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586 results for “March”
UEX1 - March 2022
<p>Measurements of UEX1 (University of Extremadura) in March 2022</p><p>Extremadura</p><p> Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/UEX1">info</a></p>
LPL7 - March 2022
<p>Measurements of LPL7 (Archipielago Chinijo) in March 2022</p><p>Archipielago Chinijo</p><p> Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL7">info</a></p>
LPL2 - March 2022
<p>Measurements of LPL2 (Caldera de Taburiente NP) in March 2022</p><p>La Palma</p><p> Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL2">info</a></p>
Data complementing the Avian influenza overview March – June 2022
<p>Annex A – Characteristics of the HPAI A(H5Nx)-positive poultry establishments</p> <p>The Annex contains table with the characteristics of the HPAI A(H5Nx)-positive poultry establishments by affected EU Member State from 4 March to 1 June 2022.</p> <p>Annex B – Applied prevention and control measures on avian influenza</p> <p>The Annex contains an overview of specific prevention and control measures applied in Albania, Belgium, Bulgaria, Czechia, France, Hungary, Iceland, Italy, Moldova, Kosovo, The Netherlands, Poland, Romania, Slovakia, Spain from 1 December 2021 to 4 March 2022 in relation to HPAI outbreaks in poultry and in wild birds.</p> <p>Annex C – Data on wild birds</p> <p>The Annex contains tables and plots on HPAI notifications in wild birds in Europe.</p>
Dataset of the deleted DOIs extracted from the difference set between Crossref DOIs as of March 2017 and January 2021
<p><strong>Abstract</strong></p> <p>Digital Object Identifiers (DOIs) are regarded as persistent; however, they are sometimes deleted. Deleted DOIs are an important issue not only for persistent access to scholarly content but also for bibliometrics, because they may cause problems in correctly identifying scholarly articles. However, little is known about how much of deleted DOIs and what causes them. We identified deleted DOIs by comparing the datasets of all Crossref DOIs on two different dates, investigated the number of deleted DOIs in the scholarly content along with the corresponding document types, and analyzed the factors that cause deleted DOIs. Using the proposed method, 708,282 deleted DOIs were identified. The majority corresponded to individual scholarly articles such as journal articles, proceedings articles, and book chapters. There were cases of many DOIs assigned to the same content, e.g., retracted journal articles and abstracts of international conferences. We show the publishers and academic societies which are the most common in deleted DOIs. In addition, the top cases of single scholarly content with a large number of deleted DOIs were revealed. The findings of this study are useful for citation analysis and altmetrics, as well as for avoiding deleted DOIs.</p> <p> </p> <p><strong>Data Records</strong></p> <p>The data format of the dataset is JSON lines, where each line is a single record. In this dataset, we identified the deleted DOIs by from the difference set between Crossref DOIs as of March 2017 and January 2021. We note that the file "00_Non-Crossref_DOIs.jsonl.gz" is not deleted DOIs but other files are deleted DOIs. Please refer the conference paper shown in the references for details. Sample of the record is the following.</p> <ul> <li>doi -- DOI name (String), e.g., "10.xxxx/xxxx"</li> <li>whichRA -- Registration agency name or error message for the DOI name according to the “<a href="https://www.doi.org/factsheets/DOIProxy.html#whichra">whichRA?</a>.” (String). "Airiti," "Crossref," "DOI does not exist," "DataCite," "KISTI," "Public," or "mEDRA."</li> <li>redirects -- Redirected URIs for the DOI name obtained by curl command (Array of String), e.g., ["https://doi.org/10.1001/archinte.166.4.387","http://archinte.jamanetwork.com/article.aspx?doi=10.1001/archinte.166.4.387"]</li> <li>redirect_to_other_doi -- The other DOI when the DOI link redirects to. (Array of String), e.g., "[10.1001/archinte.166.4.387]"</li> <li>timestamp -- Date the data was retrieved (Datetime), "2022-01-30T02:10:45Z"</li> <li>label -- The group where the DOI belongs to. Alias DOIs," "DOIs with Deleted Description in Metadata," "DOIs without Redirects," "Defunct DOIs," "Non-Crossref DOIs," "Non-existing DOIs," or "Other DOIs."</li> </ul> <p>As for the file "04_DOIs_with_Deleted_Description_on_Metadata.jsonl.gz," additional records are available as follows.</p> <ul> <li>alias_doi -- Alias DOI name, the same as the value of "doi." (String), e.g., "10.1007/bf00400428."</li> <li>primary_doi -- Primary DOI name for the alias DOI name, the same as the first value of "redirect_to_other_doi". (String), e.g., "10.1007/bf00400429"</li> <li>container_title_of_alias_doi -- the container title for the alias DOI according to the Crossref REST API. e.g., "CrossRef Listing of Deleted DOIs."</li> <li>title_of_alias_doi -- the title for the alias DOI according to the Crossref REST API. e.g., "CrossRef Listing of Deleted DOIs."</li> <li>container_title_of_primary_doi -- the container title for the primary DOI according to the Crossref REST API. e.g., "CrossRef Listing of Deleted DOIs."</li> <li>title_of_alias_doi -- the title for the primary DOI according to the Crossref REST API. e.g., "CrossRef Listing of Deleted DOIs."</li> </ul> <p><strong>References</strong></p> <ul> <li>Kikkawa, J., Takaku, M. & Yoshikane, F. "Analysis of the deletions of DOIs: What factors undermine their persistence and to what extent?", Proceedings of the 26th International Conference on Theory and Practice of Digital Libraries (<a href="http://tpdl2022.dei.unipd.it/"><em>TPDL 2022</em></a>), (to appear), 2022.</li> </ul> <p><strong>FUNDING</strong></p> <ul> <li>JSPS KAKENHI Grant Number <a href="https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-21K21303">JP21K21303</a>, <a href="https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-22K18147">JP22K18147</a>, <a href="https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-20K12543">JP20K12543</a>, and <a href="https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-21K12592">JP21K12592</a></li> </ul>
Born Digital, Born Slippery - Data Modelling for Born Digital/Hybrid objects (March 2022)
<p>The report Preserving and sharing born-digital and hybrid objects from and across the National Collection discusses the challenges for cultural heritage institutions in cataloguing, preserving, and providing access to four born digital and hybrid objects/projects. This response looks at the issues brought up by those discussions, in particular for the purpose of cataloguing, and the extent, within existing cataloguing standards, they can be supported. Where there does not appear to be support within current standards, model development activity is proposed to allow the expansion of the current `born physical` focused cataloguing standards to also handle born digital and hybrid object cataloguing.</p>
Extreme Total Water Level values for different possible combinations along the Southern Veneto, Emilia-Romagna and Northern Marche coastlines
<p><strong>Description:</strong> This data set is the result of the calculation of the extreme values of different Total Water Level combinations, including a range of components (Mean Sea Level, Tide, Residual, wave setup, wave runup). A total of 8 possible combinations:</p> <table> <tbody> <tr> <td> <p><strong>TWL Acronyms</strong></p> </td> <td> <p><strong>Used component</strong></p> </td> </tr> <tr> <td> <p>dCUE</p> </td> <td> <p>MSL (base) + Tide (Highs) + Residual + Estimated nearshore components (setup and runup)</p> </td> </tr> <tr> <td> <p>dCUU</p> </td> <td> <p>MSL (base) + Tide (Highs) + Residual + Univariated nearshore components (setup and runup)</p> </td> </tr> <tr> <td> <p>dTU</p> </td> <td> <p>TWL dynamic [MSL (base) + Tide (Highs) + Residual + Univariated nearshore components (setup and runup)]</p> <p>Based on Sanuy et al. (2020)</p> </td> </tr> <tr> <td> <p>dWUU</p> </td> <td> <p>Water Level [MSL (base) + Tide (Highs) + Residual] + Univariated nearshore components (setup and runup)</p> </td> </tr> <tr> <td> <p>sCUE</p> </td> <td> <p>MSL (base) + Tide (Highs) + Residual + Estimated Setup</p> </td> </tr> <tr> <td> <p>sCUU</p> </td> <td> <p>MSL (base) + Tide (Highs) + Residual + Univariated Setup</p> </td> </tr> <tr> <td> <p>sTU</p> </td> <td> <p>TWL static[ MSL (base) + Tide (Highs) + Residual + Univariated setup]</p> <p>Based on Sanuy et al. (2020)</p> </td> </tr> <tr> <td> <p>sWUU</p> </td> <td> <p>Water Level [ MSL (base) + Tide (Highs) + Residual] + Univariated Setup</p> </td> </tr> </tbody> </table> <div> </div> <div>The database has 3 representative extreme values for each type of frequency of event occurrence (High, Medium, Low).</div> <p>Each coastal point has the data using 3 slopes: 0.02, 0.03, 0.04. The points have a 0.025º (~2.5 km) distance between each other and 20 m depth.</p> <p><strong>Data location</strong>: The points with the data are located along the Italian coast of Regions: Veneto, Emilia-Romagna and Marche. Using the reference system WGS 84 / UTM zone 32N (EPSG:32632).</p> <p><strong>Fundings:</strong> The creation of this dataset was supported by the Autorità di Bacino Distrettuale del Fiume Po in the framework of the project “Approfondimento tecnico-scientifico sui quadri conoscitivi in ambito costiero”, coordinator Prof. P. Ciavola, University of Ferrara.</p> <p><strong>Disclaimer:</strong> Regardless of whether the data is quality-controlled or not, the authors do not accept any responsibility for the correctness and/or appropriate interpretation of the data. The correct and appropriate interpretation of the data must follow scientific rules and is always the exclusive responsibility of the users.</p>
Fig. 15 in New records of rare species in the Mediterranean Sea (March 2021)
Fig. 15: Specimens of Katsuwonus pelamis, captured off Cape Kurtoğlu, Fethiye, southern Aegean Sea (horizontal bar: 100 mm). Photo credit: E. Öçal.
Fig. 13 in New records of rare species in the Mediterranean Sea (March 2021)
Fig. 13: Distolambrus maltzami (Miers, 1881), male, North Aegean Sea, units shown in mm. a) dorsal side of the carapace; b) ventral side of the carapace.
Fig. 8 in New records of rare species in the Mediterranean Sea (March 2021)
Fig. 8: Specimens of Sphyraena viridensis caught in Tarska Cove in Northern Adriatic on 25th January 2020. Photo credit: Antonio Baras.
Fig. 12 in New records of rare species in the Mediterranean Sea (March 2021)
Fig. 12: The Ranzania laevis specimen found stranded on the Kokkini Hani beach in Crete (TL = 63 cm).
Fig. 10 in New records of rare species in the Mediterranean Sea (March 2021)
Fig. 10: Bursa scrobilator scrobilator from South Rethymno, Crete (shell height ~5-7 cm). A) Crabbed shell. B) Living specimen. Photo credit: Stelios Mantadakis.
Fig. 5 in New records of rare species in the Mediterranean Sea (March 2021)
Fig. 5: A) Antipathella subpinnata on rocks encrusted by coralline algae; B) Antipathes dichotoma (left) and Parantipathes larix (right) on small rocks interspersed with sandy mud; C) Leiopathes glaberrima on a vertical rocky wall; D) Detail of the polyps of L. glaberrima. Scale bars: 10 cm.
Fig. 6 in New records of rare species in the Mediterranean Sea (March 2021)
Fig. 6: A) The specimen of Ocypode cursor observed at Palmi, southern Tyrrhenian Sea. A specimen (B) and holes (C) of O. cursor observed at Pizzo Greco, northern Ionian Sea.
Fig. 3 in New records of rare species in the Mediterranean Sea (March 2021)
Fig. 3: A) Individual photographed in 2013 in Cadaqués, representing the first record of Gobius couchi for Spain; B) Specimen PMR VP4929 collected in 2020.
Fig. 11 in New Alien Mediterranean Biodiversity Records (March 2021)
Fig. 11: Two colonies of Arbopercula tenella from Bay of Piran (Slovenia) found in summer (A) and winter (B) 2019. o - operculum, s - spine, sp - spinous process, cry - cryptocyst. 6. CHORDATA
Fig. 2 in New records of rare species in the Mediterranean Sea (March 2021)
Fig. 2: A and B) Individuals of Chalinula nigra growing onto rocky coralligenous substrates in el 'Tajo del Pirata', partially covered by an algal turf. Scale bars are approximate. C) Detail of the oxeas as seen on an optical microscope; scale 5 μm. D) Spongin fibers in a ladder-like reticulation, with primary and secondary fibers undistinguishable; scale 50 μm. E) Detail of the spongin fibers, where several oxea can be seen forming the tracts of the skeleton; scale 50 μm.
Fig. 7 in New Alien Mediterranean Biodiversity Records (March 2021)
Fig. 7: Nudiscintilla cf. glabra from Bodrum (length = 12.3, height = 7.3 mm). Photo credit: Kemal Geyran.
Fig. 4 in New Alien Mediterranean Biodiversity Records (March 2021)
Fig. 4: Turbo radiatus from Saksakiyeh (Lebanon). A) Live specimen in the tide pools of the vermetid reef. B) Ventral and dorsal view of one of the specimens sampled (total height ~4.1 cm).
Fig. 1 in New Alien Mediterranean Biodiversity Records (March 2021)
Fig. 1: Location of new non-indigenous species, as reported in this article. Location numbers correspond to Table 1.
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.