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Dataset results
6 results for “information specialists”
Think-aloud tests with information specialists of ai-systems Iris.ai and Yewno (Danish)
<p>This dataset contains the nine think-aloud tests conducted in April-June 2021. </p> <p>Think-aloud tests were designed to test the extent an academic search could be conducted in the two AI-powered search systems, Iris.ai (https://Iris.ai/) and Yewno Discover (https://www.yewno.com/discover). Pilot tests and validation tests were undertaken with two independent reviewers in March 2021. The validity tests were based on the principles outlined in Kim 2009, testing the content, face and construct validity of the test instrument (appendix 1). Consequently, the grammar and consistency of the language were improved and questions were reframed before the final think aloud tests were conducted in April-June 2021.</p> <p> </p> <p>Ten information specialists were invited to take part in the tests. One test person from the Yewno tests dropped out of the study, resulting in an overall drop-out rate of 10%. Accordingly, five think-aloud tests in Iris.ai and four in Yewno were held at the university libraries in Aarhus and Copenhagen.</p> <p>Two testers ran each test. One conducted the dialogue and guided the test person through the tasks set in the think-aloud test. The second, noted down the test persons behavior, humour and comments. All tests were recorded using Zoom, both audio, and screen were recorded as well as the test persons behaviour was observed. The recordings were saved to Edumedia for the duration of the project and destroyed thereafter. </p>
Librarians and information specialists as methodological peer-reviewers: a case-study of the International Journal of Health Governance. Datasets
<p>Objectives of this study were to analyze the impact of including librarians and information specialist as methodological peer-reviewers, because they can enhance methodologies in evidence synthesis. We sought to determine if and how librarians’ comments differed from subject peer-reviewers’; whether there were differences in the implementation of their recommendations; how this impacted editorial decision-making, and the perceived utility of librarian peer review by librarians and authors. We used a mixed method approach, conducting a qualitative analysis of reviewer reports, author replies and editors’ decisions of submissions to the International Journal of Health Governance. Our content analysis categorized 16 thematic areas so methodological and subject peer-reviewers’ comments, decisions and rejection rates could be compared. Categories were based on the standard areas covered in peer-review (e.g., title, originality, etc.) as well as additional in-depth categories relating to the methodology (e.g., search strategy, reporting guidelines, etc.). We developed and used criteria to judge reviewers’ perspectives and code their comments. Methodological peer-reviewers assessed 13 evidence synthesis manuscripts submitted between September 2020 and March 2023. 55 reviewer reports were collected: 25 from methodological peer-reviewers, 30 from subject peer-reviewers.</p>
Bringing Back the Manchester Argus Coenonympha tullia ssp. davus (Fabricius 1777): Quantifying the habitat resource requirements to inform the successful reintroduction of a specialist peatland butterfly
<p>2021-30 has been designated the UN decade of ecosystem restoration. A landscape scale peatland restoration project is being undertaken on Chat Moss, Greater Manchester, UK, with conservation translocations an important component of this work. The Manchester Argus Coenonympha tullia ssp. davus, a specialist butterfly of lowland raised bogs in the northwest of England, UK is under threat due to severe habitat loss and degradation. A species reintroduction was planned for spring 2020. </p> <p>This study aimed to quantify the resource thresholds for C. tullia, in order to assess potential risks for the project. Thirteen peatland habitat patches with either recent historic or current C. tullia populations were surveyed for biotic and abiotic factors based on previous qualitative research on the species' requirements. </p> <p>Percentage cover of two habitat resources were found to be the strongest predictors in models of C. tullia presence: cross-leaved heath Erica tetralix and hair's-tail cotton-sedge Eriophorum vaginatum. </p> <p>Critical inflection points on logistic regression curves were used to make quantitative estimates of the minimum requirement of each resource for population survival and the near-optimum abundance of each resource. </p> <p>The results of this study improve our understanding of C. tullia's ecology and the restoration of peatlands for its reintroduction. Additionally, the method has wider utility for the quantitative assessment of habitat readiness before attempting species reintroductions.</p>
Bringing Back the Manchester Argus Coenonympha tullia ssp. davus (Fabricius 1777): Quantifying the habitat resource requirements to inform the successful reintroduction of a specialist peatland butterfly
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Determining oviposition preferences to inform population reinforcement of the specialist chequered blue butterfly (Scolitantides orion)
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PROBLEMS OF PROFESSIONAL COMPETENCE DEVELOPMENT OF INFORMATION SECURITY OF FUTURE MILITARY SPECIALISTS AND ITS CURRENT STATE
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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.