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81 results for “interview data”
Manure Cycling Interview Data
Exploring the potential for nutrient circularity in the beef production system requires an understanding of current practices. Manure nutrients produced in feedlots are an ample source of fertilizer for phosphorus deficient crop and hay lands. However, it is unclear how far manure nutrients are travelling from feedlots, what crops they’re being applied to, and whether those grains are in turn integrated into the feedlot operations. The purpose of these interviews was to ascertain the above information from feedlot managers. In addition, we sought contextual information (provenance of cattle, cattle weights/ages, manure treatment, regulations/guidelines, processing facility destination, barriers, suggestions for improvements). To answer our question about potential manure nutrient circularity, we focused and report here the elements pertaining to feed/grain provenance, crops manure was applied to, and export distance for manure.
Analysed data from interviews on FAIR-enabling services
<p>Within FAIRsFAIR task 2.4, we carried out five semi-structured interviews with data service owners to understand how services currently support the FAIR principles, what are transferable insights and recommendations, and what are common challenges and pitfalls. This document collects the insights captured from the interviews. This work has been used as input for the basic framework on FAIRness of services developed by FAIRsFAIR task 2.4 (see https://doi.org/10.5281/zenodo.4292599).</p> <p> </p>
TRESCA D1.2 Interview Data
<p>28 interview data + interview template + consent form template used for the Deliverable 1.2 "Science Communication and Policy Trend Report" and the corresponding scientific article "New trends in science communication fostering evidence-informed policy-making" funded under H2020 project TRESCA (Trustworthy, Reliable and Engaging Science Communication Actions).</p>
[DATA_SCIENCE] Interviews PomBase Users, January-February 2016
<p>Here you find the transcripts of interviews collected by Sabina Leonelli as part of the ERC project "The Epistemology of Data-Intensive Science". You also find the information sheet provided to interviewees, which gives you the context for this project. Further information and related publications can be found at www.datastudies.eu. One paper that specifically makes use of these interviews was published by Sabina Leonelli in the journal Philosophy of Science in 2018, under the title "Data in Time: Time-Scales of Data Use in the Life Sciences." The transcripts document yeast researchers' attitudes to data curation and the use of databases in their field. Researchers have consented to have these transcripts made available as Open Data. Other interviewees did not give consent, so those transcripts are held securely by the research team in Exeter.</p>
Data and analysis supplement for: Functional imagery training versus motivational interviewing for weight loss: a randomised controlled trial of brief individual interventions for overweight and obesity.
<p>This submission provides the data and code for analyses reported in our publication.</p>
Data Set of Industry Interviews on Industrial Metaverse
<p>Data Set of Industry Interviews on Industrial Metaverse</p> <p>Industrial Metaverse for Industrial Companies: An Exploratory Study<br>Smart Service Summit - Smart Services Supporting the Value Co-creation in Industrial Contexts (2024)</p> <p>This data set comprises the following components:</p> <ul> <li>Interview Questionnaire</li> <li>Interview Metadata</li> <li>Interview Data</li> <li>Interview Coding</li> <li>Interview Quotes</li> </ul>
PLANET4B coding of 29 interviews Trade & GVCs case study Brazil & EU 20250708 v2 data
<p>This file contains the coding of 29 interviews collected between 2023 and 2025, in the context of the case study "Trade & global value chains", part of the Horizon Europe Project PLANET4B. The interviews include participants from academia, environmental NGOs, Indigenous peoples and local communities, government and businesses in Brazil and in the Netherlands, connected to the global value chains of soy and beef between Brazil-Netherlands. Some of these interviews discuss the recent European Union Regulation on Deforestation-Free Products (EUDR). </p> <table> <tbody> <tr> <td> </td> </tr> </tbody> </table>
Campina de Faro pilot - data from residents interviews - INCULTUM
<p>Survey of local communities to gather ideas and identify their needs, with the aim of improving cultural tourism experiences.</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>
HRE 2021-0515 Research Data: Interview Transcripts
<p>The <a href="https://openknowledge.community/about-coki/">Curtin Open Knowledge Initiative</a> (COKI) in collaboration with <a href="https://library.curtin.edu.au/">Curtin University Library</a> undertook a project to provide better support for the creative practice research outputs (CPROs) of Faculty of Humanities researchers. The reason for this research is to identify ways to increase the visibility of CPROs at Curtin University, and document what information (metadata) is important to researchers when describing their CPROs. The Chief Investigator of this project was Dr Lucy Montgomery, Professor of Knowledge Innovation at Curtin University. This research project has approval from the Curtin University Human Research Ethics Office (HRE2021-0515).</p> <p>This dataset contains deidentified interview transcripts from six interviews with creative practice researchers at Curtin University, Perth, Australia, who consented to sharing their deidentified data as a publicly available dataset. The participants have been deidentified, and named as P1 to P6. Interviews were conducted between 20/09/2021 and 30/09/2021. Four interviews were in person, and two interviews were online via WebEx.</p> <p>The interview guide is publicly available on Zenodo:</p> <p><a href="https://doi.org/10.5281/zenodo.5774543">https://doi.org/10.5281/zenodo.5774543</a></p> <p>The metadata findings from the card sorting activity are available on Zenodo:</p> <p><a href="https://doi.org/10.5281/zenodo.5774660">https://doi.org/10.5281/zenodo.5774660</a></p>
NIRS data during sandplay and interview
<p>Interactions between the client (Cl) and therapist (Th) evolve therapeutic relationships in psychotherapy. An interpersonal link or therapeutic space is implicitly developed wherein certain important elements are expressed and shared. However, neural basis of psychotherapy, especially of non-verbal modalities, have scarcely been explored. Therefore, we examined the neural backgrounds of such therapeutic alliances during sandplay, a powerful art/play therapy technique. Real-time and simultaneous measurement of hemodynamics was conducted in the prefrontal cortex (PFC) of Cl-Th pairs participating in sandplay and subsequent interview sessions through multichannel near-infrared spectroscopy. As sandplay is highly individualized, and no two sessions and products (sandtrays) are the same, we expected variation in interactive patterns in the Cl–Th pairs. Nevertheless, we observed a statistically significant correlation between the spatio-temporal patterns in signals produced by the homologous regions of the brains. During the sandplay condition, significant correlations were obtained in the lateral PFC and frontopolar (FP) regions in the real Cl-Th pairs. Furthermore, a significant correlation was observed in the FP region for the interview condition. The correlations found in our study were explained as a "remote" synchronization (i.e., unconnected peripheral oscillators synchronizing through a hub maintaining free desynchronized dynamics) between two subjects in a pair, possibly representing the neural foundation of empathy which arises commonly in sandplay therapy.</p>
Interview data on history-oriented theologians' recommendations for visualizations in libraries
<p>Results of an interview study with the target group "history-oriented theologians" on their recommendations for visualizations in libraries. Recommendations were retrieved with the method SHIRA (Structured Hierarchical Interviewing for Requirement Analysis)[1]. This allows generating concrete qualities and implementation suggestions out of abstract qualities.</p> <p>Feel free to contact me if you have any questions!</p> <p> </p> <p> [1] M. Hassenzahl, R. Wessler, and K.-C. Hamborg. Exploring and understanding product qualities that users desire. Conference on Human-Computer Interaction IHM-HCI’2001, 2, 2001.</p>
Interview data on experts' recommendations for visualizations in libraries
<p>Results of an interview study with twelve experts on their project processes and their recommendations for visualizations in libraries. Recommendations were retrieved with the method SHIRA (Structured Hierarchical Interviewing for Requirement Analysis)[1]. This allows generating concrete qualities and implementation suggestions out of abstract qualities.</p> <p>The file contains two pages: On the first, a meta-model was constructed out of all identified steps during library visualization projects. On the second, all SHIRA suggestions were gathered and analyzed.</p> <p>Feel free to contact me if you have any questions!</p> <p> </p> <p> [1] M. Hassenzahl, R. Wessler, and K.-C. Hamborg. Exploring and understanding product qualities that users desire. Conference on Human-Computer Interaction IHM-HCI’2001, 2, 2001.</p>
Medical interview score data from PostCC-OSCE and programs for an extended many-facet IRT model
<p>Objective structured clinical examinations (OSCEs) are widely used performance assessments for medical and dental students. A common limitation of OSCEs is that the evaluation results depend on the characteristics of raters and the scoring rubric. To overcome this limitation, item response theory (IRT) models such as the many-facet models have been proposed to estimate examinee abilities while accounting for the characteristics of raters and evaluation items in a rubric. However, conventional IRT models have two impractical assumptions: constant rater severity across all evaluation items in a rubric and an equal interval rating scale among evaluation items, which can decrease model fitting and ability measurement accuracy.</p> <p>To resolve this problem, we propose a new IRT model that relaxes these assumptions. We demonstrate the effectiveness of the proposed model by applying it to actual data collected from a medical interview test conducted at Tokyo Medical and Dental University as part of a post-clinical clerkship (PostCC) OSCE. The experimental results showed that the proposed model fit our OSCE data well and measured ability accurately. Furthermore, it provided abundant information on rater and item characteristics that conventional models cannot, helping us to better understand rater and item properties.</p> <p>This dataset includes the actual score data collected from the above-mentioned medical interview test in a PostCC OSCE, as well as the program for estimating the parameters of the proposed IRT model.</p>
Interview Data: Nativism, Islamophobism and Islamism in the Age of Populism dataset
<h1><strong>Interview Data</strong></h1> <h2><strong>Nativism, Islamophobism and Islamism in the Age of Populism dataset</strong></h2> <p>Transcripts of 302 interviews conducted with self-identified Muslim youth of migrant origin and native youth with affiliation or sympathy with movements labeled far-right in Belgium, France, the Netherlands, and Germany.<a title="" href="#_ftn1" name="_ftnref1">[1]</a> Local researchers conducted the interviews using the same interview guide, including 17 questions. Interviews were not audio-recorded. The researchers took notes, verifying their transcriptions with the research participant during and after the interview. Originally, the research consisted 307 interviews but five participants (1 French native; 2 German Muslims; 2 German natives) did not want their interview transcriptions to be made public on the ERC data repository site. In accordance with our ethical guidelines, we anonymized the transcripts. The dataset also includes the summary output (as an excel file) of the values analysis of the 307 interviews. Please visit the attachment named Data Summary to learn more about our method of analysis and how to use the attached documents. As a complementary file, we hope that the additional excel sheet detailing the demographic characteristics of our research participants (sex, age, educational background, etc.) helps advance researchers’ understanding of our participant profile.</p> <p> </p> <p><strong>Additional information: </strong></p> <p>302 transcription files (zipped), 2 data summary files, 2 documentation files</p> <p> </p> <p><strong>Cadmus permanent link: </strong><a href="https://hdl.handle.net/1814/76159">https://hdl.handle.net/1814/76159</a></p> <p><strong>Series/Number: </strong>EUI; RSC; Research Data; 2023</p> <p><strong>Publisher: </strong>European University Institute</p> <p><strong>Keyword(s): </strong><a href="https://cadmus.eui.eu/discover?order=desc&rpp=10&sort_by=dc.date.issued_dt&query=%22Deprivation%22">Deprivation</a>, <a href="https://cadmus.eui.eu/discover?order=desc&rpp=10&sort_by=dc.date.issued_dt&query=%22Radicalism%22">Radicalism</a>, <a href="https://cadmus.eui.eu/discover?order=desc&rpp=10&sort_by=dc.date.issued_dt&query=%22Nativism%22">Nativism</a>, <a href="https://cadmus.eui.eu/discover?order=desc&rpp=10&sort_by=dc.date.issued_dt&query=%22Populism%22">Populism</a>, <a href="https://cadmus.eui.eu/discover?order=desc&rpp=10&sort_by=dc.date.issued_dt&query=%22Islamism%22">Islamism</a></p> <p><strong>Sponsorship and Funder information: </strong></p> <p>ERC Advanced Grant research project "Nativism, Islamophobism and Islamism in the Age of Populism: Culturalisation and Religionisation of what is Social, Economic and Political in Europe" (No: 785934). The project’s details and output can also be accessed at the project website, <strong><u> https://bpy.bilgi.edu.tr/en/</u></strong></p> <div><br> <div> <p><a title="" href="#_ftnref1" name="_ftn1">[1]</a> ERC Advanced Grant research project "Nativism, Islamophobism and Islamism in the Age of Populism: Culturalisation and Religionisation of what is Social, Economic and Political in Europe" (No: 785934). The project’s details and output can also be accessed at the project website, <a href="https://bpy.bilgi.edu.tr/en/">https://bpy.bilgi.edu.tr/en/</a> .</p> </div> </div>
Survey and Interview Data from Mixed-Method Survey of Serverless Computing and Function-as-a-Service Software Development in Industrial Practice
<p>This dataset contains the almost-raw data resulting from two out of the three methods chosen by the researchers for their namesake study «A Mixed-Method Empirical Study of Function-as-a-Service Software Development in Industrial Practice». Among the files are web survey questions, anonymised survey results, and interview guidelines. We encourage other researchers to perform open coding and other analysis techniques on the data to verify our claims and to generate new insights.</p>
[DATA_SCIENCE] Interviews Oceanography, March 2015 - May 2017
<p>This is a collection of transcripts from interviews conducted by Gregor Halfmann as part of the ERC project "The Epistemology of Data-intensive Science". The interviews served as the empirical basis for Halfmann's PhD thesis "Seafarers, Silk, and Science: Oceanographic Data in the Making", submitted at the University of Exeter in July 2018. The interviews relate to the research practices, in particular the production and processing of research samples and scientific data, by marine ecologists and biological oceanographers working at the Marine Biological Association of the UK and for the Continuous Plankton Recorder Survey. Researchers have consented to have these transcripts made available as Open Data.</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>
Codebook for the analysis of focus group interview data collected as part of the DETECT project.
<p>This is the codebook created for the analysis of focus group interview data collected as part of the <a href="http://detectproject.eu/">DETECT project</a>. In particular, nine interviews were conducted with primary and secondary school teachers in Finland, Italy, Spain and the UK in order to explore their perceptions of critical digital literacies and how these are manifested in their practices. The interviews were organised and conducted by the researchers in the respective local HEIs between February-June 2020. A total of 7 focus-groups interviews took place with a total number of 39 participating teachers (7 from Finland, 6 from the UK, 9 from Spain and 17 from Italy). The interviews were conducted both face to face (schools in Spain) and online (schools in Finland, Italy and the UK) due to pandemic-related restrictions imposed shortly after the start of the data collection period.</p> <p>The collected data were read and segmented and all interview excerpts relating to the Critical Digital Literacies framework sub-dimensions were marked and chosen for the analysis. The total number of marked segments was 666 in all nine focus group interviews. To ensure the reliability of the analyses, the researchers translated and collected a representative sample of codings (n=117 out of 666) for each sub-dimensions from each school and these were examined by all researchers in several consensus meetings and the final criteria for each sub-category were constructed together based on those discussions.</p> <p>This dataset accompanies the intellectual outputs of the DETECT project, including amongst others this report:</p> <p>Gouseti, A., Bruni, I., Ilomäki, L., Lakkala, M., Mundy, D., Raffaghelli, J., Ranieri, M., Roffi, A., Romero, M. and Romeu, T. (2021) <em>Schools’ perceptions and experiences of critical digital literacies across four European countries - DETECT Report 2. </em>Accessed at: <a href="http://doi.org/10.5281/zenodo.5070394">http://doi.org/10.5281/zenodo.5070394</a></p> <p><strong>Acknowledgement</strong></p> <p>This project was funded by Erasmus+, KA2. Project Reference: 2019-1-UK01-KA201-061508.</p>
EOSC Nordic WP4 FAIR incentives interview data
<p>Interview data were collected and analysed as part of EOSC Nordic WP4 FAIR. The main goal was to have input about the challenges and incentives of FAIRification of the research data from different stakeholder groups (researchers, data stewards/research support at institutions, representatives of research administration, and funders)</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.