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11,394 results for “Surveys”
Mapping Mobility Motivation Survey
<p>The Mapping Mobility motivation study was conducted within the ongoing H2020 project named <a href="https://actionproject.eu/">ACTION</a> (pArticipatory sCience Toolkit agaInst pollutiON) on citizen science. Volunteers participate to citizen science initiatives for multiple reasons: personal enjoyment, desire for improvement or achievement, establishment of personal relationships, care for the environment, etc.<br> Studying motivation and investigating the factors influencing people participation to citizen science projects is an essential aspect in the analysis of citizen science communities. Understanding the reasons that foster people to engage can support the successful design and implementation of effective participant involvement tasks, as well as pave the way for long-term engagement.<br> The goal of the study is to analyse the motivation to participate of a specific citizen science community focused on fighting air pollution in the Mapping Mobility pilot supported by the ACTION project. More info on the pilot available at <a href="https://actionproject.eu/citizen-science-pilots/mapping-mobility/">https://actionproject.eu/citizen-science-pilots/mapping-mobility/</a>.</p> <p>The Mapping Mobility motivation study is part of the study about motivation in citizen science projects conducted within the ACTION project (<a href="https://doi.org/10.5281/zenodo.5753092">https://doi.org/10.5281/zenodo.5753092</a>). The survey was designed and administered using the <a href="https://coney.cefriel.com/">Coney</a> toolkit.</p> <p>The research object adopts the <a href="https://www.researchobject.org/ro-crate/1.0/">RO-Crate</a> specification. Files made available within the research object are:</p> <ul> <li><em>*-procedure.ttl</em> contains the RDF representation of the structure of the conversational survey (questions, answers, etc.) using the <a href="https://w3id.org/survey-ontology">Survey Ontology</a></li> <li><em>*-results.ttl </em>contains the RDF representation of the answers collected using the <a href="https://w3id.org/survey-ontology">Survey Ontology</a></li> <li><em>*-survey.tll </em>contains a comprehensive RDF representation of the survey data using the <a href="https://w3id.org/survey-ontology">Survey Ontology</a></li> <li><em>*-results.csv </em>contains the CSV of the answers collected</li> </ul>
Open Soil Atlas Motivation Survey
<p>The Open Soil Atlas motivation study was conducted within the ongoing H2020 project named <a href="https://actionproject.eu/">ACTION</a> (pArticipatory sCience Toolkit agaInst pollutiON) on citizen science. Volunteers participate to citizen science initiatives for multiple reasons: personal enjoyment, desire for improvement or achievement, establishment of personal relationships, care for the environment, etc.<br> Studying motivation and investigating the factors influencing people participation to citizen science projects is an essential aspect in the analysis of citizen science communities. Understanding the reasons that foster people to engage can support the successful design and implementation of effective participant involvement tasks, as well as pave the way for long-term engagement.<br> The goal of the study is to analyse the motivation to participate of a specific citizen science community focused on fighting soil pollution in the Open Soil Atlas pilot supported by the ACTION project. More info on the pilot available at <a href="https://actionproject.eu/citizen-science-pilots/open-soil-atlas/">https://actionproject.eu/citizen-science-pilots/open-soil-atlas/</a>.</p> <p>The Open Soil Atlas motivation study is part of the study about motivation in citizen science projects conducted within the ACTION project (<a href="https://doi.org/10.5281/zenodo.5753092">https://doi.org/10.5281/zenodo.5753092</a>). The survey was designed and administered using the <a href="https://coney.cefriel.com/">Coney</a> toolkit.</p> <p>The research object adopts the <a href="https://www.researchobject.org/ro-crate/1.0/">RO-Crate</a> specification. Files made available within the research object are:</p> <ul> <li><em>*-procedure.ttl</em> contains the RDF representation of the structure of the conversational survey (questions, answers, etc.) using the <a href="https://w3id.org/survey-ontology">Survey Ontology</a></li> <li><em>*-results.ttl </em>contains the RDF representation of the answers collected using the <a href="https://w3id.org/survey-ontology">Survey Ontology</a></li> <li><em>*-survey.tll </em>contains a comprehensive RDF representation of the survey data using the <a href="https://w3id.org/survey-ontology">Survey Ontology</a></li> <li><em>*-results.csv </em>contains the CSV of the collected answers</li> <li>*-<em>script.R</em> is the R script developed to analyse the collected answers</li> <li>*-<em>mean-var-motivating-questions.csv </em>contains the computed mean and average for each question considered (observable variables)</li> <li>*-<em>mean-var-motivating-factor.csv </em>contains the computed mean and average for each motivation factor considered (latent variables)</li> <li>*-<em>correlation-factors-global-motivation.csv </em>contains the correlation analysis between each motivation factor and the global motivation </li> </ul>
What does it take to generate new growth - Survey data on company perceptions on innovative behavior
<p>This data includes raw survey data, a codebook and the survey form for the survey <em>what does it take to generate new growth? </em>The survey focused on comprehensively mapping the Finnish companies growth outlooks and their underlying management practices and principles. The study creates an overview of top managers’ views on Finnish companies’ growth, innovativeness, and the ability for renewal. It allows us to identify what sets high-growing companies apart from others. The Codebook is associated with an SPSS and CSV file including the data.</p>
Fostering safe food handling among consumers: Data from an online survey experiment with 1,973 consumers from Norway and the UK
<p>Data and replication codes for the article "Fostering safe food handling among consumers: Causal evidence on game- and video-based online interventions". 1,973 participants from the UK and Norway, aged 18- 89 years, were assigned to (i) a control condition, or (ii) exposed to a brief information video, or (iii) in addition played an online game (two different conditions). In all conditions, participants answered a pre-survey and seven days later a post-survey. In the survey, next to collecting some information on sociodemographic background and certain preferences, subjects reported some recent food safety behaviors and we elicited beliefs in the efficacy of certain food safety actions, as well as beliefs in myths related to food and hygiene.</p> <p>We use this data set in our publication <br> Koch, A. K., Mønster, D., Nafziger, J., & Veflen, N. (2022). Fostering safe food handling among consumers: Causal evidence on game-and video-based online interventions. <em>Food Control</em>, 108825.</p>
Dependencies in DevOps Survey 2021
<p>While various empirical studies on the application of DevOps in practice exist, the state of application dependencies and their impact on the order of deployments has not been assessed yet. Such insight would indicate whether independent, cross-functional DevOps teams may deploy their applications independently or whether they need to coordinate. Further, in case coordination is required, we do not yet have insight into how such coordination is accomplished.</p> <p>To fill this gap, we perform a cross-sectional, self-administered, online questionnaire survey with IT professionals. This report documents the survey until April 15, 2021, including the analysis of the collected data. Further, we provide the dataset and the scripts for the paper and this report.</p> <p><strong>Contents</strong></p> <ul> <li>README.md: Overview and instructions on how to use this artifact.</li> <li>report.pdf: Survey report providing documentation, results and analysis of the survey until April 15, 2021.</li> <li>survey-data.csv: Survey dataset until April 15, 2021.</li> <li>analysis.zip: Analysis scripts for all statements and generation of all contents of report.pdf. Also includes the dataset and report.</li> </ul> <p> </p>
Data quality assurance at research data repositories: Survey data
<p>This dataset documents findings form a survey on the status quo of data quality assurance practices at research data repositories.</p> <p>The personalized online survey was conducted among repositories indexed in re3data in 2021. It covered the scope of the repository, types of data quality assessment, quality criteria, responsibilities, details of the review process, and data quality information, and yielded 332 complete responses.</p> <p>The dataset comprises a documentation file, the data file, a codebook, and the survey instrument.</p> <p>The <strong>documentation file</strong> (documentation.pdf) outlines details of the survey design and administration, survey response, and data processing. The <strong>data file</strong> (01_survey_data.csv) contains all 332 complete responses to 19 survey questions, fully anonymized. The <strong>codebook</strong> (02_codebook.csv) describes the variables, and the <strong>survey instrument</strong> (03_survey_instrument.pdf) comprises the questionnaire that was distributed to survey participants.</p>
Multi-stakeholder research data management training as a tool to improve the quality, integrity, reliability and reproducibility of research: Quantitative data of the post-course surveys
<p>Data contains doctoral students' and postdoc researchers' (n=168) self-ratings of their RDM competencies before and after the 3 ECTS credits "Basics of Research Data Management" (BRDM) trainings held 2019-2021 in the University of Turku and Åbo Akademi University, Finland. Moreover, data contains respondents' self-reported further learning needs.</p>
The stellar parameters and the quantities of the residual emissions of the detected active stars in the LAMOST-K2 survey
<p>The full Table 1 in <em>Investigation of stellar magnetic activity using variational autoencoder based on low-resolution spectroscopic survey</em> (Xiang, Gu & Cao, 2022, MNRAS, 514, 4781; <a href="https://arxiv.org/abs/2206.07257">arXiv:2206.07257</a>). The columns are LAMOST obsid, K2 ID, Teff, logg, [Fe/H], EW_res_Halpha, EW_res_Ca II 8498, EW_res_Ca II 8542, EW_res_Ca II 8662, log F_Halpha, log F_Ca, log R'_Halpha, log R'_Ca. The chromospheric emissions were detected and measured with the spectral subtraction technique, which removes the inactive template spectra (photospheric contribution) from the observed stellar spectra. In this work, we used the variational autoencoder neural networks to efficiently generate the proper template spectra in a data-driven manner. More details can be found in the associated paper (<a href="https://arxiv.org/abs/2206.07257">https://arxiv.org/abs/2206.07257</a>). The demo code can be found on GitHub (<a href="https://github.com/xylib/vae-for-spectroscopic-survey">https://github.com/xylib/vae-for-spectroscopic-survey</a>).</p>
Survey on the Effects of COVID-19 on the Wellbeing of Mexico City Households (ENCOVID-19 CDMX – JULY 2021)
<p>Amid the COVID-19 outbreak, the ENCOVID-19 CDMX provides information on the well-being of Mexico City households in four main domains: labor, income, mental health, and food insecurity. It offers timely information to understand the social consequences of the pandemic and the lockdown measures. It is a cross-sectional telephone survey that, in addition to the four main domains and a set of COVID19-related questions, includes key indicators to capture the impact of the pandemic on issues like education, social programs, and crime. This is the third dataset of the project, corresponding to July 2021, collected 15 months after the lockdown began in Mexico. Data collection was performed from July 19 to 31, 2021.</p>
Online survey among students and teachers in the Swiss farm management course
<p>This dataset contains survey data including the codebook for an online survey conducted in German and French in Switzerland in spring 2021. With this survey, we aimed to find out what students learn and what teachers teach in this course about digital technologies in agriculture. </p>
FolkArtiNet: Folk music groups: their artistic practice and infrastructural needs in the COVID-19 era and beyond - survey data
<p> The online survey was one of three methods used for collecting information about the infrastructural needs of the folk music groups. It included a series of questions about different areas of artistic activity, such as working on repertoire, collaboration among group members, storage and sharing of data, and organization of artistic events. The survey data includes all questions and answers in csv format.</p>
Survey on policies for innovation in the Global South, 2022.
<p>In July-August 2022, the <a href="acceleratorlabs.undp.org">UNDP Accelerator Labs</a> launched a survey to get a big picture view on the work that its global network of 91 labs was doing to support innovation ecosystems. The results were surprisingly clear-cut and coherent.</p> <p>First, <strong>we learned that a solid majority of Labs had partnered with governments to deploy interventions in support of national innovation ecosystems, or was planning to do so in the near future</strong>. We were looking at a surge of government investment in innovation across the Global South. Furthermore, these Global South governments were looking beyond the usual Global North example of policies to support innovation and learning from each other.</p> <p>Second, <strong>we learned that UNDP was widely recognized as the leading organization in supporting Global South governments in this journey</strong>. And third, <strong>we learned that collaboration with governments that have invested in innovation becomes smoother and more impactful</strong>.</p> <p>This Zenodo entry contains a file aggregating all the responses to that survey. </p>
Drone-based photogrammetric survey raw data from ESA PANGAEA-X 2017 planetary analogue campaign - Data collected on 2017-11-19
<p>Drone-based photogrammetric survey data from ESA PANGAEA-X 2017 planetary analogue campaign. Data were collected in the framework of the ESA PANGAEA-X testing campaign held in November 2017: We acknowledge ESA for organising the campaign and providing scientific and logistic assistance on site. The authors would like also to thank the Geopark of Lanzarote, the touristic center of Cueva de Los Verdes, the Cabildo of Lanzarote, the National Park of Timanfaya and the IGEO-CSIC-UCM for providing the necessary permits. Data collected on 2017-11-19 during an aerial survey with a DJI Phantom 4 - data from AGPA experiments (AGPA-D) see http://www.agpa-project.eu</p>
OpenAIRE and FAIR Data Expert Group survey about Horizon 2020 template for Data Management Plans
<p>This dataset is published in 2017 by the OpenAIRE project and the FAIR Data Expert Group.</p> <p>It contains two survey data files, two pdf-files summarising the results in a report and an infographic, and a Readme.txt file.</p> <p>The OpenAIRE project supports the open science ambitions of the European Commission. The project and in particular the Research Data Management team provide support, training and information on the Open Research Data Pilot. In this context, a survey was carried out to collect feedback on the Horizon 2020 template for Data Management Plans (DMPs). The team collaborated with the FAIR data expert group, which is providing recommendations to the European Commission on turning FAIR data into reality. One of the specific tasks of the Expert Group is contributing to an evaluation of the Horizon 2020 approach to DMPs, including future revisions of the template and the development of additional sector/ discipline-specific guidance. The aim of the survey was to collect experiences of researchers and DMP reviewers with the DMP template and guidelines on FAIR data management in Horizon 2020. The survey assesses the usefulness of the guidelines and any aspects that are confusing and unclear to determine what improvements can be made.</p> <p>Feedback was sought from both researchers and research support staff. The survey was initially scheduled to run from 22 May to 21 June 2017. Several organisations were asked to help announce the survey, including OpenAIRE’s National Open Access Desks, the FAIR data expert group, FOSTER, LIBER, and the RDA Interest Group on Active DMPs. When the first survey responses showed only a small share of researchers, more stakeholders were contacted to specifically target this community. The European Research Area was approached, whose project officers circulated the survey call among award holders of EC projects. Early-career researchers were also informed through the YEAR network and EURODOC. This resulted in an extension of the survey to 21 July 2017.</p> <p>At the close of the survey on 21 July 2017, a total number of 289 responses were reached. 50% of the respondents indicated that they were researchers, and 60% that they were (also) research support staff. OpenAIRE and the FAIR data expert group are very pleased with this balanced outcome and would like to thank all colleagues and organisations who promoted the survey, as well as everyone who took part in it.</p> <p> </p>
Shipboard Conductivity–Temperature–Depth (CTD) and dissolved oxygen profile data collected during hypoxia surveys along six hydrographic sampling lines within Olympic Coast National Marine Sanctuary, 2004–2015
<p>This data set includes Conductivity-Temperature-Depth (CTD) and dissolved oxygen profile data that were collected along Washington State’s outer coast within Olympic Coast National Marine Sanctuary (OCNMS). Measurements were made along six cross-shelf hydrographic sampling lines during a series of hypoxia survey cruises from 2004 – 2015. The 398 CTD profiles were acquired using Sea-Bird Scientific 19 SeaCAT or 19plus SeaCAT CTD profilers with associated SBE-43 (Sea-Bird Electronics) or Beckman or YSI-type (Yellow Springs Instruments) dissolved oxygen sensors. The data were processed via Sea-Bird Scientific’s SBE Data Processing application using six of the modules in the following order: Data Conversion, Filter, Align CTD, Loop Edit, Derive, and Bin Average. These processing steps and associated methods are the same as those used to process CTD data collected during OCNMS mooring maintenance cruises (<a href="https://www.sciencedirect.com/science/article/pii/S2352340924001422">Risien et al., 2024</a>) and along the Newport Hydrographic Line (<a href="https://www.sciencedirect.com/science/article/pii/S2352340922001342">Risien et al., 2022</a>) located off the central Oregon coast.</p> <table> <tbody> <tr> <td><strong>Station Name </strong></td> <td><strong>Latitude</strong></td> <td><strong>Longitude</strong></td> <td><strong>Water Depth (m, MLLW)</strong></td> </tr> <tr> <td><strong>Cape Alava (CA)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>CA010</td> <td>48.1661oN</td> <td>124.7540oW</td> <td>10</td> </tr> <tr> <td>CA020</td> <td>48.1661oN</td> <td>124.7598oW</td> <td>20</td> </tr> <tr> <td>CA030</td> <td>48.1659oN</td> <td>124.7783oW</td> <td>30</td> </tr> <tr> <td>CA040</td> <td>48.1659oN</td> <td>124.7852oW</td> <td>40</td> </tr> <tr> <td>CA045</td> <td>48.1659oN</td> <td>124.8335oW</td> <td>45</td> </tr> <tr> <td>CA050</td> <td>48.1658oN</td> <td>124.8578oW</td> <td>50</td> </tr> <tr> <td>CA060</td> <td>48.1659oN</td> <td>124.8843oW</td> <td>60</td> </tr> <tr> <td>CA070</td> <td>48.1655oN</td> <td>124.9011oW</td> <td>70</td> </tr> <tr> <td>CA080</td> <td>48.1657oN</td> <td>124.9141oW</td> <td>80</td> </tr> <tr> <td>CA090</td> <td>48.1659oN</td> <td>124.9247oW</td> <td>90</td> </tr> <tr> <td>CA100</td> <td>48.1658oN</td> <td>124.9319oW</td> <td>100</td> </tr> <tr> <td><strong>Teahwhit Head (TH)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>TH030</td> <td>47.8759oN</td> <td>124.6481oW</td> <td>30</td> </tr> <tr> <td>TH035</td> <td>47.8761oN</td> <td>124.7024oW</td> <td>35</td> </tr> <tr> <td>TH040</td> <td>47.8760oN</td> <td>124.7281oW</td> <td>40</td> </tr> <tr> <td>TH050</td> <td>47.8761oN</td> <td>124.7567oW</td> <td>50</td> </tr> <tr> <td>TH060</td> <td>47.8765oN</td> <td>124.7822oW</td> <td>60</td> </tr> <tr> <td>TH070</td> <td>47.8765oN</td> <td>124.8084oW</td> <td>70</td> </tr> <tr> <td>TH080</td> <td>47.8768oN</td> <td>124.8415oW</td> <td>80</td> </tr> <tr> <td>TH090</td> <td>47.8769oN</td> <td>124.8868oW</td> <td>90</td> </tr> <tr> <td>TH100</td> <td>47.8769oN</td> <td>124.9182oW</td> <td>100</td> </tr> <tr> <td><strong>Hoh Head (HH)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>HH025</td> <td>47.7688oN</td> <td>124.5605oW</td> <td>25</td> </tr> <tr> <td>HH042</td> <td>47.7688oN</td> <td>124.6428oW</td> <td>42</td> </tr> <tr> <td>HH065</td> <td>47.7688oN</td> <td>124.7401oW</td> <td>65</td> </tr> <tr> <td><strong>Raft River (RR)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>RR015</td> <td>47.4632oN</td> <td>124.3748oW</td> <td>15</td> </tr> <tr> <td>RR020</td> <td>47.4644oN</td> <td>124.4510oW</td> <td>20</td> </tr> <tr> <td>RR042</td> <td>47.4632oN</td> <td>124.5199oW</td> <td>42</td> </tr> <tr> <td>RR065</td> <td>47.4629oN</td> <td>124.6074oW</td> <td>65</td> </tr> <tr> <td><strong>Cape Elizabeth (CE)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>CE010</td> <td>47.3541oN</td> <td>124.3347oW</td> <td>10</td> </tr> <tr> <td>CE020</td> <td>47.354oN</td> <td>124.3608oW</td> <td>20</td> </tr> <tr> <td>CE030</td> <td>47.3538oN</td> <td>124.3913oW</td> <td>30</td> </tr> <tr> <td>CE040</td> <td>47.3534oN</td> <td>124.4678oW</td> <td>40</td> </tr> <tr> <td>CE050</td> <td>47.3532oN</td> <td>124.5064oW</td> <td>50</td> </tr> <tr> <td>CE060</td> <td>47.3529oN</td> <td>124.5510oW</td> <td>60</td> </tr> <tr> <td>CE070</td> <td>47.3528oN</td> <td>124.5823oW</td> <td>70</td> </tr> <tr> <td>CE080</td> <td>47.3527oN</td> <td>124.6158oW</td> <td>80</td> </tr> <tr> <td>CE090</td> <td>47.3526oN</td> <td>124.6491oW</td> <td>90</td> </tr> <tr> <td>CE100</td> <td>47.3522oN</td> <td>124.6754oW</td> <td>100</td> </tr> <tr> <td><strong>Moclips (MO)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>MO010</td> <td>47.2214oN</td> <td>124.2394oW</td> <td>10</td> </tr> <tr> <td>MO015</td> <td>47.2214oN</td> <td>124.2599oW</td> <td>15</td> </tr> <tr> <td>MO020</td> <td>47.2214oN</td> <td>124.2791oW</td> <td>20</td> </tr> <tr> <td>MO030</td> <td>47.2195oN</td> <td>124.3347oW</td> <td>30</td> </tr> <tr> <td>MO042</td> <td>47.2195oN</td> <td>124.3958oW</td> <td>42</td> </tr> </tbody> </table>
Tawi Said Archaeological Survey: Photos
<p>This is part of the data (photos) obtained during the survey at Tawi Said 2018. More data can be found in the other submissions of the Tawi Said Archaeological Survey community.</p> <p>The site of Tawi Said is located in the Al-Sharqiyah governorate, approximately 5 km northwest of the modern city of Bidiyah, on the edge of the Sharqiyah Desert. It was discovered in 1976 by Beatrice de Cardi. Two years later, she returned to conduct small scale excavations at the site. Subsequently, numerous references to the site were made in the literature as the only known settlement of the Wadi Suq period (2000-1600 BC) in Central Oman.</p> <p>In November 2018, a short survey was conducted by the Goethe University Frankfurt, Germany, in Tawi Said. An area of 150 x 120 m was intensively field-walked in 1.5 m wide transects to ensure complete visual coverage of the investigated area. Each find received an ascending number and its exact location was recorded using a portable GPS device. In total, nearly 7500 objects were documented that date back to the Wadi Suq, as well as the (late) Islamic period. Among the finds, the largest group of artefacts, by far, is of pottery sherds, followed by marine shells and snails, stone artefacts, metal objects, and jewellery. Furthermore, two stamp seals, one of them of a Wadi Suq period date, were found.</p>
Tawi Said Archaeological Survey: Pottery
<p>This is part of the data (pottery) obtained during the survey at Tawi Said 2018. More data can be found in the other submissions of the Tawi Said Archaeological Survey community.</p> <p>The site of Tawi Said is located in the Al-Sharqiyah governorate, approximately 5 km northwest of the modern city of Bidiyah, on the edge of the Sharqiyah Desert. It was discovered in 1976 by Beatrice de Cardi. Two years later, she returned to conduct small scale excavations at the site. Subsequently, numerous references to the site were made in the literature as the only known settlement of the Wadi Suq period (2000-1600 BC) in Central Oman.</p> <p>In November 2018, a short survey was conducted by the Goethe University Frankfurt, Germany, in Tawi Said. An area of 150 x 120 m was intensively field-walked in 1.5 m wide transects to ensure complete visual coverage of the investigated area. Each find received an ascending number and its exact location was recorded using a portable GPS device. In total, nearly 7500 objects were documented that date back to the Wadi Suq, as well as the (late) Islamic period. Among the finds, the largest group of artefacts, by far, is of pottery sherds, followed by marine shells and snails, stone artefacts, metal objects, and jewellery. Furthermore, two stamp seals, one of them of a Wadi Suq period date, were found.</p>
Tawi Said Archaeological Survey: Small Finds
<p>This is part of the data (small finds) obtained during the survey at Tawi Said 2018. More data can be found in the other submissions of the Tawi Said Archaeological Survey community.</p> <p>The site of Tawi Said is located in the Al-Sharqiyah governorate, approximately 5 km northwest of the modern city of Bidiyah, on the edge of the Sharqiyah Desert. It was discovered in 1976 by Beatrice de Cardi. Two years later, she returned to conduct small scale excavations at the site. Subsequently, numerous references to the site were made in the literature as the only known settlement of the Wadi Suq period (2000-1600 BC) in Central Oman.</p> <p>In November 2018, a short survey was conducted by the Goethe University Frankfurt, Germany, in Tawi Said. An area of 150 x 120 m was intensively field-walked in 1.5 m wide transects to ensure complete visual coverage of the investigated area. Each find received an ascending number and its exact location was recorded using a portable GPS device. In total, nearly 7500 objects were documented that date back to the Wadi Suq, as well as the (late) Islamic period. Among the finds, the largest group of artefacts, by far, is of pottery sherds, followed by marine shells and snails, stone artefacts, metal objects, and jewellery. Furthermore, two stamp seals, one of them of a Wadi Suq period date, were found.</p>
ENLIGHT Open Science Surveys datasets
<p>This data was collected in the context of Open Science surveys of the <a href="https://enlight-eu.org/" rel="nofollow">ENLIGHT</a> European university alliance.</p> <p>ENLIGHT RISE collected data from its partner universities:</p> <ul> <li> <p>Information on research data management (RDM) policies, support services and other activities was collected in November 2021. The dataset contains information from 9 partner universities.</p> </li> <li> <p>Information on Open Science (OS) activities, infrastructure and support, skills and knowledge, community activities, policy, recognition and rewards, and environment was collected from 11 December 2021 until 31 January 2022. The dataset contains information from 9 partner universities.</p> </li> <li> <p>Updated information on OS and RDM policies, support and other activities was collected in February/March 2024. Moreover, views on joint achievements and possible future actions were investigated. The 2024 dataset contains information from 10 universities (one additional partner joined on 1 December 2023).</p> </li> </ul>
Dataset from the Survey on Industry 5.0 Concepts and Enabling Technologies, Towards an Enhanced Conservation Practice
<p>This database contains all the responses from the participants in the survey: Industry 5.0 Concepts and Enabling Technologies, Towards an Enhanced Conservation Practice.</p> <p>The main purpose of this survey was to explore how the Architecture, Engineering, Construction, Management, Operation, and Conservation (AECMO&C)<br>industry can adapt and better prepare to embrace the innovative principles and enabling technologies of Industry 5.0. This could ultimately result in<br>enhanced conservation practices for built cultural heritage.</p> <p> </p>
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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.