Fettweis, Rene Forsberg, Alex S Gardner, Linda Gilbert, Heiko Goelzer, Noel Gourmelen, Andreas Groh, Nicolaj Hansen, Christopher Harig, Veit Helm, Shfaqat Abbas Khan, Christoph Kittel, Peter L Langen, Mathias Larsen, Bryant D Loomis, Malcolm McMillan, Brooke Medley, Daniele Melini, Ruth H Mottram, Alan Muir, Johan Nilsson, Brice Noël, Mark E Pattle, Mònica Roca I Aparici, Ingo Sasgen, Himanshu V Save, Bernd Scheuchl, Ernst J O Schrama, Ludwig Schröder, Ki-Weon Seo, Sebastian B Simonsen, Thomas Slater, Giorgio Spada, Bramha Dutt Vishwakarma, Nander Wever, David N Wiese, Bert Wouters
{"title":"Mass balance of the Greenland and Antarctic ice sheets from the 1970s to 2023.","authors":"Inès N Otosaka, Andrew Shepherd, Charles Amory, Martin Horwath, Erik R Ivins, Michalea D King, Sophie Nowicki, Anthony J Payne, Eric Rignot, Louise Sandberg Sørensen, Nicole-Jeanne Schlegel, Karen M Simon, Benjamin E Smith, Tyler C Sutterley, Michiel R van den Broeke, Isabella Velicogna, Geruo A, Cécile Agosta, Pavel Ditmar, Thorben Döhne, Marcus E Engdahl, Xavier Fettweis, Rene Forsberg, Alex S Gardner, Linda Gilbert, Heiko Goelzer, Noel Gourmelen, Andreas Groh, Nicolaj Hansen, Christopher Harig, Veit Helm, Shfaqat Abbas Khan, Christoph Kittel, Peter L Langen, Mathias Larsen, Bryant D Loomis, Malcolm McMillan, Brooke Medley, Daniele Melini, Ruth H Mottram, Alan Muir, Johan Nilsson, Brice Noël, Mark E Pattle, Mònica Roca I Aparici, Ingo Sasgen, Himanshu V Save, Bernd Scheuchl, Ernst J O Schrama, Ludwig Schröder, Ki-Weon Seo, Sebastian B Simonsen, Thomas Slater, Giorgio Spada, Bramha Dutt Vishwakarma, Nander Wever, David N Wiese, Bert Wouters","doi":"10.1038/s41597-026-08088-0","DOIUrl":"10.1038/s41597-026-08088-0","url":null,"abstract":"<p><p>The Greenland and Antarctic ice sheets are major drivers of global mean sea level rise and are predicted to continue to do so in the future. However, they also represent the largest source of uncertainty in projections of future sea level rise making robust estimates of observed ice sheet mass changes critical. Here, we compare and combine 42 independent estimates of ice sheet mass balance derived from satellite observations of temporal changes in ice sheet flow, volume, and gravitational attraction to determine the ice sheet mass balance from 1972 (Greenland) and 1979 (Antarctica) until 2023. We then use regional climate models to partition the total mass balance into contributions associated with surface mass balance and ice dynamical imbalance. The ice sheets lost 11,309 ± 565 billion tonnes of ice between 1979 and 2023, with glacier dynamical imbalance driving 84% of the ice loss and surface mass balance the remainder. This dataset can be used to track the contribution of the ice sheets to sea level rise and constrain projections of future sea level rise.</p>","PeriodicalId":21597,"journal":{"name":"Scientific Data","volume":"13 1","pages":""},"PeriodicalIF":7.2,"publicationDate":"2026-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13582886/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148983678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Full-ocean-depth EM124 mapping of the Challenger Deep by R/V Hakuho-maru and depth-estimate sensitivity tests.","authors":"Masakazu Fujii, Chiori Tamura, Yasuhiko Ohara, Kyoko Okino","doi":"10.1038/s41597-026-08267-z","DOIUrl":"10.1038/s41597-026-08267-z","url":null,"abstract":"<p><p>The Challenger Deep in the Mariana Trench is the deepest known point on Earth, yet recent depth estimates still differ by several meters because of environmental and instrumental uncertainties. Here we present a new full-ocean-depth multibeam bathymetric dataset collected with a Kongsberg EM124 echosounder aboard R/V Hakuho-maru during the KH-23-9 cruise in 2023. The survey comprises east-west and north-south lines acquired at vessel speeds of 4-15 kt. Five seawater sound velocity models were constructed from contemporaneous XCTD data, historical full-depth CTD data, and a recent full-depth reference profile to test the sensitivity of depth estimates. After ping-by-ping editing and gridding, the preferred KH23XCTD+KH92CTD solution resolves three basins deeper than 10,900 m, with maximum depths of 10,926, 10,912, and 10,927 m in the western, central, and eastern basins, respectively. Alternative sound velocity models yield maximum depths from 10,914 to 10,932 m, illustrating the meter- to >10-m-scale sensitivity of full-ocean-depth multibeam estimates to the applied sound velocity structure. Cleaned point soundings, gridded bathymetric surfaces for each sound velocity model, and the gridding script are provided. The dataset enables assessment of how sound velocity structure, survey speed, and beam-footprint geometry influence depth estimates in full-ocean-depth multibeam mapping, and provides a new reference for cross-comparison of Challenger Deep bathymetry.</p>","PeriodicalId":21597,"journal":{"name":"Scientific Data","volume":"13 1","pages":""},"PeriodicalIF":7.2,"publicationDate":"2026-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13582998/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148983612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Scientific DataPub Date : 2026-09-11DOI: 10.1038/s41597-026-08047-9
Franziska Krämer, Stefan Münster, Frederic Strobl
{"title":"Sixteen isotropic 3D fluorescence live-imaging datasets of gastrulation in the red flour beetle Tribolium castaneum (Coleoptera: Tenebrionidae).","authors":"Franziska Krämer, Stefan Münster, Frederic Strobl","doi":"10.1038/s41597-026-08047-9","DOIUrl":"10.1038/s41597-026-08047-9","url":null,"abstract":"<p><p>Gastrulation is a pivotal phase of early embryogenesis during which initially uniform cells undergo coordinated movements and fate specification to establish the basic body plan. Although previous studies have advanced our understanding of gastrulation in the red flour beetle Tribolium castaneum, quantitative morphogenetic data remain limited. Here, we present the second Systematic Live Imaging Collection of Embryogenesis (SLICE-2), consisting of sixteen isotropic 3D fluorescence live imaging datasets that document gastrulation and early germband elongation in Tribolium. Imaging was performed using light sheet fluorescence microscopy in conjunction with a homozygous transgenic line that expresses mEmerald-labeled nanobodies against histone H2A/H2B. Embryos were recorded along four directions, and the resulting axial image stacks were subjected to multiview fusion to obtain isotropic 3D images of entire embryos with reduced shadowing artifacts. The collection includes weighted-average fusion and fusion-deconvolution derivatives, and nuclei segmentation data are available for selected developmental stages. SLICE-2 expands the microscopy data resources for Tribolium, enabling comprehensive analyses of gastrulation dynamics while also providing benchmark data for image processing, segmentation, and modeling approaches.</p>","PeriodicalId":21597,"journal":{"name":"Scientific Data","volume":"13 1","pages":""},"PeriodicalIF":7.2,"publicationDate":"2026-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13569860/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148945565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Scientific DataPub Date : 2026-09-08DOI: 10.1038/s41597-026-07768-1
Eliot Ruiz, Marion Thémèze-Leroy, Franck Ferraton, Jacques Panfili, Jean-Dominique Durand, Michel Kulbicki, Juliette Silhol, Austin Bernard, Raphaël Thomas, Théo Morisson, Yannis Djouldem, Elvin Baptiste, Pierre-Yves Pascal, Lucie Vanalderweireldt, Sébastien Cordonnier, Amélia Chatagnon, Pierre-Louis Rault, Prune Chareyre, Leila Leon, Iris Leone, Ylana Fouchan, Stéphanie Manel, Laureline Boulanger, Benjamin Victor, Séverine Albouy-Boyer, Thomas Le Berre, Charlotte R Dromard, Loïc Pellissier, Camille Albouy, Fabien Leprieur
{"title":"Global pelagic dispersal traits datasets for early-life stages of marine fishes.","authors":"Eliot Ruiz, Marion Thémèze-Leroy, Franck Ferraton, Jacques Panfili, Jean-Dominique Durand, Michel Kulbicki, Juliette Silhol, Austin Bernard, Raphaël Thomas, Théo Morisson, Yannis Djouldem, Elvin Baptiste, Pierre-Yves Pascal, Lucie Vanalderweireldt, Sébastien Cordonnier, Amélia Chatagnon, Pierre-Louis Rault, Prune Chareyre, Leila Leon, Iris Leone, Ylana Fouchan, Stéphanie Manel, Laureline Boulanger, Benjamin Victor, Séverine Albouy-Boyer, Thomas Le Berre, Charlotte R Dromard, Loïc Pellissier, Camille Albouy, Fabien Leprieur","doi":"10.1038/s41597-026-07768-1","DOIUrl":"10.1038/s41597-026-07768-1","url":null,"abstract":"<p><p>Although larval stages ensure most connectivity between demersal fish populations, dispersal traits are increasingly less measured, despite the importance of correctly parametrizing biophysical models for spatial conservation planning. Moreover, existing data are scattered across a vast multidisciplinary literature. To address this mismatch between need and availability, we compiled data from 3,201 references into multiple datasets covering 35 key pelagic dispersal traits across fish early-life stages. We specifically compiled data on swimming speed, vertical position, and delayed settlement in demersal fishes (rafting or pelagic juveniles), as these traits exert a major yet understudied influence on dispersal scale. We systematically reported all descriptive statistics, enabling robust fitting of probability density functions to introduce particle-level variability in Lagrangian models. Overall, datasets comprise 32,988 species-level (1,709 for higher-taxon-level) records for 6,841 marine fish species worldwide, including 1,155 unpublished records (other teams), and 313 records newly collected during two fieldworks (Maldives & Guadeloupe). We also digitized 12,322 individual-level age-at-length/weight records from rearing experiments, enabling temperature-dependent growth model fitting to forecast global warming impacts on dispersal.</p>","PeriodicalId":21597,"journal":{"name":"Scientific Data","volume":"13 1","pages":""},"PeriodicalIF":7.2,"publicationDate":"2026-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13554097/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148913364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Scientific DataPub Date : 2026-09-07DOI: 10.1038/s41597-026-07969-8
Dilek Yildiz, Guy J Abel
{"title":"A global dataset of immigration flow composition by age, sex and educational attainment.","authors":"Dilek Yildiz, Guy J Abel","doi":"10.1038/s41597-026-07969-8","DOIUrl":"10.1038/s41597-026-07969-8","url":null,"abstract":"<p><p>People at different ages and with different educational background have different migration patterns. However, international migration flows by age and educational attainment are scarce and not always comparable. We use a super learning algorithm with multiple initial models to estimate age and education composition of male and female immigrants for 199 countries over six five-year periods from 1990-1995 to 2015-2020. We access the performance of our approach through cross-validation and comparing initial learners with the super learner algorithm using multiple evaluation metrics. We also compare our age composition estimates against equivalent measures from Eurostat. The estimates indicate that while the proportion of immigration flows with higher education increase in all regions, Europe has the highest immigration flow with secondary or higher education.</p>","PeriodicalId":21597,"journal":{"name":"Scientific Data","volume":"13 1","pages":""},"PeriodicalIF":7.2,"publicationDate":"2026-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13550503/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148906999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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