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115 results for “scientific research”
Figure 3 from: Hardisty AR, Addink W, Glöckler F, Güntsch A, Islam S, Weiland C (2021) A choice of persistent identifier schemes for the Distributed System of Scientific Collections (DiSSCo). Research Ideas and Outcomes 7: e67379. https://doi.org/10.3897/rio.7.e67379
Figure 3 Governance, operations, financing and architecture (GOFA) together delivering sustainability.
Figure 2 from: Hardisty AR, Addink W, Glöckler F, Güntsch A, Islam S, Weiland C (2021) A choice of persistent identifier schemes for the Distributed System of Scientific Collections (DiSSCo). Research Ideas and Outcomes 7: e67379. https://doi.org/10.3897/rio.7.e67379
Figure 2 Scoring of PID scheme optionsKey: MPA = Multi-Primary Administrator, RA = Registration Agency.
Figure 1 from: Hardisty AR, Addink W, Glöckler F, Güntsch A, Islam S, Weiland C (2021) A choice of persistent identifier schemes for the Distributed System of Scientific Collections (DiSSCo). Research Ideas and Outcomes 7: e67379. https://doi.org/10.3897/rio.7.e67379
Figure 1 Digitally transforming collections science with Digital Specimens and persistent identifiers (PID).
Supplementary material 2 from: Hardisty AR, Addink W, Glöckler F, Güntsch A, Islam S, Weiland C (2021) A choice of persistent identifier schemes for the Distributed System of Scientific Collections (DiSSCo). Research Ideas and Outcomes 7: e67379. https://doi.org/10.3897/rio.7.e67379
Estimates of numbers of PIDs needed
Supplementary material 4 from: Hardisty AR, Addink W, Glöckler F, Güntsch A, Islam S, Weiland C (2021) A choice of persistent identifier schemes for the Distributed System of Scientific Collections (DiSSCo). Research Ideas and Outcomes 7: e67379. https://doi.org/10.3897/rio.7.e67379
Dimensions appraisal of the options
Supplementary material for "How does AI assist scientific research domains?"
<p>Supplementary material for "How does AI assist scientific research domains?" </p>
Charting the edge of chaos: challenges in mapping scientific research
<p>Content</p> <p>The illusion of certainty<br> KOS problems in science<br> Fluidity of scientific vocabulary<br> Sketches towards an approach</p>
Research on the Complex Scientific Mechanisms Underlying Exercise and Health: Construction and Application of a Mechanistic Model and Public Database（CISS）
ClinicalTrials.gov study NCT06936982. IPD Sharing: NO. Countries: 1. Publications: 0.
Figure 13 from: Owen D, Livermore L, Groom Q, Hardisty A, Leegwater T, van Walsum M, Wijkamp N, Spasić I (2020) Towards a scientific workflow featuring Natural Language Processing for the digitisation of natural history collections. Research Ideas and Outcomes 6: e55789. https://doi.org/10.3897/rio.6.e55789
Figure 13 Gold standard versus NER output.
Figure 12 from: Owen D, Livermore L, Groom Q, Hardisty A, Leegwater T, van Walsum M, Wijkamp N, Spasić I (2020) Towards a scientific workflow featuring Natural Language Processing for the digitisation of natural history collections. Research Ideas and Outcomes 6: e55789. https://doi.org/10.3897/rio.6.e55789
Figure 12 An example of a specimen label.
Figure 10 from: Owen D, Livermore L, Groom Q, Hardisty A, Leegwater T, van Walsum M, Wijkamp N, Spasić I (2020) Towards a scientific workflow featuring Natural Language Processing for the digitisation of natural history collections. Research Ideas and Outcomes 6: e55789. https://doi.org/10.3897/rio.6.e55789
Figure 10 Results per field from Google Cloud Vision.
Figure 1 from: Raes N, Casino A, Goodson H, Islam S, Koureas D, Schiller EK, Schulman L, Tilley L, Robertson T (2020) White paper on the alignment and interoperability between the Distributed System of Scientific Collections (DiSSCo) and EU infrastructures - The case of the European Environment Agency (EEA). Research Ideas and Outcomes 6: e62361. https://doi.org/10.3897/rio.6.e62361
Figure 1 The DiSSCo programme with all strategically aligned projects.
Figure 6 from: Landel S, Lymer G, Pasterk M, Guiraud M, Worley K (2024) A report on recommendations for the most suitable financial contribution model for the Distributed System of Scientific Collections Research Infrastructure (DiSSCo-RI). Research Ideas and Outcomes 10: e117217. https://doi.org/10.3897/rio.10.e117217
Figure 6 Simulating inflation, between 2024 and 2040 – Basic number: 2% inflation per year.
Figure 8 from: Landel S, Lymer G, Pasterk M, Guiraud M, Worley K (2024) A report on recommendations for the most suitable financial contribution model for the Distributed System of Scientific Collections Research Infrastructure (DiSSCo-RI). Research Ideas and Outcomes 10: e117217. https://doi.org/10.3897/rio.10.e117217
Figure 8 Simulation of inflation, Model B.
Figure 7 from: Landel S, Lymer G, Pasterk M, Guiraud M, Worley K (2024) A report on recommendations for the most suitable financial contribution model for the Distributed System of Scientific Collections Research Infrastructure (DiSSCo-RI). Research Ideas and Outcomes 10: e117217. https://doi.org/10.3897/rio.10.e117217
Figure 7 Simulation of inflation, Model A.
Figure 9 from: Landel S, Lymer G, Pasterk M, Guiraud M, Worley K (2024) A report on recommendations for the most suitable financial contribution model for the Distributed System of Scientific Collections Research Infrastructure (DiSSCo-RI). Research Ideas and Outcomes 10: e117217. https://doi.org/10.3897/rio.10.e117217
Figure 9 Simulation of inflation, Model C.
Figure 1 from: Landel S, Lymer G, Pasterk M, Guiraud M, Worley K (2024) A report on recommendations for the most suitable financial contribution model for the Distributed System of Scientific Collections Research Infrastructure (DiSSCo-RI). Research Ideas and Outcomes 10: e117217. https://doi.org/10.3897/rio.10.e117217
Figure 1 DiSSCo timeline.
Figure 11 from: Landel S, Lymer G, Pasterk M, Guiraud M, Worley K (2024) A report on recommendations for the most suitable financial contribution model for the Distributed System of Scientific Collections Research Infrastructure (DiSSCo-RI). Research Ideas and Outcomes 10: e117217. https://doi.org/10.3897/rio.10.e117217
Figure 11 DiSSCo national contribution models.
Figure 2 from: Landel S, Lymer G, Pasterk M, Guiraud M, Worley K (2024) A report on recommendations for the most suitable financial contribution model for the Distributed System of Scientific Collections Research Infrastructure (DiSSCo-RI). Research Ideas and Outcomes 10: e117217. https://doi.org/10.3897/rio.10.e117217
Figure 2 DiSSCo general membership fee calculation model.
Figure 4 from: Islam S, Papale D, Vaira L, Rosati I, Peterseil J, Pichot C (2024) Navigating taxonomic complexity: A use-case report on FAIR scientific name-matching service usage in ENVRI Research Infrastructures. Research Ideas and Outcomes 10: e121871. https://doi.org/10.3897/rio.10.e121871
Figure 4 LifeWatch web service taxon match list. Screenshot captured 10 Jan 2024.
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.