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Dataset results
23 results for “Wow”
WOW Nature - Bosco del ponte del Quarelo
<p>Air pollution Device Measurements ["pm1","pm2p5","pm4","pm10","humidity"]</p>
WOW Nature - Bosco di Prasaccon
<p>Air pollution Device Measurements ["pm1","pm2p5","pm4","pm10","humidity"]</p>
Wow Nature Motivation Survey
<p>The Wow Nature motivation study was conducted within the ongoing H2020 project named <a href="https://actionproject.eu/">ACTION</a> (pArticipatory sCience Toolkit agaInst pollutiON) on citizen science. Volunteers participate to citizen science initiatives for multiple reasons: personal enjoyment, desire for improvement or achievement, establishment of personal relationships, care for the environment, etc.<br> Studying motivation and investigating the factors influencing people participation to citizen science projects is an essential aspect in the analysis of citizen science communities. Understanding the reasons that foster people to engage can support the successful design and implementation of effective participant involvement tasks, as well as pave the way for long-term engagement.<br> The goal of the study is to analyse the motivation to participate of a specific citizen science community focused on fighting air pollution in the Wow Nature pilot supported by the ACTION project. More info on the pilot available at <a href="https://actionproject.eu/citizen-science-pilots/wow-nature/">https://actionproject.eu/citizen-science-pilots/wow-nature/</a>.</p> <p>The Wow Nature motivation study is part of the study about motivation in citizen science projects conducted within the ACTION project (<a href="https://doi.org/10.5281/zenodo.5753092">https://doi.org/10.5281/zenodo.5753092</a>). The survey was designed and administered using the <a href="https://coney.cefriel.com/">Coney</a> toolkit.</p> <p>The research object adopts the <a href="https://www.researchobject.org/ro-crate/1.0/">RO-Crate</a> specification. Files made available within the research object are:</p> <ul> <li><em>*-procedure.ttl</em> contains the RDF representation of the structure of the conversational survey (questions, answers, etc.) using the <a href="https://w3id.org/survey-ontology">Survey Ontology</a></li> <li><em>*-results.ttl </em>contains the RDF representation of the answers collected using the <a href="https://w3id.org/survey-ontology">Survey Ontology</a></li> <li><em>*-survey.tll </em>contains a comprehensive RDF representation of the survey data using the <a href="https://w3id.org/survey-ontology">Survey Ontology</a></li> <li><em>*-results.csv </em>contains the CSV of the collected answers</li> <li>*-<em>script.R</em> is the R script developed to analyse the collected answers</li> <li>*-<em>mean-var-motivating-questions.csv </em>contains the computed mean and average for each question considered (observable variables)</li> <li>*-<em>mean-var-motivating-factor.csv </em>contains the computed mean and average for each motivation factor considered (latent variables)</li> <li>*-<em>correlation-factors-global-motivation.csv </em>contains the correlation analysis between each motivation factor and the global motivation </li> </ul>
What Or When to Eat to Reduce the Risk of Type 2 Diabetes (WOW)
ClinicalTrials.gov study NCT04762251. IPD Sharing: YES. Countries: 1. Publications: 1.
Data from: Characters matter: wow narratives shape affective responses to risk communication
Introduction <p class="MsoBodyText">Whereas scientists depend on the language of probability to relay information about hazards, risk communication may be more effective when embedding scientific information in narratives. The persuasive power of narratives is theorized to reside, in part, in narrative transportation. </p> Purpose <p>This study seeks to advance the science of stories in risk communication by measuring real-time affective responses as a proxy indicator for narrative transportation during science messages that present scientific information in the context of narrative.</p> Methods <p class="MsoBodyText">This study employed a within-subjects design in which participants (n=90) were exposed to eight science messages regarding flood risk. Conventional science messages using probability and certainty language represented two conditions. The remaining six conditions were narrative science messages that embedded the two conventional science messages within three story forms that manipulated the narrative mechanism of character selection. Informed by the Narrative Policy Framework, the characters portrayed in the narrative science messages were hero, victim, and victim-to-hero. Natural language processing techniques were applied to identify and rank hero and victim vocabularies from 45 resident interviews conducted in the study area; the resulting classified vocabulary was used to build each of the three story types. Affective response data were collected over 12 group sessions across three flood-prone communities in Montana. Dial response technology was used to capture continuous, second-by-second recording of participants' affective responses while listening to each of the eight science messages. Message order was randomized across sessions. ANOVA and three linear mixed-effects models were estimated to test our predictions.</p> Results <p>First, both probabilistic and certainty science language evoked negative affective responses with no statistical differences between them. Second, narrative science messages were associated with greater variance in affective responses than conventional science messages. Third, when characters are in action, variation in the narrative mechanism of character selection leads to significantly different affective responses. Hero and victim-to-hero characters elicit positive affective responses, while victim characters produce a slightly negative response.</p> Conclusions <p>In risk communication, characters matter in audience experience of narrative transportation as measured by affective responses.</p>
FIGURES 19–26 in Wow assingi gen. and spec. n., with description of a new tribe of Aleocharinae (Coleoptera, Staphylinidae)
FIGURES 19–26. Wow assingi sp. n., holotype male. Aedeagus in parameral (19, 21) and lateral (20, 22) views; paramere in lateral view (23); tergite VIII (24); sternite VIII 25); tergites IX and X in dorsal view (26). Abbreviations: apl, apical lobe; con, condylite; hz, hinge zone; par, paramerite; tIX‒X, tergite IX‒X; vel, velum; vst, ventral strut.
FIGURES 4–5 in Wow assingi gen. and spec. n., with description of a new tribe of Aleocharinae (Coleoptera, Staphylinidae)
FIGURES 4–5. Wow assingi sp. n., holotype male. Head and prothorax in dorsal (4) and ventral (5) views. Abbreviations: acxc, anterior coxal carina; atp, anterior tentorial pit; bst, basisternal region of prosternum; cl clypeus; cmb, clypeolabral connecting membrane; cs, cervical sclerite; fr, frons; gal, galea; gen, gena; gp, gular plate; gs, gular suture; hr, hypostomal ridge; hs, hypostomal suture; lbr, labrum; mdb, mandible; mn, mentum; mxp1‒4, maxillary palpomere 1‒4; nss, notosternal suture; pcxc, posterior coxal carina; prl, prelabium; pst, prostheca; ptp, posterior tentorial pit; sat, supraantennal tubercle; sc, scape; smn, submentum; trt, trochantin; vt, vertex. Arrowheads indicate macrosetae.
FIGURES 6–11 in Wow assingi gen. and spec. n., with description of a new tribe of Aleocharinae (Coleoptera, Staphylinidae)
FIGURES 6–11. Wow assingi sp. n., holotype male. Mouthparts in dorsal (6) and ventral (9) views; right maxilla in ventral view (7, 8); labium in ventral view (10, 11). Abbreviations: aps, apical 'pseudosegment'; atp, anterior tentorial pit; bst, basistipes; cd, cardo; cl, clypeus; cmb, clypeolabral connecting membrane; gal, galea; hr, hypostomal ridge; hs, hypostomal suture; lac, lacinia; lbr, labrum; lig, ligula; llh, lateral lobe of hypopharynx; lp1‒3, labial palpomere 1‒3; mdb, mandible; mn, mentum; msc, median sclerotization of prelabium; mst, mediostipes; mxp1‒4, maxillary palpomere 1‒4; pat, preapical tooth; ppg, palpiger; pst, prostheca; ptp, posterior tentorial pit; smn, submentum.
FIGURES 12–18 in Wow assingi gen. and spec. n., with description of a new tribe of Aleocharinae (Coleoptera, Staphylinidae)
FIGURES 12–18. Wow assingi sp. n., holotype male. Elytra in dorsal view (12); pterothorax in ventral view (13); protarsus in ventral view (14); metatarsus in lateral view (15); exposed portion of abdomen in dorsal view (16); abdominal apex in dorsal (17) and ventral (18) views. Abbreviations: aest3, metanepisternum; msvp, mesoventral process; scs, scutellar shield; sIII‒VIII, sternite III‒VIII; tII‒X, tergite 2‒10; v2, mesoventrite; v3, metaventrite; 1‒4, tarsomere 1‒4. Arrowhead indicates macroseta.
FIGURES 1–3 in Wow assingi gen. and spec. n., with description of a new tribe of Aleocharinae (Coleoptera, Staphylinidae)
FIGURES 1–3. Wow assingi sp. n., holotype male. Dorsal habitus, (1); head, pronotum and anterior region of elytra in dorsolateral view (2); head in anterodorsal view (3).
WOW Nature - Bosco Limite
<p>Sensor Measurements ["pm1","pm2p5","pm4","pm10","humidity"]</p>
Working on Wellness (WOW) Intervention
ClinicalTrials.gov study NCT01494207. IPD Sharing: Not stated. Countries: 1. Publications: 1.
WoW - Single- vs Two-staged Excisions of Thin Melanoma
ClinicalTrials.gov study NCT06363591. IPD Sharing: YES. Countries: 1. Publications: 1.
Figure 3 from: Murray M, O'Donnell M, Laufersweiler MJ, Novak J, Rozum B, Thompson S (2019) A survey of the state of research data services in 35 U.S. academic libraries, or "Wow, what a sweeping question". Research Ideas and Outcomes 5: e48809. https://doi.org/10.3897/rio.5.e48809
Figure 3 Types of campus groups that provide RDS (n=103). Type codes are defined as follows: Admin: a campus administrative unit that does not fall into any other category; Center: research centers or institutes excluding HPC groups; Dept = Departments or colleges; HPC: High Performance Computing and research computing units including HPC run by IT units; Individuals: Individual staff, faculty, students, etc.; IT: Information Technology associated with the entire campus, colleges, or departments excluding HPC groups; Lab: Various labs on campus that do not fall into any other category; Research Office: Groups that oversee university research; Other: Groups that cannot be categorized under any other code.
Figure 2 from: Murray M, O'Donnell M, Laufersweiler MJ, Novak J, Rozum B, Thompson S (2019) A survey of the state of research data services in 35 U.S. academic libraries, or "Wow, what a sweeping question". Research Ideas and Outcomes 5: e48809. https://doi.org/10.3897/rio.5.e48809
Figure 2 Breakdown of the workshops or topics with a tool or programming language code applied (n=47). Only tool codes that have a frequency >1 are shown. Tool code names are self-explanatory (i.e. the name of tool).
Figure 1 from: Murray M, O'Donnell M, Laufersweiler MJ, Novak J, Rozum B, Thompson S (2019) A survey of the state of research data services in 35 U.S. academic libraries, or "Wow, what a sweeping question". Research Ideas and Outcomes 5: e48809. https://doi.org/10.3897/rio.5.e48809
Figure 1 Workshop topic code frequencies. Up to two topic codes were applied to each workshop (n=160). Topic codes are defined as follows: Carpentry: a data or software Carpentry workshop; Cleaning: data cleaning and related techniques; Coding: how to work with data via command line or in a specific language; General: the basics of data management; GIS: geographic information system or spatial data/tools; Grants: the word "grants" or the name of a funding agency was explicitly mentioned in the workshop's title or description; HPC: high performance computing; Locate: focused on how to search and locate datasets; Metadata: metadata and data documentation; Mining: focused on text and data mining; Org: data organization; Other: misc. topics or unclassifiable; Plans: data management plans; Repository: addresses a specific repository, how to use a repository, or data repositories in general; Reproducibility: focused on research reproducibility; StorageSec: data storage and/or security tools and topics; Tool: focused on how to use tools related to data and data management (see Fig. 2); Visualization: data visualization.
Supplementary material 1 from: Murray M, O'Donnell M, Laufersweiler MJ, Novak J, Rozum B, Thompson S (2019) A survey of the state of research data services in 35 U.S. academic libraries, or "Wow, what a sweeping question". Research Ideas and Outcomes 5: e48809. https://doi.org/10.3897/rio.5.e48809
Links to library and university/college research data management policies.
Figure 4 from: Murray M, O'Donnell M, Laufersweiler MJ, Novak J, Rozum B, Thompson S (2019) A survey of the state of research data services in 35 U.S. academic libraries, or "Wow, what a sweeping question". Research Ideas and Outcomes 5: e48809. https://doi.org/10.3897/rio.5.e48809
Figure 4 Disciplinary categorization of campus groups that provide RDS (n=34). Discipline codes are defined as follows: Bio: Groups that specialize in biology, including health and medicine; Bio/Stats: Groups that specialize in biology and statistics; Data: no specific discipline but has the word 'data' in the name; GIS: Groups that specialize in spatial and GIS (Geographic Information Systems) data; Humanities: Groups specializing in humanities; Social/Stats: Groups that specialize in statistics and social science; SocialSci: Groups specializing in social science; Stats: Groups specializing in statistics.
FIGURES 27–28 in Wow assingi gen. and spec. n., with description of a new tribe of Aleocharinae (Coleoptera, Staphylinidae)
FIGURES 27–28. Collecting site of Wow assingi in Wangtianshu, China (© Marek Wanat).
Wikidata Dump wow
<p> RDF dump of wikidata produced with <a href="https://tools.wmflabs.org/wdumps/">wdumps</a>. </p> <p> <br> <a href="https://tools.wmflabs.org/wdumps/dump/1801">View on wdumper</a> </p> <p> <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0 </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
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Annotated Behaviour and Observability Dataset (ABODe)
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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.