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987 results for “interviews”
Interview with Germanno Teles - Google Glass Explorer
<p>A short interview conducted by the researcher, Alexander Hayes, PhD Candidate at the University of Wollongong with Germanno Teles, Google Glass Explorer regarding the phenomenon of Google Glass, a head-worn computer enabling an augmented field-of-view. This interview was conducted by the researcher whilst in the role as Professional Associate at the University of Canberra, ACT Australia. Read more about this research at <a href="https://www.alexanderhayes.com/journal/glassmeetup-symposium">https://www.alexanderhayes.com/journal/glassmeetup-symposium</a></p> <p> </p> <p>This Google Plus 'Hangouts On Air 'livestream' was first published on the researchers own YouTube channel at <a href="https://www.youtube.com/watch?v=7yx9Kz4Pqy4">https://www.youtube.com/watch?v=7yx9Kz4Pqy4</a></p>
Interview with Andy Kropa - Google Glass Explorer
<p>A short interview conducted by the researcher, Alexander Hayes, PhD Candidate at the University of Wollongong with Andy Kropa, Google Glass Explorer regarding the phenomenon of Google Glass, a head-worn computer enabling an augmented field-of-view. This interview was conducted by the researcher whilst in the role as Professional Associate at the University of Canberra, ACT Australia. Read more about this research at <a href="https://www.alexanderhayes.com/journal/glassmeetup-symposium">https://www.alexanderhayes.com/journal/glassmeetup-symposium</a></p>
Interviewees and mapping of interview questions to areas of Innovation Diffusion Theory
<p>This submission includes two files complementing the F1000Research article "Preprints and Scholarly Communication: Adoption, Practices, Drivers and Barriers" - <a href="https://doi.org/10.12688/f1000research.19619.1">https://doi.org/10.12688/f1000research.19619.1</a></p> <p>The table '<strong>Extended data</strong>' shows how interview questions for our study were built based on the features of information diffusion theory (IDT) (Rogers, 2003). It should be noted that not all interview questions were asked to all stakeholder groups based on appropriateness and time available. Some questions in the table may appear to be repeated: this is because slightly different phrasing was used based on the stakeholder interviewed.</p> <p>Legend:</p> <ul> <li>Research Funder: RF</li> <li>Research Performing Organisation: RPO</li> <li>Preprint Server: PS</li> <li>Other Service Provider: OSP</li> <li>Engaged researcher: ER</li> <li>Unengaged researcher: UR</li> </ul> <p>The table '<strong>List of interviewees</strong>' includes all stakeholders interviewed in the context of this research. More information on this study is also available in the form of a <a href="http://doi.org/10.5281/zenodo.3357727">report</a>.</p>
CF_D1 Interviews with public authorities about climate adaptation finance
<p><span>The CLIMATEFIT dataset D1 contains data </span><span>collected</span><span> as part of </span><span>WP1’s</span> <span>T</span><span>ask 1.1</span><span>: </span><span>Assess financing barriers and drivers for territories</span><span> (Leader: </span><span>Actierra</span><span>). <span>This dataset contains interview transcripts and summaries of interviews conducted by the facilitators with the 20 territories</span>. The interviews were about challenges and barriers regarding accessing climate adaptation funds and sources.</span></p> <p><span>Data that is already published in WP1’s <a href="https://climatefit-heu.eu/knowledge-center/">Deliverable 1.1: Adaptation Investment Landscape</a>, is not included in this dataset. </span></p> <p><span>More information can be found in the Readme file in this dataset.</span></p>
CF_D3 Interviews with with best practices of climate finance
<p><span>The CLIMATEFIT dataset D1 contains data </span><span>collected</span><span> as part of </span><span>WP1’s</span> <span>T</span><span>ask 1.1</span><span>: </span><span>Understand and capitalise on the good practices (M1-M10; Leader: UA</span><span>). This dataset contains interviews that were conducted with stakeholders involved in international best practices of innovative climate finance, and innovative adaptation funding and financing solutions.</span></p> <p><span>Data that is already published on the CLIMATEFIT website in WP1’s <a href="https://climatefit-heu.eu/knowledge-center/">Deliverable 1.1: Adaptation Investment Landscape</a>, is not included in this dataset.</span></p> <p><span>More information can be found in the Readme file in this dataset.</span></p>
Perception of Mixed-Reality Shopping Assistant System to develop Design Principles : Interview Transcripts (MRDP)
<p>The dataset is a collection of transcripts where 35 participants were interviewed to collect users’’ feedback and perceptions about the mixed-reality MR shopping assistant system. The interviews were a part of the research where a personal shopping assistance system based on optical see-through mixed-reality (MR ) technology was designed. Microsoft HoloLens 2 was leveraged as the archetype to realize this novel system to facilitating consumer information search and decision making. The design incorporated various shopping assistance elements (i.e., product information, reviews, recommendations, product availability, videos, a virtual cart, and an option to buy). Users can interact with these elements with gesture-based inputs to navigate through the interface.</p> <p>Derived from the qualitative feedback from the 35 participants, we proposed six design principles that aim to support future designs and developments of mixed-reality MR shopping applications for head-mounted displays in omnichannel retail: Rigor, Informativeness, Tangibility, Summary, Comparability and Holism. </p> <p> </p>
Results of interview analyses showing the code groundedness
<p>This table presents the results of interview analyses, showing the number of mentions in each Critical Digital Literacies sub-dimension from each country. These focus group interviews were conducted with teachers from the four consortium schools of the <a href="http://detectproject.eu/">DETECT project</a> in Italy, Finland, Spain and the UK in order to gain a more in-depth understanding of the teachers' particular needs in relation to critical digital literacies. 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>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>
SQA for AI. Interviews coding
<p>This dataset includes interviews with practitioners on the topic "SQA for AI Systems" with a coding procedure. </p>
[DATA_SCIENCE] Interviews Plant Phenomics, 2015
<p>Here are two transcripts from a set of interviews executed by Sabina Leonelli in the fall of 2015 as part of the ERC project "The Epistemology of Data-Intensive Science", and in the context of a case study of phenotyping practices at the National Plant Phenomics Centre in Aberystwyth and collaborators. The transcripts document researchers' experience of data curation practices. Researchers have consented to have these transcripts made available as Open Data. Other interviewees did not give consent or ended up providing sensitive information in their interviews, so those transcripts cannot be made open and are held securely by the research team in Exeter. You also find the information sheet provided to interviewees, which gives you the context for this project. Further information can be found at <a href="http://www.datastudies.eu">www.datastudies.eu</a>. The transcripts have been redacted to exclude names of people who have not given consent to participate in the study, but have otherwise been left unedited and therefore contain several colloquial expressions. A paper by Sabina Leonelli which specifically makes use of these interviews will be published in 2019 in the European Journal for Philosophy of Science, under the title “What Distinguishes Data from Models?”. Freely accessible preprint here: <a href="http://philsci-archive.pitt.edu/id/eprint/15485">http://philsci-archive.pitt.edu/id/eprint/15485</a> . Several related publications can be found in Open Access formats on the project website: <a href="http://www.datastudies.eu">www.datastudies.eu</a>.</p>
EUREKA WP2: Regional Interview Transcripts
ZIP file containing transcripts in English of 40 interviews conducted with farmers, foresters, advisors and other professionals across Europe by several EUREKA partners in the summer of 2020. The focus of the interviews was to discuss the (digital) information needs of potential users of the EU-FarmBook knowledge platform. This work informed the development of a set of representative 'user personas' and associated 'user journeys' to aid in the design of the EU-FarmBook. See Deliverable 2.2 for a full report of the findings.
EUREKA WP2: Regional Interview Transcripts
ZIP file containing transcripts in English of 40 interviews conducted with farmers, foresters, advisors and other professionals across Europe by several EUREKA partners in the summer of 2020. The focus of the interviews was to discuss the (digital) information needs of potential users of the EU-FarmBook knowledge platform. This work informed the development of a set of representative 'user personas' and associated 'user journeys' to aid in the design of the EU-FarmBook. See Deliverable 2.2 for a full report of the findings.
Market interview data with industrial players
<p>The data is collected based on the designed interview guide with industry stakeholders such as professional buyers. The interviews are conducted in collaboration with the project partners in Spain, Brazil, and partly in South-Africa and the USA. The data will be analyzed for the four different countries representing the four zones of the Atlantic Ocean: 1) Brazil, 2) South Africa, 3) Spain 4) USA. The data will be analyzed for the professional buyers’ awareness and (interest for) trade of low trophic species and sustainable products.</p>
Interview Transcriptions related to PhD Thesis "Degrowth at a Global Scale? Geographies of Chile's Fruit Production and Export between Extractivism and Socio-Ecological Transformation"
<p>The material is composed of transcriptions of interviews conducted for the empirical work of this PhD Thesis.</p> <p>Not all conducted interviews are included (which can be seen from the accompanying table); those not included are not available mostly due to lack of consent of interviewees or because certain interviews were not registered and only hand-written notes were taken.</p>
Experimental material of the article "An Empirical Experiment of a Usability Requirements Elicitation Method based on Interviews"
<p>Questionnaires, problems description and solution, and raw data of the paper "An Empirical Experiment of a Usability Requirements Elicitation Method based on Interviews"</p>
Interview guide from the paper "Act Against the Aggression A Preliminary Model of a Digital Platform Aimed at Cyberaggressions in the Portuguese University Environment"
<p>Interview guide used in the study "Act Against the Aggression A Preliminary Model of a Digital Platform Aimed at Cyberaggressions in the Portuguese University Environment".</p>
Interview questions
<p>Semi-structured interview questions for the research paper, Implementing AI Ethics: Making Sense of the Ethical Requirements.</p>
D2.1 - Demonstrator baseline and market characteristics report - Transcripts of interviews with a French company
<p>This is the transcript of the interviews with a French company for D2.1 "Demonstrator baseline and market characteristics report" defining the current baseline and the target/improved circular business models for two demonstrators and analyzing both demonstrators´ market characteristics and their impact on the target circular business models.</p>
biogasoutcomesmalawi: Data for 61 semi-structured interviews with biogas owners in Malawi
<p>This dataset consists of 61 semi-structured interviews with biogas owners in the Southern Region of Malawi. Interviews were conducted over multiple visits to sites over the course of a two-year period between June 2021 and October 2022.</p>
How Do ML Practitioners Perceive Explainability? An Interview Study of Practices and Challenges
<p>This repository contains supplementary materials for our interview Study.</p>
Tailored Motivational Interviewing Implementation-Effectiveness Trial in Multidisciplinary Adolescent HIV Care Settings
ClinicalTrials.gov study NCT03681912. IPD Sharing: Not stated. Countries: 1. Publications: 2.
ScienceDex guides
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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)
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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.