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81 results for “interview data”
Data from: Assessing changes in distribution of the endangered snow leopard Panthera uncia and its wild prey over 2 decades in the Indian Himalaya through interview-based occupancy surveys
Understanding species distributions, patterns of change and threats can form the basis for assessing the conservation status of elusive species that are difficult to survey. The snow leopard Panthera uncia is the top predator of the Central and South Asian mountains. Knowledge of the distribution and status of this elusive felid and its wild prey is limited. Using recall-based key-informant interviews we estimated site use by snow leopards and their primary wild prey, blue sheep Pseudois nayaur and Asiatic ibex Capra sibirica, across two time periods (past: 1985–1992; recent: 2008–2012) in the state of Himachal Pradesh, India. We also conducted a threat assessment for the recent period. Probability of site use was similar across the two time periods for snow leopards, blue sheep and ibex, whereas for wild prey (blue sheep and ibex combined) overall there was an 8% contraction. Although our surveys were conducted in areas within the presumed distribution range of the snow leopard, we found snow leopards were using only 75% of the area (14,616 km2). Blue sheep and ibex had distinct distribution ranges. Snow leopards and their wild prey were not restricted to protected areas, which encompassed only 17% of their distribution within the study area. Migratory livestock grazing was pervasive across ibex distribution range and was the most widespread and serious conservation threat. Depredation by free-ranging dogs, and illegal hunting and wildlife trade were the other severe threats. Our results underscore the importance of community-based, landscape-scale conservation approaches and caution against reliance on geophysical and opinion-based distribution maps that have been used to estimate national and global snow leopard ranges.
Interview Data
<h1>Insights on the dissemination of scientific results for software engineering practitioners - LCLEI'24 submission</h1> <p> </p> <p>In the file "<span>Transcrição das entrevistas.xlsx</span>", you will find the transcripts of all conducted interviews. Each interview was transcribed on a separate tab of the Excel spreadsheet. We used the Cockatoo tool to perform the transcriptions, ensuring accuracy and minimizing writing errors.</p> <p>In the file "<span>Codificação das entrevistas.xlsx</span>", you will have access to all the coding generated from the interviews. We used the QDA Miner software in its free version to perform this coding.</p> <p> </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>
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>
Interview Data: Bioinformatician role, Melbourne Bioinformatics, Question 4
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Interview Data: Bioinformatician role, Melbourne Bioinformatics
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Interview data contributions of social enterprises in South Africa
<p>Data Set. Interviewees for contributions of social enterprises manuscript. </p>
Anonymized Researcher Interview Data - from the Raising the Profile of the NCSU Libraries Research Support Strategies & Engagement project
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Data from: Assessing changes in distribution of the endangered snow leopard Panthera uncia and its wild prey over 2 decades in the Indian Himalaya through interview-based occupancy surveys
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Data from: Robust inference on large-scale species habitat use with interview data: the status of jaguars outside protected areas in Central America
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[DATA_SCIENCE] Interviews: The Catalogue of Somatic Mutations in Cancer (COSMIC)
<p>This is a set of interview transcripts executed by Niccolò Tempini between May 2016 and July 2017, as part of the ERC project "The Epistemology of Data-Intensive Science", and in the context of a case study of COSMIC. Please read the "Notes on transcript editing" document for further information.</p> <p>Papers that specifically make use of these interviews and have been published as of February 2021:</p> <ul> <li> <p>Tempini, N., 2020. Data curation-research: practices of data standardization and exploration in a precision medicine database. New Genetics and Society. <a href="https://doi.org/10.1080/14636778.2020.1853513">https://doi.org/10.1080/14636778.2020.1853513</a></p> </li> <li> <p>Tempini, N., Leonelli, S., 2021. Actionable Data for Precision Oncology: Framing Trustworthy Evidence for Exploratory Research and Clinical Diagnostics. Social Science & Medicine. <a href="https://doi.org/10.1016/j.socscimed.2021.113760">https://doi.org/10.1016/j.socscimed.2021.113760</a></p> </li> </ul> <p>The transcripts document COSMIC researchers' experience of infrastructure development and data curation and re-use practices. 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.<br> 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.</p>
Data from: The personal and social experiences of community-dwelling younger adults after stroke in Australia: a qualitative interview study
Objectives: To examine the personal and social experiences of younger adults after stroke. Design: Qualitative study design involving in-depth semi-structured interviews and rigorous qualitative descriptive analysis informed by social constructionism. Participants: Nineteen young stroke survivors aged 18 to 55 at the time of their first-ever stroke. Setting: Participants were recruited from urban and rural settings across Australia. Interviews took place in a clinic room of the Florey Institute of Neuroscience and Mental Health (Melbourne, Australia), over an online conference platform or by telephone. Results: Four main themes emerged from the discourses: (1) psycho-emotional experiences after young stroke; (2) losing pre-stroke life construct and relationships; (3) recovering and adapting after young stroke; and (4) invalidated by the old-age, physical concept of stroke. While these themes ran through the narratives of all participants, data analysis also drew out interesting variation between individual experiences. Conclusions: For many younger adults, stroke is an unexpected and devastating life event that profoundly diverts their biography and presents complex and continued challenges to fulfilling age-normative roles. While adaptation, resilience and post-traumatic growth are common, this study suggests that more bespoke support is needed for younger adults after stroke. Increasing public awareness of young stroke is also important, as is increased research attention to this problem.
"Narrative Interview" intervention in Oncology: Qualitative and Quantitative Data
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Data from interviewed participants - Paper ECGBL 2024
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[DATA_SCIENCE] Interviews: The Medical and Environmental Data Mash-up Infrastructure (MEDMI)
<p>This is a set of interview transcripts executed by Niccolò Tempini between March and October 2016, as part of the ERC project "The Epistemology of Data-Intensive Science", and in the context of a case study of MEDMI. Please read the "Notes on transcript editing" document for further information.</p> <p>Three papers or chapters that specifically make use of these interviews have been published as of 2020:</p> <ul> <li>Tempini, N., Leonelli, S., 2018. Concealment and discovery: The role of information security in biomedical data re-use. Soc Stud Sci 48, 663–690. <a href="https://doi.org/10.1177/0306312718804875">https://doi.org/10.1177/0306312718804875</a></li> <li>Leonelli, S., Tempini, N., 2018. Where health and environment meet: the use of invariant parameters in big data analysis. Synthese 1–20. <a href="https://doi.org/10.1007/s11229-018-1844-2">https://doi.org/10.1007/s11229-018-1844-2</a></li> <li>Tempini, N. 2020. The Reuse of Digital Computer Data: Transformation, Recombination and Generation of <em>Data Mixes</em> in Big Data Science. In: Leonelli S., Tempini N. (eds) Data Journeys in the Sciences. Springer, Cham. <a href="https://doi.org/10.1007/978-3-030-37177-7_13">https://doi.org/10.1007/978-3-030-37177-7_13</a></li> </ul> <p>The transcripts document MEDMI researchers' experience of infrastructure development and data curation and re-use practices. 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.<br> 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.</p>
Data from: The personal and social experiences of community-dwelling younger adults after stroke in Australia: a qualitative interview study
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Data collected from interviews with PMs' about the developers' work
<p>We interview professionals who work with project management in the software industry to collect their opinion about the developers' work measurement.</p>
Perceived value interviews and socio-economic survey data in seven villages in rural Uganda
<p>Dataset (JSON and CSV files) of 119 interviews conducted between 2014 and 2015 in seven rural Ugandan villages from surveys and face-to-face interviews.</p>
Self-actualisation data_POI_and_interviews
<p>The two files include</p> <p>1) POI database pre- and post- intervention</p> <p>2) Interviews</p>
Interview data for 'Risks in the offshore wind supply chain and tendering process impacts: Insights from industry expert elicitations'
<p>Updated 3 category labels to reduce potential for confusion. (v3)</p> <p>Interview data with restored functionality of some unused data analysis methods. (v2)</p> <p>Original upload. (v1)</p>
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