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3 results for “community recommendations”
Community Established Best Practice Recommendations for Tephra Studies-from Collection through Analysis
<p>Tephra is a unique volcanic product with an unparalleled role in understanding past eruptions, long-term behavior of volcanoes, and the effects of volcanism on climate and the environment. Tephra deposits also provide spatially widespread, extremely high-resolution time-stratigraphic markers across a range of sedimentary settings and are used in a range of disciplines (e.g., volcanology, climate science, archaeology, ecology, and impact assessment). Nonetheless, the study of tephra deposits is challenged by a lack of standardization that often inhibits data integration across geographic regions and across disciplines.</p> <p>Here we present comprehensive recommendations for tephra data gathering and reporting that were developed by the tephra science community to serve as guidelines for future investigators and to ensure that sufficient data are gathered for transparency and interoperability. Recommendations include standardized field and laboratory data collection along with reporting and correlation guidance. These are organized as tabulated lists of key metadata with their definition and purpose. They are system independent and usable for template, tool, and database development. This new standardized framework promotes consistent tephra documentation and archiving, fosters interdisciplinary communication, and improves effectiveness of data sharing among diverse communities of researchers. Wider adoption will help to expand the applicability and usability of tephra data and facilitate scientific collaboration and data reuse.</p> <p>For additional details, see the accompanying manuscript:</p> <p>Wallace, K.*, Bursik, M. Kuehn, S., Kurbatov, A., Abbott, P., Bonadonna, C., Cashman, K., Davies, S., Jensen, B., Lane, C., Plunkett, G., Smith, V. Tomlinson, E., Thordarsson, T., and Walker, D. Community established best practice recommendations for tephra studies—from collection through analysis. <em>Sci Data</em> <strong>9, </strong>447 (2022). <a href="https://doi.org/10.1038/s41597-022-01515-y">https://doi.org/10.1038/s41597-022-01515-y</a></p> <p>*corresponding author: Kristi Wallace, <a href="mailto:kwallace@usgs.gov">kwallace@usgs.gov</a></p> <p>Open access article is available online here <a href="https://doi.org/10.1038/s41597-022-01515-y">https://doi.org/10.1038/s41597-022-01515-y</a> or as a PDF here <a href="https://gcc02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.nature.com%2Farticles%2Fs41597-022-01515-y.pdf&data=05%7C01%7Ckwallace%40usgs.gov%7C673f9f39fd3e4122dd9b08da6f3b9667%7C0693b5ba4b184d7b9341f32f400a5494%7C0%7C0%7C637944598967375940%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=%2BKVfwK2FbUKAoJf2gMerCmBMEQE1rvMDkS6xIk3DGKY%3D&reserved=0">https://www.nature.com/articles/s41597-022-01515-y.pdf</a>.</p>
Analyzing the Human Recommendation Community 'ifyoulikeblank' on Reddit — Auxiliary materials
<p>This repository contains auxiliary materials for the iConference 2024 paper "“If I like BLANK, what else will I like?”: Analyzing<br>a Human Recommendation Community on Reddit" by Thi Binh Minh Cao and Toine Bogers (= corresponding author)</p> <p>Published in: <em>Proceedings of the 2024 iConference</em>, April 15--26, 2024, Changchun, China.</p> <p>The paper presents the results of an analysis of /r/ifyoulikeblank, a Reddit community dedicated to requesting and providing for recommendations. This repository contains the following auxiliary materials:</p> <ul> <li>The annotated sample of threads from the /r/ifyoulikeblank subreddit (<strong>annotated-dataset.xlsx</strong>). The second sheet in the Excel file explains the contents of the file.</li> <li>The R code for performing the analysis described in the paper (<strong>annotation-analysis.R</strong>)</li> <li>CSV file containing the genres attributed to the artists as crawled from the Spotify API (<strong>artist-spotify-genres.csv</strong>)</li> <li>CSV file containing the popularity scores crawled from the Spotify API for the seed items and Spotify recommendations (<strong>recommendation-popularity.reddit-vs-spotify.csv</strong>)</li> <li>CSV file containing the popularity scores crawled from the Spotify API for the Reddit (<strong>recommendation-popularity.reddit.csv</strong>)</li> <li>The stopwords file used in the textual analysis (<strong>stopwords.csv</strong>)</li> <li>Excel file containing the activity data for the /r/ifyoulikeblank subreddit (<strong>subreddit-stats.xlsx</strong>)</li> </ul>
Dataset_Dryocosmus_Torymus_Article recommended by PCI Zoology: The open bar is closed: restructuration of a native parasitoid community following successful control of an invasive pest.
<p>This Dataset has been used for the analyses within the paper recommended by PCI Zoology and entitled:</p> <p>"The open bar is closed: restructuration of a native parasitoid community following successful control of an invasive pest."<br> </p> <p> </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
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.