| 1. |
- Simistira Liwicki, Foteini, et al.
(author)
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Bimodal electroencephalography-functional magnetic resonance imaging dataset for inner-speech recognition
- 2023
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In: Scientific Data. - : Springer Nature. - 2052-4463. ; 10
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Journal article (peer-reviewed)abstract
- The recognition of inner speech, which could give a ‘voice’ to patients that have no ability to speak or move, is a challenge for brain-computer interfaces (BCIs). A shortcoming of the available datasets is that they do not combine modalities to increase the performance of inner speech recognition. Multimodal datasets of brain data enable the fusion of neuroimaging modalities with complimentary properties, such as the high spatial resolution of functional magnetic resonance imaging (fMRI) and the temporal resolution of electroencephalography (EEG), and therefore are promising for decoding inner speech. This paper presents the first publicly available bimodal dataset containing EEG and fMRI data acquired nonsimultaneously during inner-speech production. Data were obtained from four healthy, right-handed participants during an inner-speech task with words in either a social or numerical category. Each of the 8-word stimuli were assessed with 40 trials, resulting in 320 trials in each modality for each participant. The aim of this work is to provide a publicly available bimodal dataset on inner speech, contributing towards speech prostheses.
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| 2. |
- Stuyver, Thijs, et al.
(author)
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Reaction profiles for quantum chemistry-computed [3 + 2] cycloaddition reactions
- 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
- Bio-orthogonal click chemistry based on [3 + 2] dipolar cycloadditions has had a profound impact on the field of biochemistry and significant effort has been devoted to identify promising new candidate reactions for this purpose. To gauge whether a prospective reaction could be a suitable bio-orthogonal click reaction, information about both on- and off-target activation and reaction energies is highly valuable. Here, we use an automated workflow, based on the autodE program, to compute over 5000 reaction profiles for [3 + 2] cycloadditions involving both synthetic dipolarophiles and a set of biologically-inspired structural motifs. Based on a succinct benchmarking study, the B3LYP-D3(BJ)/def2-TZVP//B3LYP-D3(BJ)/def2-SVP level of theory was selected for the DFT calculations, and standard conditions and an (aqueous) SMD model were imposed to mimic physiological conditions. We believe that this data, as well as the presented workflow for high-throughput reaction profile computation, will be useful to screen for new bio-orthogonal reactions, as well as for the development of novel machine learning models for the prediction of chemical reactivity more broadly.
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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. |
- 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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| 5. |
- Ghiringhelli, Luca M., et al.
(author)
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Shared metadata for data-centric materials science
- 2023
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In: Scientific Data. - : NATURE PORTFOLIO. - 2052-4463. ; 10
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Journal article (other academic/artistic)abstract
- The expansive production of data in materials science, their widespread sharing and repurposing requires educated support and stewardship. In order to ensure that this need helps rather than hinders scientific work, the implementation of the FAIR-data principles (Findable, Accessible, Interoperable, and Reusable) must not be too narrow. Besides, the wider materials-science community ought to agree on the strategies to tackle the challenges that are specific to its data, both from computations and experiments. In this paper, we present the result of the discussions held at the workshop on “Shared Metadata and Data Formats for Big-Data Driven Materials Science”. We start from an operative definition of metadata, and the features that a FAIR-compliant metadata schema should have. We will mainly focus on computational materials-science data and propose a constructive approach for the FAIRification of the (meta)data related to ground-state and excited-states calculations, potential-energy sampling, and generalized workflows. Finally, challenges with the FAIRification of experimental (meta)data and materials-science ontologies are presented together with an outlook of how to meet them.
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| 6. |
- Jansen, Joachim, 1989-, et al.
(author)
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Monitoring of carbon-water fluxes at Eurasian meteorological stations using random forest and remote sensing
- 2023
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In: Scientific Data. - : Springer Nature. - 2052-4463. ; 10:1
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Journal article (peer-reviewed)abstract
- Simulating the carbon-water fluxes at more widely distributed meteorological stations based on the sparsely and unevenly distributed eddy covariance flux stations is needed to accurately understand the carbon-water cycle of terrestrial ecosystems. We established a new framework consisting of machine learning, determination coefficient (R2), Euclidean distance, and remote sensing (RS), to simulate the daily net ecosystem carbon dioxide exchange (NEE) and water flux (WF) of the Eurasian meteorological stations using a random forest model or/and RS. The daily NEE and WF datasets with RS-based information (NEE-RS and WF-RS) for 3774 and 4427 meteorological stations during 2002-2020 were produced, respectively. And the daily NEE and WF datasets without RS-based information (NEE-WRS and WF-WRS) for 4667 and 6763 meteorological stations during 1983-2018 were generated, respectively. For each meteorological station, the carbon-water fluxes meet accuracy requirements and have quasi-observational properties. These four carbon-water flux datasets have great potential to improve the assessments of the ecosystem carbon-water dynamics.
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| 7. |
- Landi, Michael, et al.
(author)
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Haplotype-resolved genome of heterozygous African cassava cultivar TMEB117 (Manihot esculenta)
- 2023
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In: Scientific Data. - 2052-4463. ; 10
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Journal article (peer-reviewed)abstract
- Cassava (Manihot esculenta Crantz) is a vital tropical root crop providing essential dietary energy to over 800 million people in tropical and subtropical regions. As a climate-resilient crop, its significance grows as the human population expands. However, yield improvement faces challenges from biotic and abiotic stress and limited breeding. Advanced sequencing and assembly techniques enabled the generation of a highly accurate, nearly complete, haplotype-resolved genome of the African cassava cultivar TMEB117. It is the most accurate cassava genome sequence to date with a base-level accuracy of QV > 64, N50 > 35 Mbp, and 98.9% BUSCO completeness. Over 60% of the genome comprises repetitive elements. We predicted over 45,000 gene models for both haplotypes. This achievement offers valuable insights into the heterozygosity genome organization of the cassava genome, with improved accuracy, completeness, and phased genomes. Due to its high susceptibility to African Cassava Mosaic Virus (ACMV) infections compared to other cassava varieties, TMEB117 provides an ideal reference for studying virus resistance mechanisms, including epigenetic variations and smallRNA expressions.
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| 8. |
- Maxwell, Tania L., et al.
(author)
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Global dataset of soil organic carbon in tidal marshes
- 2023
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In: Scientific Data. - : Springer Nature. - 2052-4463. ; 10:1
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Journal article (peer-reviewed)abstract
- Tidal marshes store large amounts of organic carbon in their soils. Field data quantifying soil organic carbon (SOC) stocks provide an important resource for researchers, natural resource managers, and policy-makers working towards the protection, restoration, and valuation of these ecosystems. We collated a global dataset of tidal marsh soil organic carbon (MarSOC) from 99 studies that includes location, soil depth, site name, dry bulk density, SOC, and/or soil organic matter (SOM). The MarSOC dataset includes 17,454 data points from 2,329 unique locations, and 29 countries. We generated a general transfer function for the conversion of SOM to SOC. Using this data we estimated a median (± median absolute deviation) value of 79.2 ± 38.1 Mg SOC ha−1 in the top 30 cm and 231 ± 134 Mg SOC ha−1 in the top 1 m of tidal marsh soils globally. This data can serve as a basis for future work, and may contribute to incorporation of tidal marsh ecosystems into climate change mitigation and adaptation strategies and policies.
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| 9. |
- Ott, Simon, et al.
(author)
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ThoughtSource : A central hub for large language model reasoning data
- 2023
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In: Scientific Data. - : Springer Nature. - 2052-4463. ; 10:1
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Journal article (peer-reviewed)abstract
- Large language models (LLMs) such as GPT-4 have recently demonstrated impressive results across a wide range of tasks. LLMs are still limited, however, in that they frequently fail at complex reasoning, their reasoning processes are opaque, they are prone to 'hallucinate' facts, and there are concerns about their underlying biases. Letting models verbalize reasoning steps as natural language, a technique known as chain-of-thought prompting, has recently been proposed as a way to address some of these issues. Here we present ThoughtSource, a meta-dataset and software library for chain-of-thought (CoT) reasoning. The goal of ThoughtSource is to improve future artificial intelligence systems by facilitating qualitative understanding of CoTs, enabling empirical evaluations, and providing training data. This first release of ThoughtSource integrates seven scientific/medical, three general-domain and five math word question answering datasets.
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| 10. |
- Rodríguez-Gijón, Alejandro, 1996-, et al.
(author)
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Shotgun metagenomes from productive lakes in an urban region of Sweden
- 2023
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In: Scientific Data. - 2052-4463. ; 10
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Journal article (peer-reviewed)abstract
- Urban lakes provide multiple benefits to society while influencing life quality. Moreover, lakes and their microbiomes are sentinels of anthropogenic impact and can be used for natural resource management and planning. Here, we release original metagenomic data from several well-characterized and anthropogenically impacted eutrophic lakes in the vicinity of Stockholm (Sweden). Our goal was to collect representative microbial community samples and use shotgun sequencing to provide a broad view on microbial diversity of productive urban lakes. Our dataset has an emphasis on Lake Mälaren as a major drinking water reservoir under anthropogenic impact. This dataset includes short-read sequence data and metagenome assemblies from each of 17 samples collected from eutrophic lakes near the greater Stockholm area. We used genome-resolved metagenomics and obtained 2378 metagenome assembled genomes that de-replicated into 514 species representative genomes. This dataset adds new datapoints to previously sequenced lakes and it includes the first sequenced set of metagenomes from Lake Mälaren. Our dataset serves as a baseline for future monitoring of drinking water reservoirs and urban lakes.
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