| 1. |
- Agustí-Panareda, Anna, et al.
(author)
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Global nature run data with realistic high-resolution carbon weather for the year of the Paris Agreement
- 2022
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In: Scientific Data. - : Springer Science and Business Media LLC. - 2052-4463. ; 9:1
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Journal article (peer-reviewed)abstract
- The CO2 Human Emissions project has generated realistic high-resolution 9 km global simulations for atmospheric carbon tracers referred to as nature runs to foster carbon-cycle research applications with current and planned satellite missions, as well as the surge of in situ observations. Realistic atmospheric CO2, CH4 and CO fields can provide a reference for assessing the impact of proposed designs of new satellites and in situ networks and to study atmospheric variability of the tracers modulated by the weather. The simulations spanning 2015 are based on the Copernicus Atmosphere Monitoring Service forecasts at the European Centre for Medium Range Weather Forecasts, with improvements in various model components and input data such as anthropogenic emissions, in preparation of a CO2 Monitoring and Verification Support system. The relative contribution of different emissions and natural fluxes towards observed atmospheric variability is diagnosed by additional tagged tracers in the simulations. The evaluation of such high-resolution model simulations can be used to identify model deficiencies and guide further model improvements.
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| 2. |
- Akbar, Muhammad Usman, 1990-, et al.
(author)
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Brain tumor segmentation using synthetic MR images - A comparison of GANs and diffusion models
- 2024
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In: Scientific Data. - : Nature Publishing Group. - 2052-4463. ; 11:1
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Journal article (peer-reviewed)abstract
- Large annotated datasets are required for training deep learning models, but in medical imaging data sharing is often complicated due to ethics, anonymization and data protection legislation. Generative AI models, such as generative adversarial networks (GANs) and diffusion models, can today produce very realistic synthetic images, and can potentially facilitate data sharing. However, in order to share synthetic medical images it must first be demonstrated that they can be used for training different networks with acceptable performance. Here, we therefore comprehensively evaluate four GANs (progressive GAN, StyleGAN 1–3) and a diffusion model for the task of brain tumor segmentation (using two segmentation networks, U-Net and a Swin transformer). Our results show that segmentation networks trained on synthetic images reach Dice scores that are 80%–90% of Dice scores when training with real images, but that memorization of the training images can be a problem for diffusion models if the original dataset is too small. Our conclusion is that sharing synthetic medical images is a viable option to sharing real images, but that further work is required. The trained generative models and the generated synthetic images are shared on AIDA data hub.
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| 3. |
- Ali, Sharib, et al.
(author)
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A multi-centre polyp detection and segmentation dataset for generalisability assessment.
- 2023
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In: Scientific data. - : Springer Science and Business Media LLC. - 2052-4463. ; 10:1
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Journal article (peer-reviewed)abstract
- Polyps in the colon are widely known cancer precursors identified by colonoscopy. Whilst most polyps are benign, the polyp's number, size and surface structure are linked to the risk of colon cancer. Several methods have been developed to automate polyp detection and segmentation. However, the main issue is that they are not tested rigorously on a large multicentre purpose-built dataset, one reason being the lack of a comprehensive public dataset. As a result, the developed methods may not generalise to different population datasets. To this extent, we have curated a dataset from six unique centres incorporating more than 300 patients. The dataset includes both single frame and sequence data with 3762 annotated polyp labels with precise delineation of polyp boundaries verified by six senior gastroenterologists. To our knowledge, this is the most comprehensive detection and pixel-level segmentation dataset (referred to as PolypGen) curated by a team of computational scientists and expert gastroenterologists. The paper provides insight into data construction and annotation strategies, quality assurance, and technical validation.
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| 4. |
- Alneberg, Johannes, et al.
(author)
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BARM and BalticMicrobeDB, a reference metagenome and interface to meta-omic data for the Baltic Sea
- 2018
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In: Scientific Data. - : Nature Publishing Group. - 2052-4463. ; 5
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Journal article (peer-reviewed)abstract
- The Baltic Sea is one of the world's largest brackish water bodies and is characterised by pronounced physicochemical gradients where microbes are the main biogeochemical catalysts. Meta-omic methods provide rich information on the composition of, and activities within, microbial ecosystems, but are computationally heavy to perform. We here present the Baltic Sea Reference Metagenome (BARM), complete with annotated genes to facilitate further studies with much less computational effort. The assembly is constructed using 2.6 billion metagenomic reads from 81 water samples, spanning both spatial and temporal dimensions, and contains 6.8 million genes that have been annotated for function and taxonomy. The assembly is useful as a reference, facilitating taxonomic and functional annotation of additional samples by simply mapping their reads against the assembly. This capability is demonstrated by the successful mapping and annotation of 24 external samples. In addition, we present a public web interface, BalticMicrobeDB, for interactive exploratory analysis of the dataset. [GRAPHICS] .
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| 5. |
- Ammar, Yosr, et al.
(author)
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Long-term dataset for contaminants in fish, mussels, and bird eggs from the Baltic Sea
- 2024
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In: Scientific Data. - 2052-4463. ; 11:1
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Journal article (peer-reviewed)abstract
- Widespread persistent contaminants are a global environmental problem. In the Baltic Sea, wildlife contamination was first noticed in the 1960s, prompting the Swedish Environmental Protection Agency to establish a comprehensive Swedish National Monitoring Programme for Contaminants in Marine Biota (MCoM) in 1978 run by the Swedish Museum of Natural History. Eight species have been analysed, four fish species (Atlantic herring, Atlantic cod, European perch, viviparous eelpout), one bivalve species (blue mussel), and egg from three bird species (common guillemot, common tern, Eurasian oystercatcher). Here, we present a dataset containing MCoM data from its start until 2021. It includes 36 sets of time-series, each analysed for more than 100 contaminants. The longest time-series is for common guillemot and starts in 1968. We describe the structure of MCoM including historic changes to the number of stations, sample treatment, analytical methods, instruments, and laboratories. The MCoM data is available at the Bolin Centre repository and on GitHub through our R package mcomDb. The latter will be updated yearly with new MCoM records.
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| 6. |
- Andersen, Casper W., et al.
(author)
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OPTIMADE, an API for exchanging materials data
- 2021
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In: Scientific Data. - : Nature Portfolio. - 2052-4463. ; 8:1
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Journal article (peer-reviewed)abstract
- The Open Databases Integration for Materials Design (OPTIMADE) consortium has designed a universal application programming interface (API) to make materials databases accessible and interoperable. We outline the first stable release of the specification, v1.0, which is already supported by many leading databases and several software packages. We illustrate the advantages of the OPTIMADE API through worked examples on each of the public materials databases that support the full API specification.
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| 7. |
- Auffret, Alistair
(author)
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GalliForm, a database of Galliformes occurrence records from the Indo-Malay and Palaearctic, 1800-2008
- 2020
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In: Scientific Data. - : Springer Science and Business Media LLC. - 2052-4463. ; 7
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Journal article (peer-reviewed)abstract
- Historical as well as current species distribution data are needed to track changes in biodiversity. Species distribution data are found in a variety of sources, each of which has its own distinct bias toward certain taxa, time periods or places. We present GalliForm, a database that comprises 186687 galliform occurrence records linked to 118907 localities in Europe and Asia. Records were derived from museums, peer-reviewed and grey literature, unpublished field notes, diaries and correspondence, banding records, atlas records and online birding trip reports. We describe data collection processes, georeferencing methods and quality-control procedures. This database has underpinned several peer-reviewed studies, investigating spatial and temporal bias in biodiversity data, species' geographic range changes and local extirpation patterns. In our rapidly changing world, an understanding of long-term change in species' distributions is key to predicting future impacts of threatening processes such as land use change, over-exploitation of species and climate change. This database, its historical aspect in particular, provides a valuable source of information for further studies in macroecology and biodiversity conservation.
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| 8. |
- Azevedo, Flavio, et al.
(author)
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Social and moral psychology of COVID-19 across 69 countries
- 2023
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In: Scientific Data. - : NATURE PORTFOLIO. - 2052-4463. ; 10:1
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Journal article (peer-reviewed)abstract
- The COVID-19 pandemic has affected all domains of human life, including the economic and social fabric of societies. One of the central strategies for managing public health throughout the pandemic has been through persuasive messaging and collective behaviour change. To help scholars better understand the social and moral psychology behind public health behaviour, we present a dataset comprising of 51,404 individuals from 69 countries. This dataset was collected for the International Collaboration on Social & Moral Psychology of COVID-19 project (ICSMP COVID-19). This social science survey invited participants around the world to complete a series of moral and psychological measures and public health attitudes about COVID-19 during an early phase of the COVID-19 pandemic (between April and June 2020). The survey included seven broad categories of questions: COVID-19 beliefs and compliance behaviours; identity and social attitudes; ideology; health and well-being; moral beliefs and motivation; personality traits; and demographic variables. We report both raw and cleaned data, along with all survey materials, data visualisations, and psychometric evaluations of key variables.
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| 9. |
- Badian, Reza A., et al.
(author)
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Wide-field mosaics of the corneal subbasal nerve plexus in Parkinsons disease using in vivo confocal microscopy
- 2021
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In: Scientific Data. - : Nature Portfolio. - 2052-4463. ; 8:1
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Journal article (peer-reviewed)abstract
- In vivo confocal microscopy (IVCM) is a non-invasive imaging technique facilitating real-time acquisition of images from the live cornea and its layers with high resolution (1-2 mu m) and high magnification (600 to 800-fold). IVCM is extensively used to examine the cornea at a cellular level, including the subbasal nerve plexus (SBNP). IVCM of the cornea has thus gained intense interest for probing ophthalmic and systemic diseases affecting peripheral nerves. One of the main drawbacks, however, is the small field of view of IVCM, preventing an overview of SBNP architecture and necessitating subjective image sampling of small areas of the SBNP for analysis. Here, we provide a high-quality dataset of the corneal SBNP reconstructed by automated mosaicking, with an average mosaic image size corresponding to 48 individual IVCM fields of view. The mosaic dataset represents a group of 42 individuals with Parkinsons disease (PD) with and without concurrent restless leg syndrome. Additionally, mosaics from a control group (n = 13) without PD are also provided, along with clinical data for all included participants.
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| 10. |
- Ballarino, R, et al.
(author)
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An atlas of endogenous DNA double-strand breaks arising during human neural cell fate determination
- 2022
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In: Scientific data. - : Springer Science and Business Media LLC. - 2052-4463. ; 9:1, s. 400-
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Journal article (peer-reviewed)abstract
- Endogenous DNA double-strand breaks (DSBs) occurring in neural cells have been implicated in the pathogenesis of neurodevelopmental disorders (NDDs). Currently, a genomic map of endogenous DSBs arising during human neurogenesis is missing. Here, we applied in-suspension Breaks Labeling In Situ and Sequencing (sBLISS), RNA-Seq, and Hi-C to chart the genomic landscape of DSBs and relate it to gene expression and genome architecture in 2D cultures of human neuroepithelial stem cells (NES), neural progenitor cells (NPC), and post-mitotic neural cells (NEU). Endogenous DSBs were enriched at the promoter and along the gene body of transcriptionally active genes, at the borders of topologically associating domains (TADs), and around chromatin loop anchors. NDD risk genes harbored significantly more DSBs in comparison to other protein-coding genes, especially in NEU cells. We provide sBLISS, RNA-Seq, and Hi-C datasets for each differentiation stage, and all the scripts needed to reproduce our analyses. Our datasets and tools represent a unique resource that can be harnessed to investigate the role of genome fragility in the pathogenesis of NDDs.
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