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.
10,553
datasets available to search
ShareScore release 0.7.1
Dataset results
10,553 results for “measurements”
Coseismic Surface Ruptures of 20 Strike-Slip Earthquakes Measured from Geodetic Imaging Data
<p>Coseismic surface displacement maps for 20 strike-slip surface rupturing earthquakes measured from radar and optical pixel tracking data. </p> <p>This dataset contains 2D and 3D surface displacement maps, fault traces, total fault-parallel slip measured from the surface displacement maps, a number of strain maps and image IDs used to generate the surface displacement maps </p>
Cross section shape: circular elliptical unknown Siphuncle position: central marginal unknown Fig. 4 Morphometrics of orthoconic cephalopods from the Besano Formation. Measurements are compared with discrete characters of the shell. Orange circles represent definite and orange crosses likely orthoceratoids, while blue triangles represent definite and blue crosses likely coleoids. Black crosses are indeterminable. A Apical angle, calculated from length and diameters of the specimens. B Maximum diameter in Orthoceratoid and coleoid cephalopods from the Middle Triassic of Switzerland with an updated taxonomic framework for Triassic Orthoceratoidea
Cross section shape: circular elliptical unknown Siphuncle position: central marginal unknown Fig. 4 Morphometrics of orthoconic cephalopods from the Besano Formation. Measurements are compared with discrete characters of the shell. Orange circles represent definite and orange crosses likely orthoceratoids, while blue triangles represent definite and blue crosses likely coleoids. Black crosses are indeterminable. A Apical angle, calculated from length and diameters of the specimens. B Maximum diameter
Evaluation datasets and results of the paper "A Framework for Measuring the Quality of Business Process Simulation Models"
<p>Datasets and files used in the evaluation of the publication entitled "A Framework for Measuring the Quality of Business Process Simulation Models", where:</p> <ul> <li><strong><em>BPS-models/</em></strong>: folder containing the BPS models used in the evaluation (the BPS models discovered by ServiceMiner are not included due to privacy reasons). <ul> <li>The BPS models discovered by SIMOD are composed of <em>i)</em> a BPMN file with the process model structure, and <em>ii)</em> a JSON file with the parameters of the simulation. These files correspond to the format of Prosimos simulation engine (<a href="https://prosimos.cloud.ut.ee/">https://prosimos.cloud.ut.ee/</a>).</li> <li>The BPS models of the Loan Application and Procure to Pay processes are composed of a BPMN file with both the process model structure and parameters, corresponding to the format of the BIMP simulator used in APROMORE (<a href="https://apromore.com/">https://apromore.com/</a>).</li> </ul> </li> <li><em><strong>measures/</strong></em>: folder containing the distance values of each measure reported in the paper.</li> <li><em><strong>original-event-logs/</strong></em>: folder containing the (train and test) event logs used in the evaluation.</li> <li><em><strong>simulated-logs/</strong></em>: folder containing the simulated logs evaluated in the paper (synthetic, SIMOD, and ServiceMiner).</li> <li><em><strong>ComputeLogDistance.py</strong></em>: script to compute the distance measures proposed in the paper.</li> </ul> <p> </p> <p>To evaluate the distance measures of a set of simulated event logs in the folder <em>simulated_logs/</em> against the test log <em>test_event_log.csv.gz</em>, run:<br><em> python ComputeLogDistance.py -cfld test_event_log.csv.gz simulated_logs/</em></p> <p>*The flag <em>-cfld</em> is optional, due to the high computational complexity of the CFLD measure.</p> <p><strong>WARNING</strong>: set the column names of each log accordingly (where <em>log_1_ids</em> are the IDs of the test log, and <em>log_2_ids</em> the IDs of the simulated logs). Examples:</p> <pre><code># Column IDs for the (train/test) real-life logs, and the SIMOD simulated logs. EventLogIDs( case='case_id', activity='activity', start_time='start_time', end_time='end_time', resource='resource' ) # Column IDs for the Loan Application and Procure to Pay simulated logs. EventLogIDs( case='case_id', activity='activity', start_time='Start_Time', end_time='End_Time', resource='resource' ) # Column IDs for the ServiceMiner simulated logs. EventLogIDs( case='case_id', activity='Activity', start_time='start_time', end_time='end_time', resource='Resource' )</code></pre> <p> </p>
Figure 1 in Forest Status Across Micronesia from an Assessment of Micronesia Challenge Terrestrial Measures and Forest Inventory and Analysis Data
Figure 1. Map of Micronesia showing jurisdictions included in the FIA program and locations of Micronesia Challenge protected areas as of 2018.
Figure 2 in Forest Status Across Micronesia from an Assessment of Micronesia Challenge Terrestrial Measures and Forest Inventory and Analysis Data
Figure 2. Estimated percentage of all trees by diameter class (in inches) by jurisdiction across Micronesia. FSM: Federated States of Micronesia, RMI: Republic of Marshall Islands, CNMI: Commonwealth of Northern Mariana Islands.
Fig. 7 in Evaluating the utility of linear measurements to identify isolated tooth loci of extinct Hyracoidea
Fig. 7. Simulated and observed values of Borges et al.'s (Borges et al. 2019) δ values for simulated trait distributions on the tree in Fig. 1 for sets of traits (A, m1: m2 length; B, M1: M2 length; C, M2: M3 length) that show phylogenetic signal (red triangles) and phylogenetic retention (gray circles).
Fig. 2 in Evaluating the utility of linear measurements to identify isolated tooth loci of extinct Hyracoidea
Fig. 2. Illustration of measurements taken on lower (m1–m3, A–C) and upper (M1–M3, D–F) teeth in occlusal views to calculate potentially diagnostic traits. Measurements are illustrated on specimen UMZC H5101A, Procavia capensis. Abbreviations: LE, length; MW, width of the crown at metaloph; PW width of the crown at paraloph.
Fig. 6 in Evaluating the utility of linear measurements to identify isolated tooth loci of extinct Hyracoidea
Fig. 6. Overlap in potentially diagnostic trait values for upper molar loci of three example hyracoid taxa (A1, B1, Procavia capensis; A2, B2, Saghatherium bowni; A3, B3, Thyrohyrax meyeri). A. Length vs. proportional frequency, showing how a single trait, length, would be modeled in a univariate discriminant analysis using observed means and variances. Colored sections of the distributions show length values that are within 95% confidence intervals of the means of more than one tooth locus, indicating regions of ambiguous lengths. B. Length vs. relative width, showing scatter plots overlaid on 2D density diagrams showing the distribution of values for individual teeth.
Fig. 8 in Evaluating the utility of linear measurements to identify isolated tooth loci of extinct Hyracoidea
Fig. 8. Overlap in potentially diagnostic trait values for a case study of isolated molars of Meroehyrax kyongoi. In contrast to Fig. 4, molar locus identifications are based on occupation of space in this scatterplot. Question marks are overlaid over two specimens whose inferred tooth position conflicts with published diagnoses. In parentheses original identification in publication.
Fig. 1 in Evaluating the utility of linear measurements to identify isolated tooth loci of extinct Hyracoidea
Fig. 1. Phylogenetic tree and tooth size distribution in hyracoids (topology from Cooper et al. 2014). Taxa are time-scaled along the x-axis of the tree to reflect fossil occurrences based on the literature, with branches rescaled between these tip dates and a root age estimated at 70.1 million years. Taxa in bold text were included in analyses. Minimum monophyletic clade including taxa in bold indicates the range of the phylogenetic bracket applied for both length and width measures (base of clade indicated by black star). Minimum monophyletic clade for length measures from the literature is indicated by a white star at the base of the clade. Shapes to the right of tips indicate whether there is a significant fit with a model of ascending (increasing) tooth size down the molar row. Abbreviations: M, upper molars; m, lower molars.
Fig. 3 in Evaluating the utility of linear measurements to identify isolated tooth loci of extinct Hyracoidea
Fig. 3. Distribution of values for a set of univariate, potentially locus-diagnostic traits (A, length vs. m1 length; B, trigonid width vs. talonic width) described in Fig. 2 in lower molars of a range of hyracoid species.
Fig. 5 in Evaluating the utility of linear measurements to identify isolated tooth loci of extinct Hyracoidea
Fig. 5. Distribution of values for a set of univariate, potentially locus-diagnostic traits (A, length vs. M1 length; B, paraloph vs. metaloph; C, metaloph vs. length; D, paraloph vs. length) described in Fig. 2 in upper molars of a range of hyracoid species.
Fig. 4 in Evaluating the utility of linear measurements to identify isolated tooth loci of extinct Hyracoidea
Fig. 4. Overlap in potentially diagnostic trait values for lower molar loci of three example hyracoid taxa (A1, B1, Procavia capensis; A2, B2, Saghatherium bowni; A3, B3, Thyrohyrax domorictus). A. Length vs. proportional frequency, showing how a single trait, length, would be modeled in a univariate discriminant analysis using observed means and variances. Colored sections of the distributions show length values that are within 95% confidence intervals of the means of more than one tooth locus, indicating regions of ambiguous lengths. B. Length vs. relative width, showing scatter plots overlaid on 2D density diagrams showing the distribution of values for individual teeth.
Data and fitting script for "Direct measurement of a sin(2φ) current phase relation in a graphene superconducting quantum interference device"
<p>This repository contains data and Python analysis scripts used for the publication "Direct measurement of a sin(2\phi) current phase relation in a graphene superconducting quantum interference device (https://doi.org/10.48550/arXiv.2405.13642).</p> <p>The repository is organized as follows: the raw data are encapsulated in a QCoDes database (https://microsoft.github.io/Qcodes/) named 'D-SQUID-06.db'. Post-treated critical current data are included as .csv files and are indexed by measurement ids.</p> <p>The principal analysis is realized in the Jupyter notebook 'Fits_and_Figures.ipynb', which includes all article figures as well as fit functions for fitting both critical currents Ic- and Ic+ simulatenously, first using analytical expression from equation 3 then using numerical expression from equation 5. All fits mentionned in the article are performed there. The repository includes a generic notebook "Extract_Critical_Current.ipynb" used to explore the raw data in the Qcodes database and features an enhanced peak detection script that we used to automatically extract critical current data despite having some artifacts on raw differential conductance versus bias current and magnetic field.</p> <p>We acknowledge the contribution of R. Kerjouan for developing the Python fitting script.</p>
Hydrological Station Uttendorf (ÖBB): water gauge measurement
<p>The Austrian Hydrographic Service operates a basic measuring network for recording precipitation, determining flow and water levels in rivers and lakes and monitoring groundwater levels in Austria. This data is organised into precipitation, discharge and groundwater level classes and is accessible via ehyd.gv.at</p>
Wind and Wave Measurements in the Oslo Fjord
<p>Measurements of surface waves were conducted with the aim of measuring waves in the capillary-gravity regime as part of a master's thesis. An in-house built sensor equipped with an IMU, which measures acceleration and angular velocity in the unit's frame of reference, was used for a period of 26 hours. The sensor has a length of 2.5 cm and a width of 2 cm. The setup included the preprogrammed logger, SparkFun OpenLog Artemis, to record the sensor data. </p> <p>Wind measurements were also made during the same period using a commercial 3-cup anemometer, although wind direction was not recorded.</p> <p>The equipment was mounted on a jetty at Lindøya, in the inner Oslo Fjord.</p>
Figure 2 in Confounding factors affecting faecal egg count reduction as a measure of anthelmintic efficacy
Figure 2. An illustrative example of the potential effect of seasonal shifts in nematode species composition on observed faecal egg count (FEC) reduction, based on typical epidemiological patterns in sheep in temperate areas. FEC composition indicates the proportion of eggs belonging to each species, where eggs of Trichostrongylus spp., Teladorsagia circumcincta and Haemonchus contortus are not easily distinguished from each other. Months are calendar months in the northern hemisphere, with Nematodirus battus and then Teladorsagia dominating in spring and early summer, Trichostrongylus in late summer and autumn, and Haemonchus transiently dominant following favourable climatic conditions [91]. In scenario 1, only Haemonchus is resistant to treatment, with FECR of 80%; in scenario 2, only Teladorsagia is resistant (80% FECR); FEC of other species reduce by 98% following treatment. A FECRT would have different results in different months, detecting resistance (<95% FECR) only in months (% FECR in bold) in which the resistant species contributes sufficiently to total faecal egg output, and returning false-negative results for AR in other months. The simulation does not account for differences in fecundity between species, which further amplify seasonal variation in FECR. Here, FECRT conducted at different times of year produce differing results even if anthelmintic efficacy is stable within species over that period.
Figure 1 in Confounding factors affecting faecal egg count reduction as a measure of anthelmintic efficacy
Figure 1. Schematic showing the range of confounders potentially influencing faecal egg count reduction (FECR) following anthelmintic treatment, and hence classification of anthelmintic resistance (AR). These are divided into host, parasite and technical factors, which together affect actual reduction in faecal egg count (1). Technical considerations also influence the accuracy with which FECR is observed (2), and hence the detection of anthelmintic resistance (3). Technical refinements to the FECRT have very much focused on improving the accuracy with which actual FECR is measured and translated into AR classification (step 3), even though many factors other than AR can strongly influence actual FECR. These risk confounding the FECRT and should be borne in mind when designing, conducting and interpreting the test, whether in standardised form for detection of AR, or in modified forms to monitor anthelmintic effectiveness.
Hunter-gatherer child and adolescent height and tricep skinfold measures
<p>Despite agreement that humans have evolved to be unusually fat primates, adipose patterning among hunter-gatherers has received little empirical consideration. Here we consider the development of adiposity among four contemporary groups of hunter-gatherers, the Aka, Savanna Pumé, Ju'/Hoansi and Agta using multi-level generalized additive mixed modeling (GAMM) to characterize growth of tricep skinfolds from early childhood through adolescence. In contrast to references, hunter-gatherers show several consistent patterns: 1) children are lean with little fat accumulation; 2) no adiposity rebound at 5 years is evident; 3) girls on average build 90% of their body size, and reach menarche when adiposity is at its maximum velocity; 4) a metabolic tradeoff is evident in young, but not older children, such that both boys and girls prioritize skeletal growth during middle childhood, a tradeoff that diminishes during adolescence when height velocity increases in pace with fat accumulation. Consistent results across hunter-gatherers living in diverse environments suggests that these patterns reflect a general forager pattern of development. The findings provide a valuable baseline for adipose development not apparent from reference populations. We emphasize both generalized trends among hunter-gatherers, and that inter-populational differences point to the plasticity with which humans organize growth and development.</p>
Fig. 2 in A New Measure Of Conservation Value Combining Rarity And Ecological Diversity: A Case Study With Light Trap Collected Caddisflies (Insecta: Trichoptera)
Fig. 2. The Rarity and Ecological Diversity (RED)-index of the different aquatic habitats (aquatic habitats with the same letter are not significantly different at p = 0.05 by non-parametric Tukey-test)
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.