Scientific Data最新文献

The North-Eastern Europe and Northern Asia open-access dataset (NEENA) is a compilation of over 18,700 isotopic measurements (δ¹³C, δ¹⁵N, δ³⁴S, δ¹⁸O, ⁸⁷Sr/⁸⁶Sr), predominantly from archaeological human, animal, and plant samples originating from more than 750 sites ranging geographically from the Baltic and Eastern Europe to North-Central Asia and dating between 70,000 years BP and modern times. For each isotope record included in the dataset, information relating to the taxonomic categorisation of the sampled material (e.g., animal and plant species or genus names), the sample type (e.g., bone, dentine, enamel) and contextual, chronological, provenance (i.e., site location and country), and laboratory details are provided where available from original publications. The NEENA dataset can be used to conduct comparative studies of palaeodiet, spatial mobility, paleo-environmental conditions, organic remains preservation, and radiocarbon reservoir effects. NEENA is available in an open-access format via the Pandora data platform.

We developed and released an image dataset for surface defect detection on waterborne painted wood products. The dataset comprises 13400 high-resolution images capturing four defect types: scratches, cracks, bubbles, and holes. These include 3645 bubble defects, 3498 scratch defects, 3256 crack defects, and 3001 hole defects. Data were acquired in an operational production facility in Jiangshan, China, using specialized industrial cameras. Professional annotators performed rigorous labeling to ensure accuracy. This dataset provides critical data support for deploying deep learning models in real-world industrial assembly lines. Researchers may leverage this dataset to develop automated machine learning solutions for multi-class defect detection. Such techniques enable timely defect detection and remediation, ensuring finish integrity and final product quality.

Field observations provide direct evidence of how does carbon cycling in permafrost ecosystems respond to climate change. This study provides a comprehensive dataset on the impact of warming on carbon cycling and greenhouse gas (GHG) fluxes in permafrost ecosystems. The dataset is extracted and integrated from 132 peer-reviewed studies with 1430 paired observations across eight major permafrost ecosystems, including Arctic and subarctic tundra and wetland, and alpine meadow, steppe, tundra and wetland. This dataset includes 17 variables from experiments conducted during the growing season, covering the plant and soil carbon pools, soil nitrogen pool, and GHG (i.e., CO₂, CH₄, and N₂O) fluxes, among others. Background information on site climate conditions, vegetation and soil characteristics, and details of the warming experiments, including timing, methods, and warming magnitude, are also contained in the dataset. This dataset facilitates a comprehensive understanding of the impact of warming on carbon cycling and GHG fluxes in permafrost ecosystems, and provides supports for meta-analyses and literature reviews, remote sensing data validation, and land model development and parameterization.

With the increasing volume of biomedical experimental data, standardizing, sharing, and integrating heterogeneous experimental data across domains has become a major challenge. To address this challenge, we have developed an ontology-supported Study-Experiment-Assay (SEA) common data model (CDM), which includes 10 core and 3 auxiliary classes based on object-oriented modeling. SEA CDM uses interoperable ontologies for data standardization and knowledge inference. Building on the SEA CDM, we developed the Ontology-based SEA Network (OSEAN) relational database and knowledge graph, along with a set of ETL (Extract, Transform, Load) and query tools, and further applied them to represent 1,278 immune studies with over two million samples from three resources: VIGET, ImmPort, and CELLxGENE. Using simple, robust queries and analyses, our research identified multiple scientific insights into sex-specific immune responses, such as neutrophil degranulation and TNF binding to physiological receptors, following live attenuated and trivalent inactivated influenza vaccination. The novel SEA CDM system lays a foundation for establishing an integrative biodata ecosystem across biological and biomedical domains.

Solar wind measurements by the Mars Atmosphere and Volatile EvolutioN (MAVEN) mission provide samples of the heliosphere at 1.38-1.67 AU, and of the upstream conditions that drive numerous processes in the near-Mars plasma environment. We reduce ion measurements from MAVEN's Solar Wind Ion Analyzer (SWIA), using contextual magnetic field measurements, to 13 independent macroscopic plasma parameters by fitting a convolution of SWIA's 3-dimensional response function and a superposition of phase-space bi-kappa distribution functions to each measured distribution using an iterative Poisson optimization scheme. This ensemble of parameters represents the solar wind H⁺ core, H⁺ beam, and He²⁺ (alpha) populations, effectively separating each population's contribution to any measured distribution. Sporadic plasma frequency measurements from MAVEN's Langmuir Probe and Waves (LPW) instrument are used to calibrate the SWIA measurements such that ion charge densities match LPW-derived electron charge densities. The resulting dataset is effectively ground-truthed, largely corrected for instrumental particularities, and provides a rich timeline of solar wind properties at Mars, including composition, velocities, temperature anisotropies, differential drifts, and degree of thermalization.

The Ontology of Adverse Events (OAE) was launched in 2011 to define, standardize and integrate various adverse events (AEs) arising after medical interventions. The terminological framework of OAE has undergone consistent expansion since its inception, driven by its successful implementation in numerous AE investigations. In this paper, we document substantial ontological extensions addressing patient anatomic regions and clinical manifestations, encompassing symptoms, physical signs, and pathological processes. Current statistical analysis reveals that OAE has 10,829 formally defined terms with unique identifiers. Compared to the 3,088 ontology terms included in the last OAE publication in 2014, 7,741 new terms have been added to OAE, which represents significant progress of the ontology in clinical granularity and domain coverage. The OAE framework enables structured representation of critical determinants influencing clinical outcomes, including but not limited to administration routes, dosage parameters, and demographic variables such as patient age. Through its standardized semantic architecture, OAE provides an integrative platform for cross-disciplinary analysis of AE patterns, etiological factors, and outcome trajectories in clinical interventions.

Organ transplantation is a life-saving procedure for patients with advanced diseases. However, the demand for transplants far exceeds the supply of donated organs, and there are currently over 100,000 people waiting for a transplant in the United States. The lives of these patients depend on the efficacy of organ procurement organizations (OPOs), which coordinate the recovery of organs from deceased donors. However, many studies have found high variation in performance amongst OPOs. Coordinating data collection and analysis across OPOs is a crucial first step in closing performance gaps and achieving more effective organ donation. In 2021, the Federation of American Scientists announced a collaboration in which six OPOs committed to an unprecedented level of data sharing. This paper marks the release of ORCHID, this collaboration's first public dataset. ORCHID comprises detailed information on referrals for donation, procurement outcomes, and process data from the participating OPOs. Our goal in releasing this data is to promote research that leads to better services for organ donors, donor families, and patients waiting for transplants.

Public transport operation network data serves as the foundation for urban transportation research and sustainable development planning. China operates the world's largest public transport system, where buses and metros constitute primary urban mobility modes. Despite their critical importance, comprehensive integrated bus-metro operation datasets remain lacking at the national scale. This study presents the China Public Transport Operation Network Dataset (CPTOND-2025), systematically integrating bus networks from 350 cities and metro systems from 46 cities across mainland China, Hong Kong, Macao, and Taiwan regions. Based on June 2025 data collection using methodologies integrate professional platforms and commercial APIs, the dataset encompasses approximately 3,408,000 kilometers of operational routes (bus: ~3,375,000 km; metro: ~33,000 km). Key attributes including operating hours, fares, and operating companies are recorded with bilingual support. All data utilize standardized Shapefile format in WGS-84 coordinate system with 5.08-meter average spatial accuracy. This standardized, comprehensive, open-access dataset supports diverse applications including operation efficiency assessment, network analysis, accessibility evaluation, and Transit-Oriented Development (TOD) studies, facilitating transport management decisions and international research.

Coastal marine environments, such as lagoons, fjords or estuaries, experience pronounced environmental variability, with fluctuations in salinity, temperature and nutrient levels shaping microbial community structure and function. These gradients result in diverse habitats, which may harbour taxonomic and genetic novelty with biogeochemical and biotechnological relevance. To explore microbial diversity and functional potential across these dynamic ecosystems, we sampled 26 sites along the coasts of France and Chile, including lagoons, estuaries, fjords, harbours, as well as coastal and offshore marine sites. Surface waters were collected from all sites, with deeper layers included at three sites. Monthly sampling at six sites in France enabled the assessment of seasonal dynamics. In total, 116 samples were processed for both metabarcoding and metagenomic sequencing yielding over 53,000 amplicon sequence variants (ASVs) and 1,372 metagenome-assembled genomes (MAGs). This dataset further includes a comprehensive gene catalogue and environmental variables such as salinity, temperature, nutrient concentrations, productivity, as well as oxygen consumption metrics collected across the different ecosystems.

Cardiac fibroblasts (CFs) are key mediators of heart repair following myocardial infarction (MI). A specific CF subpopulation, termed Reparative Cardiac Fibroblasts (RCFs), has been shown to orchestrate scar formation and prevent ventricular rupture after MI. However, the timing of RCF appearance and the molecular events underlying this transition remain largely undefined. Here, we present a multi-modal dataset capturing the transcriptional dynamics of CFs during the early phase post-MI. Our integrative dataset combines bulk RNA sequencing, RNAscope in situ hybridization, and spatial transcriptomics to anatomically and temporally map the gene expression changes associated with the transition into RCFs. The dataset provides resources to characterize the distinct molecular programs that guide the emergence of RCFs from Periostin (Postn)⁺ activated CFs. This dataset provides a valuable resource for investigating CF heterogeneity and reparative pathways following MI. All raw and processed data, along with detailed metadata and annotations, are made available to facilitate reuse by the cardiovascular and single-cell biology communities.