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.
5,530
datasets available to search
ShareScore release 0.9.0
Dataset results
5,530 results for “informal”
Springs ecosystem classification supplementary information
<p>Springs ecosystems are globally abundant, geomorphologically diverse, and bio-culturally productive, but are highly imperiled by anthropogenic activities. More than a century of scientific discussion about the wide array of ecohydrological factors influencing springs has been informative, but has yielded little agreement on their classification. This lack of agreement has contributed to the global neglect and degradation of springs ecosystems by the public, scientific, and management communities. Here we review the historical literature on springs classification variables, concluding that site-specific source geomorphology remains the most diagnostic approach. We present a conceptual springs ecosystem model that clarifies the central role of geomorphology in springs ecosystem development, function, and typology. We present an illustrated dichotomous key to terrestrial (non-marine) springs ecosystem types and subtypes, and describe those types. We identify representative reference sites, although data limitations presently preclude selection of continentally or globally representative reference springs of each type. We tested the classification key using data from 244 randomly selected springs of 13 major types that were inventoried in North America. The dichotomous key correctly identified springs type in 87.5% of the cases, with discrepancies primarily due to differentiation of primary versus secondary typology, and insufficient inventory team training. Using that information, we identified sources of confusion and clarified the key. Among the types that required more detailed explanation were hypocrenes, springs, in which groundwater is expressed through phreatophytic vegetation. Overall, springs biodiversity and ecosystem complexity are due, in part, to the co-occurrence of multiple intra-springs microhabitats. We describe microhabitats that are commonly associated with different springs types, reporting at least 13 microhabitats, each which can support discrete biotic assemblages. Interdisciplinary agreement on basic classification is needed to enhance scientific understanding and stewardship of springs ecosystems, the loss and degradation of which constitute a global conservation crisis.</p> <p>We provide data on springs ecosystem classification using non-sensitive springs data selected in an unbiased fashion from Springs Online (springsdata.org) to test the springs classificaiton dichotomous key and description (attached as separate pages to this dataset). </p>
Data from: The dynamic transmission of positional information in stau-mutants during Drosophila embryogenesis.
It has been suggested that Staufen (Stau) is key in controlling the variability of the posterior boundary of the Hb anterior domain (xHb). However, its underlying mechanism is elusive. Here, we quantified the dynamic 3D expression of segmentation genes in Drosophila embryos. With improved control of measurement errors, we show xHb of stau- mutants reproducibly moves posteriorly by 10% of the embryo length (EL) to the wild type (WT) position in the nuclear cycle (nc) 14, and its variability at short time windows is comparable as that of the WT. Moreover, for stau- mutants, the upstream Bicoid (Bcd) gradients show equivalent relative intensity noise to that of the WT in nc12-nc14, and the downstream Even-skipped (Eve) and cephalic furrow (CF) show the same positional errors as the WT. Our results indicate that threshold-dependent activation and self-organized filtering are not mutually exclusive but could both be implemented in early Drosophila embryogenesis.
Data from: Genotyping-in-Thousands by sequencing reveals marked population structure in Western Rattlesnakes to inform conservation status
<p>Delineation of units below the species level is critical for prioritizing conservation actions for species at-risk. Genetic studies play an important role in characterizing patterns of population connectivity and diversity to inform the designation of conservation units, especially for populations that are geographically isolated. The northernmost range margin of Western Rattlesnakes (<em>Crotalus oreganus</em>) occurs in British Columbia, Canada, where it is federally classified as threatened and restricted to five geographic regions. In these areas, Western Rattlesnakes hibernate (den) communally, raising questions about connectivity within and between den complexes. At present, Western Rattlesnake conservation efforts are hindered by a complete lack of information on genetic structure and degree of isolation at multiple scales, from the den to the regional level. To fill this knowledge gap, we used Genotyping-in-Thousands by sequencing (GT-seq) to genotype an optimized panel of 362 single nucleotide polymorphisms (SNPs) from individual samples (n = 461) collected across the snake's distribution in western Canada and neighboring Washington (USA). Hierarchical STRUCTURE analyses found evidence for population structure within and among the five geographic regions in BC, as well as in Washington. Within these regions, 11 genetically distinct complexes of dens were identified, with some regions having multiple complexes. No significant pattern of isolation-by-distance and generally low levels of migration were detected among den complexes across regions. Additionally, snakes within dens generally were more related than those among den complexes within a region, indicating limited movement. Overall, our results suggest that the single, recognized designatable unit for Western Rattlesnakes in Canada should be re-assessed to proactively focus conservation efforts on preserving total genetic variation detected range wide. More broadly, our study demonstrates a novel application of GT-seq for investigating patterns of diversity in wild populations at multiple scales to better inform conservation management.</p>
Supporting Information for "How long is too long? Variogram analysis of AERONET data to aid aerosol validation and intercomparison studies"
<p>This contains data sets and their description for the paper "How long is too long? Variogram analysis of AERONET data to aid aerosol validation and intercomparison studies" submitted to the journal Earth and Space Science by this author. This study investigates the uncertainty introduced into comparisons (between e.g. AERONET ground observations, satellite retrievals, or model simulations) of aerosol optical properties due to differences in time of observation between the data sets. This uncertainty source has historically been neglected but is potentially important in some situations.</p> <p> </p> <p>Journal policies are that Supporting Information data sets can no longer be archived with the paper, but instead should be uploaded to a separate repository. As a result, I have uploaded these data here.</p> <p> </p> <p>This data set consists of one pdf file describing the data sets, and then two zip archives containing the data (ASCII format). The total size is approximately 10 MB. These data files allow the reproduction of analysis results in this paper, and enable researchers to estimate temporal mismatch uncertainties in their own analyses involving AERONET sites.</p>
Analytic dataset informing prediction of subterranean cave and mine ambient temperatures
<p>Caves and other subterranean features provide unique environments for many species. The importance of cave microclimate is particularly relevant at temperate latitudes where bats make seasonal use of caves for hibernation. White-nose syndrome (WNS), a fungal disease that has devastated populations of hibernating bats across eastern and central North America, has brought renewed interest in bat hibernation and hibernaculum conditions. A recent review synthesized current understanding of cave climatology, exploring the qualitative relationship between cave and surface climate with implications for hibernaculum suitability. However, a more quantitative understanding of the conditions in which bats hibernate and how they may promote or mediate WNS impacts is required. We compiled subterranean temperatures from caves and mines across the western United States and Canada to: a) quantify the hypothesized relationship between mean annual surface temperature (MAST) and subterranean temperature and how it is influenced by measurable site attributes, and b) use readily available gridded data to predict and continuously map the range of temperatures that may be available in caves and mines. Our analysis supports qualitative predictions that subterranean winter temperatures are correlated with MAST, that temperatures are warmer and less variable farther from the surface, and that even deep within caves temperatures tend to be lower than MAST. Effects of other site attributes (e.g., topography, vegetation, precipitation) on subterranean temperatures were not detected. We then assessed the plausibility of model-predicted temperatures using knowledge of winter bat distributions and preferred hibernaculum temperatures. Our model unavoidably simplifies complex subterranean environments, and is not intended to explain all variability in subterranean temperatures. Rather, our results offer researchers and managers improved broad-scale estimates of the geographic distribution of potential hibernaculum conditions compared to reliance on MAST alone. We expect this information to better support range-scale estimation of winter bat distributions and projection of likely WNS impacts across the West. We suggest that our model predictions should serve as hypotheses to be further tested and refined as additional data become available. </p>
Quantifying range structure to inform management in invaded landscapes - Dataset
<p>This data set was collected in Table Mountain National Park, South Africa and comprises count and location data for invasive woody plant species for the genera <em>Acacia</em>, <em>Pinus,</em> and <em>Eucalyptus</em>. The data were collected between 2013 and 2015 and span 10 058 sample plots, uniformly distributed across the protected area. Further details of the dataset are provided in the attached meta-data document.</p>
[2019 QSM Reconstruction Challenge] Metrics and Submission Information
<p>This repository contains information about submitted solutions and resulting analysis metrics of the 2019 Quantitative Susceptibility Mapping Reconstruction Challenge. The original susceptibility maps submitted for participation in the challenge are available <a href="http://dx.doi.org/10.5281/zenodo.3687342">here</a> and <a href="http://dx.doi.org/10.5281/zenodo.3688703">here</a>.</p> <p>The package contains seven Comma-Separated Values (CSV) files and two PDF files:</p> <ul> <li><em>master_stage1_anonymized.csv</em>: Results of stage 1 of the challenge at the time of presentation at the workshop (fully-blinded);</li> <li><em>master_stage2_snr1_anonymized.csv</em>: Results of stage 2 of the challenge using the high noise dataset at the time of presentation at the workshop (fully-blinded);</li> <li><em>master_stage2_snr2_anonymized.csv</em>: Results of stage 2 of the challenge using the low noise dataset at the time of presentation at the workshop (fully-blinded);</li> <li><em>submission_form_stage1.pdf</em>: PDF export of the online form used in stage 1;</li> <li><em>submission_form_stage2.pdf</em>: PDF export of the online form used in stage 2.</li> </ul> <p>For the manuscript, we analyzed these CSV files with scripts reported <a href="https://doi.org/10.5281/zenodo.4559540">here</a>.</p> <p>Each csv file contains metrics for all submitted solutions along with detailed information about the algorithm used, provided by the participant at the time of submission. The very first record in each file is a header containing a list of field names:</p> <ul> <li><em>normalized rmse</em>: Whole-brain root-mean-squared error relative to ground truth;</li> <li><em>rmse_detrend_tissue</em>: Root-mean-squared error relative to ground truth (after detrending) in grey and white matter mask;</li> <li><em>rmse_detrend_blood</em>: Root-mean-squared error relative to ground truth (after detrending) using a one-pixel dilated vein mask;</li> <li><em>rmse_detrend_DGM</em>: Root-mean-squared error relative to ground truth (after detrending) in a deep gray matter mask (substantia nigra & subthalamic nucleus, red nucleus, dentate nucleus, putamen, globus pallidus and caudate);</li> <li><em>DeviationFromLinearSlope</em>: Absolute difference between the slope of the average value of the six deep gray matter regions vs. the prescribed mean value and 1.0;</li> <li><em>CalcStreak</em>: Estimation of the impact of the streaking artifact in a region of interest surrounding the calcification through the standard deviation of the difference map between reconstruction and the ground truth;</li> <li><em>DeviationFromCalcMoment</em>: Absolute deviation from the volumetric susceptibility moment of the reconstructed calcification, compared to the ground truth (computed at in the high-resolution model);</li> <li><em>Submission Identifier</em>: Self-chosen unique identifier of the submission;</li> <li><em>Submission Identifier of the corresponding Stage 1 submission</em>: This is the Submission Identifier of the solution submitted to Stage 2 that was calculated with a similar algorithm in Stage 1;</li> <li><em>Changes with respect to Stage 1 submission</em>: Self-reported information about modifications made to the algorithm for Stage 2;</li> <li><em>Number of submissions in Stage 2</em>: The number of solutions that were submitted to Stage 2 with a similar algorithm;</li> <li><em>Sim1/Sim2</em>: Filename of the submitted solutions for Stage 1;</li> <li><em>File name of the zip-file you are going to upload</em>: Filename of the file uploaded to Stage 2;</li> <li><em>Full name of the algorithm</em>: Self-reported full name of the algorithm used;</li> <li><em>Preferred Acronym</em>: Self-reported acronym of the algorithm used;</li> <li><em>Algorithm-type</em>: Self-reported type of algorithm used;</li> <li><em>Does your algorithm incorporate information derived from magnitude images?</em>: Self-reported Yes/No;</li> <li><em>Regularization terms</em>: Self-reported types of regularization terms involved;</li> <li><em>Did your algorithm use the provided frequency map or the four individual echo phase images?</em>: Self-reported information about involved magnitude information;</li> <li><em>Publication-ready description of the reconstruction technique</em>: Self-reported description of the algorithm;</li> <li><em>Publications that describe the algorithm</em>: Self-reported literature reference;</li> <li><em>Algorithm publicly available?</em>: Self-reported public availability of the algorithm;</li> <li><em>If your algorithm is not yet publicly available, would you be willing to make it available at the end of the challenge?</em>: Self-reported willingness to share the algorithm code with the public;</li> <li><em>Specific information about this solution</em>: Self-reported detailed information about the solution;</li> <li><em>Herewith, I permit the QSM Challenge committee to publish my uploaded files (calculated maps) after the completion of the challenge</em>: Self reported agreement with publication of submitted solution;</li> <li><em>Ground truth was not explicitly or implicitly incorporated into your algorithm or solution</em>: Self-reported confirmation that the ground truth was not incorporated in the solution.</li> </ul>
Figure 4 in Optimizing biodiversity informatics to improve information flow, data quality, and utility for science and society
Figure 4. Graphical representation of original and recently modified pathways for feedback regarding Primary Biodiversity Data, showing information transfer among users, providers, and aggregators. Such feedback consists of suggested improvements or additions to data fields, for example a change in species identification or a newly determined georeference. The diagrams contrast two complementary mechanisms: (a) the original feedback loop (currently dominant); and (b) the emerging feedback pendulum (proposed for expansion). In a: (1) the user sends feedback to the provider (e.g., a given natural history museum); (2) if the provider makes a corresponding change to its database, the updated information is sent to the aggregator; and (3) that information becomes available for query by all users. In practice, because many providers do not consistently make such changes (denoted by an X), users do have access to updated information (dashed line). In b: (1) the user sends feedback to the aggregator; (2) the aggregator simultaneously both annotates the record (visible to all users) and sends the suggested information to the provider; (3) if the provider makes a corresponding change to its database, the updated information is sent to the aggregator; and (4) the aggregator makes the updated information available for query by all users. Note that even if a provider takes no action regarding the suggested information, the annotations placed by the aggregator are nevertheless available to users. Additionally, because the quantifications of data quality and use described in the text allow for benchmarks that can be tracked over time, we anticipate that the feedback pendulum will help providers become more successful in justifying and securing funding to make data improvements based on feedback from users.
Supplementary information for 'Structural and chemical properties of superconducting Co-doped BaFe2As2 thin films grown on CaF2'
<p>This repository contains supplementary information for the journal article '<a href="https://iopscience.iop.org/article/10.1088/1361-6668/abcecf">Structural and chemical properties of superconducting Co‑doped BaFe<sub>2</sub>As<sub>2</sub> thin films grown on CaF<sub>2</sub></a>'.</p> <p>The Jupyter notebooks (.ipynb) demonstrate data treatment for Fig. 4b (folder "HyperSpy EDXS Analysis") and Fig. 10a (folder "Atomap"). The notebooks can be run with the provided datasets. HTML files are also provided for quick inspection of the used procedures in a web browser. Supplementary video files (.mp4) show electron-beam-induced radiation damage at the BaFe<sub>2</sub>As<sub>2</sub>-CaF<sub>2</sub> interface.</p> <p>Please visit the websites of the <a href="https://hyperspy.org/">HyperSpy</a> and <a href="https://atomap.org/">Atomap</a> projects for more information.</p> <p>If there are any questions or bugs, please contact me under lukas.gruenewald_at_kit.edu.</p> <p> </p> <p> </p>
Supplementary material 1 from: Zermoglio PF, Plos A, Acosta N, Amaya L, Escobar DA, Grattarola F, Mancina CA, Nuñez F, Plata CA, Quintero E, Vargas M (2020) Latin American Plea for Incorporation of Other, Non-English Languages in TDWG Standards Documentation. Biodiversity Information Science and Standards 4: e58973. https://doi.org/10.3897/biss.4.58973
Signatories to the petition for incorporation of other languages to the Biodiversity Information Standards (TDWG) standards and documentation
Evaluating Bayesian stable isotope mixing models of wild animal diet and the effects of trophic discrimination factors and informative priors
<blockquote> <p>1. Ecologists quantify animal diets using direct and indirect methods, including analysis of faeces, pellets, prey items and gut contents. For stable isotope analyses of diet, Bayesian stable isotope mixing models (BSIMMs) are increasingly used to infer the relative importance of food sources to consumers. Although a powerful approach, it has been hard to test BSIMM performance for wild animals because precise, direct dietary data are difficult to collect.<br> 2. We evaluated the performance of BSIMMs in quantifying animal diets when using δ13C and δ15N stable isotope ratios from the feathers and red blood cells of common buzzard Buteo buteo chicks. We analysed mixing model outcomes with various trophic discrimination factors (TDFs), with and without informative priors, and compared these to direct observations of prey provisioned to chicks by adults at nests, using remote cameras. <br> 3. Although BSIMMs with different TDFs varied markedly in their performance, the statistical package SIDER generated TDFs for both feathers and blood that resulted in model outputs that accorded well with direct observations of prey provisioning. Using feather TDFs derived from captive peregrines Falco peregrinus resulted in estimates of diet composition that were also similar to provisioned prey, though blood TDFs from the same study performed poorly. The inclusion of informative priors, based on conventional analysis of pellet and prey remains, markedly reduced model performance.<br> 4. BSIMMs can provide accurate assessments of diet in wild animals. TDF estimates from the SIDER package performed well. The inclusion of informative priors from conventional methods in Bayesian mixing models can transfer biases into model outcomes, leading to erroneous results.</p> </blockquote>
Managing Assurance Information: A Solution Based on Issue Tracking Systems
<p>Video presentation for NIER Track article " Managing Assurance Information: A Solution Based on Issue Tracking Systems "</p>
The roles of temperature, nest predators and information parasites for geographical variation in egg covering behaviour of tits (Paridae)
<p><strong>Aim</strong>: Nest building is widespread among animals. Nests may provide receptacles for eggs, developing offspring and the parents, and protect them from adverse environmental conditions. Nests may also indicate the quality of the territory and its owner and can be considered as an extended phenotype of its builder(s). Nests may, thus, function as a sexual and social signal. Here, we examined ecological and abiotic factors—temperature, nest predation and interspecific information utilization—shaping geographical variation in a specific nest structure—hair and feather cover of eggs— and its function as an extended phenotype before incubation in great (Parus major) and blue tits (Cyanistes caeruleus) across Europe. We also tested whether egg covering is associated with reproductive success of great tits.</p> <p><strong>Location</strong>: Fourteen different study sites and 28 populations across Europe.</p> <p><strong>Taxon</strong>: Parus major, Cyanistes caeruleus.</p> <p><strong>Methods</strong>: We recorded clutch coverage estimates and collected egg covering nest material from the tit nests. We also measured nest specific breeding parameters and phenotypic measurements on adults. We tested whether mean spring temperatures, nest predation rates and flycatcher (Ficedula spp) densities in the study areas explain the large-scale geographical variation of clutch coverage and reproductive success of tits.</p> <p><strong>Results</strong>: The degree of egg coverage of great tits increased with lower mean spring temperature, higher nest predation rate and higher flycatcher density. We did not find egg covering of blue tits to be associated with any of the ecological or abiotic factors. Moreover, egg covering of great tits was not associated with reproductive success in our cross-sectional data, yet a rigorous assessment of fitness effects would require long-term data.</p> <p><strong>Main conclusions</strong>: Our findings suggest that, in great tits, egg covering may simultaneously provide thermal insulation against cold temperatures during egg-laying in spring and also represent a counter-adaptation to reduce information parasitism by flycatchers and nest predation. Hence, geographical variation in interspecific interactions, and consequently in co-evolutionary processes, may affect the evolution of nest characteristics besides environmental conditions.</p>
Data -SUPPLIMENDARY INFORMATIONS –Growth of D614G Virus – Regression Analysis
<p>Data analysis report for Growth of D614G Virus – Regression Analysis.</p>
Impact of COVID-19 lockdown on glycemic control in adults with type 1 diabetes mellitus: information and standardized questions regarding follow-up during lockdown
<p>Aim. To examine the impact of the lockdown caused by COVID-19 pandemic on both the glycemic control and the daily habits of a group of patients with type 1 diabetes mellitus (T1DM) using flash continuous glucose monitoring devices (Flash CGM). </p> <p>Methods. Retrospective analysis based on all the information gathered in virtual consultations from a cohort of 50 adult patients with T1DM with follow-up at our site. We compared their CGM metrics during lockdown with their own previous data before the pandemic occurred, as well as the potential psychological and therapeutic changes.</p> <p>Results. We observed a reduction of the average glucose: 160.26 ± 22.55 mg/dl vs. 150 ± 20.96 mg/dl, p=0.0009, estimated HbA1c: 7.21 ± 0.78% vs. 6.83 ± 0.71%, p=000.5, glucose management indicator (GMI) 7.15 ± 0.57 % vs. 6.88 ± 0.49 %, p=0.0003, and glycemic variability (CV): 40.74 ± 6.66 vs. 36.43 ± 6.09 p<0.0001. Time in range showed an improvement: 57.46 ± 11.85% vs a 65.76 ± 12.09%, p<0.0001, without an increase in percentage of time in hypoglycaemia.</p> <p>Conclusions: COVID-19 lockdown was associated with an improvement in glycemic control in patients with T1DM using CGM.</p>
Towards Olfactory Information Extraction from Text: A Case Study on Detecting Smell Experiences in Novels
<p>Dataset accompanying "Ryan Brate, Paul Groth and Marieke van Erp (2020) Towards Olfactory Information Extraction from Text: A Case Study on Detecting Smell Experiences in Novels. LaTeCH-CLfL 2020. Barcelona, December 2020."</p> <p>Abstract:</p> <p>Environmental factors determine the smells we perceive, but societal factors factors shape the importance, sentiment and biases we give to them. Descriptions of smells in text, or as we call them `smell experiences', offer a window into these factors, but they must first be identified. To the best of our knowledge, no tool exists to extract references to smell experiences from text. In this paper, we present two variations on a semi-supervised approach to identify smell experiences in English literature. The combined set of patterns from both implementations offer significantly better performance than a keyword-based baseline.</p>
Supplementary information for: Using networks to identify structure in phylogenetic tree sets
<p>Modern phylogenomic studies produce large sets of trees that can represent variation in inferred phylogenies across genes, uncertainty in estimated phylogenies for a given gene, or both. Standard practice is to condense this variation down to a small set of point estimates or consensus trees in order to facilitate display and interpretation. However, doing so results in the loss of enormous amounts of information about the structure of the underlying tree set. Here, we propose new approaches to explore and detect structure in the tree set itself. These approaches rely on the well-developed mathematical foundations of community detection in networks and leverage two different network types. The first type uses nodes to represent trees and connects these nodes with edges whose weights are determined by the similarity (affinity) of the trees. The second type uses nodes to represent bipartitions and connects nodes with edges whose weights represent the covariance in bipartition presence/absence across trees in the set. These two network types carry information that is complementary, but not identical. A variety of methods may be applied to both networks in order to identify interesting community structure. These community detection approaches provide a rich view of the information contained in phylogenomic data sets and facilitate investigation into the forces driving inferred phylogenetic variation across genomes.</p>
A co-development approach to conservation leads to informed habitat design and rapid establishment of amphibian communities
<p>1. Effective wildlife restoration is a critical requirement of many conservation actions. The outcome of conservation interventions can be optimised through knowledge of species' habitat requirements, but few studies consider the impact of using explicit evidence from dedicated local research to inform the design phase of habitat management. Furthermore, interventions administered externally from the top down, whilst simpler than those developed in discussion with multiple stakeholders including land managers (i.e. co-development), run the risk of failing to engage local people.</p> <p>2. In this study, we focus on interventions in the Scottish Highlands to improve the availability and suitability of breeding ponds for local amphibian assemblages. We collected and analysed data based on 129 ecological variables across 88 reference ponds to quantify the local habitat preferences. We used the findings from these analyses to inform the construction or restoration of 25 intervention ponds co-developed in partnership with stakeholders (landowners, foresters, citizen scientists and government agencies). Following the interventions, we monitored amphibian communities at these sites over 4 years. We assessed presence and abundance of all five native amphibians (the anurans Rana temporaria and Bufo bufo, and the salamanders Lissotriton helveticus, L. vulgaris and Triturus cristatus) using egg searching, dip-netting, torching and trapping.</p> <p>3. The new habitats were overall characterised by ecological conditions more favourable to amphibians than the reference ponds. We recorded a total of 51 colonisation events. Within two breeding seasons after construction or restoration, the intervention ponds hosted the full complement of species, mirroring amphibian diversity patterns found in the local reference ponds.</p> <p>4. Our study shows that ecological research to quantify local habitat requirements and working with commercial land-managers to ensure equitable benefits prior to designing conservation actions can promote rapid and efficient recovery of wildlife.</p>
Information Theoretic HotStuff (video)
Full video presentation of the paper: Information Theoretic HotStuff.<br><br>Appears in Session 3 of the 24th International Conference on Principles of Distributed Systems OPODIS 2020<br><a href="https://opodis2020.unistra.fr">https://opodis2020.unistra.fr</a>
Complete set of raw and processed datasets, as well as associated Jupyter notebooks for analysis, associated with manuscript entitled: "The MOUSE project: a practical approach for obtaining traceable, wide-range X-ray scattering information"
<p>This dataset is a complete set of raw, processed and analyzed data, complete with Jupiter notebooks, associated with the manuscript mentioned in the title. </p> <p>In the manuscript, we provide a ``systems architecture''-like overview and detailed discussions of the methodological and instrumental components that, together, comprise the "MOUSE" project (<strong>M</strong>ethodology <strong>O</strong>ptimization for <strong>U</strong>ltrafine <strong>S</strong>tructure <strong>E</strong>xploration). Through this project, we aim to provide a comprehensive methodology for obtaining the highest quality X-ray scattering information (at small and wide angles) from measurements on materials science samples. </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.