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387 results for “National Survey”
National Open Access Monitor Survey: Organisational Identity: Responses Dataset
<p>This dataset contains the response data from the 'National Open Access Monitor Survey: Organisational Identity which was carried out between 9th October and 9th November 2023 under the National Open Access Monitor Project: <a href="https://zenodo.org/doi/10.5281/zenodo.8420404">https://zenodo.org/doi/10.5281/zenodo.8420404</a></p><p><strong>This survey was run to:</strong></p><ul><li>compile a complete list of Irish research performing organisations (RPO) and research funding organisations (RFO) to be represented by the National Open Access Monitor.</li><li>ensure each organisation/entity is categorised correctly as an RPO or an RFO (or both), as applicable.</li><li>identify if an organisation/entity is publicly funded.</li><li>identify formally affiliated organisations/entities where <strong>all </strong>research outputs of one organisation/entity should also be included in the research outputs of another organisation/entity.</li><li>capture the persistent identifiers for RPOs, RFOs and publishers, to enable identification of relevant research outputs for the National Open Access Monitor.</li></ul><p><strong>To note: </strong></p><ul><li>Respondents' email addresses have been redacted.</li><li>Responses have been pseudonymised to the level of stakeholder-group e.g. Contributor A, Research Funding Organisation A, where requested by the participant in the participant consent form: <a href="https://doi.org/10.5281/zenodo.7589770">https://doi.org/10.5281/zenodo.7589770</a>.</li><li>Respondents were notified of the limits of pseudonymisation for this survey. Due to the nature and purpose of this survey on Organisational Identity, the identity of the organisation/entity could not be pseudonymised. Participants were advised only to participate if they were happy to do so under these conditions.</li><li>Survey responses were deleted by request of certain respondents. These responses are not included in these files.</li><li>Survey respondents were enabled to update their submissions. These changes are captured in the <i>NationalOpenAccessMonitorSurvey.OrganisationalIdentity.MasterChangeFile.</i></li></ul><p><strong>There are four files within in this dataset:</strong></p><p>- <i>Results.NationalOpenAccessMonitorSurvey.OrganisationalIdentity.README - </i>this PDF details the changes made to the raw data, as specified in the bullet points above and a description of the files within the dataset.</p><p>- <i>Results.NationalOpenAccessMonitorSurvey.OrganisationalIdentity.Pseudonymised.101123</i> - this is the original raw data, in csv format, as downloaded from the Online Surveys platform and subsequently pseudonymised and redacted.</p><p>- <i>NationalOpenAccessMonitorSurvey.OrganisationalIdentity.MasterChangeFile.101123 </i>- this is a change file, in csv format, which documents the changes which participants requested to be made to their submissions after they were received.</p><p>- R<i>esults.NationalOpenAccessMonitorSurvey.OrganisationalIdentity.Pseudonymised.Updated.101123 - </i>this is the original raw data, pseudonymised and redacted, with the requested changes implemented.</p><p><strong>Notes for data use:</strong></p><ul><li>The "affiliated organisations/entities" section of the survey was insufficiently described in the survey text. One-to-one follow-up and support was provided to clarify to respondents that questions 12 and 13 of the survey intended to identify where <strong>all </strong>research outputs of one organisation/entity should appear on that organisation's/entities' own RPO or RFO dashboard within the National Open Access Monitor, and <strong>also </strong>on the dashboard of another organisation/entity. </li><li>Survey respondents were notified in the introduction section to the "affiliated organisations/entities" section that "<strong>only where all entities agree there is a formal relationship in place</strong> that should be reflected in the Monitor will the link be implemented". Therefore, for the National Open Access Monitor project, only where both parties have asserted that <strong>all </strong>research outputs of one organisation/entity should also appear on the dashboard of another organisation/entity, will it be considered validated and implemented. </li><li>The geographic scope of the National Open Access Monitor Project is the Republic of Ireland. Where respondent's RPO or RFO organisations/entities are based outside the Republic of Ireland, or where respondents stated affiliations with overseas organisations/entities, they will not be actioned or implemented. To note: the survey invited responses from international <i>publishers</i> to enable filtering functionality by publisher within the National Open Access Monitor, these responses are <i>not </i>out of scope. </li></ul><p>-----------------------</p><p>The context for the survey is detailed in the National Open Access Monitor Project Plan: <a href="https://doi.org/10.5281/zenodo.7331431">https://doi.org/10.5281/zenodo.7331431</a>, the National Open Access Monitor Advisory Group Meeting Minutes, 18th September 2023: <a href="https://zenodo.org/doi/10.5281/zenodo.8405472">https://zenodo.org/doi/10.5281/zenodo.8405472</a> and the Developing the National Open Access Monitor, Ireland: Stakeholder Webinar, 22nd September 2023: <a href="https://zenodo.org/doi/10.5281/zenodo.8370578">https://zenodo.org/doi/10.5281/zenodo.8370578.</a></p><p>This project is managed by <a href="http://www.irel.ie/">IReL </a>and has received funding from Ireland's National Open Research Forum under the NORF Open Research Fund. <a href="https://norf.ie/funding/">https://norf.ie/funding/ </a><a href="https://norf.ie/orf-projects-announcement/">https://norf.ie/orf-projects-announcement/</a></p>
Conductivity–Temperature–Depth (CTD) and dissolved oxygen profile data from shipboard surveys collected within Olympic Coast National Marine Sanctuary, 2005-2023
<p>This data set includes Conductivity-Temperature-Depth (CTD) and dissolved oxygen profile data that were collected along Washington State’s outer coast within Olympic Coast National Marine Sanctuary towards the northernmost extent of the California Current System. Measurements were made at fourteen hydrographic stations during mooring deployment, recovery, and maintenance cruises between the months of May and October from 2005–2023. The 792 CTD profiles were acquired using Sea-Bird Scientific 19 SeaCAT or 19plus SeaCAT CTD profilers with associated SBE-43 (Sea-Bird Electronics) or Beckman or YSI-type (Yellow Springs Instruments) dissolved oxygen sensors. The data were processed via Sea-Bird Scientific’s SBE Data Processing application using six of the modules in the following order: <em>Data Conversion, Filter, Align CTD, Loop Edit, Derive, and Bin Average</em>. These processing steps and associated methods are the same as those used to process CTD data that make up the <a href="../records/5814071">Newport Hydrographic Line time series</a> located off the central Oregon coast thus allowing for a direct comparison between the two regions.</p> <table> <tbody> <tr> <td><strong>Station Name </strong></td> <td><strong>Latitude</strong></td> <td><strong>Longitude</strong></td> <td><strong>Water Depth (m, MLLW)</strong></td> </tr> <tr> <td><strong>Makah Bay (MB)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>MB015</td> <td>48.3254oN</td> <td>124.6768oW</td> <td>15</td> </tr> <tr> <td>MB042</td> <td>48.3240oN</td> <td>124.7354oW</td> <td>42</td> </tr> <tr> <td><strong>Cape Alava (CA)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>CA015</td> <td>48.1663oN</td> <td>124.7568oW</td> <td>15</td> </tr> <tr> <td>CA042</td> <td>48.1660oN</td> <td>124.8234oW</td> <td>42</td> </tr> <tr> <td>CA065 </td> <td>48.1659oN</td> <td>124.8949oW</td> <td>65</td> </tr> <tr> <td><strong>Teahwhit Head (TH)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>TH015</td> <td>47.8761oN</td> <td>124.6195oW</td> <td>15</td> </tr> <tr> <td>TH042</td> <td>47.8762oN</td> <td>124.7334oW</td> <td>42</td> </tr> <tr> <td>TH065 </td> <td>47.8767oN</td> <td>124.7967oW</td> <td>65</td> </tr> <tr> <td><strong>Kalaloch (KL)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>KL015</td> <td>47.6008oN</td> <td>124.4284oW</td> <td>15</td> </tr> <tr> <td>KL027</td> <td>47.5946oN</td> <td>124.4971oW</td> <td>27</td> </tr> <tr> <td>KL050 </td> <td>47.5933oN</td> <td>124.6112oW</td> <td>50</td> </tr> <tr> <td><strong>Cape Elizabeth (CE)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>CE015</td> <td>47.3568oN</td> <td>124.3481oW</td> <td>15</td> </tr> <tr> <td>CE042</td> <td>47.3531oN</td> <td>124.4887oW</td> <td>42</td> </tr> <tr> <td>CE065 </td> <td> 47.3528oN</td> <td>124.5669oW</td> <td>65</td> </tr> </tbody> </table>
Orangutan habitat survey in Sebangau National Park, Central Kalimantan, Indonesia
<p>This dataset is used to initialise BORNEO (arBOReal aNimal movEment mOdel), as a part of publication entitled:</p> <p>Assessing the impact of forest structure disturbances on the arboreal movement oforangutans - an agent-based modelling approach.</p> <p>The article manuscript is being prepared to be submitted to Frontiers in Ecology and Evolution</p> <p><strong>Data collection</strong></p> <p>The data is collected in Sebangau, Central Kalimantan, Indonesia. Two 1-ha plots were established, each in unburned and burned forest. </p>
Nutritional table to estimate the availability of nutrients in households from the Mexican National Survey of Household Income and Expenditures (ENIGH) 2008-2020
<p>The database contains the amount of six nutrients (calories, proteins, vitamin A and C, iron, and zinc) per 100 grams/mililiters for each of the food categories used in the Mexican National Survey of Household Income and Expenditures 2008-2020.</p>
Grand Bay National Estuarine Research Reserve Seagrass Survey Data (2005 - 2010)
<p>Seagrass beds at the Grand Bay National Estuarine Research Reserve were surveyed using a transect method, twice a year at five sites.</p> <p>Details of the transect location and methods are described in the following:</p> <p>https://www.jstor.org/stable/26367667</p>
Coyote Scat Surveys in Chihuahuan Desert Grassland and Shrubland Sites, Spring, Summer and Fall at the Sevilleta National Wildlife Refuge, New Mexico (2008-2009)
This data set contains information regarding carnivore scat surveys that were performed at sites in grama grassland and both creosote and mesquite shrubland habitats at the Sevilleta NWR. A total of nine surveys were carried out along road-based transects, each of which is a mile long, during one season in 2008 (June-July) and three seasons in 2009: spring (April-May), summer (July-August), and fall (October-November). There were 10 transects in grassland areas and 10 in shrubland areas in 2008. All 20 transects, as well as two additional transects in grassland areas, were surveyed in 2009. For more information on the structure of the vegetation surrounding these road based transects, see the "Vegetation surveys in grassland and shrubland sites that are associated with coyote scat surveys at the Sevilleta NWR, 2008-2009" data set. Scat samples were identified in the field and collected for genetic and stable carbon isotope analysis. Field recorded variables include: scat freshness, maximum diameter, length, and GPS coordinates, as well as the field-based species identification for the sample. Information on the lab based species and individual identification results are also presented.This data was collected in order to obtain information on the size and feeding ecology of the coyote populations in grassland vs. shrubland habitats in three seasons (spring, summer and fall) and two years (2008 and 2009) at the Sevilleta NWR. A mark recapture analysis can be performed on the data from 2009 since two surveys were carried out for each scat transect in each of the three seasons and coyote scats were run through a genetic analysis to determine individual identity of the coyotes. A rough assessment of coyote habitat use can also be performed using the individual identity and coyote scat location information. Future isotope analysis will indicate whether the base of the food chain is C4 (grass) vs. C3 (shrubs) plants in grassland vs. shrubland habitats in each of the three
Ground Arthropod Community Survey in Grassland, Shrubland, and Woodland at the Sevilleta National Wildlife Refuge, New Mexico (1992-2004)
This data set contains records for the numbers of selected groups of ground-dwelling arthropod species and individuals collected from pitfall traps at 4 sites on the Sevilleta NWR, including creotostebush shrubland, both black and blue grama grasslands, and a pinyon/juniper woodland. Data collections begin in May of 1989, and are represented by subsequent sample collections every 2 months. One site (Goat Draw/Cerro Montosa) was discontinued in 2001, and a new site (Blue Grama) was initiated . Only three sites, creosotebush, black grama, and blue grama were continued between 2001-2004.
Figure 15 in New species of Australian arid zone chelonine wasps from the genera Phanerotoma and Ascogaster (Hymenoptera: Braconidae) informed by the 'Bush Blitz' surveys of national reserves
Figure 15. Distribution map: Ascogaster brevivena sp. nov., grey circle; Ascogaster ferruginegaster sp. nov., black triangle; Ascogaster prolixogaster sp. nov., grey triangle; Ascogaster rubriscapa sp. nov., black square.
Figure 13 in New species of Australian arid zone chelonine wasps from the genera Phanerotoma and Ascogaster (Hymenoptera: Braconidae) informed by the 'Bush Blitz' surveys of national reserves
Figure 13. Phanerotoma nigriscapulata sp. nov.: (a) habitus, lateral, paratype, scale line = 1 mm; (b) head, anterior, holotype, scale line = 0.5 mm; (c) mesosoma, dorsal, paratype, scale line = 1 mm; (d) fore wing, paratype, scale line = 1 mm.
Figure 2 in New species of Australian arid zone chelonine wasps from the genera Phanerotoma and Ascogaster (Hymenoptera: Braconidae) informed by the 'Bush Blitz' surveys of national reserves
Figure 2. Tree resulting from the Bayesian phylogenetic analysis of the COI data for the genus Ascogaster. Numbers on branches show posterior probabilities. Abbreviations: (a) PTP analysis; (b) GMYC (single); (c) GMYC (multi); (d) morphology.
Figure 3 in New species of Australian arid zone chelonine wasps from the genera Phanerotoma and Ascogaster (Hymenoptera: Braconidae) informed by the 'Bush Blitz' surveys of national reserves
Figure 3. Tree resulting from the Bayesian phylogenetic analysis of the COI data for the genus Phanerotoma. Numbers on branches show posterior probabilities. Abbreviations: (a) PTP analysis; (b) GMYC (single); (c) GMYC (multi); (d) morphology.
Figure 10 in New species of Australian arid zone chelonine wasps from the genera Phanerotoma and Ascogaster (Hymenoptera: Braconidae) informed by the 'Bush Blitz' surveys of national reserves
Figure 10. Phanerotoma bushblitz sp. nov.: (a) habitus, lateral, holotype, scale line = 1 mm; (b) head, anterior view, paratype, scale line = 0.5 mm; (c) metasoma, dorsal, paratype, scale line = 1 mm; (d) fore wing, paratype, scale line = 1 mm.
Figure 6 in New species of Australian arid zone chelonine wasps from the genera Phanerotoma and Ascogaster (Hymenoptera: Braconidae) informed by the 'Bush Blitz' surveys of national reserves
Figure 6. Ascogaster prolixogaster sp. nov.: (a) habitus, lateral, holotype, scale line = 1 mm; (b) head, anterior, holotype, scale line = 0.5 mm; (c) metasoma, dorsal, holotype, scale line = 1 mm, metasomal teeth arrowed; (d) fore wing, paratype, scale line = 1 mm.
Figure 8. Phanerotoma behriae Zettel, 1988a in New species of Australian arid zone chelonine wasps from the genera Phanerotoma and Ascogaster (Hymenoptera: Braconidae) informed by the 'Bush Blitz' surveys of national reserves
Figure 8. Phanerotoma behriae Zettel, 1988a: (a) habitus, lateral, holotype, scale line = 1 mm, inset type label; (b) head, anterior, holotype, scale line = 0.5 mm; (c) head, dorsal, holotype, scale line = 1 mm; (d) metasoma, dorsal, holotype, scale line = 1 mm; (e) fore wing, other material, scale line = 1 mm.
Figure 4 in New species of Australian arid zone chelonine wasps from the genera Phanerotoma and Ascogaster (Hymenoptera: Braconidae) informed by the 'Bush Blitz' surveys of national reserves
Figure 4. Ascogaster brevivena sp. nov.: (a) habitus, lateral, holotype, scale line = 1 mm; (b) mesosoma and metasoma, dorsal view, holotype, scale line = 1 mm; (c) head, dorsal, holotype, scale line = 0.5 mm; (d) head, anterior, holotype, scale line = 0.5 mm; (e) fore wing, paratype, scale line = 0.5 mm.
[J.D. Hooker s.n., CAL] [© Botanical Survey of India, Central National Herbarium. Reproduced with permission] in Lectotypification of Arisaema consanguineum Schott (Araceae)
[J.D. Hooker s.n., CAL] [© Botanical Survey of India, Central National Herbarium. Reproduced with permission]
Figure 2 in Archival sea turtles in National Zoological Collections of Zoological Survey of India
Figure 2. Representatives of the archival Sea turtle specimens (the Green Sea Turtle, Chelonia mydas) preserved in Zoological Survey of India, Kolkata. A. Hatchling of C. mydas, Reg. No. ZSI 14544 (dorsal view, wet collection). B. Hatchling of C. mydas, Reg. No. ZSI 14543 (ventral view, wet collection). C. Eggs of C. mydas (wet collection). D. Skull of C. mydas, Reg. No. ZSI 389 (1404) (lateral view, dry collection). E. Adult individuals of C. mydas, Reg. No. ZSI 22489 (lateral view, wet collection).
Figure 1 in Archival sea turtles in National Zoological Collections of Zoological Survey of India
Figure 1. Representatives of the archival Sea turtle specimens (the Hawksbill Sea Turtle, Eretmochelys imbricata) preserved in Amphibia and Reptilia gallery of Indian museum, Kolkata and morphometric measurements. HD= Head diameter, FL= Forelimb length, HL= Hindlimb length, CCL=Curved carapace length, CPL= Curved plastron length, CCW= Curved carapace width, CPW= Curved plastron width, TL= Total length.
2007-2017 Quarterly Ecuadorian National Employment Survey
<p>This repository contains the raw data from the Ecuadorian employment surveys from 2007-06 to 2017-12. PDF are questionnaires. Most datasets are in .SPPSS format (.sav). Each database was downloaded and unzipped as-is from the institutional website of INEC ECUADOR on November 15, 2021, using the "banco de informacion estadistica": https://aplicaciones3.ecuadorencifras.gob.ec/sbi-war/</p>
Dataset: Cross-Sectional National Survey on Risk Perception and Tourism Behaviour (SNF NRP 78)
<p>The data set contains scales (<em>rating items</em>) on the willingness of the Swiss resident population to take risks in connection with touristic travel during the coronavirus pandemic. The data includes a selection of items of the <em>Domain-Specific Risk-Taking Scale</em> (<em>DOSPERT) </em>(Weber et al., 2002). The data contains measures of the <em>health belief model</em> (<em>HBM</em>; Rosenstock, 1960, see also Champion & Skinner, 2008) that is used both in health research and in tourism research to explain and predict the preventive health behaviour of individuals. Furthermore, the data covers all three elements of the t<em>heory of planned behaviour (</em>Ajzen, 1991). This is a representative data set for the Swiss population aged 18 and above. A trilingual and national survey of the Swiss resident population was carried out in the period from March to May 2021. A letter of invitation to participate in the study was sent by post to a total of 4,530 randomly selected persons residing in Switzerland. The address data was provided by the Federal Statistical Office (BfS). Of the total of 4,530 people contacted, 164 were reported as unreachable (no longer at the address, deceased, or due to old age). A total of 1,683 persons participated in the survey. This corresponds to a response rate of 39%. The structure of the respondents corresponds to that of the Swiss resident population 18 years of age and older with regard to gender, age, and language region.</p> <p>Ajzen, I. (1991). The theory of planned behavior. <em>Organizational Behavior and Human Decision Processes</em>, <em>50</em>(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T</p> <p>Weber, E., Blais, A.-R., & Betz, N. E. (2002). A domain-specific risk-attitude scale: Measuring risk perceptions and risk behaviors. <em>Journal of Behavioral Decision Making</em>, <em>15</em>, 263–290. https://doi.org/10.1002/bdm.414</p> <p>Champion, V. L., & Skinner, C. S. (2008). The health belief model. In K. Glanz, B. Rimer, & K. Viswanath (Eds.), <em>Health behavior and health education: Theory, research, and practice</em> (4th ed., pp. 45–65). San Francisco, CA: Jossey-Bass.</p> <p>Rosenstock, I. M. (1960). What research in motivation suggests for public health. <em>American Journal of Public Health, 50</em>(3), 295-302. https://doi.org/10.2105/AJPH.50.3_Pt_1.295</p>
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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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.