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13,499 results for “researcher”
The LOTUS Initiative for Open Natural Products Research: waste to recycle
<p>Dataset not uploaded to Wikidata. </p> <p>Generated in the frame of the LOTUS Initiative: <a href="https://doi.org/10.7554/eLife.70780">https://doi.org/10.7554/eLife.70780</a></p> <p>Shared for further curation.</p>
The LOTUS Initiative for Open Natural Products Research: metadata
<p>Metadata of each of the three objects (structures, organisms, references) used in the frame of the LOTUS Initiative: <a href="https://doi.org/10.7554/eLife.70780">https://doi.org/10.7554/eLife.70780</a></p>
Aerosol particles observed onboard the research vessel Mirai over the Southern Ocean in the austral summer of 2017
<p>We have compiled a dataset of field observations to measure aerosol particle size distributions and to collect the aerosols for the following laboratory analyses to quantify the chemical composition and ice nucleating properties of aerosols over the Southern Ocean in the austral summer of 2017 as a part of the research cruise of Japanese research vessel (R/V) Mirai (Cruise number of MR16-09 leg3). The particle size distributions (PSDs) of the submicron aerosols (14–737 nm in the electrical mobility diameter) were measured using a scanning mobility particle sizer, SMPS, which is composed of a differential mobility analyzer, DMA (model 3081, TSI Inc., Minnesota, USA) and a condensation particle counter, CPC (model 3010, TSI Inc.). Since a custom-made inlet system was installed in front of the SMPS, the PSDs of total and non-volatile aerosols upon heating at the 300°C were alternatively measured every 5 min. The PSDs of the coarse fluorescent and non-fluorescent particles (700–3000 nm in the optical diameter) were measured using a waveband integrated bioaerosol sensor, WIBS (type 4A, Droplet Measurement Technologies Ltd., Colorado, USA). Hourly averaged PSDs for the diameter range of 14–3000 nm were analyzed in the associated paper in order to relate the wave breaking state derived from the hourly observations of significant wave height on the R/V. Chemical compositions were derived from the collected samples with the following techniques at the laboratory, ion chromatography for water soluble ions (chloride, nitrate, sulfate, ammonium, sodium, potassium, magnesium, calcium ions), thermal optical transmittance technique for carbonaceous aerosols (organic and elemental carbons), and inductively coupled plasma mass spectrometry for aluminum (Al). Ice nucleating properties of the aerosol particles were analyzed using a droplet freezing method (Cryogenic Refrigerator Applied to Freezing Test, CRAFT) at National Institute of Polar Research (Tobo, 2016 <a href="https://doi.org/10.1038/srep32930">https://doi.org/10.1038/srep32930</a>). All the data indicating the concentrations were reported at standard temperature and pressure (0°C and 1 atm).</p> <p>We prepared five files (comma-separated values) in total, which are hourly aerosol concentrations measured using the SMPS and WIBS, Particle size distributions measured using the SMPS, Particle size distributions measured using the WIBS, Aerosol chemical compositions, and Ice nucleating particle concentrations during the research cruise of MR16-09 leg3. Each file includes the header part to describe the aerosol data including the date and time in UTC, and the positions of the R/V.</p> <p>The associated paper discusses some aspects of data treatment and questions regarding to the methods employed in this study.</p>
Diversity Awareness in Software Engineering Participant Research
<p>This dataset contains the result of a classification of three ICSE venues namely, ICSE 2019, 2020, and 2021 technical tracks, as stated in the methodology of the paper “Diversity awareness in software engineering participant studies” by Dutta et al. (2023).</p>
Research Iceberg
<p>Figure 3 from <a href="https://doi.org/10.5281/zenodo.7320029">Removing Barriers to Reproducible Research in Archaeology</a>.</p> <p>Figure 3: The Research Iceberg, where only the article, preprint, and presentations on research are visible. The components of the research on which these visible outputs are based remain invisible (research questions, methods, data, mistakes and corrections, discussions, community consultation, documentation and ideas). Image by Esther Plomp.</p> <p>Please adapt and reuse for your own needs!</p>
A census of research software in 171 academic institutional repositories.
<p> A dataset of metadata for 171 UK academic institutional repositories, including a census of research software contained.</p> <table> <tbody> <tr> <td><strong>URL</strong></td> <td>The OAI url</td> </tr> <tr> <td><strong>id</strong></td> <td>CORE Identifier</td> </tr> <tr> <td><strong>openDoarId</strong></td> <td>Open DOAR identifier</td> </tr> <tr> <td><strong>name</strong></td> <td>Name of repository</td> </tr> <tr> <td><strong>Russell_member</strong></td> <td>If the university is a member of the Russell Group of research intensive universities</td> </tr> <tr> <td><strong>RSE_group</strong></td> <td>If an RSE group is present (based on Soc of RSE data)</td> </tr> <tr> <td><strong>email</strong></td> <td>Redacted</td> </tr> <tr> <td><strong>uri</strong></td> <td>Not used</td> </tr> <tr> <td><strong>uni_sld</strong></td> <td>Second level domain (the part of the url between . And .ac.uk</td> </tr> <tr> <td><strong>homepageUrl</strong></td> <td>University website</td> </tr> <tr> <td><strong>source</strong></td> <td>Not used</td> </tr> <tr> <td><strong>ris_software</strong></td> <td>the Research Information System software used</td> </tr> <tr> <td><strong>ris_software_enum</strong></td> <td>Resolve ris_software into similar types (e.g. Eprints 3, EPrints3.3.16 both equal eprints)</td> </tr> <tr> <td><strong>metadataFormat</strong></td> <td>the protocol used for metadata</td> </tr> <tr> <td><strong>createdDate</strong></td> <td>Repository creation date</td> </tr> <tr> <td><strong>location</strong></td> <td>location of university</td> </tr> <tr> <td><strong>logo</strong></td> <td>University logo (resolves in error)</td> </tr> <tr> <td><strong>type</strong></td> <td>Only = Repository for this dataset. Can be = journal etc.</td> </tr> <tr> <td><strong>stats</strong></td> <td>Not used</td> </tr> <tr> <td><strong>contains_software_set</strong></td> <td>Whether the OAI-PMH software set is present in the repository.</td> </tr> <tr> <td><strong>Num_sw_records</strong></td> <td>The response of the OAI-PMH query for software (erroneous as discussed in paper)</td> </tr> <tr> <td><strong>Error</strong></td> <td>The category of error returned by the experiment’s OAI-PMH queries (see paper)</td> </tr> <tr> <td><strong>Manual_Num_sw_records</strong></td> <td>The true amount of software contained in the repository as found by a manual exhaustive search of each university website</td> </tr> <tr> <td><strong>Category</strong></td> <td>Whether the repository (a) contains software; (b) can contain software, but doesn’t yet; (c) has no separate type of research output called software or similar</td> </tr> </tbody> </table>
Supplying renewable energy to Central European research facilities: A techno-economic comparison of electricity and hydrogen (Dataset)
<p>This dataset contains central input assumptions and results related to the publication "Supplying renewable energy to Central European research facilities: A techno-economic comparison of electricity and hydrogen".</p> <p>Result files are contained in the <strong> results.zip</strong> archive file. The file contains for each scenario, as indicated by the folder structure, the following files:</p> <ul> <li><strong>results.csv</strong>: Central scenario results exported as <em>character separated value</em> <em>(csv)</em> file, with a semicolon (<strong>;</strong>) as field separator. All fields are quoted using double quotation marks <strong>"..."</strong>. Can be explored using standard office software like Microsoft Excel/Libre Office or other tools.</li> <li><strong>network.nc</strong>: PyPSA network file containing the optimized scenario with all input and unprocessed outputs (results). Can be explored using the <a href="https://pypsa.readthedocs.io">PyPSA software package</a>.</li> <li><strong>lcoes.csv</strong>: Levelised Cost of Electricity used to construct the renewable energy source (RES) based supply curve for each scenario.</li> </ul> <p>The dataset further contains the following files which represent central input assumptions to the model and scenarios, both as <em>CSV</em> files:</p> <ul> <li><strong>efficiencies.csv</strong>: Technology process and conversion efficiencies<em> </em>including more details on the assumptions and information on which references the assumptions are based.</li> <li><strong>costs_2030.csv</strong>: Technology cost assumptions for 2030 including more details on the assumptions and information on which references the assumptions are based. This data is based on this <a href="https://github.com/pypsa/technology-data">Technology Data repository</a> on GitHub.</li> </ul>
A study on biomedical researchers' perspectives on public engagement in Southeast Asia
<p>Survey data from biomedical researchers in Southeast Asia about their perceptions of public engagement. The survey used open and closed questions.</p>
Water chemistry of LTER-Europe research site Lake Paione Superiore LTER_EU_IT_089 (1984-2013)
<p>This dataset provides information about water chemical parameters for Lake Paione Superiore LTER_EU_IT_089: pH, Total alkalinity, conductivity, total nitrogen, major cations (calcium, magnesium, sodium, potassium), major anions (sulphate, nitrate, chloride) and silica for the period 1984-2013.</p> <p>Lake Paione Superiore (LPS) is a high altitude Alpine lake, located at 2269 m a.s.l. in the Bognanco Valley, Province of Verbania, Piedmont Region, Italy. It has a surface area of 0.68 ha and a maximum depth of 11.5 m. The Lake, together with Lake Paione Inferiore (LPI), is included in the monitoring sites of the UN-ECE Program ICP WATERS (International Cooperative Programme on Assessment and Monitoring of Acidification of Rivers and Lakes) for which the CNR Water Research Institute is the National Focal Centre for Italy.</p> <p>This dataset includes the following files: Metadata LTER_EU_IT_089.xls and per each parameter one xls file with data records.</p> <p>Detailed description of the site LPS is available at https://deims.org/7e5837a9-ee27-4e27-822a-f50e5217c313</p> <p>Dataset for water chemistry of LPS for the period 2014-2020 is available at https://doi.org/10.5281/zenodo.10519126</p>
Research Data for System test results for the R290 systems
<p>This dataset provides the research data system test results of R-290 (propane) systems. In the TRI-HP project, a new heat pump system with R-290 was integrated into multiple renewable energy sources. There were two experimental campaigns. After analysing the results of the first experimental campaign, the prototype was further improved. The second experimental campaign was conducted with the improved prototype.</p> <p>The detailed information can be found in ZENODO:</p> <p><a href="https://zenodo.org/record/7324246">Refined heat pump design and results of final testing</a></p> <p><a href="https://zenodo.org/record/7285499">Critical review of heat pump prototype operation and required modications</a></p> <p><a href="https://zenodo.org/record/5937065">Experimental results of dual source heat exchanger</a></p> <p>The background of this dataset:</p> <p>During the first experimental campaign, the heat pump prototypes were tested in the laboratories of the project<br> partners in static conditions. These conditions are defined in standards like, for example, EN 14511 [1], providing<br> specific temperatures on the evaporator and condenser sides. These tests enable us to characterize the COP and<br> EER in the nominal conditions of the equipment. However, when such heat pumps are installed in a real building<br> in a specific climate, they will be subject to varying conditions, depending on the load, the weather along<br> the seasons, intermediate storage vessels etc. For this reason, it is important also to carry out</p> <p>dynamic tests.<br> The dynamic tests presented in this deliverable were performed in two laboratories, following the principles of the<br> hardware-in-the-loop where part of the systems is installed in the lab (e.g. the heat pump), and part of the systems<br> is simulated and emulated to provide to real installed systems the response of the virtual element (e.g. building,<br> ground source, weather, solar thermal and PV). The full methodology and setups are described in detail in the<br> deliverable D7.1 [2].<br> The solar-ice system was tested in SPF-OST facilities in Rapperswil, Switzerland. The applied methodology was<br> the Concise Cycle Test (CCT), where 7 individual days along the year for the given climate of Bern were selected.<br> The complete system includes solar thermal, ice storage and water storage. The system was assembled in<br> the laboratory, and the actual setup is described in deliverable D7.3 [3]. The electrical part, including<br> household electricity, PV and the battery, will be tested for the CO2 slurry system due to time constraints since this<br> part does not affect the thermal behaviour of the installed system. The full efficiency of the propane solar-ice<br> slurry system, including the electrical part, will be provided in D7.9, "Demonstrated energetic performance and cost<br> competitiveness of systems".<br> The dual-source system was tested in the IREC laboratory SEILAB in Tarragona, Spain. The methodology is slightly<br> different since the selected periods are not individual days but a series of four consecutive days in<br> the summer and winter seasons. The overall system includes storage tanks, a geothermal loop as well as<br> Photovoltaics (PV) and an electrical battery. The assembled system and the lab setup were described in <br> deliverable D7.2 [4].<br> The present deliverable compiles the results of these two series of dynamic experiments with the propane heat<br> pumps. The results of the solar ice system are first analyzed in section 2, including a summary of the laboratory<br> setup and the control strategies used. The same structure is followed for the dual source system in section 3.<br> 2 Deliverable D7.4</p>
Research data for Refined heat pump design and results of final testing
<p>In this dataset, the data of the second experimental test campaign of the CO2-ice heat pump is shared. The report, which analyzes the data and makes the necessary explanations, has already been shared as a "Refined heat pump design and results of final testing (Deliverable: D5.6)". The report has already been published on ZENODO.</p>
Research data for Critical review of heat pump prototype operation and required modications
<p>In this dataset, the data of the first experimental test campaign of the CO2-ice heat pump is shared. The report, which analyzes the data and makes the necessary explanations, has already been shared as a "Critical review of heat pump prototype operation and required modifications (Deliverable: D5.5)".</p>
Ethics of Research Funding: A survey
<p>Anonymized data set of the ethics of research funding survey. To anonymize the data, the responses to the open comment field (Q57) have been removed. The publication of these anonymized data has been approved by the ethics committee of KU Leuven.</p>
Does size matter? Quality assessment of the size property in research data repositories
<p>Code and data for master's thesis on quality assessment of the size property in research data repositories. Research questions:</p> <ul> <li> <p> For what semantic concepts is the size property of repositories being used?</p> </li> <li> <p>What kind of quality factors can be detected when assessing the size property in a registry for research data repositories?</p> </li> <li> <p>Which automated and intellectual measures can improve the quality of the size property?</p> </li> </ul> <p>Method 1: Data analysis of size and related properties over all re3data records</p> <ul> <li> <p>Property selection</p> </li> <li> <p>Data extraction from API</p> </li> <li> <p>Data normalization</p> </li> <li> <p>Typing of patterns: mainly units of size</p> </li> <li> <p>Analysis: ~quantitative, mainly univariate, but also some multivariate / time</p> </li> </ul> <p>[Included in the publication:</p> <p>Method 2: Case Study of size in individual repositories</p> <ul> <li> <p>Repository selection: purposive sampling</p> </li> <li> <p>Data capture from GUI / API</p> </li> <li> <p>Analysis: ~qualitative]</p> </li> </ul>
Research data supporting: "Unsupervised Data-Driven Reconstruction of Molecular Motifs in Simple to Complex Dynamic Micelles"
<p>This repository contains the set of data shown in the paper <strong>"Unsupervised Data-Driven Reconstruction of Molecular Motifs in Simple to Complex Dynamic Micelles"</strong>, published on The Journal of Physical Chemistry B (DOI:10.1021/acs.jpcb.2c08726).</p>
Energy-Saving Strategies for Mobile Web Apps and their Measurement: Results from a Decade of Research - Dataset
<p>In 2022, over half of the web traffic was accessed through mobile devices. By reducing the energy consumption of mobile web apps, we can not only extend the battery life of our devices, but also make a significant contribution to energy conservation efforts. For example, if we could save only 5% of the energy used by web apps, we estimate that it would be enough to shut down one of the nuclear reactors in Fukushima. This paper presents a comprehensive overview of energy-saving experiments and related approaches for mobile web apps, relevant for researchers and practitioners. To achieve this objective, we conducted a systematic literature review and identified 44 primary studies for inclusion. Through the mapping and analysis of scientific papers, this work contributes: (1) an overview of the energy-draining aspects of mobile web apps, (2) a comprehensive description of the methodology used for the energy-saving experiments, and (3) a categorization and synthesis of various energy-saving approaches.</p>
ETHNA Validation Survey on Drivers and Barriers of Responsible Research & Innovation (RRI)
<p>This entry includes the ETHNA Validation Survey on Drivers and Barriers of Responsible Research & Innovation (RRI) questions in PDF and the servey results in Excel. Ths survey was conducted by Centre for Social Innovation (ZSI) as part of the WP4 of the European ETHNA System project. The survey explores potential good RRI practices and possible measures to gauge the RRI institutionalisation progress at research-performing organisations.</p> <p>The online survey was sent in October 2021 to a broad group (10.000+) of potentially relevant expert stakeholders identified through a Web of Science database search with the aim of assessing the relevance of the identified drivers, barriers and good practices of RRI institutionalisation. Altogether 888 responses were received from 69 countries with a balanced gender representation, involving the opinion of mostly senior experts (55% having more than 15 years of experience). After filling out general demographic and organisational information, the respondents rated the perceived relevance of the RRI incentives, barriers and good practices that were the highest ranked at the end of the second consultation phase (using a Likert scale of 1-10). </p>
Extensive crowdsourced dataset of in-situ evaluated binaural soundscapes of private dwellings containing subjective sound-related and situational ratings along with person factors to study time-varying influences on sound perception — research data
<p><strong>Abstract:</strong></p> <p>The soundscape approach highlights the role of situational factors in sound evaluations; however, only a few studies have applied a multi‐domain approach including sound‐related, person‐related, and time‐varying situational variables. Therefore, we conducted a study based on the Experience Sampling Method to measure the relative contribution of a broad range of potentially relevant acoustic and non‐auditory variables in predicting indoor soundscape evaluations. Here we present the comprehensive dataset for which 105 participants reported temporally (rather) stable trait variables such as noise sensitivity, trait affect, and quality of life. They rated 6.594 situations regarding the soundscape standard dimensions, perceived loudness, and the saliency of its sound components and evaluated situational variables such as state affect, perceived control, activity, and location. To complement these subject‐centered data, we additionally crowdsourced object‐centered data by having participants make binaural measurements of each indoor soundscape at their homes using a low‐(self‐)noise recorder. These recordings were used to compute (psycho‐)acoustical indices such as the energetically averaged loudness level, the A‐weighted energetically averaged equivalent continuous sound pressure level, and the A‐weighted five‐percent exceedance level. This complex hierarchical data can be used to investigate time‐varying non‐auditory influences on sound perception and to develop soundscape indicators based on the binaural recordings to predict soundscape evaluations.</p> <p><strong>Content:</strong></p> <ul> <li><a href="https://zenodo.org/record/7858848/files/01%20StudyDescription.pdf">01 StudyDescription.pdf </a> <ul> <li>Description of the field study.</li> <li>Information about the methods and materials used.</li> </ul> </li> <li><a href="https://zenodo.org/record/7858848/files/02%20Dataset.csv">02 Dataset.csv</a> <ul> <li>The dataset, consisting of 93 variables describing 6594 observations taken by 105 participants.</li> </ul> </li> <li><a href="https://zenodo.org/record/7858848/files/03%20VariableDescriptions_EnglishPersonQuestionnaire.pdf">03 VariableDescriptions_EnglishPersonQuestionnaire.pdf</a> <ul> <li>Descriptions of all variables, their measurement scale, scale ranges and levels.</li> <li>Questions and task descriptions of the Experience Sampling Method questionnaire in German language with an English translation.</li> <li>English translations of questions asked in the person questionnaire.</li> </ul> </li> <li><a href="https://zenodo.org/record/7858848/files/04%20ESM-Questionnaire.pdf">04 ESM-Questionnaire.pdf</a> <ul> <li>Screenshots of the original Experience Sampling Method questionnaire with English translations.</li> </ul> </li> <li><a href="https://zenodo.org/record/7858848/files/05%20PersonQuestionnaire_OriginalGermanVersion.pdf">05 PersonQuestionnaire_OriginalGermanVersion.pdf</a> <ul> <li>Original version of the person questionnaire in German language.</li> </ul> </li> <li><a href="https://zenodo.org/record/7858848/files/06%20HelpTexts.pdf">06 HelpTexts.pdf</a> <ul> <li>Descriptions of the study task.</li> <li>Explanations of the scales used in the questionnaire.</li> <li>Explanations of the sound categories and the soundscape composition.</li> <li>Explanation of the operation of the recording device.</li> </ul> </li> <li><a href="https://zenodo.org/record/7858848/files/AcousticFeatures_README.md">AcousticFeatures_README.md</a> <a href="https://zenodo.org/api/files/3d784540-c0f4-412f-8742-df1db6f5401d/TimeSeries_and_Spectrograms_README.md?versionId=9291496c-d2c6-4151-96f1-a2ad99e1a540"> </a> <ul> <li>Descriptions of the structure of the AcousticFeatures_xxx.csv and .zip files.</li> <li>Analyis settings used in Artemis Suite to generate the acoustic features.</li> </ul> </li> <li><a href="https://zenodo.org/record/7858848/files/AcousticFeatures_SingleValues.csv">AcousticFeatures_SingleValues.csv</a> <ul> <li>All acoustic features, aggregated to single values per feature, recording, and channel.</li> </ul> </li> <li><a href="https://zenodo.org/record/7858848/files/AcousticFeatures_Spectra.csv">AcousticFeatures_Spectra.csv</a> <ul> <li>Time-averaged 1/3 octave spectra of each channel of each recording, A-weichted and un-weighted.</li> </ul> </li> <li><a href="https://zenodo.org/record/7858848/files/AcousticFeatures_Spectrograms.zip">AcousticFeatures_Spectrograms.zip</a> <ul> <li>13188 .csv files with un-weighted spetrograms of each channel of each recording.</li> </ul> </li> <li><a href="https://zenodo.org/record/7858848/files/AcousticFeatures_TimeSeries.zip">AcousticFeatures_TimeSeries.zip</a> <ul> <li>A .csv file containing LAeq and LZeq time series of each channel of each recording.</li> </ul> </li> </ul> <p><strong>Publications refering to this dataset:</strong></p> <p>Versümer, Siegbert; Steffens, Jochen; Weinzierl, Stefan (currently under review): "The role of loudness predictions, personal and situational factors in day-to-day loudness assessments of indoor soundscapes."</p> <p><strong>Funding:</strong></p> <p>This study was sponsored by the German Federal Ministry of Education and Research. “FHprofUnt” funding code: 13FH729IX6. </p> <p><strong>License: </strong></p> <p>CC 4.0 BY, <a href="https://creativecommons.org/licenses/by/4.0/legalcode">https://creativecommons.org/licenses/by/4.0/legalcode</a></p> <p><strong>Version history:</strong></p> <p>Details can be found in the <a href="https://zenodo.org/api/files/a15d6a91-1a35-4b5e-a7ec-da8a9bcbee2b/Changelog.md">Changelog.md</a> file.</p> <ul> <li> V.01.0. March 7, 2023: Initial publication. <a href="https://doi.org/10.5281/zenodo.7193938">https://doi.org/10.5281/zenodo.7193938</a></li> <li> V.01.1. April 25, 2023. <a href="https://doi.org/10.5281/zenodo.7858848">https://doi.org/10.5281/zenodo.7858848</a></li> </ul>
A study on biomedical researchers' perspectives on public engagement in Southeast Asia
<p>Qualitative data on researcher's perceptions of public and community engagement in South and Southeast Asia</p>
Pilot 2 - Research Data
<p>In Pilot 2, data have been collected mainly for the following purposes: [1] achieving the pilots' research objectives, as outlined in the previous section, and [2] managing and monitoring the pilots' implementation and [3] informing technical developments in the ARETE CLB app.</p> <p>In Pilot 2, anonymized student data have been collected in correspondence with the research objective of testing the efficiency of Augmented Reality for STEM education, to evaluate if the CLB apps can help students improve test scores by up to 33 % and increase the retention rate by up to 100 %. Additionally, pedagogical aspects of the AR use and its impact on teaching and learning will be evaluated. To respond to these claims, the methodology applied included pre-tests and post-tests for students and additional qualitative surveys for teachers.</p> <p>Pilot 2 collected only personal information (name, surname, contact information) from the participating teachers, in the form of consent forms (necessary to obtain the participants’ consent to participate in the ARETE research activities). These consent forms have been collected by European Schoolnet (EUN) and stored on EUN’s secure servers. All personal data collected within the project activities will be anonymised upon completion of the project, apart from data that need to be kept for the full audit period.</p> <p>As in the case of Pilot 1, and in accordance with the data minimization principle, no personal information from the participating students or their parents/legal guardians will be transferred to EUN or to other members of the ARETE consortium for the purpose of Pilot 2. The only personal information collected from students and their parents/legal guardians will be for the purpose of acquiring consent/assent, and these forms have been collected at the level of each participating school. EUN has established a Memorandum of Understanding with each participating school in Pilots 2 in order to ensure that:</p> <ul> <li>the heads of the participating schools are appropriately informed about the research carried out in the context of the ARETE project and have provided their agreement for the school to participate in research and</li> </ul> <p>that the schools have all the necessary permissions from the parents/legal guardians of the pupils participating in the ARETE research or, in the case such permissions do not exist at the school level, ensure that the schools collect all necessary consent forms from the participating students. This measure is meant to reduce the transfer of sensitive personal information between organisations unless absolutely necessary.</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.