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.
357
datasets available to search
ShareScore release 0.9.0
Dataset results
357 results for “supplementary information”
Evaluating refugia in recent human evolution in Africa: Supplementary information
Open the record for dataset details and reuse information.
Supplementary information from: A systematic review of trace elements in the tissues of bats (Chiroptera)
Open the record for dataset details and reuse information.
Supplementary information for: Redundancy analysis, genome-wide association studies, and the pigmentation of brown trout (Salmo trutta L.)
Open the record for dataset details and reuse information.
Supplementary Information for Phylogenetic analyses of ray-finned fishes (Actinopterygii) using collagen type I protein sequences
Open the record for dataset details and reuse information.
Supplementary Information to: Increasing the spatial resolution of cloud property retrievals from Meteosat SEVIRI by use of its high–resolution visible channel: Evaluation of candidate approaches with MODIS observations
<p>This repository contains the Python programmes and datasets used for</p> <p>the research described in the following paper:<br> https://doi.org/10.5194/amt-2019-334</p> <p>It has been prepared as supplementary information to the final paper.<br> <br> Note that the actual Cloud Property Retrieval (CPP) which would be<br> required for full reproducability of the results cannot be made<br> available by the authors, that the code included here is based on Python2, and that<br> paths to the dataset have to be adapted in the code.<br> <br> The repository consists of three separate parts/directories:<br> <br> * method: Python routines for generating the cloud property retrieval<br> input based on the Meteosat and MODIS data<br> <br> * analysis: Python routines for analysing the different experiments<br> from the CPP outputs, producing the figures and calculating the<br> comparison statistics<br> <br> * datasets: the various input and output datasets used for the<br> analyses of the paper</p>
Supplementary material 2 from: Chapman AD, Belbin L, Zermoglio PF, Wieczorek J, Morris PJ, Nicholls M, Rees ER, Veiga AK, Thompson A, Saraiva AM, James SA, Gendreau C, Benson A, Schigel D (2020) Developing Standards for Improved Data Quality and for Selecting Fit for Use Biodiversity Data. Biodiversity Information Science and Standards 4: e50889. https://doi.org/10.3897/biss.4.50889
Use cases were collected using a number of methods to maximise responses. Lead authors of papers published using data accessed via the Atlas of Living Australia (ALA) were contacted and asked to contribute their research data use cases, and a number of papers describing fitness for use determination were sent to the ALA Data Quality group. Fitness for use and quality check information from these papers were extracted and transferred to the use case library. These are the results of those surveys.
Supplementary material 4 from: Chapman AD, Belbin L, Zermoglio PF, Wieczorek J, Morris PJ, Nicholls M, Rees ER, Veiga AK, Thompson A, Saraiva AM, James SA, Gendreau C, Benson A, Schigel D (2020) Developing Standards for Improved Data Quality and for Selecting Fit for Use Biodiversity Data. Biodiversity Information Science and Standards 4: e50889. https://doi.org/10.3897/biss.4.50889
Description and specifications for the tests following the conventions of the Fitness For Use Framework. This supplement is a copy of https://github.com/tdwg/bdq/blob/master/tg2/core/TG2_tests.csv as of commit 941e774 2019-Aug-20.
Supplementary material 3 from: Chapman AD, Belbin L, Zermoglio PF, Wieczorek J, Morris PJ, Nicholls M, Rees ER, Veiga AK, Thompson A, Saraiva AM, James SA, Gendreau C, Benson A, Schigel D (2020) Developing Standards for Improved Data Quality and for Selecting Fit for Use Biodiversity Data. Biodiversity Information Science and Standards 4: e50889. https://doi.org/10.3897/biss.4.50889
Counts of occurrence records in 2019-04-15 snapshot of GBIF-mediated data that fit the three categories of expected responses for each of the event date-related validation tests.
Supplementary material 1 from: Chapman AD, Belbin L, Zermoglio PF, Wieczorek J, Morris PJ, Nicholls M, Rees ER, Veiga AK, Thompson A, Saraiva AM, James SA, Gendreau C, Benson A, Schigel D (2020) Developing Standards for Improved Data Quality and for Selecting Fit for Use Biodiversity Data. Biodiversity Information Science and Standards 4: e50889. https://doi.org/10.3897/biss.4.50889
Vocabulary of Terms used for the TDWG Task Group on Data Quality Tests and Assertions, plus key additional terms from the Use Case Study. Ther terms are consistent with the terms used in the Fitness for Use Framework (Veiga et al. 2017)
Figure S1 in Supplementary information: Bat coronavirus phylogeography in the Western Indian Ocean
Figure S1. Mean CoV prevalence (± 95% confidence interval) as function of the bat family. Letters a–c above the bars refer to significantly different averages based upon a Pairwise test. Bars can have more than one letter to reflect the "overlap" between them.
Figure S3 in Supplementary information: Bat coronavirus phylogeography in the Western Indian Ocean
Figure S3. Mean CoV prevalence (mean ± 95% confidence interval) as function of the bat sampling season in Mozambique.
Improving early estimates of large earthquake's final fault lengths and magnitudes leveraging source fault structural maturity information - supplementary data
<p>Supplementary dataset for <em>Improving early estimates of large ea­­rthquake’s final fault lengths and magnitudes leveraging source fault structural maturity information. </em>This contains individual performance test results for the algorithm discussed in this publication for each earthquake included in the study</p>
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>
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
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>
Supplementary material 3 from: Duron Q, Cornulier T, Vidal E, Bourguet E, Ruffino L (2020) Combining live and lethal trapping to inform the management of alien invasive rodent populations in a tropical montane forest. NeoBiota 63: 101-125. https://doi.org/10.3897/neobiota.63.53811
Mean distances (± se) of trapped rats from the edge of the removal area during the four trapping sessions
Supplementary material 4 from: Duron Q, Cornulier T, Vidal E, Bourguet E, Ruffino L (2020) Combining live and lethal trapping to inform the management of alien invasive rodent populations in a tropical montane forest. NeoBiota 63: 101-125. https://doi.org/10.3897/neobiota.63.53811
Distances (in meters) travelled between rats' home range centers in the CMR area and their recapture in the removal area for 27 individuals
Supplementary information for integrating sequence capture and restriction-site associated DNA sequencing to resolve recent radiations of Pelagic seabirds
<p><b>The diversification of modern birds has been shaped by a number of radiations. Rapid diversification events make reconstructing the evolutionary relationships among taxa challenging due to the convoluted effects of incomplete lineage sorting (ILS) and introgression. Phylogenomic datasets have the potential to detect patterns of phylogenetic incongruence, and to address their causes. However, the footprints of ILS and introgression on sequence data can vary between different phylogenomic markers at different phylogenetic scales depending on factors such as their evolutionary rates or their selection pressures. We show that combining phylogenomic markers that evolve at different rates, such as paired-end double-digest restriction site-associated DNA (PE-ddRAD) and ultraconserved elements (UCEs), allows a comprehensive exploration of the causes of phylogenetic discordance associated with short internodes at different timescales. We used thousands of UCE and PE-ddRAD markers to produce the first well-resolved phylogeny of shearwaters, a group of medium-sized pelagic seabirds amongst the most phylogenetically controversial and endangered bird groups. We found that phylogenomic conflict was mainly derived from high levels of ILS due to rapid speciation events. We also documented a case of introgression, despite the high philopatry of shearwaters to their breeding sites, which typically limits gene flow. We integrated state-of-the-art concatenated and coalescent-based approaches to expand on previous comparisons of UCE and RAD-Seq datasets for phylogenetics, divergence time estimation and inference of introgression, and we propose a strategy to optimise RAD-Seq data for phylogenetic analyses. Our results highlight the usefulness of combining phylogenomic markers evolving at different rates to understand the causes of phylogenetic discordance at different timescales.</b></p>
Supplementary information for: "A voltage-dependent fluorescent indicator for optogenetic applications, archaerhodopsin-3: Structure and optical properties from in silico modeling".
<p>This is supplementary data for F1000Research article: A voltage-dependent fluorescent indicator for optogenetic applications, archaerhodopsin-3: Structure and optical properties from in silico modeling.</p> <p>Here are files for modeling archaerhodopsin-3 with I-TASSER, Medeller and RosettaCM algorithms, structure postprocessing and spectra calculations.</p> <p>Please, refer to the readme.txt for the description.</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.