Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
8
datasets available to search
ShareScore release 0.7.1
Dataset results
8 results for “Aesthetic values”
Dataset and code for submission of "Aesthetic values predict bird trade, but the association varies across product types and trade regions"
<p>Data and code used for analyses in the manuscript titled "Aesthetic values predict bird trade, but the association varies across product types and trade regions". The raw data files are given as .xlsx files for the trade data ("birdtrade_data_clean.xlsx" & "EU_birdtrade_data_clean.xlsx"), as a .csv file ("iratebirds_data_151122.csv") for the aeshtetic value data. and all final merged datasets used in the analysis and figure codes are given as .RData -files. All code is given as .R files.<br><br>The data descriptor is currently given in the submitted manuscript and it's supplements, and will be added here too in more detail upon acceptance of the manuscript.</p>
Quantitative dissection of color patterning in the foliar ornamental Coleus reveals underlying features driving aesthetic value
<p>readMe.txt (this file) /Coleus_scans.zip: This directory contains 3 sub-directories:</p> <p>1. raw_scans: Raw scans of coleus leaves. Data collection described below.</p> <p>2. binary_leaves: A zip file of individual binary leaves isolated from the raw scans. Data processing described below.</p> <p>3. colored_leaves: A zip file of individual colored leaves isolated from the raw scans using the binary leaf silhouettes. Data processing described below.</p> <p>Data collection</p> <p>Coleus leaf scans were collected from a starting population of 50,000 seedlings that were originally harvested from 133 open-pollinated mother plants in early January in Gainesville, FL. We organized the seedlings into families based on their maternal parents, grew the plants for five weeks and then selected ~2,000 individuals as potential new cultivars based on their foliar color patterning and branching architecture in mid-February. This data represents the youngest fully expanded leaf from each plant between 5-6 weeks of age. Leaves were imaged on Epson Perfection V550 Scanners with Kodak KOCSGS color separation guides included for color calibration. Analysis App Color analysis can be performed using an open-access software program called ColourQuant (Li et al., 2019); available on github: github.com/maoli0923/ColourQuant).</p> <p>Explanation of isolated binary and colored leaf files</p> <p>To isolate individual leaves from the raw data scans - we adjusted the RGB color balance on each scan by a white balance method so that the white swatch in the Kodak KOCSGS color separation guide is pure white, to ensure that scanners were not biasing the color data. Next, we segmented the leaves from the background by converting the RGB matrix into hue-saturation-value (HSV) format. Since most background pixels become grey in HSV, this was used to set a threshold that separates grey values from true leaf values. We then used the binary leaf silhouettes to extract the individual colored leaves by setting the background to pure white, and the foreground to pure black. We manually adjusted the thresholding for leaves that could not be automatically extracted due to shadows in the scan. The binary and colored leaf folder contain outliers, including leaves that were overlapping on the scanner, very small, or broken. These can be manually removed before analysis. </p> <p>File ID Key</p> <p>Files are named with the following code: Year_Family_Scan#. Files containing selected leaves for cultivar development are prepended with an “S” and files containing maternal leaf scans are prepended with an “M.”</p> <p>For questions regarding released dataset contact: Margaret Frank mhf47@cornell.edu</p> <p><br> Li, M., Frank, M.H., and Migicovsky, Z.. 2019a. ColourQuant: A high throughput technique to extract and quantify colour phenotypes from plant images. arXiv 190301652. http://arxiv.org/abs/1903.01652</p>
Wildlife trade targets colourful birds and threatens the aesthetic value of nature
<p>Data to support findings of the paper "Wildlife trade targets colourful birds and threatens the aesthetic value of nature". Code available on <a href="https://github.com/rasenior/colour-trade">GitHub</a> and also the related Zenodo entry at DOI:10.5281/zenodo.6577817</p>
Resources for studying the aesthetic and diversity values of plants and pets in shaping biodiversity loss belief among urban residents
<p><span>Considering the issues of data transparency and the cost of reproduction, all data and code snippets of the study titled "From beauty to belief: The aesthetic and diversity values of plants and pets in shaping biodiversity loss belief among urban residents" are deposited here.</span></p>
Species diversity and composition drive the aesthetic value of coral reef fish assemblages
Open the record for dataset details and reuse information.
Data from: Using virtual reality to estimate aesthetic values of coral reefs
Aesthetic value, or beauty, is important to the relationship between humans and natural environments and is, therefore, a fundamental socioeconomic attribute of conservation alongside other ecosystem services. However, beauty is difficult to quantify and is not estimated well using traditional approaches to monitoring coral reef aesthetics. To improve the estimation of ecosystem aesthetic values, we developed and implemented a novel framework used to quantify features of coral reef aesthetics based on people's perceptions of beauty. Three observer groups with different experience to reef environments (Marine Scientist, Experienced Diver and Citizen) were virtually immersed in Australian's Great Barrier Reef using 360-degree images. Perceptions of beauty and observations were used to assess the importance of eight potential attributes of reef aesthetic value. Among these, heterogeneity, defined by structural complexity and colour diversity, was positively associated with coral-reef aesthetic values. There were no group-level differences in the way the observer groups perceived reef aesthetics suggesting that past experiences with coral reefs do not necessarily influence the perception of beauty by the observer. The framework developed here provides a generic tool to help identify indicators of aesthetic value applicable to a wide variety of natural systems. The ability to estimate aesthetic values robustly adds an important dimension to the holistic conservation of the Great Barrier Reef, coral reefs worldwide, and other natural ecosystems.
Data from: Using virtual reality to estimate aesthetic values of coral reefs
Open the record for dataset details and reuse information.
Wildlife trade targets colourful birds and threatens the aesthetic value of nature
<p>Additional supplementary material (two figures, 1 table) to support findings of the paper "Wildlife trade targets colourful birds and threatens the aesthetic value of nature".</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.