Aims and scope

Scientific Data is an open access journal dedicated to data, publishing descriptions of research datasets and articles on research data sharing from all areas of natural sciences, medicine, engineering and social sciences.

We believe that:  

    Open research data sharing is crucial for facilitating scientific advancement. 
    Articles describing how to source and use data can greatly facilitate data discovery and reuse, underpinning the aims of the FAIR principles, across any subject discipline.
    If data are scientifically valid and of potential interest to someone it should be described and made available to the research community. Manuscripts must make an original contribution but they are not assessed based on their perceived significance, importance or impact. This is especially true for Data Descriptors (see below), which do not present hypotheses or conclusions.

Special Issue on Data for crop management
Submission Date: 2026-01-17

This Collection welcomes submissions of Data Descriptors associated with datasets for crop management, which are essential for optimising agricultural productivity, sustainability, and food security. Providing insights into soil health, weather patterns, pest control, irrigation, and fertilisation, such data can help the agricultural sector make data-driven decisions. By integrating data from remote sensing, precision agriculture technologies, and field trials, researchers can find ways to improve crop yields, reduce resource waste, and mitigate environmental impacts.

This Collection aims to provide a useful resource for researchers working to enhance food production efficiency, ensure sustainable land use, and help address global challenges like climate change, population growth, and food scarcity.

Special Issue on Computer Vision Data for Fault Detection in Engineering
Submission Date: 2026-01-22

Fault detection involves identifying and diagnosing issues in machines or equipment to prevent failures and ensure optimal performance. Computer vision plays a role in engineering fault detection by enabling automated, efficient, and precise monitoring of equipment, infrastructure, and manufacturing processes.

This collection focuses on annotated image or video datasets for use in fault detection in engineering contexts. Datasets are presented without hypotheses or conclusions, and analyses should focus on validating the dataset to ensure reliability and quality for reuse in the community.

Special Issue on Geodata for human wellbeing
Submission Date: 2026-02-02

Geospatial data can link people, places, and the environment. It can help us understand the complex relationships between public health, societal development, and resource management.

This Collection welcomes Data Descriptors detailing the curation, validation, and open sharing of georeferenced datasets that support research on human wellbeing. We encourage submissions covering health and disease mapping, environmental exposures, urban and rural development/infrastructure, disaster resilience, and socio-economic trends. Equally, datasets that support natural resource management, biodiversity conservation, habitat monitoring, or ecosystem services mapping are highly relevant. We particularly welcome datasets that bridge these themes. These may include (but are not limited to) data from remote sensing, spatial surveys, or GPS-tracked mobility patterns.

Special Issue on Invertebrate omics
Submission Date: 2026-02-08

Spanning a large range of taxa from insects, molluscs, and crustaceans to annelids, cnidarians, and beyond, invertebrates make up the vast majority of Earth's biodiversity - yet their genomes remain significantly underrepresented in public databases. Advances in sequencing technologies now provide unprecedented opportunities to generate high-quality genomic resources for these ecologically, evolutionarily, and economically important organisms.

This Collection welcomes Data Descriptors documenting the curation, validation, and open sharing of genomic, transcriptomic, and proteomic datasets for invertebrate species. Datasets that can be used downstream by researchers studying gene expression, developmental biology, adaptation, or species interactions are highly relevant. We are particularly interested in genomic resources for non-model organisms, keystone species, and those of conservation, agricultural, or biomedical significance.

We advise authors to carefully read our scope and submission guidelines prior to submission, and make particular note of Springer Nature's policies for the publication of mandated data types.

Special Issue on Computed Tomography (CT) Datasets
Submission Date: 2026-02-21

Computed Tomography (CT) imaging is a medical imaging technique that uses specialized X-ray equipment to create cross-sectional images, which can be used individually or combined to form three-dimensional images. This non-invasive technique can provide detailed information to help diagnose injuries and illnesses, detect disease, and help guide medical procedures. This Collection highlights a series of articles that describe CT imaging datasets. Datasets are presented without hypotheses or conclusions, and analyses should focus on validating the dataset to ensure reliability and quality for reuse in the community.

For all datasets that contain data from participants, please complete our Human Data Checklist at the time of submission and supply a copy with the manuscript files. All described datasets are assessed to ensure their open availability (where possible) or secure access controls (where required) via Scientific Data's editorial and peer review processes.

Special Issue on Terrestrial carbon cycle
Submission Date: 2026-03-04

This Collection presents a series of datasets for the terrestrial carbon cycle. Such datasets are crucial for understanding how carbon moves through land ecosystems, influencing climate change and ecosystem health. These data tend to track carbon fluxes in soils, plants, and the atmosphere, providing insights into carbon sequestration, greenhouse gas emissions, and the impacts of land use changes. By integrating data from remote sensing, eddy covariance flux towers, soil samples, and vegetation models, researchers can assess carbon storage and predict climate feedbacks. Accurate carbon cycle data supports climate policy, forest management, and conservation efforts, helping mitigate global warming and ensuring sustainable land use practices for maintaining ecosystem stability and resilience.

Special Issue on Annotated Optical Microscopy Datasets
Submission Date: 2026-03-12

Optical Microscopy methods offer a range of tools for observing cellular structures, interactions, and dynamics in both fixed and live samples. This collection of articles focuses on datasets of annotated microscopy images from a variety of cell types and tissues. Datasets are presented without hypotheses or conclusions, and analyses should focus on validating the dataset to ensure reliability and quality for reuse in the community. For all datasets that contain data from participants, please complete our Human Data Checklist at the time of submission and supply a copy with the manuscript files.

Special Issue on Environmental pollution in aquatic systems
Submission Date: 2026-03-12

Pollution in aquatic environments can have severe consequences for ecosystems, wildlife, and human health. This Collection presents descriptions of contamination and pollution data collected from marine and freshwater ecosystems. Data can include information on plastic pollution, chemical and agricultural runoff, biological contamination, and other aquatic pollutants. Datasets are presented without hypotheses or conclusions, and analyses should focus on validating the dataset to ensure reliability and quality for reuse in the community.

Special Issue on Neurogenetics
Submission Date: 2026-03-19

Understanding the genetic underpinnings of neural function, development, and disease is a rapidly evolving field with profound implications for neuroscience and medicine. This Collection welcomes the submission of Data Descriptors describing the curation, validation, and sharing of datasets relevant to neurogenetics. By ensuring data documentation and open accessibility, this Collection aims to support reproducibility and accelerate discoveries at the intersection of genetics and neuroscience.

We encourage submissions detailing genomic, transcriptomic, epigenomic, and proteomic datasets that may be used to shed light on the genetic basis of neurological traits and disorders. Studies focusing on single-cell sequencing, population genetics, model organism data, and multi-omics integration are particularly welcome. Datasets facilitating the study of neurodevelopmental conditions, neurodegenerative diseases, and psychiatric disorders are of high interest.

We encourage authors submitting human data to look carefully through our submission policies to ensure compliance, and note that a Human Data Submission Checklist should be filled and appended to the submission.

Special Issue on Data on Science and Innovation Processes, Outputs and Outcomes
Submission Date: 2026-03-26

The analytical study of science and innovation—also termed metascience, science of science, scientometrics, technometrics, among others—is becoming increasingly critical as global research and development efforts expand in scope and complexity. Understanding this complexity requires sophisticated analytical tools and, crucially, rich and comprehensive data. This collection aims to gather data descriptors on high-quality, reusable datasets that illuminate the inputs, processes, and outputs of science and innovation. This collection also welcomes other article types supported by the journal - please see Scientific Data’s Aims & Scope for general information.

The key topics in this collection include, but are not limited to, data on publications and patents, funding, collaborations and networks, workforce and its mobility, infrastructure, diffusion, and the societal impact of science and innovation. Datasets related to study replication and result reproducibility are especially encouraged.

Special Issue on Droughts
Submission Date: 2026-03-31

Droughts can have serious environmental and economic consequences, such as resource scarcity, loss of biodiversity, and an increased risk of wildfires. Accurate drought data can help in managing water resources, and supports disaster response, climate change studies, and informed decision making to reduce future risk. This Collection highlights a series of articles describing drought datasets. Datasets are presented without hypotheses or conclusions, and analyses should focus on validating the dataset to ensure reliability and quality for reuse in the community. Data can be sourced from remote sensing, primary measurements, or theoretical models, with Data Descriptors providing the full details of data sources, modelling, and any associated computational resources.

Special Issue on Genomes of endangered species
Submission Date: 2026-04-01

Conserving endangered species is essential for protecting global biodiversity and maintaining healthy ecosystems. Despite their value, genomic tools remain underused in conservation, with only a small fraction of species having sequenced genomes. This collection of articles focuses on genome assemblies of endangered or threatened species. Datasets are presented without hypotheses or conclusions, and analyses should focus on validating the dataset to ensure reliability and quality for reuse in the community. For all datasets that contain data from protected species, please ensure that any local legal and ethical permits to generate the data have been obtained.

Special Issue on Computer vision in plant science and agriculture
Submission Date: 2026-04-10

Computer vision is rapidly transforming plant sciences and agriculture by enabling high-throughput, precise, and scalable phenotyping and monitoring. This Collection invites Data Descriptors documenting the generation, curation, and validation of datasets that underpin computer vision applications across plant biology, crop science, and agricultural systems.

We welcome datasets derived from image-based phenotyping platforms, such as UAV and satellite imagery, field cameras, root imaging systems, hyperspectral or multispectral, and event-based (neuromorphic) imaging technologies. Relevant datasets may include annotated image sets for tasks such as plant disease detection, yield estimation, weed identification, crop classification, growth monitoring and tracking, real-time pest detection, pollinator tracking, leaf motion analysis, or trait quantification. Datasets supporting the training and evaluation of machine learning or deep learning models are particularly encouraged, provided they are well documented and openly accessible.

This Collection aims to support the development of reproducible, high-quality datasets that serve as benchmarks or foundational resources for the plant science and agricultural research communities. Contributions involving both model and non-model plant species, as well as data relevant to precision agriculture, sustainable farming, and food security, are highly welcome.

Special Issue on Bioacoustic Data
Submission Date: 2026-04-17

Bioacoustic data can help provide insight into the behaviour, communication, and health of animal populations, as well as the environmental conditions in which they live.

This collection focuses on annotated bioacoustics datasets, collected from a variety of sources and environments. Datasets are presented without hypotheses or conclusions, and analyses should focus on validating the dataset to ensure reliability and quality for reuse in the community.

Special Issue on Datasets for language sciences
Submission Date: 2026-04-21

Language is central to human communication, cognition, and culture; psycholinguistics provides tools to explore the structure, variation, and evolution of language by harnessing insights from the human cognitive system and behaviour. This Collection invites Data Descriptors that describe the generation, curation, and validation of openly shared and useful datasets relevant to the field of psycholinguistics.

We welcome submissions presenting lexicography, speech recordings, syntactic and morphological data, phonetic or orthographic datasets, language acquisition data, and other structured psycholinguistic resources. Multilingual, underrepresented, or endangered language datasets are especially encouraged, as are resources supporting computational linguistics research. All manuscripts should include clear documentation of data collection methods, metadata standards.

This Collection aims to highlight the value of open data in advancing psycholinguistic theory, supporting cross-linguistic comparisons, and enabling computational applications. By focusing on psycholinguistics data, this Collection supports collaborative and reproducible research across theoretical, applied, and computational domains in language science.

Special Issue on Data to support drug discovery
Submission Date: 2026-04-22

A successful drug discovery and development pipeline involves a wide variety of data, including molecular and macromolecular structures, in vivo and in vitro bioactivity, bioavailability, toxicology/pharmacology, and many other data needed to turn candidates into marketable drugs. This collection will focus on descriptions of data relevant to the drug discovery process from experimental or computational methods and applicable to any clinical or disease area. We will also welcome articles and comments on the science of data sharing within this domain, as per Scientific Data's scope.

Special Issue on Volcanism
Submission Date: 2026-04-24

Volcanism data is crucial to understand the geological processes driving volcanic activity and to improve eruption prediction models. This collection of articles focuses on volcanic data, including data sourced from seismic monitoring, satellite imagery, and gas emissions. Datasets are presented without hypotheses or conclusions, and analyses should focus on validating the dataset to ensure reliability and quality for reuse in the community

Special Issue on Wearable and Computer Vision Data for Health and Behaviour Research
Submission Date: 2026-05-08

Wearable and non-wearable devices are transforming how we monitor health, activity, and environmental exposure in real time. These technologies generate rich, continuous data streams that support research across disciplines including physiology, behavioural science, public health, and environmental monitoring.

This Collection highlights a series of articles describing datasets derived from both wearable devices and non-contact sensing methods. Datasets are presented without hypotheses or conclusions, and analyses should focus on validating the dataset to ensure reliability and quality for reuse in the community. Data may originate from consumer-grade or research-grade devices, and may include physiological signals, movement patterns, environmental exposures, or contextual metadata. The collected signals may include, but not be limited to, (x,y,z) coordinate data, joint positions and angles, velocity, acceleration, postural metrics, gait metrics, EMG, EEG, and ECG.

Authors submitting datasets involving human participants must complete the Human Data Checklist and include it with their manuscript files.

Special Issue on Trophic webs
Submission Date: 2026-05-11

Trophic webs, describing connections between organisms and predator/prey relationships, are vital for understanding ecosystem structure, diversity, and change. Such systems require extensive input data from sources such as literature extraction, direct observation, and sampling to allow relationships to be deduced.

This Scientific Data collection will focus on Data Descriptors and other outputs relating to trophic web data collection, covering raw and processed data as well as efforts to create data standards and other structures to support FAIR data collection in this field. All ecosystem types, geographic regions and scales and considered.

Special Issue on Paleoclimate Records and Reconstructions
Submission Date: 2026-05-28

Reconstructing Earth’s past climate provides a baseline for interpreting present-day climate variability and refining future projections. Paleoclimate data offer critical insights into long-term climate dynamics, past atmospheric composition, and the natural drivers of change over geological timescales. This Collection features datasets derived from historical records and proxy indicators that reconstruct past climates.

Datasets are presented without hypotheses or conclusions, and analyses should focus on validating the dataset to ensure reliability and quality for reuse in the community. Data may be derived from field measurements, laboratory analyses, or model-based reconstructions, with Data Descriptors providing full details of data acquisition, processing methods, and any associated computational tools.

Special Issue on Lipidomics
Submission Date: 2026-05-29

Lipidomics, relates to the make-up and processes of the “lipidome” and is a vital component of modern metabolomics. Researchers applying analytical techniques to further our understanding of cellular lipids are invited to contribute to this Scientific Data collection. Descriptions of datasets will be considered for any technique relevant to lipidomics research, including mass spectrometry, NMR, theoretical studies, and spectroscopy, and may be related to the study of lipids within any relevant organism, system, or disease area. The collection is also open to submissions related to data standards, repositories, or related works within Scientific Data’s Article or Comment format.

Special Issue on Transcriptomics data from clinical isolates
Submission Date: 2026-07-08

Transcriptomic datasets from clinical isolates provide vital insights into pathogen biology, host-pathogen interactions, and antimicrobial resistance. Captured directly from patient-derived samples, these datasets reflect gene expression patterns shaped by complex clinical environments. This Collection features articles describing transcriptomic data from a range of microbial pathogens, including bacteria, viruses, fungi, and parasites isolated in clinical settings. Submissions are presented without hypotheses or conclusions, with a focus on dataset validation to ensure quality and reusability. Data may be generated using RNA sequencing, microarrays, or other transcriptomic technologies, and should be accompanied by detailed descriptions of sample origin and processing methods. Authors submitting datasets involving human participants must complete the Human Data Checklist and include it with their manuscript files.

Special Issue on Genomics in freshwater and marine science
Submission Date: 2026-07-23

Freshwater and marine ecosystems support a rich diversity of organisms, many of which remain genomically understudied. Advances in transcriptomics and genome assembly are enabling deeper insights into the physiology, adaptation, and evolutionary history of aquatic species, from phytoplankton to fish and benthic invertebrates. This Collection features articles describing transcriptomic datasets and genome assemblies from freshwater and marine taxa.

Datasets are presented without hypotheses or conclusions, and analyses should focus on validating the data to ensure quality, reproducibility, and reusability. Submissions should include detailed metadata on sample collection, sequencing technologies, and assembly methods to support transparency and reuse across the research community.

Special Issue on Plant transcriptomic responses
Submission Date: 2026-07-28

Studying plant transcriptomic responses allows us to understand how plants regulate gene expression in response to environmental changes, stress, and developmental processes. Predominantly through RNAseq, researchers can identify genes involved in traits such as drought resistance, disease defence, and growth regulation. These datasets help improve crop resilience, enhance agricultural productivity, and inform breeding strategies for climate adaptation. Additionally, transcriptomic data provides insights into plant signalling pathways, metabolic processes, and responses to biotic and abiotic stressors.

This Collection presents a series of such datasets, as this information is crucial for developing sustainable agricultural practices, conserving plant biodiversity, and advancing biotechnology for food security and ecosystem health.

Special Issue on Biogeochemistry in terrestrial environments
Submission Date: 2026-07-29

Terrestrial biogeochemistry plays a critical role in regulating Earth’s climate, nutrient cycles, and ecosystem health. As environmental change accelerates, the availability of high-quality, well-documented datasets is essential for monitoring, modelling, and managing these complex systems.

We invite Data Descriptors that detail the collection, curation, and validation of datasets from forests, grasslands, wetlands, agricultural systems, and other land-based environments. Relevant datasets may include, but are not limited to, measurements of soil chemistry, greenhouse gas fluxes, nutrient cycling, plant-soil interactions, microbial community composition, and long-term ecological monitoring. Submissions should provide clear documentation of sampling methods, analytical protocols, data quality assurance, and repository access.

By bringing together openly accessible datasets from across the terrestrial biosphere, this Collection aims to support reproducible research and foster interdisciplinary collaboration in ecology, environmental science, and Earth system science. We encourage contributions from researchers, field stations, monitoring networks, and institutions working to make terrestrial biogeochemical data more transparent, standardised, and reusable.

Special Issue on Glaciology, sea ice and inland waters ice
Submission Date: 2026-08-12

Glaciers, sea ice, lake ice, and river ice are critical components of the Earth system, influencing global sea levels and ocean circulation. Their rapid transformation due to climate warming has significant environmental and societal consequences, including rising sea levels, altered freshwater and surface energy fluxes, disrupted marine and riverine ecosystems, and changes in regional weather patterns and local transport routes. Observing and understanding the dynamics of glaciers, sea ice, and river ice is essential for tracking climate change and predicting its global impacts.

This Collection features a series of articles describing datasets related to glaciology, sea ice, and river ice. Datasets are presented without hypotheses or conclusions, and analyses should focus on validating the dataset to ensure reliability and quality for reuse within the research community. Data may be sourced from satellite remote sensing, field measurements, autonomous platforms, or numerical models, with Data Descriptors providing full details of data acquisition, processing methods, and any associated computational tools.

Special Issue on 10 years of the FAIR principles
Submission Date: 2026-08-14

The FAIR principles, which provide foundational guidance for sharing data and metadata, were published in Scientific Data in 2016 (Wilkinson, et al). Since then, the core concepts of Findable, Accessible, Interoperable, and Reusable data have become embedded in the design of key infrastructure across the data-sharing ecosystem, including repositories, data standards, policies, and workflows for curating and sharing machine-readable data.

To celebrate this milestone, Scientific Data invites researchers to submit manuscripts related to FAIR-aligned infrastructure, policy, or standardisation to this collection. Submissions are welcome under our "Article" manuscript type only (see Aims and Scope). 

Special Issue on Datasets in education
Submission Date: 2026-08-19

Education research increasingly relies on data to inform policy, improve pedagogy, and understand learning outcomes. This Collection invites Data Descriptors that describe the generation, curation, and validation of open datasets related to educational systems, practices, and outcomes across diverse contexts and populations.

We welcome submissions presenting datasets from classroom observations, standardized assessments, digital learning platforms, educational interventions, teacher training programs, curriculum analyses, and more. Relevant data might include student performance metrics, longitudinal learning trajectories, multimodal data from learning environments (e.g., video, eye-tracking, keystroke logs), or survey responses from students, educators, or institutions. Submissions should include detailed methodological descriptions and information about data repositories to ensure accessibility and reuse.

We are especially interested in datasets that support equity in education, cross-cultural comparisons, or interdisciplinary approaches—such as those integrating education with psychology, linguistics, or technology-enhanced learning. Ethical considerations, including anonymisation and consent, must be thoroughly addressed.

Special Issue on Data from Unmanned Aerial Vehicles (UAVs)
Submission Date: 2026-09-01

This collection welcomes submissions describing datasets generated using Unmanned Aerial Vehicles (UAVs), also known as drones, across a wide range of scientific disciplines.

UAVs have become indispensable tools for data acquisition in fields such as environmental monitoring, agriculture, archaeology, disaster response, urban planning, and beyond. Their ability to capture high-resolution spatial, spectral, and temporal data has opened new frontiers in research and resource management. We invite Data Descriptors that detail the collection, processing, and validation of UAV-derived datasets, including but not limited to aerial imagery, LiDAR scans, thermal and multispectral data, 3D reconstructions, and time-series observations. Submissions should clearly document the methods used for data acquisition, calibration, georeferencing, and quality control, as well as provide information on data accessibility and reuse potential.

By assembling high-quality, well-documented UAV datasets, this collection aims to support reproducible research and foster cross-disciplinary collaboration. We encourage contributions from researchers, engineers, and practitioners working to advance the use of UAVs in scientific data collection and to make these valuable datasets openly available to the global research community.

Special Issue on Data from archaeological samples, museum collections and historical records
Submission Date: 2026-09-08

This Collection invites submissions that describe datasets derived from the rich and diverse sources of our shared past, including: archaeological samples, museum holdings, and historical records. These datasets are vital for understanding human history, cultural evolution, and environmental change across time. We welcome Data Descriptors that detail the curation, digitisation, and validation of data from excavated materials, artefact inventories, archival documents, and other historical sources.

Submissions may include datasets from archaeological fieldwork, radiocarbon dating, palaeoenvironmental reconstructions, digitized museum catalogues, historical maps, and transcribed archival records. All datasets should be openly accessible, reusable, and accompanied by rigorous documentation of their provenance, structure, and quality control processes. We encourage contributions from researchers, curators, archivists, and data stewards working to preserve and share the legacy of historical and archaeological data.