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1,453 results for “Outcome research”
Figure 3 from: Petersen M, Hoffmann J, Glöckler F (2019) Access to Geosciences – Ways and Means to share and publish collection data. Research Ideas and Outcomes 5: e32987. https://doi.org/10.3897/rio.5.e32987
Figure 3 Reasons for publication of (meta)data on geoscientific collection objects (a) and not publishing particular datasets through a data portal (b). Shown is the frequency of answers per reason. Note that the y-axes are scaled differently.
Figure 2 from: Petersen M, Hoffmann J, Glöckler F (2019) Access to Geosciences – Ways and Means to share and publish collection data. Research Ideas and Outcomes 5: e32987. https://doi.org/10.3897/rio.5.e32987
Figure 2 Estimated value of cross-institutional search possibilities through data portals on geoscientific object (meta)data for different target groups. Shown is the frequency of answers for different scopes and their respective importance (see legend).
Figure 1 from: Costa da Silva R, Sufi S, Aragon Camarasa S (2019) Collaborations Workshop 2018 (CW18) Report – Culture Change, Productivity and Sustainability. Research Ideas and Outcomes 5: e30250. https://doi.org/10.3897/rio.5.e30250
Figure 1 "Such collaboration helps the work spread" slide from John Hammerley's presentation during Collaborations Workshop 2018.
Figure 4 from: Costa da Silva R, Sufi S, Aragon Camarasa S (2019) Collaborations Workshop 2018 (CW18) Report – Culture Change, Productivity and Sustainability. Research Ideas and Outcomes 5: e30250. https://doi.org/10.3897/rio.5.e30250
Figure 4 gov.uk report pipeline slide from Matthew Upson's presentation during Collaborations Workshop 2018.
Figure 3 from: Costa da Silva R, Sufi S, Aragon Camarasa S (2019) Collaborations Workshop 2018 (CW18) Report – Culture Change, Productivity and Sustainability. Research Ideas and Outcomes 5: e30250. https://doi.org/10.3897/rio.5.e30250
Figure 3 Data presentation in spreadsheets slide from Naomi Penfold's presentation during Collaborations Workshop 2018.
Figure 2 from: Costa da Silva R, Sufi S, Aragon Camarasa S (2019) Collaborations Workshop 2018 (CW18) Report – Culture Change, Productivity and Sustainability. Research Ideas and Outcomes 5: e30250. https://doi.org/10.3897/rio.5.e30250
Figure 2 WSSSPE5.1 speed blog mapped slide from Daniel S. Katz's presentation during Collaborations Workshop 2018.
Figure 2 from: Kelly-Quinn M, Bruen M, Carlsson J, Gurnell A, Jarvie H, Piggott J (2019) Managing the small stream network for improved water quality, biodiversity and ecosystem services protection (SSNet). Research Ideas and Outcomes 5: e33400. https://doi.org/10.3897/rio.5.e33400
Figure 2 Schema illustrating the eight work packages in SSNet and their linkages. Note: stakeholder engagement occurs throughout the project particularly in relation to the recommendations relating to the management of the small stream network.
Supplementary material 1 from: Petersen M, Glöckler F, Hoffmann J (2019) Harmonizing plot data with collection data. Research Ideas and Outcomes 5: e33509. https://doi.org/10.3897/rio.5.e33509
Workshop_Program_Plot_Dat
Figure 4 from: Smith R (2019) The CLUZ plugin for QGIS: designing conservation area systems and other ecological networks. Research Ideas and Outcomes 5: e33510. https://doi.org/10.3897/rio.5.e33510
Figure 4 Screenshots from QGIS showing the two Marxan outputs displayed in CLUZ. The map on the left shows the best portfolio of planning units selected by Marxan, while the map on the right shows the selection frequency score of each planning unit based on running Marxan ten times, with planning units in red being selected in every one of the ten Marxan runs.
Figure 3 from: Smith R (2019) The CLUZ plugin for QGIS: designing conservation area systems and other ecological networks. Research Ideas and Outcomes 5: e33510. https://doi.org/10.3897/rio.5.e33510
Figure 3 Screenshot of QGIS showing the planning units layer, CLUZ target table and Change Status panel. The Change Status Panel was used to change the status of the patch of planning units in the northwest of the planning region from Conserved to Earmarked. This updated the target table, which shows that adding this new patch to the protected area network would meet the target for rock faces and would contribute towards targets for another five conservation features.
Figure 1 from: Smith R (2019) The CLUZ plugin for QGIS: designing conservation area systems and other ecological networks. Research Ideas and Outcomes 5: e33510. https://doi.org/10.3897/rio.5.e33510
Figure 1 Screenshot of QGIS showing the planning units layer and CLUZ target table. The CLUZ target table provides details on all the conservation features, including the PC_target field showing the "gap" features that are currently under-represented.
Figure 1 from: Petersen M, Glöckler F, Hoffmann J (2019) Harmonizing plot data with collection data. Research Ideas and Outcomes 5: e33509. https://doi.org/10.3897/rio.5.e33509
Figure 1 First version of an application schema for plot-based data. Shown is a list of terms, their relations, and partly their cardinality important for habitat and biotope mapping (status: 30 May 2018, end of the workshop). Given is the flipchart diagram created during the workshop (see Table 1 for english translation of terms).
Figure 2 from: Smith R (2019) The CLUZ plugin for QGIS: designing conservation area systems and other ecological networks. Research Ideas and Outcomes 5: e33510. https://doi.org/10.3897/rio.5.e33510
Figure 2 Screenshots of QGIS showing on the left, a CLUZ distribution map of one of the conservation features, and on the right a map of the number of conservation features found in each planning unit.
Figure 8b from: Briz-Redón Á (2019) SpNetPrep: An R package using Shiny to facilitate spatial statistics on road networks. Research Ideas and Outcomes 5: e33521. https://doi.org/10.3897/rio.5.e33521
Figure 8b "Point Pattern Edition" features. - Information that is displayed (marks of the point pattern, if available, as defined by the user) when an event is clicked
Figure 5a from: Briz-Redón Á (2019) SpNetPrep: An R package using Shiny to facilitate spatial statistics on road networks. Research Ideas and Outcomes 5: e33521. https://doi.org/10.3897/rio.5.e33521
Figure 5a Example of use of the SimplifyLinearNetwork function. - A road network introduced as input in which there is an excess of road segments and vertex
Figure 1 from: Briz-Redón Á (2019) SpNetPrep: An R package using Shiny to facilitate spatial statistics on road networks. Research Ideas and Outcomes 5: e33521. https://doi.org/10.3897/rio.5.e33521
Figure 1 Workflow that describes all the steps that could be carried out in order to perform a spatial analysis on a point pattern that lies on a linear network. Some of these steps which lead to the final statistical analysis may be skipped but, at least, all of them should be considered. The blocks pointing the steps of the process include some of the R packages that would allow to successfully achieve each of them.
Figure 3b from: Briz-Redón Á (2019) SpNetPrep: An R package using Shiny to facilitate spatial statistics on road networks. Research Ideas and Outcomes 5: e33521. https://doi.org/10.3897/rio.5.e33521
Figure 3b "Network Edition" example of use (I). - Network resulting from clicking on "Rebuild linear network" in the situation of a
Figure 2a from: Briz-Redón Á (2019) SpNetPrep: An R package using Shiny to facilitate spatial statistics on road networks. Research Ideas and Outcomes 5: e33521. https://doi.org/10.3897/rio.5.e33521
Figure 2a "Network Edition" features. - Overview of the "Network Edition" section of the SpNetPrep application
Figure 6b from: Briz-Redón Á (2019) SpNetPrep: An R package using Shiny to facilitate spatial statistics on road networks. Research Ideas and Outcomes 5: e33521. https://doi.org/10.3897/rio.5.e33521
Figure 6b "Network Direction" features. - Manual addition of traffic flow to the network by using the options "Add flow" and "Add long flow"
Figure 3a from: Briz-Redón Á (2019) SpNetPrep: An R package using Shiny to facilitate spatial statistics on road networks. Research Ideas and Outcomes 5: e33521. https://doi.org/10.3897/rio.5.e33521
Figure 3a "Network Edition" example of use (I). - Use of the "Join vertex" (in green), "Remove edge" (in red) and "Add point" options (in green) in the SpNetPrep application
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.