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773 results for “data science”
Survey Data: Public Engagement with Science: A Survey for India Alliance Grantees
<p>Lately, the Indian research ecosystem has seen an upward trend in scientists showing interest in communicating their science and engaging with non-scientific audiences; however, the number and variety of science communication or public engagement activities undertaken formally by scientists remains low in the country. There could be many contributing factors for this trend. To explore this further, the science funding public charity in India, DBT/Wellcome Trust India Alliance (India Alliance), in a first of its kind of study by a funding agency in India, surveyed its 243 research grantees in November 2020 requesting their views on public engagement with science in India through an online survey. The survey included both quantitative as well as open-ended questions to assess the understanding of, participation in, and attitude of India Alliance Fellows/Grantees towards public engagement with research, identify the enablers, challenges, and barriers to public engagement for India Alliance Fellows/Grantees, understand the specific needs (training/capacity-building, funding, etc.) and develop recommendations for India Alliance as well as for the larger scientific ecosystem in the country. The survey showed that India Alliance grantees are largely motivated to engage with the public about science or their research but lack professional recognition and incentives, training and structural support to undertake public engagement activities.</p> <p>A shareable survey was designed using Microsoft Forms. The survey employed a mixed methods strategy and included 24 closed-ended questions (multiple choice and Likert scale) and nine qualitative questions, similar to open-ended questions. The questions were modelled on a similar survey carried out by Wellcome in 2016 to gather views of researchers on public engagement in Asia and Africa.</p> <p>The survey was shared by email with 243 Indian researchers in receipt of India Alliance fellowships or grants, out of which 137 (male – 78; female – 59) responded to the survey. Of these, 90 respondents were basic science researchers, 22 were clinical researchers, and 25 were public health researchers. A majority, i.e. 81% of the respondents indicated working as an independent researcher for more than 4 years (time post-PhD). Furthermore, 58% of the respondents were based at research institutions, 18% at higher education institutions, and 17% at central, state and private universities; these organisations geographically represent around 31 cities of India (9 respondents chose to not reveal their host institution in the survey). Periodic reminders were sent by email to the fellows to complete the survey. Three fellows who received funding from India Alliance for their public engagement projects were contacted via email after the survey for their views (in 50-150 words) on the public engagement funding programme of India Alliance. They were informed that their input is intended to be included in a report of the survey results, and they can choose to either stay anonymous or be credited. The data was collected from 27 November 2020 until 28 April 2021.</p> <p>Following the end of the survey, the data automatically mapped on Microsoft Excel was cleaned for duplication and errors. Microsoft Excel tools were used to analyse and visualise the data.</p> <p>The study did not undergo a formal ethical clearance process as the primary objective of the study was to gather insights of grantees to inform India Alliance’s public engagement support mechanisms. At the start of the survey, the objectives of the survey were clearly stated and the respondents were informed that the anonymized data of the survey may be communicated in the future. Participation in the survey was entirely voluntary.</p>
Mirror of data from NOAA U.S. Climate Reference Network for Research Computing in Earth Science
<p>This is a mirror of data from the NOAA U.S. Climate Reference Network (https://www.ncei.noaa.gov/products/land-based-station/us-climate-reference-network).</p> <p>It was created because outbound FTP access is not allowed from some cloud-based JupyterHub setups.</p>
Dataset test: Master Data Science (LEB Oro)
<p>Archivo de prueba para la asignatura de ciclo de vida de los datos. El dataset contiene las estadísticas principales de los equipos de la LEB Oro (2022/2023) de las primeras 20 jornadas.</p>
Data for "A snapshot of the long term evolution of a distributed tectonic plate boundary" submitted to Science Advances
<p>This compressed folder contains data presented in Figures of the following paper: "<strong>A snapshot of the long term evolution of a distributed tectonic plate boundary</strong>" by M. Dalaison, R. Jolivet, L. Le Pourhiet; submitted to <em>Science Advances</em> in February 2023</p> <p>Please open the README.txt file for details about the folder's content</p>
Bibliographic data on datasets affiliated to Poznan University of Technology and indexed in Data Citation Index (retrieved by Web of Science service in January 2023))
<p>The file contains the number of datasets published by the researchers affiliated to Poznan University of Technology and indexed in Data Citation Index provided by Web of Science (database updated 10.01.2023). The Search was performed using the name of institution in the 'Affiliation' field. Dataset contains two files in two diffrent formats: plain text and xls.</p>
Assessment of the acoustic adaptation hypothesis in frogs using large-scale citizen science data
<p>This is the data required to reproduce the results of the manuscript "Assessment of the acoustic adaptation hypothesis in frogs using large-scale citizen science data", including measurements of tree canopy cover extracted from the Global Forest Cover Change dataset (Townshend 2016).</p> <p> </p> <p><strong>Reference</strong></p> <p>Gillard, G. L. & Rowley, J. J. L. (2023). Assessment of the acoustic adaptation hypothesis in frogs using large-scale citizen science data. <em>Journal of Zoology</em>. [In publication].</p> <p> </p> <p><strong>Global Forest Cover Change Dataset</strong></p> <p>Townshend J. 2016. Global Forest Cover Change (GFCC) Tree Cover Multi-Year Global 30 m V003 [Data set]. NASA EOSDIS Land Processes DAAC. Accessed June 22, 2022. doi:10.5067/MEaSUREs/GFCC/GFCC30TC.003.Townshend J. 2016. Global Forest Cover Change (GFCC) Tree Cover Multi-Year Global 30 m V003 [Data set]. NASA EOSDIS Land Processes DAAC. Accessed June 22, 2022. doi:10.5067/MEaSUREs/GFCC/GFCC30TC.003.</p>
Uncovering the Citation Landscape: Exploring OpenCitations COCI, OpenCitations Meta, and ERIH-PLUS in Social Sciences and Humanities Journals - DATA PRODUCED
<p>This zipped folders contain all the data produced for the research "Uncovering the Citation Landscape: Exploring OpenCitations COCI, OpenCitations Meta, and ERIH-PLUS in Social Sciences and Humanities Journals": the results datasets (dataset_map_disciplines, dataset_no_SSH, dataset_SSH, erih_meta_with_disciplines and erih_meta_without_disciplines).</p> <ul> <li> <p><strong>dataset_map_disciplines.zip </strong>contains CSV files with four columns ("id", "citing", "cited", "disciplines") giving information about publications stored in OpenCitations META (version 3 released on February 2023) and part of SSH journals, according to ERIH PLUS (version downloaded on 2023-04-27), specifying the disciplines associated to them and a boolean value stating if they cite or are cited, according to the OpenCitations COCI dataset (version 19 released on January 2023).</p> </li> <li> <p><strong>dataset_no_SSH.zip </strong>and <strong>dataset_SSH.zip</strong> contain CSV files with the same structure. Each dataset has four columns: "citing", "is_citing_SSH", "cited", and "is_cited_SSH". ”Citing” and “cited” columns are filled with DOIs of publications stored in OpenCitations META that according to OpenCitations COCI are involved in a citation. The "is_citing_SSH" and "is_cited_SSH" columns contain boolean values: "True" if the corresponding publication is associated with a SSH (Social Sciences and Humanities) discipline, according to ERIH PLUS, and "False" otherwise. The two datasets are built starting from the two different subsets obtained as a result of the union between OpenCitations META and ERIH PLUS: dataset_SSH comes from erih_meta_with_disciplines and dataset_no_SSH from <strong>erih_meta_without_disciplines. </strong>dataset_no_SSH comes from <strong>erih_meta_with_disciplines.zip</strong> and erih_meta_without_disciplines.zip, as explained before, contain CSV files originating from ERIH PLUS and META. erih_meta_without_disciplines has just one column “id” and contains the DOIs of all the publications in META that do not have any discipline associated, that is, have not been published on a SSH journal, while erih_meta_with_disciplines derives from all the publications in META that have at least one linked discipline and has two columns: “id” and “erih_disciplines”, containing a string with all the disciplines linked to that publication like "History, Interdisciplinary research in the Humanities, Interdisciplinary research in the Social Sciences, Sociology".</p> </li> </ul> <p>Software: https://doi.org/10.5281/zenodo.8326023</p> <p>Data preprocessed: https://doi.org/10.5281/zenodo.7973159</p> <p>Article: https://zenodo.org/record/8326044</p> <p>DMP: https://zenodo.org/record/8324973</p> <p>Protocol: https://doi.org/10.17504/protocols.io.n92ldpeenl5b/v5</p>
Uncovering the Citation Landscape: Exploring OpenCitations COCI, OpenCitations Meta, and ERIH-PLUS in Social Sciences and Humanities Journals - DATA PREPROCESSED
<p>This zipped folders contain all the data preprocessed for the research "Uncovering the Citation Landscape: Exploring OpenCitations COCI, OpenCitations Meta, and ERIH-PLUS in Social Sciences and Humanities Journals": the cleaned datasets (coci_preprocessed, meta_preprocessed, erih_preprocessed and erih_meta).</p> <ul> <li> <p><strong>coci_preprocessed.zip</strong>: this archive contains CSVs with two columns “citing” and “cited”, giving information about publications involved in citations according to the OpenCitations COCI dataset (version 19 released on January 2023), and that are entirely contained in OpenCitations META (version 3 released on February 2023). This means that the citations which have either the citing or the cited entity (or both) not contained in META are excluded from coci_preprocessed dataset.</p> </li> <li> <p><strong>meta_preprocessed.zip</strong>: all the original columns of OpenCitations META are maintained in this dataset, so the CSVs have the columns: “id”, “title”, “author”, “issue”, “volume”, “venue”, “page”, “pub_date”, “type”, “publisher” and “editor”. The only difference with the original dataset is that meta_preprocessed in the columns “id” and “venue” has respectively just the DOIs and the ISSNs, without all the other identifiers specified for each entity in META.</p> </li> <li> <p><strong>erih_preprocessed.zip</strong>: it contains a CSV file with two columns "venue_id" and "ERIH_disciplines". "venue_id" is the union of the original columns "Online ISSN" and "Print ISSN" of ERIH_PLUS (version downloaded on 2023-04-27).</p> </li> <li> <p><strong>erih_meta.zip</strong>: it contains CSV files obtained from the union of meta_preprocessed and erih_preprocessed, they have all the columns of meta_preprocessed plus a new column “erih_disciplines” containing all the disciplines linked to a venue (identified by an ISSN).</p> </li> </ul> <p> </p> <p>Software: https://doi.org/10.5281/zenodo.8326023</p> <p>Data produced: https://doi.org/10.5281/zenodo.7974816</p> <p>Article: https://zenodo.org/record/8326044</p> <p>DMP: https://zenodo.org/record/8324973</p> <p>Protocol: https://doi.org/10.17504/protocols.io.n92ldpeenl5b/v5</p>
Data for: Home security cameras as a tool for behavior observations and science equity
<p class="MsoNormal">Reliably capturing transient animal behavior in the field and laboratory remains a logistical and financial challenge, especially for small ectotherms. Here, we present a camera system that is affordable, accessible, and suitable to monitor small, cold-blooded animals historically overlooked by commercial camera traps, such as small amphibians. The system is weather-resistant, can operate offline or online, and allows collection of time-sensitive behavioral data in laboratory and field conditions with continuous data storage for up to four weeks. The lightweight camera can also utilize phone notifications over Wi-Fi so that observers can be alerted when animals enter a space of interest, enabling sample collection at proper time periods. We present our findings, both technological and scientific, in an effort to elevate tools that enable researchers to maximize use of their research budgets. We discuss the relative affordability of our system for researchers in South America, which is home to the largest population of ectotherm diversity.</p>
Raw P-SHG data and processing codes for Raoux et al, Light Science and Applications 2023
<p><strong>Raw P-SHG data and processing codes</strong> for Raoux et al, Light Science and Applications 2023</p> <p>Article DOI: 10.1038/s41377-023-01224-0</p> <p>Raw P-SHG data: 10 human corneas</p> <p>Important: crop 20 pixels on left and right sides of all images to remove scanning artefacts and obtain 250 x 250 images</p> <p>voxel size: 1 µm in all directions<br> Channel 0: trans-2PEF<br> Channel 1: epi-2PEF<br> Channel 2: epi-SHG<br> Channel 3: trans-SHG</p>
Data for: Legacy community science data suggest reduced beached litter in response to a container deposit scheme at a local scale
<p>Marine debris is causing significant environmental harm. Legislation is being implemented to reduce litter, including schemes like container deposit legislation that incentivize the return of commonly littered items for recycling. While there is a suggestion that these schemes reduce litter, no study has examined the long-term impact on the local environment before and after implementation. This study analyzes community science data from 8 years prior to the implementation of a container deposit scheme, paired with 3 years of data afterwards, to assess the scheme's effectiveness at a local scale. Although using legacy datasets limits the generalizability of the conclusions compared to dedicated studies, the findings strongly indicate that container deposit schemes effectively manage targeted containers but have little impact on overall waste abundances. Long-term datasets like these are invaluable for assessing the impact of management efforts.</p>
Sixty-years of community-science data suggest earlier fall migration and short-stopping of several species of waterfowl in North America
<p>Worldwide, migratory phenology and movement of many bird species are shifting in response to anthropogenic climate and habitat changes. However, due to variation among species and a shortage of analyses, changes in waterfowl migration, particularly in the fall, are not well understood. Fall migration phenology and movement patterns dictate waterfowl hunting success and satisfaction, with cascading implications on economies and support for habitat management and securement. Using 60 years of band recovery data for waterfowl banded in the Canadian Prairie Pothole Region (PPR), we evaluated whether fall migration timing and/or distribution changed in Mallard (<em>Anas</em> <em>platyrhynchos</em>), Northern Pintail (<em>A. acuta</em>), and Blue-winged Teal (<em>Spatula</em> <em>discors</em>) between 1960 and 2019. We found that in the Midcontinent Flyways, Mallards and Blue-winged Teal migrated faster in more recent time periods, while Northern Pintail began fall migration earlier. In the Pacific Flyway, Mallards began fall migration earlier. Both Mallards and Northern Pintails showed evidence of short-stopping in the Midcontinent Flyways. Indeed, the Mallard and Northern Pintail distribution of band recovery data shifted 180 km and 226 km north respectively from 1960 to 2019. Conversely, Blue-winged Teal recovery distributions were consistent across years. Mallards and Northern Pintails also exhibited an increased proportion of band recoveries in the Pacific Flyway in recent decades. We provide clear evidence that the timing and routes of fall migration have shifted over the past six decades, but these phenological and spatial shifts differ among species. We suggest that using community-science data collected by hunters themselves to explain one of the group's major concerns (changes in duck abundance at traditional hunting grounds), within the environmental lens of climate change, may help lead to further engagement and two-way dialogue to support effective waterfowl management for these culturally and ecologically important species. </p>
Data from: Using network science to evaluate vulnerability of landslides on Big Sur Coast, California, USA
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Sixty-years of community-science data suggest earlier fall migration and short-stopping of several species of waterfowl in North America
Open the record for dataset details and reuse information.
Data from: Utilising citizen science data to rapidly assess changing associations between wild birds and avian influenza outbreaks in poultry
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Data from: Fun surveys? Developing an innovative approach to assessing learning through citizen science
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Data from: Sectorial pathways to achieve net-zero and 1.5°C targets for Eu-27: Energy and emissions data to inform science-based decarbonization targets
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Using convolutional neural networks to efficiently extract immense phenological data from community science images
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Data for: Legacy community science data suggest reduced beached litter in response to a container deposit scheme at a local scale
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Data for: Home security cameras as a tool for behavior observations and science equity
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Allen Brain Atlas
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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.