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493 results for “Iris”
Edgar Anderson's Iris Data
<p>This famous (Fisher's or Anderson's) iris data set gives the measurements in centimeters of the variables sepal length and width and petal length and width, respectively, for 50 flowers from each of 3 species of iris. The species are Iris setosa, versicolor, and virginica.</p> <p>The <em>iris_dataset.rds</em> serialisation is a replication of datasets::iris_dataset as dataset s3 class.</p> <p>The <em>iris_dataset.csv </em>serialisation is an incomplete replication of the iris_dataset because the CSV file does not contain important semantic information; that is exported to <em>iris_dataset.json</em> (in a not standardised form) and the dataset-level metadata into the <em>iris_dataset.bib </em>BibLatex text file.</p>
IRIS: ICESat-2 River Surface Slope
<p><strong>ICESat-2 River Surface Slope (IRIS)</strong></p> <p>When using this data please cite<strong> </strong><em>Scherer D., Schwatke C., Dettmering D., Seitz F.</em>: <strong>ICESat-2 river surface slope (IRIS): A global reach-scale water surface slope dataset</strong>. Scientific Data, 10(1), 359, <a href="https://doi.org/10.1038/s41597-023-02215-x">10.1038/s41597-023-02215-x</a>, 2023.</p> <p>A detailed description of the methodology and validation is published in <em>Scherer D., Schwatke C., Dettmering D., Seitz F. </em>: <strong>ICESat-2 Based River Surface Slope and Its Impact on Water Level Time Series From Satellite Altimetry</strong>. Water Resources Research, <a href="http://doi.org/10.1029/2022WR032842">10.1029/2022WR032842</a>, 2022.</p> <p><strong>1. Summary</strong><br>The unique multibeam lidar altimeter of ICESat-2 is used to measure reach-scale water surface slope (WSS) every time the spacecraft’s orbit crosses a reach. The method of deriving WSS from simultaneous ICESat-2 ATL13 (<em>Jasinski et al., 2021</em>) observations is described in detail and validated in <em>Scherer et al. </em>(2022). In this ICESat-2 River Surface Slope (IRIS) dataset, we provide the minimum, average, and maximum slope derived with three different approaches (across, along, and combined) per reach. Additionally, we give the standard deviation and epochs of the derived WSS data. The reaches are defined by the SWOT River Database (SWORD, <em>Altenau et al., 2021</em>).</p> <p>An interactive map is available at <a href="https://dahiti.dgfi.tum.de/en/products/water-surface-slope/.">DAHITI</a>.</p> <p><strong>2. Version History</strong></p> <p>IRIS <strong>v0</strong>: Only includes the reaches studied in Scherer et al. (2022).<br>Based on ICESat-2 ATL13 v5, Cycle 1-13 (October 2018 to October 2021) and SWORD Version v1.</p> <p>IRIS <strong>v1</strong>: Global coverage (limited by ICESat-2 data availability and cloud cover).<br>Based on ICESat-2 ATL13 v5, Cycle 1-16 (October 2018 to August 2022) and SWORD Version v2.</p> <p>IRIS <strong>v2</strong>: Global coverage with 6,083 additional reaches and 92,347 more observations compared to v1.<br>Based on ICESat-2 ATL13 <strong>v6</strong>, Cycle 1-19 (October 2018 to April 2023) and SWORD Version v15.</p> <p>IRIS <strong>v2.1</strong>: Based on ICESat-2 ATL13 v6, Cycle 1-19 (October 2018 to April 2023) and <strong>SWORD Version v16</strong>.</p> <p>IRIS <strong>v2.2</strong>: 3,251 additional reaches and 58,862 new observations compared to v2.1.<br>Based on ICESat-2 ATL13 v6, Cycle 1-<strong>20</strong> (October 2018 to <strong>August</strong> 2023) and SWORD Version v16.</p> <p>IRIS <strong>v2.3</strong>: 1,595 additional reaches and 32,590 new observations compared to v2.2.<br>Based on ICESat-2 ATL13 v6, Cycle 1-<strong>21</strong> (October 2018 to <strong>October </strong>2023) and SWORD Version v16.</p> <p>IRIS <strong>v2.6</strong>: 2,755 additional reaches and 362,136 new observations compared to v2.3.<br>Based on ICESat-2 ATL13 v6, Cycle 1-<strong>23</strong> (October 2018 to <strong>May 2024</strong>) and SWORD Version v16.</p> <p>IRIS <strong>v2.9</strong>: 2,485 additional reaches and 184,549 new observations compared to v2.6.<br>Based on ICESat-2 ATL13 v6, Cycle 1-<strong>24</strong> (October 2018 to <strong>August 2024</strong>) and SWORD Version v16.<br>Fixed some broken geometries in the gpkg data.</p> <p>IRIS <strong>v3.0</strong>: Based on ICESat-2 ATL13 v6, Cycle 1-24 (October 2018 to August 2024) and <strong>SWORD Version</strong> <strong>v17</strong>.</p> <p>IRIS <strong>v3.2</strong>: 1,370 additional reaches and 210,951 new observations compared to v3.0.<br>Based on ICESat-2 ATL13 v6, Cycle 1-<strong>26</strong> (October 2018 to <strong>December 2024</strong>) and SWORD Version v17.</p> <p><strong>3. Data Format and Variable Description</strong></p> <p>From Version 2.6, <strong>IRIS is also available as GeoPackage</strong>.<br>The IRIS data is stored in a single NetCDF4 file which is structured in a single group containing the following variables:<br><strong><em>reach_id</em></strong>:<br>The SWORD reach identifier [-]<br><strong><em>lon</em></strong>:<br>Approx. centroid longitude of the SWORD reach [degrees east]<br><strong><em>lat</em></strong>:<br>Approx. centroid latitude of the SWORD reach [degrees north]<br><strong><em>across_flag, along_flag, combined_flag:</em></strong><br>Flags indicating whether ICESat-2 [across/along/combined] slope is available (1) for the reach or not (0) [-]<br><strong><em>avg_across_slope, avg_along_slope, avg_combined_slope:</em></strong><br>Average (median) ICESat-2 [across/along/combined] slope for the reach [mm/km]<br><strong><em>min_across_slope, min_along_slope, min_combined_slope:</em></strong><br>Minimum ICESat-2 [across/along/combined] slope for the reach [mm/km]<br><strong><em>max_across_slope, max_along_slope, max_combined_slope:</em></strong><br>Maximum ICESat-2 [across/along/combined] slope for the reach [mm/km]<br><strong><em>std_across_slope, std_along_slope, std_combined_slope:</em></strong><br>ICESat-2 [across/along/combined] slope standard deviation for the reach [mm/km]<br><strong><em>n_across_slope, n_along_slope, n_combined_slope:</em></strong><br>Number of days with ICESat-2 [across/along/combined] slope observations for the reach [-]<br><strong><em>min_date_across_slope, min_date_along_slope:, min_date_combined_slope:</em></strong><br>First date of ICESat-2 [across/along/combined] slope observations for the reach [days since 2000-01-01]<br><strong><em>max_date_across_slope, max_date_along_slope:, max_date_combined_slope:</em></strong><br>Latest date of ICESat-2 [across/along/combined] slope observations for the reach [days since 2000-01-01]</p> <p><strong>4. References</strong></p> <p><em>Scherer D., Schwatke C., Dettmering D., Seitz F.</em>: <strong>ICESat-2 river surface slope (IRIS): A global reach-scale water surface slope dataset</strong>. Scientific Data, 10(1), 359, <a href="https://doi.org/10.1038/s41597-023-02215-x">10.1038/s41597-023-02215-x</a>, 2023<br><em>Scherer D., Schwatke C., Dettmering D., Seitz F. (2022): <strong>ICESat-2 Based River Surface Slope and Its Impact on Water Level Time Series From Satellite Altimetry</strong>, Water Resources Research, https://doi.org/10.1029/2022WR032842</em><br><em>Jasinski M., Stoll J., Hancock D., Robbins J., Nattala J., Morison J., Jones B., Ondrusek M., Pavelsky T.M., Parrish C. and the ICESat-2-Science-Team (2021). <strong>ATLAS/ICESat-2 L3A Inland Water Surface Height</strong>, Version 5. [Dataset]</em><br><em>Altenau E.H., Pavelsky T.M., Durand, M.T., Yang X., Frasson, R.P.d.M., Bendezu, L. (2021): <strong>SWOT River Database (SWORD)</strong> [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3898569</em></p>
Ionospheric Vertical Correlation Lengths Derived From IRI-2016 Model Errors
<p>Ionospheric vertical correlation lengths based on IRI-2016 model and Incoherent Scatter Radar (ISR) data.</p> <p><strong>Important! The analysis was performed in log space. </strong></p> <p>ISR used for this analysis:</p> <p>Jicamarca, Arecibo, Millstone Hill, Poker Flat ISR, and ResoluteBay North ISR.</p> <p>This metadata can be used for the construction of the covariance matrix for ionospheric data assimilation.</p> <p>Inside of the .nc file:</p> <p>lat=array of geomagnetic latitudes (degrees)<br> alt=arrays of altitudes (km)<br> vert_corr1=array of size (nalt, nlat), contains vertical correlation length above the reference point for different latitudes<br> vert_corr2=array of size (nalt, nlat), contains vertical correlation length below the reference point for different latitudes<br> </p>
Dataset for "IRIS analyser assessment reveals sub-hourly variability of isotope ratios in carbon dioxide at Baring Head, New Zealand's atmospheric observatory in the Southern Ocean"
<p>Dataset for</p> <p>Sperlich, P., Brailsford, G. W., Moss, R. C., McGregor, J., Martin, R. J., Nichol, S., Mikaloff-Fletcher, S., Bukosa, B., Mandic, M., Schipper, I., Krummel, P. and Griffiths, A. D.: IRIS analyser assessment reveals sub-hourly variability of isotope ratios in carbon dioxide at Baring Head, New Zealand's atmospheric observatory in the Southern Ocean, Atmos. Meas. Tech., https://doi.org/10.5194/amt-15-1-2022, 2022.</p>
Herbarium specimen image of Iris tenuifolia Pall., part of the collection of Royal Botanic Garden Edinburgh
Part of a training dataset of scanned herbarium specimens. The data paper and a summary landing page will be published on Zenodo as it gets published.<br><br>Content of this deposition:<br><br>- A JSON-LD datafile listing the label data associated with this herbarium specimen. The Darwin and Dublin Core data standards are used for most values.<br>- A JPEG image file of the scanned herbarium sheet.<br>- A lossless TIFF image from which the JPEG image has been derived.<br>- Two PNG files containing segmented image overlays of the scanned herbarium sheet. The _all extension indicates that all labels, color charts and pieces of text have received a different color against a black background color. The _sel extension indicates that these elements are white if they're barcode labels, yellow if they're color charts and red if they're anything else.
Herbarium specimen image of Iris chamaeiris Bertol., part of the collection of National Museum of Natural History, Paris
Part of a training dataset of scanned herbarium specimens. The data paper and a summary landing page will be published on Zenodo as it gets published.<br><br>Content of this deposition:<br><br>- A JSON-LD datafile listing the label data associated with this herbarium specimen. The Darwin and Dublin Core data standards are used for most values.<br>- A JPEG image file of the scanned herbarium sheet.
Metrics As Scores Dataset: The Iris Flower Data Set
<p>The Iris flower data set or Fisher’s Iris data set is a multivariate data set used and made famous by the British statistician and biologist Ronald Fisher. The dataset was introduced in his 1936 paper "The Use of Multiple Measurements in Taxonomic Problems" (Fisher 1936) as an example of linear discriminant analysis.</p> <p>This dataset has the following Features:</p> <ul> <li><em>Petal.Length</em>: Length of the petal</li> <li><em>Petal.Width</em>: Width of the petal</li> <li><em>Sepal.Length</em>: Length of the sepal</li> <li><em>Sepal.Width</em>: Width of the sepal</li> </ul> <p>It has a total of 3 <strong>Groups</strong>: <em>setosa</em>, <em>versicolor</em>, and <em>virginica</em>.</p>
IRIS preprocessed data used in paper "Multi variables time series information bottleneck"
<p>Prprocessed data used in paper "Multi variables time series information bottleneck" with the <a href="https://github.com/DenisUllmann/IB-MTS">GitHub</a> code</p> <p>This dataset is created from a public available dataset of observations performed by IRIS, a NASA small explorer mission developed and operated by LMSAL with mission operations executed at NASA Ames Research Center and major contributions to downlink communications funded by ESA and the Norwegian Space Centre.</p> <p>Multiple Time Series of IRIS level 2 data are available <a href="https://iris.lmsal.com/search/">here</a></p> <p>The selected data was labeled using these definitions:</p> <p>QS: Quiet Sun<br> AR: Active Regions of the Sun<br> FL: Flare</p> <p>A time series is labeled QS when every single time step refer to a quiet sun activity.<br> When a given time series is partially composed of flaring events, the global time series is labeled as FL.</p> <p>The npz file is a numpy (np) compressed data and can be loaded using np.load with allow_pickle=True<br> Loaded data is then a python dict described bellow.</p> <p>Each sample 'data' is a np.ndarray with 2 dimensions: time (various length) and wavelength (length=240 representing a range between 2793.8401Å and 2806.02Å).</p> <p>Each sample is given a 'position' which is a list of length 4:<br> position[1] is a string that gives the name of the event<br> position[4] is a boolean vector that gives the time positionsof the corresponding sample in the original sequence of public IRIS level2 data</p> <p>Data file info :</p> <p>Type: .npz<br> Size: 11.89GB</p> <p>*** Key: 'data_TR_QS'<br> ndarray data of length 2467<br> containing np.ndarray of shapes ['various', 240]</p> <p> </p> <p>*** Key: 'data_TR_AR'<br> ndarray data of length 1042<br> containing np.ndarray of shapes ['various', 240]</p> <p> </p> <p>*** Key: 'data_TR_FL'<br> ndarray data of length 1055<br> containing np.ndarray of shapes ['various', 240]</p> <p> </p> <p>*** Key: 'data_VAL_QS'<br> ndarray data of length 325<br> containing np.ndarray of shapes ['various', 240]</p> <p> </p> <p>*** Key: 'data_VAL_AR'<br> ndarray data of length 1042<br> containing np.ndarray of shapes ['various', 240]</p> <p> </p> <p>*** Key: 'data_VAL_FL'<br> ndarray data of length 714<br> containing np.ndarray of shapes ['various', 240]</p> <p> </p> <p>*** Key: 'data_TE_QS'<br> ndarray data of length 1428<br> containing np.ndarray of shapes ['various', 240]</p> <p> </p> <p>*** Key: 'data_TE_AR'<br> ndarray data of length 792<br> containing np.ndarray of shapes ['various', 240]</p> <p> </p> <p>*** Key: 'data_TE_FL'<br> ndarray data of length 356<br> containing np.ndarray of shapes ['various', 240]</p> <p> </p> <p>*** Key: 'data_TR'<br> ndarray data of length 4564<br> containing np.ndarray of shapes ['various', 240]</p> <p> </p> <p>*** Key: 'data_VAL'<br> ndarray data of length 2081<br> containing np.ndarray of shapes ['various', 240]</p> <p><br> *** Key: 'data_TE'<br> ndarray data of length 2576<br> containing np.ndarray of shapes ['various', 240]</p> <p> </p> <p>*** Key: 'position_TR_QS'<br> ndarray data of length 2467<br> containing ndarray data of length 4<br> containing mix of types {'ndarray', 'int', 'str'}</p> <p> </p> <p>*** Key: 'position_TR_AR'<br> ndarray data of length 1042<br> containing ndarray data of length 4<br> containing mix of types {'ndarray', 'int', 'str'}</p> <p> </p> <p>*** Key: 'position_TR_FL'<br> ndarray data of length 1055<br> containing ndarray data of length 4<br> containing mix of types {'ndarray', 'int', 'str'}</p> <p> </p> <p>*** Key: 'position_VAL_QS'<br> ndarray data of length 325<br> containing ndarray data of length 4<br> containing mix of types {'ndarray', 'int', 'str'}</p> <p> </p> <p>*** Key: 'position_VAL_AR'<br> ndarray data of length 1042<br> containing ndarray data of length 4<br> containing mix of types {'ndarray', 'int', 'str'}</p> <p> </p> <p>*** Key: 'position_VAL_FL'<br> ndarray data of length 714<br> containing ndarray data of length 4<br> containing mix of types {'ndarray', 'int', 'str'}</p> <p> </p> <p>*** Key: 'position_TE_QS'<br> ndarray data of length 1428<br> containing ndarray data of length 4<br> containing mix of types {'ndarray', 'int', 'str'}</p> <p> </p> <p>*** Key: 'position_TE_AR'<br> ndarray data of length 792<br> containing ndarray data of length 4<br> containing mix of types {'ndarray', 'int', 'str'}</p> <p> </p> <p>*** Key: 'position_TE_FL'<br> ndarray data of length 356<br> containing ndarray data of length 4<br> containing mix of types {'ndarray', 'int', 'str'}</p> <p> </p> <p>*** Key: 'position_TR'<br> ndarray data of length 4564<br> containing ndarray data of length 4<br> containing mix of types {'ndarray', 'int', 'str'}</p> <p> </p> <p>*** Key: 'position_VAL'<br> ndarray data of length 2081<br> containing ndarray data of length 4<br> containing mix of types {'ndarray', 'int', 'str'}</p> <p> </p> <p>*** Key: 'position_TE'<br> ndarray data of length 2576<br> containing ndarray data of length 4<br> containing mix of types {'ndarray', 'int', 'str'}</p>
PROLIFIC_790157_IRIS_WP2_MAE_protein
<p>Technical data regarding the extraction of protein assisted by microwave.</p>
Iris. Rainbow Goddess
<p>This animation shows Iris, the rainbow goddess, taking flight. Iris carried messages from one god to another, especially messages from Zeus and Hera. The ancient Greeks said that rainbows were caused by Iris streaking across the sky, leaving rainbows in her wake. She was called ‘storm-footed’, because storms followed her. Her rainbows were an sign of bad weather, and maybe of bigger trouble such as war.</p> <p>The animation was created from a vase that was made in Athens in around 450BCE. The vase is now housed in the National Museum in Warsaw, in Poland (number 142289).</p>
Iris cristata (Iridaceae) - inflorescence - frontal view of flower
Image of Iris cristata (Iridaceae) - inflorescence - frontal view of flower
Iris cristata (Iridaceae) - inflorescence - lateral view of flower
Image of Iris cristata (Iridaceae) - inflorescence - lateral view of flower
Iris cristata (Iridaceae) - inflorescence - frontal view of flower
Image of Iris cristata (Iridaceae) - inflorescence - frontal view of flower
Iris cristata (Iridaceae) - whole plant - in flower - general view
Image of Iris cristata (Iridaceae) - whole plant - in flower - general view
Iris cristata (Iridaceae) - inflorescence - lateral view of flower
Image of Iris cristata (Iridaceae) - inflorescence - lateral view of flower
Iris cristata (Iridaceae) - leaf - basal or on lower stem
Image of Iris cristata (Iridaceae) - leaf - basal or on lower stem
Iris cristata (Iridaceae) - whole plant - in flower - general view
Image of Iris cristata (Iridaceae) - whole plant - in flower - general view
Iris cristata (Iridaceae) - inflorescence - frontal view of flower
Image of Iris cristata (Iridaceae) - inflorescence - frontal view of flower
Iris cristata (Iridaceae) - stem - showing leaf bases
Image of Iris cristata (Iridaceae) - stem - showing leaf bases
Iris cristata (Iridaceae) - inflorescence - whole - unspecified
Image of Iris cristata (Iridaceae) - inflorescence - whole - unspecified
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