Data in Brief最新文献

{"title":"Demand starter data kit: Selected socio-economic and technical energy system demand modelling data for all 47 counties in Kenya","authors":"Neve Fields ,&nbsp;Ariane Millot ,&nbsp;Martin Mutembei ,&nbsp;Anne Nganga ,&nbsp;Pietro Lubello ,&nbsp;Leonhard Hofbauer ,&nbsp;Mark Howells ,&nbsp;Ed Brown","doi":"10.1016/j.dib.2025.111556","DOIUrl":"10.1016/j.dib.2025.111556","url":null,"abstract":"<div><div>The need for data-driven models to inform energy planning and policy making is increasingly important as Kenya looks to transform its energy system to be clean, efficient, diverse and secure. Modelling softwares can be used by policy makers to assess the impacts of different scenarios on energy systems to support planning and decision making. Demand forms an integral foundation of energy planning and insights into possible projections can aid in policy creation, yet access to data is often a barrier to utilising energy demand modelling to support such decision making. Despite the official launch of the energy governance devolution process within Kenya, through the Kenya Energy Act (2019), progress towards county energy planning and developing modelling data and tools to reflect this remains limited and inaccessible. Therefore, this article provides data that can be used to create a simple whole energy system demand model for the individual counties in Kenya, acting as a starting point for teaching, capacity building efforts, and for further data collection, model development and scenario analysis to produce county resolution demand projections. The data was collected from websites, annual reports, and databases of international and national organisations alongside existing modelling databases and academic articles and can be easily updated based on the latest available local data and information. As a demonstration, these data were used to calibrate a demand model for Kilifi County using the Model for the Analysis of Energy Demand (MAED) for a baseline scenario from 2019 to 2070. The assumptions used and results gained are illustrated in the appendix of the article as a demonstration of what can be achieved through application of this dataset.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111556"},"PeriodicalIF":1.0,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143870544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dataset of benthic foraminiferal community structure from sediment eDNA of Sundarbans mangrove ecosystem","authors":"Arkaprava Mandal,&nbsp;Anwesha Ghosh,&nbsp;Gauraw Kumar,&nbsp;Punyasloke Bhadury","doi":"10.1016/j.dib.2025.111554","DOIUrl":"10.1016/j.dib.2025.111554","url":null,"abstract":"<div><div>Sundarbans, the world's largest contiguous mangrove wetland, a UNESCO World Heritage Site and a RAMSAR site formed on the delta of Ganga-Brahmaputra-Meghna (GBM) and influenced by coastal water entering from the Bay of Bengal contribute immensely to biodiversity and blue economy. To track the changes driven by natural and anthropogenic stressors, sediment based environmental DNA (eDNA) biomonitoring of benthic foraminifera communities, an important biological group sensitive to changes, has been initiated along with estimation of dissolved nutrients from estuarine surface water of Sundarbans. In pre-monsoon of 2022 (June), sediment cores and surface water were collected as well as <em>in situ</em> environmental parameters were measured from two pre-designated sampling points of Sundarbans to elucidate the benthic foraminifera community based on sediment eDNA approach. Based on Oxford Nanopore Technologies (ONT) sequencing in MinION platform, high abundance of <em>Sorites</em> sp., <em>Elphidium excavatum, Textularia gramen, Quinqueloculina</em> sp. and <em>Trochammina hadai</em> were detected. The increasing nutrient concentrations and elucidated benthic foraminiferal signals can contribute towards tracking the state of ecological health of Sundarbans. This study is aimed at generating baseline information on mangrove benthic foraminifera communities using sediment eDNA based high-throughput sequencing.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111554"},"PeriodicalIF":1.0,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143864829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metabolomic datasets of an apple progeny carrying resistance quantitative trait loci to apple scab before or after inoculation of the pathogen Venturia inaequalis","authors":"Romane Lapous ,&nbsp;Florent Magot ,&nbsp;Romain Larbat ,&nbsp;Caroline Denancé ,&nbsp;Christian Cattanéo ,&nbsp;Hélène Muranty ,&nbsp;Charles-Eric Durel ,&nbsp;Julie Ferreira de Carvalho","doi":"10.1016/j.dib.2025.111566","DOIUrl":"10.1016/j.dib.2025.111566","url":null,"abstract":"<div><div>Phytosanitary treatments are massively used in orchards to fight apple scab, a disease caused by the fungus <em>Venturia inaequalis</em> (<em>Vi</em>). To reduce these treatments, resistant varieties are largely deployed but their effectiveness can decrease over time. The combination of complementary molecular mechanisms within new varieties could enhance the durability of genetic resistance however, the underlying resistance mechanisms remain poorly understood. An apple pseudo-F1 progeny was previously widely investigated for its quantitative trait loci (QTL) controlling resistance to scab and at least three of them seem to act complementarily; notably, one of them is specific to some <em>Vi</em> isolates while the others have a broader spectra of action. The aim of this approach is to better understand the underlying molecular mechanisms and metabolites associated with resistance alleles by exploring apple leaf specialized metabolism. A total of three experiments was conducted: one experiment included non-inoculated leaves whereas in the two other experiments, leaf samples were collected five days after inoculation with two different <em>Vi</em> isolates, including one known to overcome one QTL. Metabolic content was extracted in aqueous methanol before performing an untargeted metabolomic analysis using an Orbitrap IDX^TM mass spectrometer, allowing high-resolution mass spectrometry (HRMS) detection. This approach without <em>a priori</em> enables the detection of potentially new chemical families involved in resistance to apple scab. The current data article includes 1) the protocol of plant sample production with a table summarizing key elements of the experimental designs, 2) overview of the raw metabolomic profiles from all three experiments and 3) assessment of metabolic feature reproducibility between replicates in each dataset through Principal Component Analysis. The raw data files are available on the recherche.data.gouv repository (10.57745/XJBD8V). These datasets are valuable resources to further investigate the molecular mechanisms underlying genetic resistance to apple scab, with a focus on specialized metabolism. In the long term, it should improve apple breeding strategies by informing on how to combine appropriate genetic and biochemical factors in new varieties to ensure a more durable resistance.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111566"},"PeriodicalIF":1.0,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143864830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating datasets to dissect NFYC-AS1 RNA- and transcription-dependent functions: comparative transcriptome profiling of knockdown strategies","authors":"Giulia Pagani ,&nbsp;Cecilia Pandini ,&nbsp;Martina Tassinari,&nbsp;Paolo Gandellini","doi":"10.1016/j.dib.2025.111565","DOIUrl":"10.1016/j.dib.2025.111565","url":null,"abstract":"<div><div>The recent discovery of antisense RNAs (asRNAs) as key regulators of biological processes has highlighted the need to challenge their mechanism(s) of action using complementary approaches. Indeed, asRNAs can act <em>in cis</em> on their sense gene or <em>in trans</em> on distally located targets, by exploiting either transcription- or RNA-dependent mechanisms. Here we present a comparative transcriptome profiling of cancer cells knocked-down for the asRNA <em>NFYC-AS1</em> with two different approaches: i) Gapmer Antisense Oligonucleotides to assess RNA-dependent mechanisms, and ii) CRISPR/Cas9 deletion of the transcription start site to study transcription-dependent mechanisms. We describe in detail the strategies used to silence the asRNA and evaluate the consequences at the transcriptome level by RNA-sequencing. Moreover, we outline the analyses conducted to correctly manage the variability across replicates and the off-target effects of either method. The integration of the obtained datasets revealed commonalities and divergencies of the two approaches, which was fundamental for dissecting <em>NFYC-AS1</em> function. The information reported here can help researchers to reuse the data described in the datasets. Finally, the comparative workflow can be potentially applied to the functional study of any asRNA of interest.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111565"},"PeriodicalIF":1.0,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143864705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A comprehensive image dataset of Bangladeshi mango variety","authors":"Rup Kumar Bharati ,&nbsp;Md. Masudul Islam ,&nbsp;Md Ripon Sheikh ,&nbsp;Galib Muhammad Shahriar Himel","doi":"10.1016/j.dib.2025.111560","DOIUrl":"10.1016/j.dib.2025.111560","url":null,"abstract":"<div><div>This data article presents a primary dataset collected from various locations in Bangladesh, featuring 10 different mango varieties that are mostly consumed locally. This mango dataset includes the following types: Amrapali, Bari-4, Bari-7, Fazlee, Harivanga, Kanchon Langra, Katimon, Langra, Mollika, and Nilambori. A DSLR camera was used to take high-resolution pictures of every mango variety; as a consequence, 2012 photographs were obtained, although the distribution of images among types is not uniform. This dataset, which provides a thorough representation of 10 distinct mango types, each with a distinct flavour, has a great deal of potential for impact and application. It offers a range of uses in the food production and agriculture sectors and offers insightful information for further study and development.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111560"},"PeriodicalIF":1.0,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143870692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A dataset on forest stand structures, deadwood, and tree-related microhabitats along an urban-periurban gradient in Central Italy","authors":"Costanza Borghi ,&nbsp;Soraya Versace ,&nbsp;Elena Di Pirro ,&nbsp;Davide Travaglini ,&nbsp;Gherardo Chirici ,&nbsp;Bruno Lasserre ,&nbsp;Marco Marchetti ,&nbsp;Giovanni D’Amico ,&nbsp;Elia Vangi ,&nbsp;Saverio Francini ,&nbsp;Marco Montella ,&nbsp;Giovanni Santopuoli ,&nbsp;Marco Ottaviano ,&nbsp;Francesco Parisi","doi":"10.1016/j.dib.2025.111561","DOIUrl":"10.1016/j.dib.2025.111561","url":null,"abstract":"<div><div>This database provides accessible and georeferenced information on forest structure, tree-related microhabitats, and deadwood of 12 urban forests located in 12 different urban parks across three Italian cities, Florence, Rome, and Campobasso. Four urban parks – varying in size, forest type, and history – were selected following an urban-periurban gradient in each city. Inner city parks are typically ancient, with native and non-native trees planted for aesthetic and cultural purposes, and scarce semi-natural vegetation remains. Periurban parks usually host native and semi-natural vegetation and may include agricultural areas. 15 plots were placed to survey a selected urban forest located in each of the 12 urban parks, using a systematic aligned sampling scheme and then visited in the field, for a total of 180 plots. The collected data contributed to the construction of three different datasets. Two tree-level datasets present information on tree-related microhabitats and dendrometric variables including tree species, diameter at breast height, tree height, height-to-base of the live crown, tree volume, and tree basal area. The deadwood dataset presents information on five categories of deadwood, particularly snags, standing dead trees, coarse woody debris, stumps, and dead downed trees, where height, diameter, and decay status were sampled. Other research can employ these data to integrate and compare databases from different cities and forest types. Additionally, data can be linked to future analyses of urban forest fauna (e.g., beetle and bird communities) and updated to assess variability over time as well as employed in landscape analysis to guide improved management actions.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111561"},"PeriodicalIF":1.0,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143870540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"UGV-NBWASTE: An oriented dataset for non-biodegradable waste in Bangladesh","authors":"Md. Riadul Isalm ,&nbsp;Nabil Bin Mahabub ,&nbsp;Md. Jubayar Alam Rafi ,&nbsp;Pronoy Kanti Roy ,&nbsp;Turjo Roy ,&nbsp;Md. Tariqul Islam ,&nbsp;Md. Abdur Razzak","doi":"10.1016/j.dib.2025.111559","DOIUrl":"10.1016/j.dib.2025.111559","url":null,"abstract":"<div><div>The “UGV-NBWASTE” dataset is built for those who manage non-biodegradable waste. The selection of non-biodegradable waste has been decided on adverse environmental conditions, particularly waste management in landfills and water. The dataset is collected from the Barisal district of Bangladesh, where eight distinct types of waste (Plastic Bottle, Hard Plastic, Mask, Medicine Packet, Packet, Polythene, Cocksheet, and Plastic Sandal) are selected based on their widespread use, durability, and difficulty in recycling or managing them via conventional waste disposal methods. Furthermore, waste images are captured using smartphones in indoor and outdoor situations, such as floating in water or partially buried in the mud, which is crucial to diversifying the dataset for effective detection and classification. After data collection, various techniques are applied during the image pre-processing stage to significantly improve the quality of the original images. These include Image Quality Assurance (i.e., image verification and image cleaning) and Image Enhancement (i.e., brightness normalization and image resizing). Then, all images are annotated in oriented bounding box (OBB) format, ensuring waste detection at different angles. The total number of original images is 3600. Waste can be reliably identified whether it is flat, crumpled, or partially obscured, which guarantees the dataset's ability to identify waste in different circumstances and orientations.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111559"},"PeriodicalIF":1.0,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143870542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The mechanomyographic dataset of hand gestures harvested using an accelerometer and gyroscope","authors":"Khalid A. Abbas ,&nbsp;Mofeed Turky Rashid ,&nbsp;Luigi Fortuna","doi":"10.1016/j.dib.2025.111558","DOIUrl":"10.1016/j.dib.2025.111558","url":null,"abstract":"<div><div>Mechanomyography (MMG) datasets are crucial due to their unique characteristics, non-invasive techniques, fewer required sensors, improved signal-to-noise ratio, lightweight equipment, and no need for skin preparation, unlike some other techniques. This paper introduces a mechanomyography (MMG) signal dataset intended for application in human-computer interaction (HCI) research. The dataset is obtained from integrated sensor data, capturing mechanical signals from muscle activity via the accelerometer, augmented by the gyroscope for motion analysis. The dataset comprises 6-axis accelerometer and gyroscope data from 43 participants, ranging in age from 18 to 69 years, exhibiting a male-to-female distribution of 60 % to 40 % respectively. The dataset includes the following 11 gestures: clapping, coin flipping, finger snapping, fist making, horizontal wrist extension, index finger flicking, index thumb tapping, shooting, thumb up, wrist extension, and wrist flexion. A novel, assembled, and manufactured wearable system collected data from the main muscles that end at the wrist, just below the watch strap. These muscles include flexors and extensors, which work together to move the wrist and fingers when making the hand gestures listed above. Every participant completed a total of fifty repetitions for each of the eleven hand motions, resulting in 550 samples per subject. Before recording the signals, a demographic survey with the participants is conducted. Researchers focusing on classification, recognition, and prediction can use the gathered data to develop MMG-based hand motion controller systems. The collected data can also serve as a reference for developing a model using artificial intelligence (e.g., a deep learning or machine learning model) that is capable of identifying gesture-related MMG signals. It is suggested that the proposed dataset is used to evaluate existing datasets in the literature or to validate artificial intelligence models developed with alternative datasets through the participant-independent evaluation approach. This dataset can be useful in a variety of applications and fields, including interaction between humans and robots, gaming, assistive technology, healthcare observation, and sports analytics, to name a few specific examples.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111558"},"PeriodicalIF":1.0,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143854738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reference framework for metadata description to commensurate data in grain production","authors":"Katariina Pussi ,&nbsp;Petri Linna ,&nbsp;Pasi Suomi ,&nbsp;Kim Kaustell ,&nbsp;Liisa Pesonen","doi":"10.1016/j.dib.2025.111557","DOIUrl":"10.1016/j.dib.2025.111557","url":null,"abstract":"<div><div>Data spaces will bring the need to harmonize the farm collected data for better interoperability. Attention needs also to be paid to data accessibility, since the value of data is strongly linked to its use. The evolving data space technologies will bring service providers that help farmers to translate farm born datasets to data products that can have measurable value. Data products can then be published to the data space catalog, allowing other people to discover and consume them. Data used for data products, decision-making, reporting, or analysis should be reliable and trustworthy. Common metadata standards, catalogs and ontologies will help to achieve this goal. The scope of this paper is to discuss requirements for metadata in grain production.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111557"},"PeriodicalIF":1.0,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143870693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ShrimpDiseaseBD: An image dataset for detecting shrimp diseases in the aquaculture sector of Bangladesh","authors":"Mohammad Manzurul Islam,&nbsp;Anabil Sarker,&nbsp;Ashiquzzaman Choudhury,&nbsp;Noortaz Ahmed,&nbsp;Ahmed Abdal Shafi,&nbsp;Nishat Tasnim Niloy,&nbsp;Md Shorif Hossain,&nbsp;Md Sawkat Ali,&nbsp;Abdullahi Chowdhury,&nbsp;Md. Hasanul Ferdaus","doi":"10.1016/j.dib.2025.111553","DOIUrl":"10.1016/j.dib.2025.111553","url":null,"abstract":"<div><div>Shrimp farming is a significant contributor to Bangladesh's economy, providing livelihoods for millions of people in coastal areas. However, the shrimp industry faces challenges from prevalent shrimp diseases, which can disrupt the economy and harm the environment. Detecting these diseases early and effectively is crucial. To address this concern, a dataset has been developed containing images of healthy and diseased shrimp of different types. The images were collected from local shrimp farms under expert supervision using high-quality smartphone cameras. The dataset includes 1149 original images, with diseased shrimp images annotated to improve detection capabilities. This dataset is expected to be valuable for detecting shrimp diseases with precision and timing and is likely to encourage research and practical applications in automated shrimp health monitoring. It will also be a valuable resource for computer vision and aquaculture researchers.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"60 ","pages":"Article 111553"},"PeriodicalIF":1.0,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143864706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}