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3,126 results for “france”
L'achat de produits de contrefaçon en France : une application de la théorie du comportement planifié
<p>Cette base de données est issue d’une enquête quantitative par questionnaire (n= 415, année 2021). Elle est construite sur la base de la théorie du comportement planifié. La variable dépendante est le comportement d’achat de produits de contrefaçon.</p> <p><em>Contenu de la base de données</em></p> <p>Le questionnaire comprend les mesures suivantes : 3 variables de signalétique, 7 variables de segmentation, le comportement d’achat (2 items : fréquence et récence), l’intention comportementale (2 items dont 1 d’identité personnelle ; cf. infra pour la justification théorique), les croyances sur les bénéfices attendus (9 items), l’attitude (3 items), les croyances sur les freins perçus (12 items), la perception de contrôle sur le comportement (2 items), les normes descriptives (2 items), les normes injonctives (2 items). L’administration étant réalisée en ligne, la base de données comprend également une variable « temps de saisie » du questionnaire qui pourra servir à épurer la base. Toutes les variables à échelle sont mesurées en 6 points.</p>
Intention de parler positivement des LGBT chez les jeunes en France. Une application de la théorie du comportement planifié
<p>Cette base de données est issue d’une enquête quantitative par questionnaire (n= 372, année : 2020). Elle est construite sur la base de la théorie du comportement planifié. La variable dépendante est l’intention Intention de parler positivement des LGBT lors d'une discussion. La population mère : les jeunes de 17 à 25 ans.</p> <p><em>Contenu de la base de données</em></p> <p>Le questionnaire comprend les mesures suivantes : 1 item de connaissance objective, 1 item d’engagement dans le questionnaire, 7 variables de segmentation, l’intention comportementale (2 items dont 1 d’identité personnelle ; cf. infra pour la justification théorique), les croyances sur les bénéfices attendus (9 items), l’attitude (3 items), les croyances sur les freins perçus (7 items), la perception de contrôle sur le comportement (2 items), les normes descriptives (2 items), les normes injonctives (2 items) et 5 variables de signalétique. L’administration étant réalisée en ligne, la base de données comprend également une variable « temps de saisie » du questionnaire qui pourra servir à épurer la base. Toutes les variables à échelle sont mesurées en 7 points.</p>
La consommation de contenus sur Netflix chez les jeunes en France : une application de la théorie du comportement planifié.
<p>Cette base de données est issue d’une enquête quantitative par questionnaire (n= 325, année 2020, février-mars). Elle est construite sur la base de la théorie du comportement planifié. La variable dépendante est la consommation de contenus sur Netflix. La population mère : les jeunes de 17 à 25 ans.</p> <p><em>Contenu de la base de données</em></p> <p>Le questionnaire comprend les mesures suivantes : 3 variables de segmentation, le comportement de l’individu (2 items : fréquence et récence), l’intention comportementale (2 items dont 1 d’identité personnelle ; cf. infra pour la justification théorique), les croyances sur les bénéfices attendus (13 items), l’attitude (3 items), les croyances sur les freins perçus (9 items), la perception de contrôle sur le comportement (2 items), les normes descriptives (2 items), les normes injonctives (2 items), 2 variables de signalétique (sexe et âge). L’administration étant réalisée en ligne, la base de données comprend également une variable « temps de saisie » du questionnaire qui pourra servir à épurer la base. Toutes les variables à échelle sont mesurées en 6 points.</p>
Intention de soutenir la légalisation du cannabis chez les jeunes en France : une application de la théorie du comportement planifié.
<p>Cette base de données est issue d’une enquête quantitative par questionnaire (n= 434, année 2021). Elle est construite sur la base de la théorie du comportement planifié. La variable dépendante est l’intention de soutenir la légalisation du cannabis lors d'une discussion. La population mère : les jeunes de 17 à 25 ans.</p> <p><em>Contenu de la base de données</em></p> <p>Le questionnaire comprend les mesures suivantes : 4 variables de signalétique, l’intention comportementale (2 items dont 1 d’identité personnelle), les croyances sur les bénéfices attendus (14 items), l’attitude (3 items), les croyances sur les freins perçus (7 items), la perception de contrôle sur le comportement (2 items), les normes descriptives (2 items), les normes injonctives (2 items), les comportements de consommation de cannabis et les modalités de la légalisation (7 items). L’administration étant réalisée en ligne, la base de données comprend également une variable « temps de saisie » du questionnaire qui pourra servir à épurer la base. Toutes les variables à échelle sont mesurées en 6 points.</p>
E-commerce et covid 19 en France. Une application de la théorie du comportement planifié
<p>Cette base de données est issue d’une enquête quantitative par questionnaire (n= 378, année 2021). Elle est construite sur la base de la théorie du comportement planifié. La variable dépendante est l’achat de biens et/ou de services par internet.</p> <p><em>Contenu de la base de données</em></p> <p>Le questionnaire comprend les mesures suivantes : 2 variables de segmentation (piratage et type d’achat), le comportement de l’individu (2 items : fréquence et récence), l’impact du Covid-19 sur la fréquence d’achat (1 item), l’intention comportementale (2 items dont 1 d’identité personnelle), les croyances sur les bénéfices attendus (11 items), l’attitude (3 items), les croyances sur les freins perçus (13 items), la perception de contrôle sur le comportement (2 items), les normes descriptives (2 items), les normes injonctives (2 items), 3 variables de signalétique (sexe, âge et CSP). L’administration étant réalisée en ligne, la base de données comprend également une variable « temps de saisie » du questionnaire qui pourra servir à épurer la base. Toutes les variables à échelle sont mesurées en 6 points.</p>
RookID: an annotated dataset of vocalisations produced by individually-identified rooks housed together in an outdoors aviary in France
<p>A dataset of annotated recordings of a captive colony of rooks, recorded in Strasbourg, France in 2020 and 2021. Each rook was individually identifiable with leg rings. All recordings were taken in the morning a few hours after sunrise, when the birds were most vocally active. The colony was housed outdoors, so other noises are present, including both biotic (most notably various birds, human voices, and other animals) and abiotic (mostly car and train noises).</p> <p>Audio files (.wav): recorded at 48 kHz, 16-bit using 1 to 3 Song Meter 4 recorders (Wildlife Acoustics). Each recorder had two microphone with different gains to maximise dynamic range. The files were then manually synchronised and merged into multichannel (2 to 6) files.</p> <p>Label files (.tsv): Labels corresponding to each recording (each pair has the same name), noting the time stamps and individual emitter for each vocalisation. A single observer annotated all the recordings. Only rook vocalisations from the captive colony were annotated, not other bird vocalisations or the various noises in the data. The annotations consist of tables with 5 columns: </p> <ul> <li>Source: the individual producing the vocalisation. Note that only the bird's name is indicated. "Inc" and "Pls" are special cases: the first was for when identity could not be determined, the second when multiple individuals vocalised at once in such a manner that individuals could not be separated</li> <li>Start: starting time point for the vocalisation, in seconds (determined as the earliest point when the vocalisation was heard on any channel)</li> <li>End: ending time point for the vocalisation, in seconds (determined as the last point when the vocalisation was head on any channel)</li> <li>Event: gives information for the bird's activity at the time of the vocalisation, but largely in abbreviated form. One particular case is "sing", which correspond to vocalisations part of a song bout (which are defined as sequences of different vocalisations separated by less than approximately 10 seconds).</li> <li>Comment: other observations regarding the vocalisation. These are usually not standardised compared to the Event column. One special case is for "Pls": the Comment column then bears information regarding the identity of the individuals involved.</li> </ul> <p> </p> <p>This dataset was used in our article "Acoustic detection and identification of individual rooks in field recordings using multi-task neural networks", to train neural networks to identify individual rooks. The dataset was therefore randomly split into train-validation-test datasets. For reproducibility, we provide the "splitting.csv" which contains the information pertaining to which files go in each dataset, and two scripts to do the split automatically.</p> <p>To do so: download and unpack the RookID folder somewhere on your computer, then download splitting.csv and either of the scripts to the same location. Both scripts will MOVE, not copy, the files to new folders corresponding to each dataset.</p> <ul> <li>with split_data.R: open the scrip in an RStudio environment, edit the out_path variable to the desired location, and run the script</li> <li>with split_data.py: run the following command line: python /path/to/split_data.py --out_path path/to/desired/location (note that the script will automatically create the necessary tree structure)</li> <li>Both scripts can be run without editing the out_path variables, in which case the new folders will be created at the same location</li> </ul> <p> </p> <p>For further information, see our code at <a href="https://gitlab.com/kimartin/rook-vocalisation-detection">https://gitlab.com/kimartin/rook-vocalisation-detection</a></p> <p>For any inquiries, please contact Killian Martin (<a href="mailto:killian.martin@ens-lyon.fr?subject=Inquiry%20about%20the%20RookID%20dataset">killian.martin@ens-lyon.fr</a>)</p>
State of open science practices in France _ Dataset
<p>L’enquête State of Open Science Practices in France (SOSP-FR) a été conduite entre juin 2020 et septembre 2020. Elle a pour but d’interroger les pratiques des outils numériques et autour des données de la recherche dans les communautés scientifiques françaises. Le questionnaire se compose de 38 questions réparties en 9 thématiques. Les questions portent sur des pratiques déjà établies et des pratiques ou usages émergents comme l’<em>open peer review </em>ou les articles de données dits <em>data papers</em>. Le nombre de répondants est de 1 089, permettant d’interroger une répartition disciplinaire, genrée et statutaire assez représentative de l’état de l’emploi dans l’enseignement supérieur et de recherche en France.</p> <p>Les données ont été recueillies en 2020 via le logiciel Sphinx, mis à disposition par la TGIR Huma-Num.</p> <p>Le fichier SOSP_metadonnées_variables liste les variables avec les questions et les modalités associées. Il précise le traitement des données.</p> <p>Cette recherche a été financée par le Comité pour la science ouverte: <a href="https://www.ouvrirlascience.fr/sosp_-state-of-open-science-practices-in-france/">https://www.ouvrirlascience.fr/sosp_-state-of-open-science-practices-in-france/</a></p> <p>The State of Open Science Practices in France (SOSP-FR) survey was carried out between June 2020 and September 2020. It aims to question the practices of digital tools and about research data in French scientific communities. The questionnaire consists of 38 questions divided into 9 themes. The questions concern practices already fixed and those emerging uses such as open peer review or data papers. The number of respondents was 1089, making possible a fairly representative disciplinary, gender and status analyse of the state of employment in higher education and research in France.</p> <p>The data were collected in 2020 using the Sphinx software, provided by the TGIR Huma-Num.</p> <p>The SOSP_metadonnées_variables.csv file lists the variables with the associated questions and modalities.</p> <p>This research was funded by the Open Science Committee: <a href="http://The data were collected in 2020 using the Sphinx software, provided by the TGIR Huma-Num. The readme.csv file lists the variables with the associated questions and modalities. This research was funded by the Open Science Committee: https://www.ouvrirlascience.fr/sosp_-state-of-open-science-practices-in-france/">https://www.ouvrirlascience.fr/sosp_-state-of-open-science-practices-in-france/</a></p>
Periodic Hydraulic Testing Dataset for "Borehole-based fracture unclogging experiment: bridging the gap between laboratory- and field-scale evidence (FRANC)"
<p>This dataset is associated with the SNSF-SPARK project “Borehole-based fracture unclogging experiment: bridging the gap between laboratory- and field-scale evidence (FRANC)”. Please read the ReadMe file for more information.</p>
CoMix social contact data (France)
<p>CoMix social contact data for France.</p> <p>We gratefully acknowledge the efforts of all teams involved in the implementation of the CoMix study in their country. More specifically: the team of Guillaume Béraud at the Centre Hospitalier Universitaire de Poitiers.</p>
MAL04 Causal loop diagrams for the Charente River basin and its coastal zone (France)
<p>This dataset includes the causal loop diagrams (CLDs) developed by the H2020 COASTAL project’s MAL #4 for the Charente River basin and its coastal zone. These CLDs represent the functioning of the territory in a systemic way, highlighting its main components and interactions among them. The CLDs are the result of multiple sectoral and multi-actor workshops during which stakeholders from different sectors discussed and collaborated to establish a common vision of the land-sea system. The CLDs concern the whole territory and some specific sectors.</p>
MAL04 Territorial development scenarios for the Charente River basin and its coastal zone (France)
<p>This dataset includes the territorial development scenarios developed by the H2020 COASTAL project’s MAL #4 for the Charente River basin and its coastal zone. These scenarios were co-designed with local stakeholders to depict possible futures of the territory. “Towards a desirable future” represents the implementation of the business roadmap also designed in collaboration with stakeholders to achieve a desirable and sustainable future. “Improving current trends” describes the expected evolution of the territory if current efforts are maintained without significant innovation. “Towards a fragmented territory” illustrates a negative development of the territory, exacerbating current issues and inequalities. Each scenario consists in a narrative and in a set of values attributed to the decision variables of the MAL #4 system dynamics model. These values are converted into time-series to simulate the scenarios (cf. data_scenarios.xlsx in <a href="https://doi.org/10.5281/zenodo.7075123">https://doi.org/10.5281/zenodo.7075123</a>).</p>
AI results complementing the 2021 Annual Report on surveillance for Avian Influenza in poultry and wild birds in Member States of the European Union - France
<p>This dataset contains the results of the EU co-funded surveillance activities conducted in 2021, which consisted of:</p> <ul> <li>Serological surveys to monitor the circulation of AIV subtypes H5 and H7 in poultry (active surveillance). These surveys should preferentially target poultry species or production systems with increased risk for introduction of avian influenza (AI).</li> <li>Passive surveillance aiming at the virological detection of AI in wild birds found dead or moribund.</li> </ul>
Atomic clock dataset for 'Coherent Optical-Fiber Link Across Italy and France'
<p>Dataset of the comparison of the atomic clocks at LNE-SYRTE and INRIM via optical fibre link between October 2021 and February 2022. Results discussed in Clivati et al., Coherent Optical-Fiber Link Across Italy and France, <em>Phys. Rev. Applied, American Physical Society, </em><em> 18</em>, 054009, <strong>202<em>2</em></strong>.</p> <p>The involved atomic clocks are the Cs fountains SYRTE-F02Cs, IT-CsF2, the Rb fountain SYRTE-F02Rb and the Yb optical lattice clock IT-Yb1.</p> <p>Data is organized in folders, one for each comparison. In the folders data is separated is one file per day. Data is reported as fractional frequency ratios in bins of 864 s. Timetags are reported in modified Julian date (MJD). A validity flag is given where 0 = invalid, valid otherwise. Each folder includes a yaml file with metadata required for generalized data processing as in [Lodewyck et al., 2020]. The Python package used for data processing can be found on <a href="https://github.com/INRIM/tintervals">github.</a></p> <p> </p>
Franc Laporšek (l2168)
<b>-- <a href="https://doi.org/10.5281/zenodo.11582199">Documentation</a> --</b><br><br><u>Name</u>: Franc Laporšek<br><u>musiXplora-ID</u>: l2168<br><u>musiXplora-URI</u>: <a href="https://musixplora.de/mxp/l2168">https://musixplora.de/mxp/l2168</a><br><u>Gender</u>: m<br><u>Date of Birth</u>: 1930<br><u>Place of Birth</u>: Undefined<br><u>Date of Death</u>: 1998<br><u>Place of Death</u>: Undefined<br><u>First Mentioned</u>: 1960<br><u>Professions (Historical)</u>: Fozhobelspieler<br><u>Professions (Musical)</u>: Flötenbauer, Flötist<br><u>Professions (Non-Musical)</u>: Bauer<br><u>Other Places of Activity</u>: Jablovcu<br><br><br><br><u>Changelog</u>:<br> - v0.0.1: Initial Upload.<br>
Franc Jenko (j0628)
<b>-- <a href="https://doi.org/10.5281/zenodo.11582199">Documentation</a> --</b><br><br><u>Name</u>: Franc Jenko<br><u>musiXplora-ID</u>: j0628<br><u>musiXplora-URI</u>: <a href="https://musixplora.de/mxp/j0628">https://musixplora.de/mxp/j0628</a><br><u>Gender</u>: m<br><u>Date of Birth</u>: 1895<br><u>Place of Birth</u>: Mengeš<br><u>Date of Death</u>: 1968<br><u>Place of Death</u>: Ljubljana<br><u>First Mentioned</u>: 1927<br><u>Sectors</u>: Kirche, Orgelbau<br><u>Professions (Musical)</u>: Orgelbauer<br><u>Other Places of Activity</u>: Belgrad, Dubrovnik, Ljubljana, Pula, Šibenik<br><br><br><br><u>Changelog</u>:<br> - v0.0.1: Initial Upload.<br>
Franc Goršič (g2313)
<b>-- <a href="https://doi.org/10.5281/zenodo.11582199">Documentation</a> --</b><br><br><u>Name</u>: Franc Goršič<br><u>musiXplora-ID</u>: g2313<br><u>musiXplora-URI</u>: <a href="https://musixplora.de/mxp/g2313">https://musixplora.de/mxp/g2313</a><br><u>Gender</u>: m<br><u>Date of Birth</u>: 21 October 1836<br><u>Place of Birth</u>: Ljubljana<br><u>Date of Death</u>: 29 August 1898<br><u>Place of Death</u>: Ljubljana<br><u>First Mentioned</u>: 1864<br><u>Sectors</u>: Orgelbau<br><u>Professions (Musical)</u>: Orgelbauer<br><u>Other Places of Activity</u>: Dübendorf, Ljubljana, Novo mesto, Triest, Zagorje ob Savi, Škofja Loka<br><br><br><u>Ausbildung:</u><br><table><tbody><tr><th>Group</th><th>Role</th><th>Name</th><th>mXp-ID</th></tr><tr><td>LehrerInnen und AusbilderInnen</td><td>Lehrer</td><td>Ivan Milavec</td><td><a href="https://musixplora.de/mxp/m2786">m2786</a></td></tr></tbody></table><br><br><u>Changelog</u>:<br> - v0.0.1: Initial Upload.<br>
Franc Focht (f1915)
<b>-- <a href="https://doi.org/10.5281/zenodo.11582199">Documentation</a> --</b><br><br><u>Name</u>: Franc Focht<br><u>musiXplora-ID</u>: f1915<br><u>musiXplora-URI</u>: <a href="https://musixplora.de/mxp/f1915">https://musixplora.de/mxp/f1915</a><br><u>Gender</u>: m<br><u>Date of Birth</u>: 1779<br><u>Place of Birth</u>: Grottkau<br><u>Date of Death</u>: 1852<br><u>Place of Death</u>: Pécs<br><u>First Mentioned</u>: 1816<br><u>Sectors</u>: Orgelbau<br><u>Professions (Musical)</u>: Orgelbauer<br><u>Other Places of Activity</u>: Großwardein, Metschge, Pregrada, Pécs, Wien, Zagreb<br><br><br><u>Herkunftsfamilie:</u><br><table><tbody><tr><th>Group</th><th>Role</th><th>Name</th><th>mXp-ID</th></tr><tr><td>Eltern</td><td>Vater</td><td>Karl Focht</td><td><a href="https://musixplora.de/mxp/f1916">f1916</a></td></tr></tbody></table><br><br><u>Changelog</u>:<br> - v0.0.1: Initial Upload.<br>
Socio-political attitudes in France (2023)
<p>This dataset captures the responses of over 1500 participants in France to an original online survey.</p> <p>This online survey was designed by a group of experts in populism from Universidad Nacional de Educación a Distancia (UNED, Madrid), King's College London, Univerity of York, Universidad Diego Portales, Chile, Universidad Autónoma de Madrid (UAM) and University of Liverpool.</p> <p>The survey contains over a hundred items:</p> <ul> <li>Socio-demographic items: education, age, religion, gender, employment</li> <li>Populism items: including Akkerman et al.'s 2014 scale of populist attitudes, and a new items corresponding to a new multi-dimensional scale of populist attitudes (Olivas Osuna 2021; Olivas Osuna 2024; Olivas Osuna et al. forthcoming) (32 items)</li> <li>Items related to trust on institutions and media (9 items)</li> <li>Items related to satisfaction with the functioning of democracy, services and institutions (7 items)</li> <li>Authoritarian values (Feldman and Stenner 1997)</li> <li>Liberal democratic values (Zanotti and Rama 2021)</li> <li>Authoritarian personality indexes (Hibbing 2020)</li> <li>Conspiracy theories (3 items)</li> <li>Nationalism (5 items)</li> <li>Nativism (Young et al. 2019)</li> <li>Affective polarisation</li> <li>Support for political party (past vote and vote intention)</li> <li>Left-right ideological self-placement</li> <li>Other socio-political questions.</li> </ul> <p>Fieldwork was conducted by YouGov Spain in February 2023. The surveys was part of the projects: <em>Populism and Borders: a Supply- and Demand-Side Comparative Analysis of Discourses and Attitudes (PBSDCA) </em>and <em>Principal Investigator Interdisciplinary Comparative Project on Populism and Secessionism (ICPPS).</em></p> <p>The uploaded files contain:</p> <ul> <li>Detail of survey results (.sav)</li> <li>Questionnaire (.doc)</li> <li>Summary of results (.xls)</li> <li>Fieldwork summary file (.pdf)(this file is in Spanish)</li> </ul>
XRS carbon K-edge speciation mapping of an Eocene (ca. 53 Mya) ant entrapped in amber from Oise, France
<p>XRS carbon K-edge speciation mapping of an Eocene (ca. 53 Mya) ant entrapped in amber from Oise, France</p>
A new Geo-Lithological Map (Geo-LiM) for Central Europe (Germany, France, Switzerland, Austria, Slovenia, and Northern Italy)
<p><strong>We introduce a new geo-lithological map of Central Europe (Geo-LiM) elaborated adopting a lithological classification compliant to the methods more used in the litterature for estimating the consumption of atmospheric CO2 due by chemical weathering. <br> Geo-LiM represents a novelty if compared with published global geo-lithological maps. The first novelty is due by the attention paid in discriminating metamorphic rocks that were classified according to the chemistry of protoliths. The second novelty is that the procedure used for the definition of the map is made available on the web to allow the replicability and reproducibility of the product.</strong></p>
ScienceDex guides
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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.