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242 results for “distributed systems”
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
Emergence of structures from parasitic species in a spatially distributed molecular system
Open the record for dataset details and reuse information.
Data from: microCT-based phenomics in the zebrafish skeleton reveals virtues of deep phenotyping in a distributed organ system
Open the record for dataset details and reuse information.
Figure 1 from: Bayçelebi E (2020) Distribution and diversity of fish from Seyhan, Ceyhan and Orontes river systems. Zoosystematics and Evolution 96(2): 747-767. https://doi.org/10.3897/zse.96.55837
Figure 1 Map of the northeastern Mediterranean Sea Basin of Turkey and Syria with sampling points.
Monitoring Distributed Systems under Partial Synchrony (video)
Full video presentation of the paper: Monitoring Distributed Systems under Partial Synchrony.<br><br>Appears in Session 6 of the 24th International Conference on Principles of Distributed Systems OPODIS 2020<br><a href="https://opodis2020.unistra.fr">https://opodis2020.unistra.fr</a>
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 7 from: Bogutskaya NG, Zupančič P, Jelić D, Diripasko OA, Naseka AM (2017) Description of a new species of Alburnus Rafinesque, 1820 (Actinopterygii, Cyprinidae, Leuciscinae) from the Kolpa River in the Sava River system (upper Danube drainage), with remarks on the geographical distribution of shemayas in the Danube. ZooKeys 688: 81-110. https://doi.org/10.3897/zookeys.688.11261
Figure 7 - Alburnus mento NMW 55629, general appearance and radiograph, Kremsmünster, 144 mm SL.
Data set for "Novel surrogate measures for improving water distribution systems' resilience via pipe diameter uniformity enhancement"
<p>This dataset contains the optimization results using resilience surrogate measures in four chosen cases (i.e., HAN, FOS, PES, MOD). It also includes mechanical reliability calculation results of optimized network layouts obtained by the surrogate measures.</p>
Data from: The pollination system of the widely distributed mammal-pollinated Mucuna macrocarpa (Fabaceae) in the tropics
Although the pollinators of some plant species differ across regions, only a few mammal-pollinated plant species have regional pollinator differences in Asia. Mucuna macrocarpa is pollinated by squirrels, flying foxes, and macaques in subtropical and temperate islands. In this study, the pollination system of M. macrocarpa was identified in tropical Asia, where the genus originally diversified. This species requires "explosive opening" of the flower, where the wing petals must be pressed down and the banner petal pushed upward to fully expose the stamens and pistil. A bagging experiment showed that fruits did not develop in inflorescences (n = 66) with unopened flowers, whereas fruits developed in 68.7% of inflorescences (n = 131) with opened flowers. This indicated that the explosive opening is needed for the species to reproduce. Four potential pollinator mammals were identified by a video camera-trap survey, and more than 60% of monitored inflorescences (n = 138) were opened by two diurnal squirrels (Callosciurus caniceps and C. finlaysonii), even though more than 10 mammal species visited flowers. Nectar was surrounded by the calyx, and the volume and sugar concentration of nectar did not change during the day. This nectar secretion pattern is similar to those reported by previous studies in other regions. These results showed that the main pollinators of M. macrocarpa in the tropics are squirrels. However, the species' nectar secretion pattern is not specifically adapted to this particular pollinator. Pollinators of M. macrocarpa differ throughout the distribution range based on the fauna present, but there might not have been no distinctive changes in the attractive traits that accompanied these changes in pollinators.
Figure 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
Figure 4 A PID services model with the essential components in place.
Data for the paper: "Folding a Cluster containing a Distributed File-System"
<p>Associated paper: https://hal.science/hal-04038000</p><p>The repository containing the analysis scripts is available <a href="https://archive.softwareheritage.org/swh:1:dir:7b37ae5308065c18081acae7fac97d5028492948;origin=https://gitlab.inria.fr/nixos-compose/hpc-io/articles/folding;visit=swh:1:snp:12def87049b0c7d551b704428f96b2dc9aa39ed7;anchor=swh:1:rev:320df486b8ff44eb95610bf591cbea30948399f0">here</a></p><ul><li><a href=" https://archive.softwareheritage.org/swh:1:dir:882f068849839146a5fd0eb0c56493b64aaa91ec;origin=https://gitlab.inria.fr/nixos-compose/hpc-io/nfs;visit=swh:1:snp:9ed7f3abdd6c00f8573a7fb9ab29fac0e2c1a38c;anchor=swh:1:rev:fd0a1c51b01a9533f870cee38d51f223d45eb0ac">NFS repo</a></li><li><a href="https://archive.softwareheritage.org/swh:1:dir:8f05ae8165fc653aeab06b96039aef7972f4bece;origin=https://gitlab.inria.fr/nixos-compose/hpc-io/orangefs;visit=swh:1:snp:6a5f80f4ab7ad9411833f91397d901dc84588ba8;anchor=swh:1:rev:9d5c43ad846036114c2edabe024ed1640b2011f7">OrangeFS repo</a></li></ul>
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.