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111 results for “qualitative data”
Qualitative Data on 60 Small-Scale Fisheries: A socio-ecological rapid appraisal applied to cases from America (Colombia, Ecuador, and Mexico), Africa (Kenya, Madagascar, and Nigeria), and Europe (France and Spain)
<h2><span lang="EN-US">Dataset name</span></h2> <p><span lang="EN-US">Small_Scale_Fishery_Data_2023_v2 </span><span lang="EN-US"> </span></p> <h2><span lang="EN-US">Title</span></h2> <p><span lang="EN-US">Qualitative Data on 60 Small-Scale Fisheries: A socio-ecological rapid appraisal applied to cases from America (Colombia, Ecuador, and Mexico), Africa (Kenya, Madagascar, and Nigeria), and Europe (France and Spain). </span><span lang="EN-US"> </span></p> <h2><span lang="EN-US">Description </span></h2> <p><span lang="EN-US"> This dataset was created for the Fish2Sustainability research project, which aims to evaluate how small-scale fisheries (SSF) contribute to Sustainable Development Goals (SDGs). The dataset includes 60 case studies across eight countries and was developed using a rapid appraisal framework. The framework includes a four-step process: </span></p> <p><span lang="EN-US"> 1. Identifying specific SDG targets influenced by SSF;</span></p> <p><span lang="EN-US"> 2. Extracting relevant variables from UN indicators;</span></p> <p><span lang="EN-US"> 3. Gathering expert input via a questionnaire to score these variables;</span></p> <p><span lang="EN-US"> 4. Creating composite indicators to measure SSF performance against SDGs.</span></p> <p><span lang="EN-US"> The dataset contains raw data from step 3, case study details, variable scores, and comments from data collectors (contributing authors). The dataset is valuable for researchers interested in small-scale fisheries and socio-ecological systems. By incorporating expert judgments from individuals with expertise in SSF, particularly in data-poor contexts, the dataset offers a wealth of knowledge for conducting comparative analyses across different contexts.</span><span lang="EN-US"> </span></p> <h2><span lang="EN-US">Authors </span></h2> <p><span lang="EN-US">Léopold, M.1, Bitoun, R.E.2, Beckensteiner, J.3, Chuenpagdee, R.4, Fondo, E.N.5, Akintola, S.L.6, Bach, P.7, Frangoudes, K.8, Gaibor, N.9, Gutierrez-Cala, L.10, Massey, Y.7, Randrianandrasana, R.11, Razanakoto, T.11, Saavedra-Díaz, L.M.10, Schreiber Arias, M.12,13, Salas, S.14, Devillers, R.2,4 </span></p> <h3><span lang="EN-US">Affiliations </span></h3> <p><span lang="EN-US">1 ENTROPIE (IRD, University of La Reunion, CNRS, University of New Caledonia, Ifremer), c/o IUEM, Plouzané, France </span></p> <p><span lang="EN-US">2 Espace-Dev (IRD, Univ. </span>Montpellier, Univ. Guyane, Univ. La Réunion, Univ. Antilles, Univ. Nouvelle Calédonie), Montpellier, France</p> <p>3 AMURE (Ifremer, UBO, CNRS), Plouzané, France</p> <p><span lang="EN-US">4 Department of Geography, Memorial University of Newfoundland, St. John’s, NL, Canada</span></p> <p><span lang="EN-US">5 Kenya Marine and Fisheries Research Institute, Mombasa, Kenya</span></p> <p><span lang="EN-US">6 Department of Fisheries, Faculty of Science, Lagos State University, Nigeria</span></p> <p><span lang="EN-US">7 MARBEC, University of Montpellier, CNRS, Ifremer, IRD, Sète, France</span></p> <p>8 Université de Bretagne Occidentale: Brest, France</p> <p>9 Instituto Público de Investigación de Acuicultura y Pesca (IPIAP), Universidad del Pacifico (UPAC), Guayaquil, Ecuador</p> <p>10 Grupo de Investigación en Sistemas Socioecológicos para el Bienestar Humano (GISSBH), Programa de Biología, Universidad del Magdalena, Colombia</p> <p>11 Centre d’Etudes et de Recherches Economiques pour le Développement (CERED), Université d’Antananarivo, Madagascar</p> <p><span lang="EN-US">12 EqualSea Lab, Universidad Santiago de Compostela, A Coruña, Spain</span></p> <p><span lang="EN-US">13 School of Global Studies, University of Gothenburg, Gothenburg, Sweden</span></p> <p>14 Centro de Investigación y de Estudios Avanzados (CINVESTAV), IPN, Unidad Mérida, Mexico </p> <h2><span lang="EN-US">Method </span></h2> <p><span lang="EN-US">Case studies were selected in eight countries by national SSF experts, based on specific criteria and research priorities. Case studies were not selected to represent the full diversity of SSF globally or even nationally. Instead, they were chosen to capture a range of fisheries that could showcase different contributions to SDGs. SSF were defined based on various characteristics, such as resources harvested, gear used, and location of the fishery. </span><span lang="EN-US"> </span></p> <h3><span lang="EN-US">Geographical Coverage </span></h3> <p><span lang="EN-US">60 small-scale fisheries located in seven countries are documented in the data:</span></p> <ul> <li><span lang="EN-US">Colombia (4 case studies) – Pacifico: La Guajira, San Andrés y Providencia; Caribe: Chocó, Cauca, Valle del Cauca, Nariño.</span></li> <li><span lang="EN-US">Ecuador (3) – Region: Esmeraldas, Manabi, Guayas, El Oro.</span></li> <li><span lang="EN-US">France (2) – Region: Bretagne, Occitanie.</span></li> <li><span lang="EN-US">Kenya (22) – County: Kilifi, Kwale, Lamu, Mombasa, Tana River.</span></li> <li><span lang="EN-US">Madagascar (20) – Region: Analanjirofo, Anosy, Atsimo Andrefana, Boeny, Diana, Menabe, Vatovavy Fitovinany.</span></li> <li><span lang="EN-US">Mexico (2) – State: Baja California Sur, Campeche, Yucatan.</span></li> <li><span lang="EN-US">Nigeria (6) – State: Bayelsa, Cross River, Lagos, Ondo, Ogun. </span></li> <li><span lang="EN-US">Spain (1) – State: Galicia.</span> </li> </ul> <h3><span lang="EN-US">Data Collection </span></h3> <p><span lang="EN-US">Data collection took place from November 30, 2022, to July 3, 2023, spanning approximately seven months. The data presented serve as a snapshot of the conditions within a specific small-scale fishery during the assessment period. To consider the evolution of trends such as exports, economic growth, and income, we considered any relevant variables over the past decade. </span></p> <p><span lang="EN-US">Data collection approaches varied depending on the context, and data collectors received training to ensure survey consistency. We used primary data sources such as interviews, observations, and measurements whenever possible. In cases where resources were limited, we preferred secondary sources such as existing datasets and literature. Our methods were standardized, but data collectors could adjust them based on their resources. We primarily used direct observation, focus groups, and interviews to collect data. Scoring in interviews and focus groups was done directly or through group analysis by interviewers. Disagreements were resolved through additional interviews or group discussions, with secondary data used if needed. Please refer to the methods in : </span></p> <p><strong><span lang="EN-US">Bitoun et al., (2024). A methodological framework for capturing marine small-scale fisheries’ contributions to the sustainable development goals. Sustainability Science, 19(4), 1119–1137. https://doi.org/10.1007/s11625-024-01470-0. </span></strong><span lang="EN-US"><strong> </strong> </span></p> <h3><span lang="EN-US">Ethics </span></h3> <p><span lang="EN-US">Participants had the option to join of their own accord, were fully briefed on the research goals, and were given the opportunity to review interview guidelines before proceeding. Depending on the circumstances, interviews could last 45 minutes to 4.5 hours. Participants were guaranteed confidentiality and anonymity in the handling and reporting of their data.</span><span lang="EN-US"> </span></p> <h3><span lang="EN-US">Suggested citation</span></h3> <p><span lang="EN-US">Léopold, M., Bitoun, R., & Devillers, R. (2023). Qualitative Data on 61 Small-Scale Fisheries: A socio-ecological rapid appraisal applied to cases from America (Colombia, Ecuador, and Mexico), Africa (Kenya, Madagascar, and Nigeria), and Europe (France and Spain) (Version 2) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.16077739</span></p> <h2><span lang="EN-US">Data Files</span></h2> <p><span lang="EN-US">The dataset includes the following:</span></p> <ul> <li><span lang="EN-US">The raw dataset (.xls format).</span></li> <li><span lang="EN-US">A data dictionary describing and defining each dataset column (.xls format).</span></li> </ul>
Empirical data, qualitative codes, analysis: Schuur J.S. et al. Identifying levers of urban neighbourhood transformation. npj Urban Sustainability (2023)
<p>Please refer to the stand-alone "2023_SchuurJS_UrbanSustainabilityfinal.html" file where the analysis and results corresponding to the article titled: "Identifying levers of urban neighbourhood transformation using serious games" is presented. The underlying data sets and Rmarkdown script used for the analysis can be used to re-run the analysis. Ensure to read the "0_README.txt" file to build the appropriate folder structure to do so.</p>
Educational transformation and network learning dataset – qualitative data from an international collaborative EU-project
<p>We are releasing our dataset of workshop outcomes acquired from the annual consortium conferences organized by the international “NextFood” consortium. The purpose of this project is to develop new ways of educating the future sustainability leaders of the agrifood sector, making sure that the professionals (farmers, advisers, businesses, students) have the right set of skills and competences needed to tackle the sustainability challenges we face ahead. Data gathering started from May 2018 yielding considerable amount of data on achievements, challenges and action plans related to educational transformation. This dataset will be updated by the time of project finalization. This work was funded by the European Union, through the Horizon 2020 project “NextFood”, Grant agreement No. 771738.</p>
Sharing research data and findings relevant to the novel coronavirus (COVID-19) outbreak - Thematic coding of qualitative research findings
<p>The spreadsheet in the present dataset (CSV format) includes the anonymised thematic coding that has been applied to our interview and literature review findings to inform the preparation of the report: From intent to impact: Investigating the effects of open sharing commitments.</p> <p>The thematic coding has been applied by using <a href="https://www.qsrinternational.com/nvivo-qualitative-data-analysis-software/home">NVivo</a>, a professional qualitative analysis software, and then exported in spreadsheet form for public sharing.</p> <p>Find out more about this project in our dedicated <a href="https://zenodo.org/communities/data-sharing-in-public-health-emergencies">Zenodo project community</a>.</p>
Dataset for: Exploring the experiences of academic libraries with research data management: a meta-ethnographic analysis of qualitative studies
<p><strong>Overview</strong></p> <p>This dataset contains the raw data for the manusript:<br> Perrier L, Blondal E, MacDonald H. Exploring the experiences of academic libraries with research data management: a meta-ethnographic analysis of qualitative studies. 2018; 40(3-4): 173-183. doi: 10.1016/j.lisr.2018.08.002</p> <p>Full-text available at: <a href="https://doi.org/10.1016/j.lisr.2018.08.002">https://doi.org/10.1016/j.lisr.2018.08.002</a> </p> <p><strong>Data and Documentation Files</strong></p> <p>Five files make up the dataset:</p> <ol> <li>Data Dictionary: RDMMetaEthnography_DataDictionary_v1.pdf</li> <li>Data Abstraction Sheet: RDMMetaEthnography_StudyCharacteristics.csv</li> <li>Data Abstraction Sheet: RDMMetaEthnography_ParticipantCharacteristics.csv</li> <li>Data Abstraction Sheet: RDMMetaEthnography_Outcomes.csv</li> <li>Data Abstraction Sheet: RDMMetaEthnography_COREQ,csv</li> </ol> <p>Contact: Laure Perrier: <a href="https://orcid.org/0000-0001-9941-7129">orcid.org/0000-0001-9941-7129</a></p>
Qualitative Data on Effects of Early and Prolonged Parent-Child Separation: Understanding Mental Health of Separated-Reunited Chinese American Children
<div> <div> <div> <div>Early and prolonged parent-child separation due to parental migration or immigration may result in attachment disruption that can threaten the long-term mental health and functioning of affected children, and these risks can persist following reunification and through adulthood. Although sending infants back to the home country for rearing is often practiced among <em>Chinese</em> immigrants, especially low-income families, research has been sparse in understanding the long-term impact of early and prolonged parent-child separation and reunification on disparities in mental health and functioning among separated-reunited children and the mechanism through which such relationships may operate.</div> <div>Funded by National Institute on Minority Health and Health Disparities (NIMH), we collected semi-structured interview data from 24 parent-child dyads who have experienced separation. The data included interview scrpits with primary coding to understand the mental health impacts, risk/protective factors, and service needs among separated-reunited <em>Chinese</em> American children.</div> </div> </div> </div> <div> </div>
Data set for "Quantitative and Qualitative bibliometric scope toward the Synthesis of Rose Oxide as a Natural Product in perfumery"
<p>This is the bibliometric data for "Quantitative and Qualitative bibliometric scope toward the Synthesis of Rose Oxide as a Natural Product in perfumery" study which were derived from SCOPUS database, on 23<sup>rd</sup> September 2019, based on title search.</p>
Toy Qualitative Data Project (Interview Transcripts)
<p><strong>Please be advised that this project is intended solely for instructional purposes and should not be used for actual research. This dataset is intended to complement the instructional material and provide a hands-on learning experience for the workshop: <a href="https://rcurty.github.io/qualdata-training">Handling and Sharing Qualitative Data Responsibly and Effectively</a>.</strong></p> <p>This hypothetical research project is designed to demonstrate key concepts related to human subject qualitative data management and thematic analysis coding. It includes interview transcripts generated with ChatGPT 4.0 Mini for a fictional graduate student in Communication named Sarah, whose main research question is: <em><strong>How do content creators/digital influencers view their role in shaping their followers' consumer behavior, and what ethical dilemmas do they face when promoting products?</strong></em></p> <div> <p>Given the novelty of this research topic and the limited academic literature available, Sarah hopes that the insights gained from this small-scale qualitative exploratory study will help identify key variables for a larger survey study with a representative sample of content creators/digital influencers across the U.S.</p> <p>Sarah has previous experience with quantitative methods but is very new to qualitative research and could use our help for better handling the data. Having already conducted six short structured interviews with subjects from top revenue niches (i.e., Home Decor and DYI, Travel & Adventure, Fashion & Style, Health & Wellness, Finance & Investment, Beauty & Skincare) and planning to conduct a dozen more, Sarah is eager to begin engaging with the data she has collected so far and deciding how to best organize and interpret it. We’ll be walking her through this process, providing the necessary guidance and support for effective and responsible data management.</p> <p>Interviews were conducted over Zoom and audio recorded with participants' consent. The interview included four main questions, which were consistent across all interviews:</p> <p><em>Q1. Please tell me a little about your work as a content creator/digital influencer how it started, and how you have established yourself in your current niche.</em></p> <p><em>Q2. In what ways do you believe content creators/digital influencers shape consumer behavior? Could you share any examples?</em></p> <p><em>Q3. What strategies would you say content creators/digital influencers typically use to increase sales of sponsored products and services? Which ones have you used? What worked and what did not work for you? Why?</em></p> <p><em>Q4. In your view, what are the essential ethical responsibilities that content creators and digital influencers should uphold? Can you share any personal experiences that illustrate these responsibilities in action?</em></p> <p>Each interview generated approximately 15 minutes of audio recording, which Sarah manually transcribed. Sarah decided to keep the transcription true to the recordings and seek assistance to mitigate any risk of identification. </p> </div>
The input data set includes 729 objects (patients) and 39 variables (clinical qualitative and quantitative descriptors).
<p>For reliable data treatment and interpretation qualitative descriptors were omitted and only numerical clinical indicators were included in the data matrix. Finally, the data set dimension was [729 x 18].</p> <p> The data were treated by hierarchical cluster analysis and factor analysis. The major goal of the data mining was to reach statistically significant partitioning of the objects and variables into similarity patterns (clusters) which helps to better understand the data structure, to assess the meaning of the partitioning achieved, thus promoting the evaluation of the health status of the patients and the role of specific descriptors for the formation of the partitioning patterns.</p> <p>3D classification Python tool.</p>
Extracted and Anonymised Qualitative Data on Students' Acceptance of an Early Warning System
<p>The data published in this record was adopted in the following study: </p> <p><em><strong>Exploring Higher Education students' experience with AI-powered educational tools: The case of an Early Warning System </strong></em></p> <p>The study analyses the students' experience of an early warning system developed at a fully online university. The study is based on 21 semi-structured interviews that yielded a corpus of 21,761 words, for which a mixed inductive and deductive codification approach was applied after thematic analysis. We focused on 11 themes, 52 subthemes, and 396 coded segments to perform content analysis. Our findings revealed that the students, primarily senior workers with a high-level academic self-efficacy, had little experience with this type of system and low expectations about it. However, a usage experience triggered interest and meaningful reflections on the mentioned tool. Nevertheless, a comparative analysis between disciplines related to Computer Science and Economics showed higher confidence and expectation about the system and artificial intelligence overall by the first group. These results highlight the relevance of supporting students' further experiences and understanding of artificial intelligence systems in education to accept them and mainly to participate in iterative development processes of such tools to achieve quality, relevance, and fairness.</p> <p>The three records attached as part of the dataset include:</p> <p>1- The General CodeTree with exemplar coding excerpts in Spanish<br> 2- Extract of transcriptions in English<br> 3- Full Report in Spanish as extracted from NVIVO, including the extracted codes for the synthesis (1,2) in blue, and the comments made by the two researchers engaged in the interrater agreement.<br> 4- General Content Analysis (Spreadsheet ODS)</p> <p> </p>
Data set - What Defines Quality of Life for Older Patients Diagnosed with Cancer? A Qualitative Study
<p><strong>Data set from- What Defines Quality of Life for Older Patients Diagnosed with Cancer? A Qualitative Study</strong></p> <p><strong>Abstract of the study: </strong>The treatment of cancer can have a significant impact on quality of life in older patients and this needs to be taken into account in decision making. However, quality of life can consist of many different components with varying importance between individuals. We set out to assess how older patients with cancer define quality of life and the components that are most significant to them. This was a single-centre, qualitative interview study. Patients aged 70 years or older with cancer were asked to answer open-ended questions: What makes life worthwhile? What does quality of life mean to you? What could affect your quality of life? Subsequently, they were asked to choose the five most important determinants of quality of life from a predefined list: cognition, contact with family or with community, independence, staying in your own home, helping others, having enough energy, emotional well-being, life satisfaction, religion and leisure activities. Afterwards, answers to the open-ended questions were independently categorized by two authors. The proportion of patients mentioning each category in the open-ended questions were compared to the predefined questions. Overall, 63 patients (median age 76 years) were included. When asked, “What makes life worthwhile?”, patients identified social functioning (86%) most frequently. Moreover, to define quality of life, patients most frequently mentioned categories in the domains of physical functioning (70%) and physical health (48%). Maintaining cognition was mentioned in 17% of the open-ended questions and it was the most commonly chosen option from the list of determinants (72% of respondents). In conclusion, physical functioning, social functioning, physical health and cognition are important components in quality of life. When discussing treatment options, the impact of treatment on these aspects should be taken into consideration.</p> <p><strong>Reference of research paper: </strong>Seghers PAL, Kregting JA, van Huis-Tanja LH, Soubeyran P, O'Hanlon S, Rostoft S, Hamaker ME, Portielje JEA. What Defines Quality of Life for Older Patients Diagnosed with Cancer? A Qualitative Study. <em>Cancers</em>. 2022; 14(5):1123. https://doi.org/10.3390/cancers14051123</p> <p><strong>Content of the data set: </strong>The first Tab describes what questions were asked, the second tab shows all individual anonymised answers to the open questions, the fourth shows the definitions that were used to classify all answers. Q1-Q4 show how the answers were categorised. </p>
Qualitative Interview Data: Users and therapists perceptions of myoelectric multi-function upper limb prostheses with direct and pattern recognition control
<p>The data uploaded here were collected in 2016/2017 through semi-structured interviews with prosthesis users and hand therapists. Participants were mainly asked about satisfaction with their prosthetic device and about activities which they perform with the prosthesis. Interviews were conducted in Dutch and German language.</p> <p>All interview data are made publicly available, except for data of prosthesis users who were experienced with pattern recognition control (n=4). Due to the small number of these participants, their interview data is only available upon reasonable request to not compromise participant privacy. </p> <p> </p>
Data Workbook - Ex-Situ Geoheritage Case Study: Quantitative and Qualitative Analysis of the Uppsala University Museum of Evolution Collections
<p>Data Workbook for Thesis.</p> <p>Ex-Situ Geoheritage Case Study: Quantitative and Qualitative Analysis of the Uppsala University Museum of Evolution Collections. </p> <p>Includes; Images, Conservation Results, Inventory, Valuation Grades, RStudio Results</p>
Qualitative review data of Indian Public Sector Banks' qualitative review data
<p>This data is very useful in text mining. This data s useful for identifying key service quality dimensions for mobile banking apps using text mining.</p>
360-degree video recording of an outdoor camerawork training session for qualitative data collection
<p>In this equirectangular 360° video clip, a recording of an outdoor camerawork training session is stitched together from the footage taken by a stereoscopic 360° camera with eight lenses. To play the video and spatial sound correctly, use a digital video player that can play equirectangular videos with the YouTube ambiX First Order Ambisonic audio format, eg. VLC or PotPlayer. Please wear headphones.</p> <p>In the camerawork training session, all the participants are playing particular roles in the training session, and each carries a camera. In preparation for the real data collection with a guide, one person is pretending to be a nature guide. She carries a GoPro camera on a gimbal. There is an instructor, who is carrying a single lens 360° camera on a raised extension pole with a separate ambisonic microphone. Two others are filming with a prosumer camcorder and a single lens 360° camera on a lowered extension pole respectively. And a fifth person is filming with a stereoscopic 360° camera and an independent ambisonic microphone on a monopod. In a nutshell, this is a typical team filming arrangement, in which the team needs to attentively yet silently coordinate their joint camerawork. Languages: Danish and English</p>
Qualitative raw data and behavioral analysis for understanding VMMC policy decision-making
<p>Faced with declining donor funding for HIV, low- and middle-income countries must identify efficient and cost-effective ways to integrate HIV prevention programs into public health systems for long-term sustainability. In Zambia, donor support to the voluntary medical male circumcision (VMMC) program, which previously funded non-governmental organizations as implementing partners, is increasingly being directed through government structures instead. We developed a framework to understand how the behaviors of individual decision-makers within the government could be barriers to this transition. We interviewed key stakeholders from the national, provincial, and district levels of the Ministry of Health, and from donors and partners funding and implementing Zambia's VMMC program, exploring the decisions required to attain a sustainable VMMC program and the behavioral dynamics involved at personal and institutional levels. Using pattern identification and theme matching to analyze the content of the responses, we derived three core decision-making phases in the transition to a sustainable VMMC program: 1) developing an alternative funding strategy, 2) developing a policy for early-infant (0-2 months) and early-adolescent (15-17 years) male circumcision, which is crucial to sustainable HIV prevention; and 3) identifying integrated and efficient implementation models. We formulated a framework showing how, in each phase, a range of behavioral dynamics can form barriers that hinder effective decision-making among stakeholders at the same level (e.g., national ministries and donors) or across levels (e.g., national, provincial and district). Our research methodology and the resulting framework offer a systematic approach for in-depth investigations into organizational decision-making in public health programs, as well as development programs beyond VMMC and HIV prevention. It provides the insights necessary to map organizational development and policy-making transition plans to sustainability, by explaining tangible factors such as organizational processes and systems, as well as intangibles such as the behaviors of policymakers and institutional actors.</p>
Data from: A qualitative analysis of an Aβ-monomer model with inflammation processes for Alzheimer's disease
<p>We introduce and study a new model for the progression of Alzheimer's disease incorporating the interactions of Aβ-monomers, oligomers, microglial cells and interleukins with neurons through different mechanisms such as protein polymerization, inflammation processes and neural stress reactions. In order to understand the complete interactions between these elements, we study a spatially-homogeneous simplified model that allows to determine the effect of key parameters such as degradation rates in the asymptotic behavior of the system and the stability of equilibriums. We observe that inflammation appears to be a crucial factor in the initiation and progression of Alzheimer's disease through a phenomenon of hysteresis, which means that there exists a critical threshold of initial concentration of interleukins that determines if the disease persists or not in the long term. These results give perspectives on possible anti-inflammatory treatments that could be applied to mitigate the progression of Alzheimer's disease. We also present numerical simulations that allow to observe the effect of initial inflammation and concentration of monomers in our model.</p>
Study Data: Obtaining Semi-Formal Models from Qualitative Data: From Interviews into BPMN Models in User-Centered Design Processes
<p>This dataset (Data.zip) contains the raw data of a user study on the investigation of transforming think aloud interviews into BPMN models. All information on how to use the data are provide in the SPSS files and as a readme file. This transformation is executed following a manual additionally provided in Documents.zip. For the training phase, a website was used provided in Website.zip including Screenshots for simpler re-use. Further information are also included as readme file in the zip container.</p> <p>Main research question answered is in how far the manual reduces interpretation and variance in the created models. </p>
Descriptive data from 265 Quantified Self Show&Tell videos - Qualitative dataset
<p>Descriptive data collected on 265 videos published on the Show&Tell projects archive of the Quantified Self website.</p> <p>Data include :</p> <ul> <li>The talk's characteristics : title, link, year and topic(s)</li> <li>Characteristics of the self-researcher(s) : origin, gender, number of participants in the project and if they are professional scientists</li> <li>Description of the data collection : items tracked, type and frequency of the collection, tools used</li> <li>The data exploration tools</li> <li>The duration of the project and if results where significant and given with insights</li> <li>Motivations for starting the project and reason to the end of it</li> <li>Additional comments</li> </ul>
Student Qualitative Data_FoodFactory-4-Us Cycles 1-4
<p>Qualitative data from students’ initial understanding, contributions and expectations of their competences and compare these with their final understanding of own contributions and competence development as participants of <a href="https://www.iseki-food.net/foodfactory-4-us">FoodFactory-4-Us</a> from 2018-2022.</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.