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3,172 results for “public”
Survey results for: Public perceptions of cultural ecosystem services provided by beach nourishment and eelgrass restoration in southern Sweden
<p>Ecosystem-based protection is becoming a viable adaptation option to conventional engineered solutions to rising sea levels and coastal erosion. While the environmental and biological ecosystem services provided by ecosystem-based adaptation measures such as beach nourishment and/or seagrass plantations are being acknowledged and analysed, less attention has been paid to the social or cultural dimensions of these services. This paper builds upon the emerging body of research that explores cultural ecosystem services in coastal areas and how they are perceived by the people who live, work and recreate in these areas. The aim of the paper is to take stock of and understand public and stakeholder perceptions of the cultural ecosystem services that may accrue through eelgrass (<em>Zostera marina</em>) restoration in tandem with beach nourishment in Southern Sweden. The empirical research is based on an online open-ended questionnaire in the coastal municipalities of Båstad, Trelleborg, Ystad and Kristianstad. The results demonstrate that virtually all respondents had noticed a change in the coastline in recent years, mainly that the coastline had retreated. While beach nourishment measures were recognized among respondents to counter the shoreline erosion, there was very little understanding of the role that eelgrass plantations can play in creating biodiversity and benefits for society. Still, most acknowledged the importance of making room for water and biodiversity at the coast, stating how the coastline was valued for primarily health and spiritual reasons. This knowledge will help local, regional, and national decision-makers and regulatory authorities to make evidence-based choices for coastal protection, by complementing the analysis of environmental and physical ecosystem-services with cultural and socio-economic considerations. Nature-based solutions such as eelgrass reintroduction or beach nourishment should be tailored to the values, perspectives, and perceptions of the local communities to help ensure their continued contribution to biodiversity.</p>
An Analysis of the Current Bibliographical Data Landscape in the Humanities. A Case for the Joint Bibliodata Agendas of Public Stakeholders - video presentation
<p>A video presenting the DARIAH's Bibliographical Data Working Group entitled <em>An Analysis of the Current Bibliographical Data Landscape in the Humanities. A Case for the Joint Bibliodata Agendas of Public Stakeholders. </em>The report is freely available on Zenodo: <a href="https://zenodo.org/record/6559857#.Y0XDo3ZBy5f">https://zenodo.org/record/6559857#.Y0XDo3ZBy5f</a>. </p> <p>This presentation aims to present the original work - co-authored by 18 WG's members - in a condensed manner.</p>
SSHOC Training Material Video 5 - Leveraging the the Ethnic and Migrant Minorities' (EMM) Survey Registry for public policy - training video in English, French and Spanish
<p>EMM Survey Registry - D9.4 - Video 5 Live Demo - Policy Making Stackholders (front- and back-end)</p> <p><strong>The video will begin by reiterating what the EMM Survey Registry is and why policy-making stakeholders (e.g. civil society and think tank communities; policymakers) interested in quantitative surveys on ethnic and migrant minorities’ integration and/or inclusion should be using this service. It will then explain how this target user group can both leverage the EMM Survey Registry for finding and learning about surveys, as well as showcasing surveys they have produced and/or have been involved in.</strong></p>
Data and scripts related to Cottaar, Martin, Li, Parai (2022) publication in Seismica
<p><strong>Codes and data for<br> Cottaar, Martin, Li, Parai, 2022, The root to the Galápagos mantle plume on the core-mantle boundary, Seismica</strong></p> <p>The four tar files with data (20161225.tar, 20190929.tar, 20150519.tar, 20170224.tar) need to be unpacked and moved into the ‘Data’ directory. Separate tar files were created to aid the upload process.</p> <p><br> Warning: These are not well-commented codes, but should run after dependencies are installed. Unfortunately, I do not currently have time to clean and comment them. Do feel free to get in touch at sc845@cam.ac.uk about anything.</p> <p>Figures from the paper:</p> <ul> <li>Figure 1- plot_map_paper.py</li> <li>Figures 2-5 - plot_everything_single_event.py</li> <li>Figure 6 - plot_beamresults.py</li> <li>Figure 7 - Cross-sections are obtained from http://www.earth.ox.ac.uk/~smachine/</li> <li>Figure 8 - Geochem_plot/plot_ulvzs.py Uses results from various publications as indicated in the paper.</li> </ul> <p><br> Dependencies (besides ‘standard’ python libraries)</p> <ul> <li>ObsPy - www.obspy.org - library for seismic data processing</li> <li>Basemap - https://matplotlib.org/basemap/ - now deprecated library for map plotting in matplotlib</li> </ul> <p>Observed data and synthetics are stored PICKLE format. Metadata are stored within. Using the data and accessing metadata is demonstrated in the various script. The process to download and process the data from the IRIS database, is included in the folder ‘Download_processing_codes’. Note that after this process quality control of the traces is applied by eye. This is why the final data set is included in the repository. </p> <p>Synthetics are made with the ‘sandwiched’ coupled-spectral element method (‘sandwiched’-CSEM). For access, please contact the authors of Capdeville, Y., To, A. and Romanowicz, B. (2003) ‘Coupling spectral elements and modes in a spherical Earth: an extension to the “sandwich” case’, Geophysical Journal International, 154(1), pp. 44–57. doi: 10.1046/j.1365-246X.2003.01959.x.</p> <p><br> Data is provided for the four events presented in the main paper. Synthetic data are stored in the subdirectory CSEM for each event. Input of the ULVZ model for each synthetic case are stored in the folder ‘Synthetic_ULVZ_input_files’. Model directories are named ULVZ160 to ULVZ180 and input files are anomalies.ULVZ160 to anomalies.ULVZ180.</p> <p>Vik colormap is from https://www.fabiocrameri.ch/colourmaps/</p> <p> </p> <p> </p> <p> </p> <p> </p>
Research - a Public Culture in 2065
<p>This presentation envisions an event from 2065, discussing the research environment around the year 2025 and how we enjoy research being a popular culture 40 years later. This short presentation draws parallels between Gastronomy and Research, originally two unpopular cultures that eventually spread to the masses in the 19ths and 21st centuries, respectively.</p> <p>Notes (for 2065): This event is not optimized for Meta environments. The organisers are compensating for the environmental impact.</p>
Data for publication: Nanomechanical and Structural Study of Au38 Nanocluster Langmuir-Blodgett Films Using Bimodal Atomic Force Microscopy and X-Ray Reflectivity
<p>Original data of Figures published in:</p> <p><strong>Nanomechanical and Structural Study of Au<sub>38</sub> Nanocluster Langmuir-Blodgett Films Using Bimodal Atomic Force Microscopy and X-Ray Reflectivity</strong></p> <p>Journal of Colloid and Interface Science, 2022, Michal Swierczewski<sup>,</sup> Alexis Chenneviere, Lay-Theng Lee, Plinio Maroni and Thomas Bürgi*<sup>[</sup></p> <p> </p>
Pompeii - Public Water Fountain 20
This public water fountain was scanned as part of the 2022 Pompeii Water and Sanitation Project field school run by the University of Missouri. The fountain is situated at VI.16.19 and is made of grey peperino slabs. The relief on the spout stone is of aflask with straps. The brass spout and plumbing is modern. More photos can be seen here: https://pompeiiinpictures.com/pompeiiinpictures/Fountains/Fountain%2061619.htm The model was generated in Agisoft Metashape from 232 photos taken using a Nikon Z5. Photo alignment was run on high, as was model generation - model has been decimated for export, and made manifold for 3D printing. Source: Objaverse 1.0 / Sketchfab
Public primary school in 19. century
Public primary school in 19. century (Croatia) in Military area add info - https://www.youtube.com/watch?v=_EHjTUXqoHE&t=78s The work represents a public school from **1877** in the area of Vojna Krajina (**Administrative Municipality of Sibinj**). The novelty from that time is that he had a toilet and that it was mixed. Source: Objaverse 1.0 / Sketchfab
Koriyama City Public Hall(japan)
# A nationally registered, tangible cultural property # 国登録有形文化財 郡山公会堂 Completed in 1924 to commemorate the city status of Koriyama City in 1924. Simulating a drawing of the Hague Peace Palace in the Netherlands, it has a continuous semicircular arched colonnade, window sills, a tower that emphasizes it's height via a long glass surface installed in the corner of the frame; all carefully designed with raised and lowered windows. It is popular as a symbol of Koriyama City and is still used today for concerts. Address is Koriyama City, Fukushima Prefecture, Japan https://goo.gl/maps/VxsWYHZBptg7jzju6 Source: Objaverse 1.0 / Sketchfab
Ježek - Hedgehog public art
**Ježek - Hedgehog**, public art sculpture statue object 2021 repaint version: https://skfb.ly/o7wsp Sculpture artist: Karel Kučera @ Ústí nad Labem CZ, Park republiky • https://goo.gl/maps/ecbpQxznPmTfARbr9 July 27 2019 photogrammetry scan (24MP, 200 photos) • https://pavelmatousek.cz Source: Objaverse 1.0 / Sketchfab
Money of the Ufa Public Meeting (1918).
Banknote of the Public meeting (club) of the city of Ufa. Monetary unit: ruble. Denomination: 3. Year of issue: June 1, 1918. Material: paper. Published after the liberation of Ufa from the Bolsheviks by the Czechoslovak Corps. Деньги Уфимского Общественного собрания (1918). Денежная марка Общественного собрания (клуба) города Уфы. Денежная единица: рубль. Номинал: 3. Год выпуска: 1 июня 1918 года. Материал: бумага. Напечатано после освобождения Уфы от большевиков чехо-словацким корпусом. Source: Objaverse 1.0 / Sketchfab
Species Photos.zip Archive of fish species images for the publication of: Starck, W.A., Estapé C.J. & Morgan Estapé, A. (2017) The fishes of Alligator Reef and environs in the Florida Keys: a half-century update. Journal of the Ocean Science Foundation, 27, 74–117.
<p>Species Photos.zip </p> <p>Archive of fish species images for the publication of:</p> <p>Starck, W.A., Estapé C.J. & Morgan Estapé, A. (2017) The fishes of Alligator Reef and environs in the Florida Keys: a half-century update. Journal of the Ocean Science Foundation, 27, 74–117.</p> <p>323 images, 318 species total,(5 species of Pomacentridae have pictures of both juvenile and adult phases)</p> <p>Carcharodon carcharias screen grab from video*<br> Centropristis ocyurus photo by C.Wangen<br> Dasyatis centroura screen grab from video by Ed. Martin<br> Diapterus sp. photo by Ed Martin. </p> <p>All other photos taken by Carlos Estapé and Allison Estapé in the study area (319 images of 314 species)</p> <p>*YouTube video - Snorkelers Spot Great White Shark Off Islamorada, https://www.youtube.com/watch?v=50l2grfaNQ4</p>
Reproducible Self-Publication Pitch 2017-08-31
<p>The <strong>Rep</strong>roducible <strong>Se</strong>lf <strong>P</strong>ublishing toolkit demonstrates how to dynamically include publication-quality data analysis output in most common science communication formats. Data analysis is defined in one and only one place, and styling is applied at the document or output element level. Data <em>and</em> code dependencies are provided or specified, so that both the toolkit itself - as well as your own derivatives - can be reproduced locally and autonomosly by your colleagues, reviewers, students, and everybody else.</p>
Dataset for the publication 'Feasibility of track-based multiple scattering tomography'
<p>This repository holds the data on which the publication `Feasibility of track-based multiple scattering tomography' is based on.</p> <p>This data were produced using the AllPix framework version 1.1 (c.f. references in the publication) with the template appended.</p> <p>The data is organised in one file per rotation angle. 180 angles have been scanned, 0 degrees corresponds to run0081500.raw.</p> <p>All run numbers, angle settings and additional parameters are detailed in the README file and the AllPix template file.</p>
Publications Office SPARQL queries for RDF benchmark
<p>This dataset contains the queries used for the benchmarking of the RDF stores for the EU Publications Office (PO).</p> <p>The queries are divided in three categories according to the types of queries. The initial queries from PO where validated using Jena tool to make them compliant with any SPARQL endpoint. </p>
pyigm/pyigm: Initial release for publications
<p>This is the first release of pyigm to give it a DOI and thereby enable it to be cited.</p> <p>It is a combination of software and published datasets.</p>
Data for publication on GARRLiC and LIRIC
<p>Data used in publication:</p> <p> </p> <p>Tsekeri, A., Lopatin, A., Amiridis, V., Marinou, E., Igloffstein, J., Siomos, N., Solomos, S., Kokkalis, P., Engelmann, R., Baars, H., Gratsea, M., Raptis, P. I., Binietoglou, I., Mihalopoulos, N., Kalivitis, N., Kouvarakis, G., Bartsotas, N., Kallos, G., Basart, S., Schuettemeyer, D., Wandinger, U., Ansmann, A., Chaikovsky, A. P., and Dubovik, O.: GARRLiC and LIRIC: strengths and limitations for the characterization of dust and marine particles along with their mixtures, Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2017-214, in review, 2017.</p>
Somatosensory data for group analyses in the Frontiers Reseach Topic: From raw MEG/EEG to publication: how to perform MEG/EEG group analysis with free academic software.
<p><strong>If you use the data or the analysis pipeline, please refer to:</strong></p> <p>Andersen, L.M., 2018. Group Analysis in MNE-Python of Evoked Responses from a Tactile Stimulation Paradigm: A Pipeline for Reproducibility at Every Step of Processing, Going from Individual Sensor Space Representations to an across-Group Source Space Representation. Front. Neurosci. 12. <a href="https://doi.org/10.3389/fnins.2018.00006">https://doi.org/10.3389/fnins.2018.00006</a></p> <p><strong>and/or</strong></p> <p>Andersen, L.M., 2018. Group Analysis in FieldTrip of Time-Frequency Responses: A Pipeline for Reproducibility at Every Step of Processing, Going From Individual Sensor Space Representations to an Across-Group Source Space Representation. Front. Neurosci. 12. <a href="https://doi.org/10.3389/fnins.2018.00261">https://doi.org/10.3389/fnins.2018.00261</a></p> <p><strong>IMPORTANT</strong><br> Version 2 only contains subjects 1, 18, 20 and a new version of the FreeSurfer folder. This is due to a (very) wrong co-registration for subject 1 and due to 18 and 20 having had their anatomy files mixed up. This has now been fixed. For all other subjects, please see version 1. Also, get the updated scripts from github instead at: <a href="https://github.com/ualsbombe/omission_frontiers.git">https://github.com/ualsbombe/omission_frontiers.git</a></p> <p><br> </p> <p>Dataset with tactile expectations to be analysed with pipelines for either <a href="https://mne.tools/stable/index.html">MNE-Python</a> or <a href="http://www.fieldtriptoolbox.org/">FieldTrip</a>, aiming to follow the MEG-BIDS structure</p> <p><br> <strong>Unzipping the data</strong></p> <p>Data is compressed into twenty-two different zip-files, one for each of the twenty subjects, one for the FreeSurfer data, one for the scripts files . The easiest way to uncompress and prepare the analysis directories is to create a directory in your home folder called "analyses", which has a sub-directory called "omission_frontiers_BIDS-FieldTrip", which has a sub-directory called "data".<br> Thus, as an example, in my case, I should have the path: /home/lau/analyses/omission_frontiers_BIDS-FieldTrip/data</p> <p><strong>Path:</strong><br> on a Linux system the path would be /home/your_name/analyses/omission_frontiers_BIDS-FieldTrip/data<br> on a macOS system the path would be /Users/your_name/analyses/omission_frontiers_BIDS-FieldTrip/data<br> on a Windows system the path would be C:\Users\your_name\analyses\omission_frontiers_BIDS-FieldTrip\data</p> <p><strong>Steps for unzipping:</strong></p> <p>1. Set up the folder above according to your operating system, following the examples above and substitute "your_name" for your user name.<br> 2. Unzip each of the subject folders into the data folder (sub-01 - sub-20) (/home/your_name/analyses/omission_frontiers_BIDS-FieldTrip/data)<br> 3. Also unzip the FreeSurfer folder into the data folder (/home/your_name/analyses/omission_frontiers_BIDS-FieldTrip/data)<br> 4. Finally, unzip the scripts folder into /home/your_name/analyses/omission_frontiers_BIDS-FieldTrip/</p> <p>Now you are ready to run the analyses.</p> <p><br> <strong>The MEG data</strong></p> <p>Raw fif files are contained in the data folder, ordered by subject (n=20)<br> There is one recording for each subject, MaxFiltered, called oddball_absence-tsss-mc_meg.fif. These are split into three files with -1 and -2 being the remainder of the recording</p> <p><strong>Processed MRI data </strong></p> <p>For the MRI, only the segmented data are provided. This is to sufficient to make the volume conduction model and the source model, while protecting the subjects' identity</p> <p>For Fieldtrip, there is an mri_segmented.mat for each subject, which is found in the meg (sic!) folder for each subject. This has been co-registered to the MEG data<br> For MNE-Python, the FreeSurfer directory should also be used, which contains a folder for each subject that contains surfaces (surf) and boundary element methods models (bem) that are used for source reconstruction in MNE-python. There is also a trans-file for each subject (oddball_absence_dense-trans.fif) in the meg folder specifying the co-registration between MEG and MRI coordinate systems for the MNE-Python analysis. Finally, the FreeSurfer folder also contains the labels for the cortical surface. This is not used in any of the analyses, but are supplied for interested users.</p> <p><br> <strong>Metadata</strong></p> <p>Each subject has a number of tsv-files:<br> *channel.tsv contain information about the channels in that recording<br> *events.tsv contain information about the events in that recording<br> removed_trial_indices.tsv contains information about which events were removed manually (NB! this is only used for the FieldTrip analysis)<br> ica_components.tsv contains information which independent component were removed manually (NB! this is only used for the FieldTrip analysis)<br> *scans_tsv contain information about the scans conducted</p> <p><br> <strong>Scripts </strong></p> <p>Please see Github for the updated scripts at: <a href="https://github.com/ualsbombe/omission_frontiers.git">https://github.com/ualsbombe/omission_frontiers.git</a></p>
Publication_Data
<p>This repository contains code and dataset used in the co-authored article titled: Machine Learning for UAV and Ground-Captured Imagery: Toward Standard Practices. </p>
ArXiv OAI-PMH arXivRaw publication metadata
<p>This dataset contains <a href="https://www.openarchives.org/pmh/">OAI-PMH</a> metadata for all <a href="https://arxiv.org/">ArXiv</a> publications up until 2024-04-23 in the <a href="http://arxiv.org/OAI/arXivRaw.xsd"><em>arXivRaw</em> XML format</a>.</p> <p>The metadata has been harvested using the <a href="https://github.com/miku/metha/releases/tag/v0.3.3"><em>metha</em> Go package v0.3.3</a> [1] on <a href="https://go.dev/"><em>go1.18</em></a>. Specifically, harvesting was run on a small HPC cluster using the following <a href="https://slurm.schedmd.com">SLURM</a> script. The script had to be scheduled twice due to the connection being reset by the peer (see <em>combined-slurm.out</em>). <em>metha</em> caters for these situations and is able to pick up where it left off with cumulative harvesting.</p> <pre><code>#!/bin/bash #SBATCH --job-name=metha #SBATCH --nodes=1 #SBATCH --cpus-per-task=1 #SBATCH --ntasks=1 #SBATCH --time=10-20:00:00 module purge echo "Installing Go module." module add go/go-1.18/go-1.18-gcc-9.4.0-okbjyoy echo "Installed Go module: $(go version)." echo "Installing metha." go install -v github.com/miku/metha/cmd/...@latest echo "Installed metha: $(<retracted>/go/bin/metha-sync -v)" echo "Harvesting ArXiv OAI-PMH metadata in format 'arXivRaw' from http://export.arxiv.org/oai2." <retracted>/go/bin/metha-sync -T 5m -base-dir /scratch/<retracted>/arxiv -format "arXivRaw" http://export.arxiv.org/oai2 # For the second run, '-from' was specified to pick up the harvest where it was left off. # <retracted>/go/bin/metha-sync -from 2020-09-29 -T 5m -base-dir /scratch/<retracted>/arxiv -format "arXivRaw" http://export.arxiv.org/oai2 echo "Done." exit 0</code></pre> <h2>Dataset contents</h2> <p>This deposit of the dataset contains the following files:</p> <ul> <li><strong>metha-output-OAI-PMH-arXivRaw-until-2024-03-24.tar.gz</strong>: an archive file containing the archive files (gzipped, <em>*.xml.gz</em>) produced by <em>metha</em>, which in turn contain the XML metadata files. The gzipped files contained in the archive are named following the pattern <em>YYYY-MM-DD-<8-digit zero-padded 0-index file count>.xml.gz</em>, e.g., <em>2024-03-24-00000001.xml.gz</em>.</li> <li><strong>README.md</strong>: This file, containing basic information about the dataset and deposit.</li> <li><strong>combined-slurm.out</strong>: The combined SLURM log for the two consecutive SLURM runs that have produced the dataset. Run-specific information has been retracted.</li> </ul> <h2>Reproducibility</h2> <p>As the OAI-PMH metadata is not static but may change at any time, this dataset isn't fully reproducible. However, running the same <em>metha</em> version on the same <em>go</em> version with the same commands should yield very similar results, but will contain newer metadata.</p> <h2>Licenses</h2> <ul> <li>All ArXiv OAI-PMH metadata is <a href="https://info.arxiv.org/help/license/index.html#metadata-license">licensed</a> under <a href="https://creativecommons.org/publicdomain/zero/1.0/deed">CC0-1.0</a>.</li> <li>combined-slurm.out is licensed under <a href="https://creativecommons.org/publicdomain/zero/1.0/deed">CC0-1.0</a>.</li> <li>README.md is licensed under <a href="https://creativecommons.org/publicdomain/zero/1.0/deed">CC0-1.0</a>.</li> </ul> <p>Licenses are documented in a machine-readble manner following the <a href="https://reuse.software/spec/">REUSE 3.0 Specification</a>. License deeds are included in this deposit as <em>.txt</em> files named using the respective SPDX license identifiers.</p> <p>[1] Martin Czygan, Thomas Gersch, ACz-UniBi, Justin Kelly, Gunnar Þór Magnússon, dvglc, & Natanael Arndt. (2024). miku/metha: v0.3.3 (v0.3.3). Zenodo. doi:<a href="https://doi.org/10.5281/zenodo.10940212">10.5281/zenodo.10940212</a>.</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.