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.
67
datasets available to search
ShareScore release 0.9.0
Dataset results
67 results for “expertise”
fMRI dataset on program comprehension and expertise
Open the record for dataset details and reuse information.
Software Developer Expertise GitHub and Stack Overflow data sets
<p>Cross-Platform Software Developer Expertise Learning by Norbert Eke</p> <p>This data set is part of my Master's thesis project on developer expertise learning by mining Stack Overflow (SOTorrent) and Github (GHTorrent) data. Check out my portfolio website at norberte.github.io</p>
Developer Expertise Dataset on JavaScript Libraries
<p>This dataset contains an anonymized list of surveyed developers who provided their expertise level on three popular JavaScript libraries:</p> <ol> <li><a href="https://github.com/facebook/react">ReactJS</a>, a library for building enriched web interfaces </li> <li><a href="https://github.com/mongodb/node-mongodb-native">MongoDB</a>, a driver for accessing MongoDB databased </li> <li><a href="https://github.com/socketio/socket.io">Socket.IO</a>, a library for realtime communication </li> </ol>
The influence of art expertise and training on emotion and preference ratings for representational and abstract artworks.
<p>Across cultures and throughout recorded history, humans have produced visual art. This raises the question of why people report such an emotional response to artworks and find some works more beautiful or compelling than others. In the current study we investigated the interplay between art expertise, and emotional and preference judgments. Sixty participants (40 novices, 20 art experts) rated a set of 150 abstract artworks and portraits during two occasions: in a laboratory setting and in a museum. Before commencing their second session, half of the art novices received a brief training on stylistic and art historical aspects of abstract art and portraiture. Results showed that art experts rated the artworks higher than novices on aesthetic facets (beauty and wanting), but no group differences were observed on affective evaluations (valence and arousal). The training session made a small effect on ratings of preference compared to the non-trained group of novices. Overall, these findings are consistent with the idea that affective components of art appreciation are less driven by expertise and largely consistent across observers, while more cognitive aspects of aesthetic viewing depend on viewer characteristics such as art expertise.</p>
Replication Package for ICSE'21 paper - Representation of Developer Expertise in Open Source Software
<p>Replication package for ICSE'21 paper: Representation of Developer Expertise in Open Source Software.</p> <p>See README for details.</p>
Deep learning models challenge the prevailing assumption that face-like effects for objects of expertise support domain-general mechanisms
<p>The question of whether perceptual expertise is mediated by general-expert or domain-specific processing mechanisms has been debated for decades. Because humans are experts in face recognition, face-like neural and cognitive effects for objects of expertise were considered to support for the general-expertise hypothesis. Conversely, stronger effects for faces than objects of expertise were considered to support the domain-specific hypothesis. However, the effects of domain, experience, and level of categorization, are confounded in human studies, which may lead to erroneous inferences. To overcome these limitations, we used computational models of perceptual expertise and tested different domains (objects, faces, birds) and levels of categorization (basic, sub-ordinate, individual) in isolation, matched for amount of experience. Like humans, the models generated a larger inversion effect for faces than for objects. Importantly, a face-like inversion effect was found for individual-based categorization of non-faces (birds) but only in a network specialized for that domain. Thus, contrary to prevalent assumptions, face-like effects in objects of expertise may originate from domain-specific rather than domain-general processing mechanisms. More generally, we show how deep learning algorithms can be used to isolate the effects of factors that are inherently confounded in the natural environment of biological organisms.</p>
Deep learning models challenge the prevailing assumption that face-like effects for objects of expertise support domain-general mechanisms
Open the record for dataset details and reuse information.
Data for Manuscript "Changes in P300 Latency and Amplitude Reflect Expertise Acquisition in a Football Visuomotor Learning Task"
<p>Open-access data for the manuscript "Changes in P300 Latency and Amplitude Reflect Expertise Acquisition in a Football Visuomotor Learning Task". Includes:</p> <p>Grand Average dEEG file containing data from all days and all conditions. .csv file outputs used for all analyses. .rmd file detailing the statistical workflow used to obtain the stats presented in the manuscript.</p>
Figure 1 in George Lyell and Frederick Parkhurst Dodd: authority and expertise in nineteenth-century Australian entomology
Figure 1. George Lyell as a young man.
Figure 4 in George Lyell and Frederick Parkhurst Dodd: authority and expertise in nineteenth-century Australian entomology
Figure 4. Aenetus mirabilis Rothschild (female).
Figure 2 in George Lyell and Frederick Parkhurst Dodd: authority and expertise in nineteenth-century Australian entomology
Figure 2. Dudgeonea actinias Turner.
Figure 3 in George Lyell and Frederick Parkhurst Dodd: authority and expertise in nineteenth-century Australian entomology
Figure 3. Seven specimens of Dudgeonea actinias Turner.
Figure 5. F. P in George Lyell and Frederick Parkhurst Dodd: authority and expertise in nineteenth-century Australian entomology
Figure 5. F. P. Dodd in his garden at Kuranda. Image courtesy of Queensland Museum.
Towards a Theory of Software Development Expertise — Supplementary Material
<p>Software development includes diverse tasks such as implementing new features, analyzing requirements, and fixing bugs. Being an expert in those tasks requires a certain set of skills, knowledge, and experience. Several studies investigated individual aspects of software development expertise, but what is missing is a comprehensive theory. We present a first conceptual theory of software development expertise that is grounded in data from a mixed-methods survey with 335 software developers and in literature on expertise and expert performance. Our theory currently focuses on programming, but already provides valuable insights for researchers, developers, and employers. The theory describes important properties of software development expertise and which factors foster or hinder its formation, including how developers' performance may decline over time. Moreover, our quantitative results show that developers' expertise self-assessments are context-dependent and that experience is not necessarily related to expertise.</p>
Expertise-Driven Semi-Quantitative Analysis for Policy Evaluation tool
<p>This dataset contains the underlying data for the following publication: <strong>A semi-quantitative modelling application for assessing energy efficiency strategies, Applied Soft Computing. </strong></p>
Is reputation on Stack Overflow always a good indicator for users' expertise? No!
<p>Dataset for RQ1 and RQ2. </p>
Data from: The role of taxonomic expertise in interpretation of metabarcoding studies
<p>The performance of DNA metabarcoding approaches for characterizing biodiversity can be influenced by multiple factors. Here we used morphological assessment of taxa in zooplankton samples to develop a large barcode database and to assess the congruence of taxonomic identification with metabarcoding under different conditions. We analyzed taxonomic assignment of metabarcoded samples using two genetic markers (COI, 18S V1-2), two types of clustering into molecular operational taxonomic units (OTUs, ZOTUs), and three methods for taxonomic assignment (RDP Classifier, BLASTn to GenBank, BLASTn to a local barcode database). The local database includes 1042 COI and 1108 18S (SSU) barcode sequences, and we added new high-quality sequences to GenBank for both markers, including 109 contributions at the species level. The number of phyla detected and the number of taxa identified to phylum varied between genetic marker and among the three methods used for taxonomic assignments. Blasting the metabarcodes to the local database generated multiple unique contributions to identify OTUs and ZOTUs. We argue that a multi-marker approach combined with taxonomic expertise to develop a curated, vouchered, local barcode database increases taxon detection with metabarcoding, and its potential as a tool for zooplankton biodiversity surveys.</p>
EASE TRICUSPID Expertise-based Assessment Study on Clinical Efficacy of Contour 3D® in TRICUSPID Valve Annuloplasty
ClinicalTrials.gov study NCT01532921. IPD Sharing: NO. Countries: 3. Publications: 1.
Surmounting the ceiling effect of motor expertise by novel sensory experience with a hand exoskeleton
Open the record for dataset details and reuse information.
Data from: The role of taxonomic expertise in interpretation of metabarcoding studies
Open the record for dataset details and reuse information.
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.