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1,249 results for “R data”
Supplementary material 1 from: Niehues A, de Visser C, Hagenbeek FA, Karu N, Kindt ASD, Kulkarni P, Pool R, Boomsma DI, van Dongen J, van Gool AJ, `t Hoen PAC (2022) A Multi-omics Data Analysis Workflow Packaged as a FAIR Digital Object. Research Ideas and Outcomes 8: e94042. https://doi.org/10.3897/rio.8.e94042
Members of the ACTION Consortium
Adaptive Empirical Modeling Data for "Thin Current Sheet Formation and Reconnection at $X\sim$-10\,R$_E$ during the Main Phase of a Magnetic Storm"
<p>The ZIP file contains results of AM03 model run for the magnetic storm event on 17 June 2012. </p>
Supplementary material 1 from: Martin-Cabrera P, Perez Perez R, Irrison J-O, Lombard F, Ove Möller K, Rühl S, Creach V, Lindh M, Stemmann L, Schepers L (2022) Establishing Plankton Imagery Dataflows Towards International Biodiversity Data Aggregators. Biodiversity Information Science and Standards 6: e94196. https://doi.org/10.3897/biss.6.94196
Imagery dataset example
Data from the rfPred R package
<p>Large dataset to be used with the rfPred R package</p>
R Code for Count data, spatial data, environmental data - Dee Estuary Waders 1970-2020
<p>R Code for analysis of spatio temporal data of waders on the Dee Estuary</p>
Supplementary material 1 from: Cardoso A, Tsiamis K, Gervasini E, Schade S, Taucer F, Adriaens T, Copas K, Flevaris S, Galiay P, Jennings E, Josefsson M, López B, Magan J, Marchante E, Montani E, Roy H, von Schomberg R, See L, Quintas M (2017) Citizen Science and Open Data: a model for Invasive Alien Species in Europe. Research Ideas and Outcomes 3: e14811. https://doi.org/10.3897/rio.3.e14811
Appendix 2.
Supplementary material 1 from: Radek R, Wurzbacher C, Gisder S, Nilsson RH, Owerfeldt A, Genersch E, Kirk PM, Voigt K (2017) Morphologic and molecular data help adopting the insect-pathogenic nephridiophagids (Nephridiophagidae) among the early diverging fungal lineages, close to the Chytridiomycota. MycoKeys 25: 31-50. https://doi.org/10.3897/mycokeys.25.12446
Figure S1 : Data type: molecular data
Supplementary material 1 from: Vissers J, Bosch FV, Bogaerts A, Cocquyt C, Degreef J, Diagre D, de Haan M, De Smedt S, Engledow H, Ertz D, Fabri R, Godefroid S, Hanquart N, Mergen P, Ronse A, Sosef M, Stévart T, Stoffelen P, Vanderhoeven S, Groom Q (2017) Scientific user requirements for a herbarium data portal. PhytoKeys 78: 37-57. https://doi.org/10.3897/phytokeys.78.10936
Gathered needs per type of researcher :
Figure 1 from: Cardoso A, Tsiamis K, Gervasini E, Schade S, Taucer F, Adriaens T, Copas K, Flevaris S, Galiay P, Jennings E, Josefsson M, López B, Magan J, Marchante E, Montani E, Roy H, von Schomberg R, See L, Quintas M (2017) Citizen Science and Open Data: a model for Invasive Alien Species in Europe. Research Ideas and Outcomes 3: e14811. https://doi.org/10.3897/rio.3.e14811
Figure 1 - Participants of the workshop on "Citizen Science and Open Data: a model for Invasive Alien Species in Europe". Image: COST Association.
Figure 4 from: Cardoso A, Tsiamis K, Gervasini E, Schade S, Taucer F, Adriaens T, Copas K, Flevaris S, Galiay P, Jennings E, Josefsson M, López B, Magan J, Marchante E, Montani E, Roy H, von Schomberg R, See L, Quintas M (2017) Citizen Science and Open Data: a model for Invasive Alien Species in Europe. Research Ideas and Outcomes 3: e14811. https://doi.org/10.3897/rio.3.e14811
Figure 4 - Flipchart with participants notes addressing the topic "Main characteristics of a model for a citizen participation replicable across different policies" during Session 1. Image: COST Association.
Figure 3 from: Cardoso A, Tsiamis K, Gervasini E, Schade S, Taucer F, Adriaens T, Copas K, Flevaris S, Galiay P, Jennings E, Josefsson M, López B, Magan J, Marchante E, Montani E, Roy H, von Schomberg R, See L, Quintas M (2017) Citizen Science and Open Data: a model for Invasive Alien Species in Europe. Research Ideas and Outcomes 3: e14811. https://doi.org/10.3897/rio.3.e14811
Figure 3 - Discussion of a round table through the "world café" method, addressing the topic "List of methods for mainstreaming inputs from CS in policy making including quality assurance and validations and other parameters" during Session 1. Image: COST Association.
Figure 2 from: Cardoso A, Tsiamis K, Gervasini E, Schade S, Taucer F, Adriaens T, Copas K, Flevaris S, Galiay P, Jennings E, Josefsson M, López B, Magan J, Marchante E, Montani E, Roy H, von Schomberg R, See L, Quintas M (2017) Citizen Science and Open Data: a model for Invasive Alien Species in Europe. Research Ideas and Outcomes 3: e14811. https://doi.org/10.3897/rio.3.e14811
Figure 2 - Discussion of a round table through the "world café" method, addressing the topic "List of successful case-studies and examples of good practices in environment and IAS" during Session 1. Image: COST Association.
Figure 1 from: Vanderhoeven S, Adriaens T, Desmet P, Strubbe D, Backeljau T, Barbier Y, Brosens D, Cigar J, Coupremanne M, De Troch R, Eggermont H, Heughebaert A, Hostens K, Huybrechts P, Jacquemart A, Lens L, Monty A, Paquet J, Prévot C, Robertson T, Termonia P, Van De Kerchove R, Van Hoey G, Van Schaeybroeck B, Vercayie D, Verleye T, Welby S, Groom Q (2017) Tracking Invasive Alien Species (TrIAS): Building a data-driven framework to inform policy. Research Ideas and Outcomes 3: e13414. https://doi.org/10.3897/rio.3.e13414
Figure 1 - A visual description of the TrIAS workflow through work packages. Work package 1 generates the input data; Work package 2 creates indicators and summaries of the data; Work package 3 uses the data and generates models and predications of future distributions; Work package 4 involves experts using the information from the other work packages, together with their own experience to create impact assessments.
Figures 1-9 from: Radek R, Wurzbacher C, Gisder S, Nilsson RH, Owerfeldt A, Genersch E, Kirk PM, Voigt K (2017) Morphologic and molecular data help adopting the insect-pathogenic nephridiophagids (Nephridiophagidae) among the early diverging fungal lineages, close to the Chytridiomycota. MycoKeys 25: 31-50. https://doi.org/10.3897/mycokeys.25.12446
Figures 1-9 Nephridiophaga maderae, 1, 2, 5–9 bright field 3 phase contrast 4 scanning electron microscopy. 1 Three sporogonial plasmodia with different numbers of included spores. Arrows point to plasma membrane. 2 Merogonial plasmodium with numerous nuclei. 3 Mature spores. 4 The upper surface of the spore possesses a central spore opening (arrow, left spore) while the lower surface of the spore lacks an opening (right spore). 5, 6 Paraffin sections stained with hematoxylin-eosin. Generally, the plasmodia (pl) are found in the lumen of the Malpighian tubule but are often attached to the microvilli (mv) (5). Rarely, aggregates of vegetative plasmodia (arrow) occur in the epithelial cells of the Malpighian tubules (6). n = nuclei of epithelial cells. 7–9 Smears of macerated tubules stained with Giemsa depicting vegetative plasmodia (7), stained young spores (8), and unstained mature spores with residual nuclei (arrows) of the mother sporoplasm. Scale bars: 5 µm (1–4), 50 µm (5), 10 µm (6–9).
Figures 10-14 from: Radek R, Wurzbacher C, Gisder S, Nilsson RH, Owerfeldt A, Genersch E, Kirk PM, Voigt K (2017) Morphologic and molecular data help adopting the insect-pathogenic nephridiophagids (Nephridiophagidae) among the early diverging fungal lineages, close to the Chytridiomycota. MycoKeys 25: 31-50. https://doi.org/10.3897/mycokeys.25.12446
Figures 10-14 Nephridiophaga blattellae, 10–13 transmission electron microscopy, 14 Calcofluor white staining. 10 Meront with several nuclei (n) and mitochondria (mi) in the lumen of Malpighian tubule. Inset: Mitochondrium with tubular to sac-like cristae. 11 Sporogenic plasmodium containing mature spores (sp), mitochondria (mi), and vegetative nuclei (n) in the cytoplasm. The plasmodium is anchored to the microvilli (mv) of epithelial cells (ep) of the tubule. 12 Young spore within the cytoplasm of a sporogenic plasmodium, surrounded by a layer of vesicles. The spore cytoplasm contains one nucleus (n), mitochondria (mi), and endoplasmic reticulum (er). 13 An infectious sporoplasm hatches through the central spore opening, leaving behind the spore wall of the emptying spore (sp). The nucleus (n) is squeezed through the tiny spore opening. 14 Calcofluor white stains the spore wall indicating the presence of chitin (bluish color). Scale bars: 1 µm (10–13), inset 0.1 µm (10), 5 µm (14).
Figure 15 from: Radek R, Wurzbacher C, Gisder S, Nilsson RH, Owerfeldt A, Genersch E, Kirk PM, Voigt K (2017) Morphologic and molecular data help adopting the insect-pathogenic nephridiophagids (Nephridiophagidae) among the early diverging fungal lineages, close to the Chytridiomycota. MycoKeys 25: 31-50. https://doi.org/10.3897/mycokeys.25.12446
Figure 15 - Bayesian phylogenetic tree including major lineages of the Holomycota (Liu et al. 2009; syn.: Nucletmycea, Brown et al. 2009), i.e. Fungi, Cryptomycota, and the basal Nucleariida, together with Holomycota sister clades Choanomonada, Ichthyosporea, and Filasterea (Holozoa; Lang et al. 2002). Nephridiophaga species (star) form a clade together with the flagellate fungi, here indicated as Chytridiomycota s.l. The scale indicates expected changes per site. Branch support is given as Bayesian posterior probabilities above 0.95 (black circles) and maximum likelihood resampling values above 90% (white circles). Filled black circles mark support from both methods.
Figure 1 from: Huntenburg J, Wagstyl K, Steele C, Funck T, Bethlehem R, Foubet O, Larrat B, Borrell V, Bazin P (2017) Laminar Python: tools for cortical depth-resolved analysis of high-resolution brain imaging data in Python. Research Ideas and Outcomes 3: e12346. https://doi.org/10.3897/rio.3.e12346
Figure 1 - Laminar python pipeline, demonstrated using high-resolution MR data of a ferret brain. a) Binary images demarcating inner (grey-white matter interface, top) and outer (pial surface, bottom) boundaries of the cortex. b) Levelset representations of the same surfaces, where positive values are assigned to voxels outside of the volume deliminated by the surface, and negative values to voxels inside, each increasing in value with euclidean distance from the surface. c) Continuous equivolumetric intracortical depth, which models the positions of laminae relative to cortical morphology. d) Discrete representations of equivolumetric depth levels. e) T2 values, sampled at the six equivolumetric intracortical depths. Note that the equivolumetric laminae do not represent architectonic layers, but provide an anatomically meaningful coordinate system of cortical depth.
Figure 1 from: Vissers J, Bosch FV, Bogaerts A, Cocquyt C, Degreef J, Diagre D, de Haan M, De Smedt S, Engledow H, Ertz D, Fabri R, Godefroid S, Hanquart N, Mergen P, Ronse A, Sosef M, Stévart T, Stoffelen P, Vanderhoeven S, Groom Q (2017) Scientific user requirements for a herbarium data portal. PhytoKeys 78: 37-57. https://doi.org/10.3897/phytokeys.78.10936
Figure 1 - Stakeholders interacting with the Botanic Garden Meise and potentially using its data portal. The stakeholders prefixed by the words 'internal' refer to those that work at the Botanic Garden, whereas those referred to as 'external' refer to researchers in other institutions.
Figure 3 from: Vissers J, Bosch FV, Bogaerts A, Cocquyt C, Degreef J, Diagre D, de Haan M, De Smedt S, Engledow H, Ertz D, Fabri R, Godefroid S, Hanquart N, Mergen P, Ronse A, Sosef M, Stévart T, Stoffelen P, Vanderhoeven S, Groom Q (2017) Scientific user requirements for a herbarium data portal. PhytoKeys 78: 37-57. https://doi.org/10.3897/phytokeys.78.10936
Figure 3 - A summary of the data elements mentioned by the different researcher types, showing which data elements researchers had in common and which were unique. This does not mean that any particular data element is not of interest to another group, only that it did not arise in the series of interviews. Details of these data elements can be found in the supplementary information. The full list of common data elements is listed in Table 2.
Figure 2 from: Vissers J, Bosch FV, Bogaerts A, Cocquyt C, Degreef J, Diagre D, de Haan M, De Smedt S, Engledow H, Ertz D, Fabri R, Godefroid S, Hanquart N, Mergen P, Ronse A, Sosef M, Stévart T, Stoffelen P, Vanderhoeven S, Groom Q (2017) Scientific user requirements for a herbarium data portal. PhytoKeys 78: 37-57. https://doi.org/10.3897/phytokeys.78.10936
Figure 2 - A user experience researcher using affinity diagramming to cluster user requirements from the results of the interviews.
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.