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.
1,019
datasets available to search
ShareScore release 0.7.1
Dataset results
1,019 results for “Assignment”
Output dataset for the PRA1 of Assignment 'Tipología y ciclo de vida de los datos' of UOC's Master in Data Scince
<p>Dataset containing the concatenation of the results of a web scraping process for the portals of Idealista and Fotocasa for the area of Vilanova i la Geltrú, Barcelona, compiled on on 2022-04-19 and 2022-04-25 respectively. </p>
Data from: Assigning harvested waterfowl to geographic origin using feather δ2H isoscapes: What is the best analytical approach?
<p class="MsoListParagraph">Establishing links between breeding, stopover, and wintering sites for migratory species is important for their effective conservation and management. Isotopic assignment methods used to create these connections rely on the use of predictable, established relationships between the isotopic composition of environmental hydrogen and that of the non-exchangeable hydrogen in animal tissues, often in the form of a calibration equation relating feather (<em>δ</em><sup>2</sup>H<sub>f</sub>) values derived from known-origin individuals and amount-weighted long-term precipitation (<em>δ</em><sup>2</sup>H<sub>p</sub>) data. The efficacy of assigning waterfowl to moult origin using stable isotopes depends on the accuracy of these relationships and their statistical uncertainty. Most current calibrations for terrestrial species in North America are done using amount-weighted mean growing-season <em>δ</em><sup>2</sup>H<sub>p</sub> values, but the calibration relationship is less clear for aquatic and semi-aquatic species. Our objective was to critically evaluate current methods used to calibrate <em>δ</em><sup>2</sup>H<sub>p</sub> isoscapes to predicted <em>δ</em><sup>2</sup>H<sub>f</sub> values for waterfowl. Specifically, we evaluated the strength of the relationships between <em>δ</em><sup>2</sup>H<sub>p</sub> values from three commonly used isoscapes and known-origin <em>δ</em><sup>2</sup>H<sub>f</sub> values from three published and one collected as part of this study, also grouping these data into foraging guilds (dabbling vs diving ducks). </p>
Data from: Two complementary AI approaches for predicting UMLS semantic group assignment: heuristic reasoning and deep learning
<p><strong>Objective</strong>: Use heuristic, deep learning (DL), and hybrid AI methods to predict semantic group (SG) assignments for new UMLS Metathesaurus atoms, with target accuracy ≥ 95%.</p> <p><strong>Materials and Methods</strong>: We used train-test datasets from successive 2020AA-2022AB UMLS Metathesaurus releases. Our heuristic "waterfall" approach employed a sequence of seven different SG prediction methods. Atoms not qualifying for a method were passed on to the next method. The DL approach generated BioWordVec and SapBERT embeddings for atom names, BioWordVec embeddings for source vocabulary names, and BioWordVec embeddings for atom names of the second-to-top nodes of an atom's source hierarchy. We fed a concatenation of the four embeddings into a fully connected multi-layer neural network with an output layer of 15 nodes (one for each SG). Both methods were capable of estimating the probability that their predicted SG for an atom would be correct. We developed two hybrid SG prediction methods combining the strengths of heuristic and DL methods.</p> <p><strong>Results</strong>: The heuristic waterfall approach accurately predicted 94.3% of SGs for 1,563,692 new unseen atoms. The DL accuracy on the same dataset was also 94.3%. The hybrid approaches achieved an average accuracy of 96.5%.</p> <p><strong>Conclusion</strong>: Our study demonstrated that AI methods can predict SG assignments for new UMLS atoms with sufficient accuracy to be potentially useful as an intermediate step in the time-consuming task of assigning new atoms to UMLS concepts (CUIs). We showed that for SG prediction, combining heuristic methods and DL methods can produce better results than either alone.</p>
Low-coverage whole genome sequencing for highly accurate population assignment: Mapping migratory connectivity in the American Redstart (Setophaga ruticilla)
<p>Understanding the geographic linkages among populations across the annual cycle is an essential component for understanding the ecology and evolution of migratory species and for facilitating their effective conservation. While genetic markers have been widely applied to describe migratory connections, the rapid development of new sequencing methods, such as low-coverage whole genome sequencing (lcWGS), provides new opportunities for improved estimates of migratory connectivity. Here, we use lcWGS to identify fine-scale population structure in a widespread songbird, the American Redstart (<em>Setophaga</em> <em>ruticilla</em>), and accurately assign individuals to genetically distinct breeding populations. Assignment of individuals from the nonbreeding range reveals population-specific patterns of varying migratory connectivity. By combining migratory connectivity results with demographic analysis of population abundance and trends, we consider full annual cycle conservation strategies for preserving numbers of individuals and genetic diversity. Notably, we highlight the importance of the Northern Temperate-Greater Antilles migratory population as containing the largest proportion of individuals in the species. Finally, we highlight valuable considerations for other population assignment studies aimed at using lcWGS. Our results have broad implications for improving our understanding of the ecology and evolution of migratory species through conservation genomics approaches.</p>
Adherence Interventions for HIV Youth Via Text & Cell Phone - Sequential Multiple Assignment Randomized Trial (SMART)
ClinicalTrials.gov study NCT03535337. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Random Assignment of Intervention Messages for Developing Personalized Decision Rules to Promote Physical Activity
ClinicalTrials.gov study NCT03907683. IPD Sharing: NO. Countries: 1. Publications: 1.
A Placebo-Controlled Adaptive Treatment Assignment Study of Intravenous COL-144 in the Acute Treatment of Migraine
ClinicalTrials.gov study NCT00384774. IPD Sharing: YES. Countries: 3. Publications: 2.
Sequential Multiple Assignment Treatment for Bipolar Disorder
ClinicalTrials.gov study NCT01588457. IPD Sharing: Not stated. Countries: 1. Publications: 1.
General principles for assignments of communities from eDNA: Open versus closed taxonomic databases
Open the record for dataset details and reuse information.
Data from: Inferring the timing of long-distance dispersal between Rail metapopulations using genetic and isotopic assignments
Open the record for dataset details and reuse information.
Data from: Validating dispersal distances inferred from autoregressive occupancy models with genetic parentage assignments
Open the record for dataset details and reuse information.
Development of a SNP panel for geographic assignment and population monitoring of jaguars (Panthera onca)
Open the record for dataset details and reuse information.
Population assignment tests uncover rare long-distance larval dispersal events
Open the record for dataset details and reuse information.
Data from: Population genomics and morphometric assignment of western honey bees (Apis mellifera L.) in the Republic of South Africa
Open the record for dataset details and reuse information.
Data from: Assigning harvested waterfowl to geographic origin using feather δ2H isoscapes: What is the best analytical approach?
Open the record for dataset details and reuse information.
Data from: Double-digest RAD sequencing outperforms microsatellite loci at assigning paternity and estimating relatedness: a proof of concept in a highly promiscuous bird
Open the record for dataset details and reuse information.
Data from: Two complementary AI approaches for predicting UMLS semantic group assignment: heuristic reasoning and deep learning
Open the record for dataset details and reuse information.
Low-coverage whole genome sequencing for highly accurate population assignment: Mapping migratory connectivity in the American Redstart (Setophaga ruticilla)
Open the record for dataset details and reuse information.
Genetic assignment of individuals to source populations using network estimation tools
Open the record for dataset details and reuse information.
The TCR assigns naive T cells to a preferred lymph node
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.