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987 results for “interviews”
Cory Battey, Carlos Avila, Eduardo Chama_Interview Clips for 'Accompaniment in America'
<p>7 .mp3 clips featuring Cory Battey, Carlos Avila, and Eduardo Chama, interviewed online by Kathleen Kelly and Chanda VanderHart on 13 July, 7 June, and 15 July 2024, respectively.</p> <p>Edited by Bill Lloyd and curated by Kathleen Kelly and Chanda VanderHart in connection with the hybrid publication<em> Accompaniment in America</em> (Routledge 2025).</p>
Karl Paulnack_Interview Clip for 'Accompaniment in America'
<p>1 .mp3 clip featuring Karl Paulnack, interviewed online by Elvia Puccinelli and Chanda VanderHart on 12 August 2024.</p> <p>Edited by Bill Lloyd and curated by Kathleen Kelly and Chanda VanderHart in connection with the hybrid publication Accompaniment in America (Routledge 2025).</p>
SNSF Spark project "Sonic Imagination" – Video documentation of on-site scenarios and interview excerpts
<p>We aimed to investigate the hypothesis that virtual sound sources in audio augmented environments are particularly suitable for triggering and directing imaginations within human inner perception. Our hypothesis was that the binaural listening to imaginary entities at the place of recording (so to speak 'in-situ') enhances the imagination in a special way, since sound as a non-visual medium favours the creation of images in human inner perception. We narrowed down our research question especially in regards to our practical experimentations to possible applications in areas that rely on the guided creation of individual or intersubjective imaginations, such as urban planning and scenario development, certain forms of trauma therapy, as well as audiovisual art and fiction.</p> <p>Further information: </p> <p><a href="https://www.ludwigzeller.net/projects/sonic-imagination/">https://www.ludwigzeller.net/projects/sonic-imagination/</a></p> <p><a href="https://p3.snf.ch/project-195868">https://p3.snf.ch/project-195868</a></p> <p> </p>
metanovas_interview
<p>Interview sample data for Metanovas Biotech. Data comes from ChEMBL</p>
mock interview with caretaker for ABA based pediatric feeding therapy
<p>cover all the basis: variety, volume, reinforcers, termination of meals, meal location, feeder, self or nonself feeder, texture, medical background... </p>
mock parental/ caregiver interview for pediatric feeding intake
<p>This is a mock interview. It covers most of the basics. Good to conduct this type of interview prior to home baseline and assessment. </p>
Interview Data on Challenges in big data based communication amid C19
<p><strong>Transcriptions of Interview Data that follows the Semi-Structured Interview Guide</strong></p> <p>Introduction</p> <p>Prior to beginning the interview, the research participant is given the option to accept or decline the interview being recorded. The interviewers then explained that the interview is entirely confidential and any references to company names, colleague names, or product names will be redacted from the transcripts and kept anonymous. The research participant’s name will not be used or recorded in the transcript or in the final manuscript. </p> <p>Background</p> <ol> <li> <p>Can you tell us about your education and professional background?</p> </li> </ol> <p>Current role and responsibilities</p> <ol> <li> <p>What is your current role/position? </p> </li> <li> <p>What industry is your company part of?</p> </li> <li> <p>What department are you part of? </p> </li> <li> <p>What area of the business do you support? </p> </li> <li> <p>What types of communications are you creating (e.g. communications channels, deliverables, platforms, etc.)?</p> </li> <li> <p>Are you utilizing RPA, AI, or data visualizations tools to communicate data? If so, how? </p> </li> <li> <p>Who are your stakeholders (who is the audience)?</p> </li> </ol> <p>Data and communications</p> <ol> <li> <p>When communicating data, what are the communication objectives/goals?</p> <ol> <li> <p>What communications problems are seeking to solve?</p> </li> </ol> </li> <li> <p>What type of data do you use in your role? </p> </li> <li> <p>How do you determine which datasets to use and communicate? </p> <ol> <li> <p>How do you assess the datasets for variety, volume, velocity, veracity?</p> </li> </ol> </li> <li> <p>How do you use it? (To describe, predict, diagnose, or make recommendations?)</p> </li> <li> <p>What has been the outcome or impact of using data in communications?</p> </li> <li> <p>How do you measure the impact of your communications?</p> </li> <li> <p>What are the challenges in communicating data?</p> </li> <li> <p>Do you use these communications across regions and international markets?</p> <ol> <li> <p>What are the challenges in communicating data across regions and international markets?</p> </li> <li> <p>What adjustments are required or what factors are taken into consideration when communicating data across countries? </p> </li> </ol> </li> <li> <p>Are these communications shared or utilized across business units, functions, and departments?</p> </li> </ol> <p>Conclusion </p> <ol> <li> <p>What value do your communications add to achieving business objectives? </p> </li> </ol>
Locating a National Collection - Schools survey and interview
<p>Questions posed as part of a survey of schools (teachers and pupils) conducted by Locating a National Collection and funded by the AHRC.</p> <p>The survey consisted of a series of questions to be completed anonymously online via Google Forms by teachers and pupils in response to an invitation on the Historical Association website. The survey was intended to take around around 15 minutes. The survey aimed to investigate attitudes and behaviours in two areas: history/cultural heritage and digital technologies, with a clear focus on location and eliciting responses to both class room and out of school behaviours. Teachers were invited to participate in a follow-up interview posing more indepth questions about engagement with heritage in teaching, use of sources, use of technology and ways of improving accessibility for schools and their understanding of history. </p> <p>The research has been led by Historic Royal Palaces in collaboration with the British Library and the National Trust.</p> <p> </p>
What do we mean by "data" in the arts and humanities? Interview transcripts (University of Bologna, FICLIT) and qualitative data coding
<p>This dataset contains the anonymised transcripts of the interviews conducted between November and December 2021 at the department of Classical Philology and Italian Studies (FICLIT) at the University of Bologna. It further includes the qualitative data analysis of the interviews, carried out using a grounded theory approach and the open source software QualCoder version 2.9.</p>
Replication Package - How Do Requirements Evolve During Elicitation? An Empirical Study Combining Interviews and App Store Analysis
<p>This is the replication package for the paper titled "How Do Requirements Evolve During</p> <p>Elicitation? An Empirical Study Combining Interviews and App Store Analysis", by Alessio Ferrari, Paola Spoletini and Sourav Debnath.</p> <p> </p> <p>The package contains the following folders and files. </p> <p> </p> <p>**<strong>/Experiment Material</strong>**</p> <p>This folder contains the material used for the experiment, and provided to the participants.</p> <p>In particular, it includes the following files:</p> <p> </p> <p>- Happy CampingTM_briefdescription.pdf/docx: brief description of the product for which requirements need to be elicited</p> <p>- Hw_description.pdf/docx: desciption of the tasks to be performed by the participants</p> <p>- Modeling_Intro_Slides.pdf: introductory slides to modelling for requirements engineering</p> <p>- Self-assessment Questionnaire.pdf: first questionnaire to self-assess the mistakes, from the SaPeer method (https://doi.org/10.1007/s00766-020-00334-0) </p> <p>- Self-assessment Questionnaire (Second Interview).pdf: second questionnare to self-assess the mistakes, from the Sapeer method</p> <p> </p> <p>**<strong>/R-analysis</strong>**</p> <p> </p> <p>This is a folder containing all the R implementations of the the statistical tests included in the paper, together with the source .csv file used to produce the results. Each R file has the same title as the associated .csv file. The titles of the files reflect the RQs as they appear in the paper. The association between R files and Tables in the paper is as follows:</p> <p> </p> <p>- RQ1-1-analyse-story-rates.R: Tabe 1, user story rates </p> <p>- RQ1-1-analyse-role-rates.R: Table 1, role rates</p> <p>- RQ1-2-analyse-story-category-phase-1.R: Table 3, user story category rates in phase 1 compared to original rates</p> <p>- RQ1-2-analyse-role-category-phase-1.R: Table 5, role category rates in phase 1 compared to original rates</p> <p>- RQ2.1-analysis-app-store-rates-phase-2.R: Table 8, user story and role rates in phase 2</p> <p>- RQ2.2-analysis-percent-three-CAT-groups-ph1-ph2.R: Table 9, comparison of the categories of user stories in phase 1 and 2</p> <p>- RQ2.2-analysis-percent-two-CAT-roles-ph1-ph2.R: Table 10, comparison of the categories of roles in phase 1 and 2. </p> <p> </p> <p>The .csv files used for statistical tests are also used to produce boxplots. The association betwee boxplot figures and files is as follows. </p> <p> </p> <p>- RQ1-1-story-rates.csv: Figure 4 </p> <p>- RQ1-1-role-rates.csv: Figure 5</p> <p>- RQ1-2-categories-phase-1.csv: Figure 8</p> <p>- RQ1-2-role-category-phase-1.csv: Figure 9</p> <p>- RQ2-1-user-story-and-roles-phase-2.csv: Figure 13</p> <p>- RQ2.2-percent-three-CAT-groups-ph1-ph2.csv: Figure 14</p> <p>- RQ2.2-percent-two-CAT-roles-ph1-ph2.csv: Figure 17</p> <p>- IMG-only-RQ2.2-us-category-comparison-ph1-ph2.csv: Figure 15</p> <p>- IMG-only-RQ2.2-frequent-roles.csv: Figure 18</p> <p> </p> <p>NOTE: The last two .csv files do not have an associated statistical tests, but are used solely to produce boxplots.</p> <p> </p> <p>**<strong>/Data-Analysis</strong>**</p> <p> </p> <p>This folder contains all the data used to answer the research questions. </p> <p> </p> <p>**<strong>RQ1.xlsx</strong>**: includes all the data associated to RQ1 subquestions, two tabs for each subquestion (one for user stories and one for roles). The names of the tabs are self-explanatory of their content.</p> <p> </p> <p>**<strong>RQ2.1.xlsx</strong>**: includes all the data for the RQ1.1 subquestion. Specifically, it includes the following tabs:</p> <p> </p> <p>* Data Source-US-category: for each category of user story, and for each analyst, there are two lines. </p> <p>The first one reports the number of user stories in that category for phase 1, and the second one reports the</p> <p>number of user stories in that category for phase 2, considering the specific analyst. </p> <p> </p> <p>* Data Source-role: for each category of role, and for each analyst, there are two lines. </p> <p>The first one reports the number of user stories in that role for phase 1, and the second one reports the</p> <p>number of user stories in that role for phase 2, considering the specific analyst. </p> <p> </p> <p>* RQ2.1 rates: reports the final rates for RQ2.1. </p> <p>NOTE: The other tabs are used to support the computation of the final rates.</p> <p> </p> <p>**<strong>RQ2.2.xlsx</strong>**: includes all the data for the RQ2.2 subquestion. Specifically, it includes the following tabs:</p> <p> </p> <p>* Data Source-US-category: same as RQ2.1.xlsx</p> <p> </p> <p>* Data Source-role: same as RQ2.1.xlsx</p> <p> </p> <p>* RQ2.2-category-group: comparison between groups of categories in the different phases, used to produce Figure 14</p> <p> </p> <p>* RQ2.2-role-group: comparison between role groups in the different phases, used to produce Figure 17</p> <p> </p> <p>* RQ2.2-specific-roles-diff: difference between specific roles, used to produce Figure 18</p> <p> </p> <p>**<strong>NOTE:</strong>** the other tabs are used to support the computation of the values reported in the tabs above. </p> <p> </p> <p>**<strong>RQ2.2-single-US-category.xlsx</strong>**: includes the data for the RQ2.2 subquestion associated to single categories of user stories.</p> <p>A separate tab is used given the complexity of the computations. </p> <p> </p> <p>* Data Source-US-category: same as RQ2.1.xlsx</p> <p> </p> <p>* Totals: total number of user stories for each analyst in phase 1 and phase 2</p> <p> </p> <p>* Results-Rate-Comparison: difference between rates of user stories in phase 1 and phase 2, used to produce the file</p> <p>"img/IMG-only-RQ2.2-us-category-comparison-ph1-ph2.csv", which is in turn used to produce Figure 15</p> <p> </p> <p>* Results-Analysts: number of analysts using each novel category produced in phase 2, used to produce Figure 16.</p> <p>NOTE: the other tabs are used to support the computation of the values reported in the tabs above. </p> <p> </p> <p>**<strong>RQ2.3.xlsx</strong>**: includes the data for the RQ2.3 subquestion. Specifically, it includes the following tabs:</p> <p> </p> <p>* Data Source-US-category: same as RQ2.1.xlsx</p> <p> </p> <p>* Data Source-role: same as RQ2.1.xlsx</p> <p> </p> <p>* RQ2.3-categories: novel categories produced in phase 2, used to produce Figure 19</p> <p> </p> <p>* RQ2-3-most-frequent-categories: most frequent novel categories</p> <p> </p> <p>**<strong>/Raw-Data-Phase-I</strong>**</p> <p>The folder contains one Excel file for each analyst, s1.xlsx...s30.xlsx, plus the file of the original user stories with annotations (original-us.xlsx). Each file contains two tabs:</p> <p> </p> <p>- Evaluation: includes the annotation of the user stories as existing user story in the original categories (annotated with "E"), novel user story in a certain category (refinement, annotated with "N"), and novel user story in novel category (Name of the category in column "New Feature"). **<strong>NOTE 1:</strong>** It should be noticed that in the paper the case "refinement" is said to be annotated with "R" (instead of "N", as in the files) to make the paper clearer and easy to read. </p> <p> </p> <p>- Roles: roles used in the user stories, and count of the user stories belonging to a certain role.</p> <p> </p> <p>**<strong>/Raw-Data-Phaes-II</strong>**</p> <p>The folder contains one Excel file for each analyst, s1.xlsx...s30.xlsx. Each file contains two tabs:</p> <p> </p> <p>- Analysis: includes the annotation of the user stories as belonging to existing original </p> <p>category (X), or to categories introduced after interviews, or to categories introduced </p> <p>after app store inspired elicitation (name of category in "Cat. Created in PH1"), or to </p> <p>entirely novel categories (name of category in "New Category").</p> <p> </p> <p>- Roles: roles used in the user stories, and count of the user stories belonging to a certain role.</p> <p> </p> <p>**<strong>/Figures</strong>**</p> <p> </p> <p>This folder includes the figures reported in the paper. The boxplots are generated from the </p> <p>data using the tool http://shiny.chemgrid.org/boxplotr/. The histograms and other plots are </p> <p>produced with Excel, and are also reported in the excel files listed above. </p>
LoGov Poland Interview Report n°4
<p>The interviews have been realised in the framework of the H2020-MSCA-RISE-2018 project “LoGov - Local Government and the Changing Urban-Rural Interplay” as part of the implementation phase of the project. The interviews have been conducted with experts in the field of public administration, public law and political science, both researchers and practitioners, with the aim of widening the scope of the Country Report on Poland. To access the full transcription of this interview, the other interview reports on Poland, and to receive more information about the project, please visit: https://www.logov-rise.eu/. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 823961.</p>
Pre-walk interview 1 (belongs to: Ille & Salah 2022, Walking on fire)
<p>Summary of a pre-walk interview in frame of research on date palm fires in Sudan's Northern State. Translated from original Sudanese Arabic by author. Georeference: N20° 45.441' E30° 19.171'.</p>
Pre-walk interview 2 (belongs to: Ille & Salah 2022, Walking on fire)
<p>Summary of a pre-walk interview in frame of research on date palm fires in Sudan's Northern State.</p>
Open Access Interviews - Professor Arunachalam
<p>An interview during Open Access Week 2011 with Subbiah Arunachalam, was conducted by Tom Dane.</p>
FUR4Sustain video - Interview to Dr Martin Ocepek fromHelios 2021
<p>Interview to Dr Martin Ocepek from Helios. A great perspective on furanics for coattings.</p>
AFFIRMO - the interviews: Marco Proietti
<p><span>Get to know the people behind the AFFIRMO project with the series "AFFIRMO - the Interviews" . AFFIRMO has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 899871 Find out more on our website: </span><span><a href="https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbjNNeUtPYnlKTGx4LXB5QzBhNUpRRXA3VklIQXxBQ3Jtc0tsbGE4UVFPeG8ybjdKWkdCejA5UDZUUWRSQnF2MlFFUHo1YmhIUlZ3MEI4YUJWTVBTeFBtaDN3cUZ2U3pGRnMyZDJzZFBveTRUSmpwVm8xMmlnVWwtaS1OWFZTbkczU0hGcG0yblVRQzRPMV8xMEdTUQ&q=https%3A%2F%2Faffirmo.eu%2F&v=MmmTBFvHD7A" target="_blank" rel="nofollow noopener">https://affirmo.eu/</a></span></p>
AFFIRMO - the interviews: Cheima Amrouch
<p><span>Get to know Cheima Amrouch PhD student at Ghent University. Get to know the people behind the AFFIRMO project with the series "AFFIRMO - the Interviews". AFFIRMO has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 899871 Find out more on our website: </span><span><a href="https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqa0ppNHNhYjFWSWJEaFdyQk1UVTY1OXBNUmV4UXxBQ3Jtc0tuVlFURmM4X3BUX2M1RjdFNEJORERzdjZuZHA2d1pSdmlhM1J1NVhFY3k4MW1FZDJJbEdrdl81X3lfTWxoak5fT1d6S1p5WFByaFBMOWRuNXZaLXB5Wk5wRGpPUUdhWVlsc1loTHpiZWlaXzJkdm5STQ&q=https%3A%2F%2Faffirmo.eu%2F&v=VkUIop4Zb7k" target="_blank" rel="nofollow noopener">https://affirmo.eu/</a></span></p>
AFFIRMO - the interviews: Leo Donato Giuseppe
<p><span>Get to know Donato Giuseppe LEO from the University of Liverpool - Department of Cardiovascular and Metabolic Medicine. Get to know the people behind the AFFIRMO project with the series "AFFIRMO - the Interviews". AFFIRMO has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 899871 Find out more on our website: </span><span><a href="https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbkZHS2QyZDhqTUNtdVcxUllFR2FRZHNwSmo2Z3xBQ3Jtc0tucFpHXzhRZ0xIWFZwa3lKeTF5WWYwTzNuXzZQenFQbDBBMlJkSV9GdDdXME55dDZQelhna1NlUm5nNndkMGVTWlpqYXRHekZSa3FCNEdBU25GX2ZnRzA2MWxidmp4NkxKb2JsNkdTTzdPRlhfS0lhNA&q=https%3A%2F%2Faffirmo.eu%2F&v=U_SBwXaBHFU" target="_blank" rel="nofollow noopener">https://affirmo.eu/</a></span></p>
AFFIRMO - the interviews: Guendalina Graffigna
<p><span>Guendalina Graffigna is a Full Professor in Consumer Health Psychology at Università Cattolica del Sacro Cuore. Get to know the people behind the AFFIRMO project with the series "AFFIRMO - the Interviews" . AFFIRMO has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 899871 Find out more on our website: </span><span><a href="https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbVFvUGZ4cjhVa2JLVGNnMXd2akd3VVlyM3VDZ3xBQ3Jtc0trdTZ5UlFLSDFENERpbWtaMjdYbFBUNXhfay1oM2R1WURSZUU2V3lSS0had1VHU3VzOHBQMHA1MnZmRl9XZHJYenNnRmhnNTZXQnhkMGFFQjFFemYtRmJ6MllCbnctOGNtOWxYUmd3N3JaTWxuQnJEMA&q=https%3A%2F%2Faffirmo.eu%2F&v=ixdaMfsjxF4" target="_blank" rel="nofollow noopener">https://affirmo.eu/</a></span></p>
AFFIRMO - the interviews: Caterina Bosio
<p><span>Caterina Bosio is a Project Manager at EnageMinds HUB, a scientific health engagement research center founded at Università Cattolica del Sacro Cuore. Get to know the people behind the AFFIRMO project with the series "AFFIRMO - the Interviews" . AFFIRMO has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 899871 Find out more on our website: </span><span><a href="https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbUI1SUpLS1k0cGRnQ3l5WktUbHNrcmRYVkllUXxBQ3Jtc0tsMHVwUlQzeTdGZjdNZUNQVkh6UWdjM2dpUmIzOWZFWnM1TlluR1hBSlp6VFBTQ3Q2OE5CWlNSM2Q5T2JjQldaXzJBZlRXeEhCOTZ4ekR2X2FIUUo0ZWo0bU9iWXJiWWExajdnRTc1MXRtRS1ray12MA&q=https%3A%2F%2Faffirmo.eu%2F&v=Em3AFhE1TgY" target="_blank" rel="nofollow noopener">https://affirmo.eu/</a></span></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.