Data in Brief

Journal: Data in Brief

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Elsevier

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2352-3409

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Publications 1 - 10 of 58

Data on Swiss grape growers’ production, pest and labour management decisions
Höper, Philipp; Zachmann, Lucca; Finger, Robert (2025)
Data in Brief
This dataset comprises survey responses from 489 grape growers in Switzerland, focusing on their decisions related to production, pest management, risk management, behavioural factors, and labour management. The online survey was conducted in early spring 2025 and includes details on grape variety selection, farm practices, and characteristics of both the farmers and their farms. Additional data covers all other relevant pest management strategies targeting weeds, insects, and fungal threats. Farmer-specific attributes such as education, gender, age, and sources of information were recorded, alongside general labour force characteristics and perceptions regarding recruitment, and mechanization. Behavioural factors including risk and time preferences, self-efficacy, and locus of control were assessed using self-report scales. Farm-level data includes marketing approaches, labels and production systems, agri-environmental programs, and pesticide application equipment. The survey responses were linked with environmental variables—such as temperature and rainfall—and spatial data on the infection risk of Oidium and Peronospora viticola. Innovatively, the data contains the adoption stage of growers (not just binary adoption) for four key pesticide-reducing practices (i.e. the plantation of fungus-resistant varieties, the use of plant resistance inducers, inorganic materials and mechanical weeding), along with their views on influencing factors and labour demands associated with these measures. This dataset provides an extensive resource for standalone analyses on production, pest management, risk management, behavioural factors, and labour management, as well as for use in meta-analyses or as part of a panel dataset combined with previous similar surveys.
Water contact angle data and FTIR data of stem cell/tenocyte co-culture-derived secretome releasing electrospun tube; and adhesion data of fully transected and sutured rabbit Achilles tendons three weeks post-operation under application of such a tube
Rieber , Julia; Miescher , Iris; Wolint , Petra; et al. (2025)
Data in Brief
Tendon ruptures may result in unsatisfactory outcomes, even after long rehabilitation programs and careful return to daily activities and sports. One major problem after a tendon rupture is the fibrotic adhesion formation to the adjacent tissue, which hampers proper motion and may end up in a permanent reduced range of motion. Following a cell-free approach, we cultivated rabbit adipose-derived stem cells (ASCs) and rabbit Achilles tenocytes in a ratio of 3:1 and incorporated the secretome harvested from this co-culture into an emulsion electrospun tubular DegraPol® fiber mesh. These tubes were characterized by thestatic and dynamic water contact angles and by FTIR spectra, with a comparison to tubes without secretome incorporation (control). Furthermore, we present adhesion data from an in vivo experiment, where these tubes were implanted around a fully transected rabbit Achilles tendon after suture at 3 weeks post-operation.
Data on DOC and N from the Muz taw glacier in Central Asia
Gao, Tanguang; Kang, Shichang; Zhang, Yulan; et al. (2020)
Data in Brief
This Data in Brief article provides a supplementary information to the dissolved organic carbon and nitrogen from the snow of Muz taw glacier in the Central Asia, which is related to the scientific article titled with “Characterization, sources and transport of dissolved organic carbon and nitrogen from a glacier in the Central Asia”[1]. Meanwhile, major ions (including Na+, K+, NH4+, Ca2+, Mg2+, Cl−, SO42−, NO3−, and NO2−) were also reported. These data were analysed using descriptive statistics such as correlations and principle component analysis. Additionally, we conducted a literature review on DOC and N concentrations for the comparison. This article also presents the analysis data of the mass absorption cross section of DOC in snow.
Zircon U-Pb geochronology and trace element dataset from the Southern Rocky Mountain Volcanic Field, Colorado, USA
Sliwinski, Jakub; Guillong, Marcel; Lipman, Peter W.; et al. (2022)
Data in Brief
This contribution provides in-situ LA-ICP-MS U-Pb ages and trace element determinations of zircons from dacitic to rhyolitic lavas, ignimbrites and intrusions in the Southern Rocky Mountain Volcanic Field (SRMVF) in Colorado, USA. The data record a period of intense magmatic activity in the Oligocene-early Miocene (∼37–22 Ma) which gave rise to some of the largest explosive ignimbrites in the geological record (e.g. the Fish Canyon Tuff). Age data are drift corrected, but not corrected for radiation dosage or Th disequilibrium, in order to allow users to apply their own algorithms. Xenocrysts (much older crystals up to 2 Ga from the Proterozoic basement) are included in this record.
Spectral data of specular reflectance, narrow-angle transmittance and angle-resolved surface scattering of materials for solar concentrators
Good, Philipp; Cooper, Thomas A.; Querci, Marco; et al. (2016)
Data in Brief
The spectral specular reflectance of conventional and novel reflective materials for solar concentrators is measured with an acceptance angle of 17.5 mrad over the wavelength range 300−2500 nm at incidence angles 15–60° using a spectroscopic goniometry system. The same experimental setup is used to determine the spectral narrow-angle transmittance of semi-transparent materials for solar collector covers at incidence angles 0–60°. In addition, the angle-resolved surface scattering of reflective materials is recorded by an area-scan CCD detector over the spectral range 350–1050 nm. A comprehensive summary, discussion, and interpretation of the results are included in the associated research article “Spectral reflectance, transmittance, and angular scattering of materials for solar concentrators” in Solar Energy Materials and Solar Cells.
Real-time fMRI data for testing OpenNFT functionality
Koush, Yury; Ashburner, John; Prilepin, Evgeny; et al. (2017)
Data in Brief
Here, we briefly describe the real-time fMRI data that is provided for testing the functionality of the open-source Python/Matlab framework for neurofeedback, termed Open NeuroFeedback Training (OpenNFT, Koush et al. [1]). The data set contains real-time fMRI runs from three anonymized participants (i.e., one neurofeedback run per participant), their structural scans and pre-selected ROIs/masks/weights. The data allows for simulating the neurofeedback experiment without an MR scanner, exploring the software functionality, and measuring data processing times on the local hardware. In accordance with the descriptions in our main article, we provide data of (1) periodically displayed (intermittent) activation-based feedback; (2) intermittent effective connectivity feedback, based on dynamic causal modeling (DCM) estimations; and (3) continuous classification-based feedback based on support-vector-machine (SVM) estimations. The data is available on our public GitHub repository: https://github.com/OpenNFT/OpenNFT_Demo/releases.
Farm-level data on production systems, farmer- and farm characteristics of apple growers in Switzerland
Zachmann, Lucca; McCallum, Chloe; Finger, Robert (2023)
Data in Brief
We here present survey data from apple growers across Switzerland. Data from 245 apple growers was collected, using an online survey in French and German in 2022. The sampled growers represent 24.4% from total land under apples. Apple production is one of the most economically relevant and pesticide intensive crops. Hence, the focus of the survey is on growers’ pest management decisions and marketing strategies. Survey data contains details on growers’ agronomic practices such as grown cultivars, pest management against fungi, insects, and weeds, as well as pesticide use for cosmetic purposes. Moreover, we collected information on pest management after harvest, i.e. storage loss strategies. Marketing characteristics include the sales channel chosen as well as labels used and contract arrangements with buyers. Moreover, detailed data about farm management strategies, behavioral factors, as well as other farm- and farmer characteristics was collected. Survey data is matched with a rich set of environmental data, i.e. precipitation, temperature, and apple scab infection risk.
HoloSelecta dataset: 10'035 GTIN-labelled product instances in vending machines for object detection of packaged products in retail environments
Fuchs, Klaus Ludwig; Grundmann, Tobias; Haldimann, Mirella; et al. (2020)
Data in Brief
To assess the potential of current neural network architectures to reliably identify packaged products within a retail environment, we created an open-source dataset of 295 shelf images of vending machines with 10'035 labelled instances of 109 products. The dataset contains photos of vending machines by the provider Selecta, the largest European operator of vending machines. The vending machines are a mix of machines in public and private office spaces. The vending machines contain food as well as beverage products. The product instances in the vending machine images are labelled with bounding boxes, where a bounding box encapsulates the entire product with as little overlap as possible. The labels corresponding to the bounding box consist of a structured, human-readable labels including brand, product name and size as well as the GTIN of the product. The GTIN is the global standard to identify products in the retail environment and therefore increases the value as a dataset for the retail industry. Contrary to typical object detection datasets that choose labels at a higher level such as a can or bottle for a much wider variety of objects, this dataset chooses a far more detailed label that depends less on the shape but rather on the exact design of the product. The dataset falls into the category of object detection datasets with a large number of objects, which next to the GTIN label, represents a main differentiator of the dataset to other object detection datasets. (C) 2020 The Authors. Published by Elsevier Inc.
Life cycle inventories of waste management processes
Haupt, Melanie; Kägi, Thomas; Hellweg, Stefanie (2018)
Data in Brief
To allow for an up-to-date and geographically specific life cycle assessment, updated and regionally specific life cycle inventories are crucial. This data article present up-to-date life cycle inventories of several collection, sorting and recycling processes of municipal solid waste fractions for life cycle assessments of waste management systems. In total, 190 life cycle inventories for processes within municipal solid waste management were either newly developed or adapted from existing datasets. The data for 51 recycling processes has been collected to update existing processes or create new process models. Two modules for biogenic processes were taken from literature and 10 processes were modeled based on the existing ecoinvent processes with minor adjustments [1]. The substitution of 36 materials from recycling processes was modeled. In addition, the thermal treatment of 12 waste fractions was modeled within 84 life cycle inventories compromising the thermal waste treatment and the recovery and recycling of recovered fractions from fly and bottom ash. The assumptions and the modelling of the waste treatment processes are described. All life cycle inventory datasets which were newly created, updated or modified compared to the original dataset are described and provided as Excel table. The data are associated with the research article "Modular Life Cycle Assessment of Municipal Solid Waste Management” [2].
Data on the existence ratio and social utility of Nash equilibria and of the Perfectly Transparent Equilibrium
Fourny, Ghislain; Sulser, Felipe (2021)
Data in Brief

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