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65 results for “collections digitisation”
Figure 3 from: Torralba-Burrial A, Merino-Sáinz I, Anadón A (2014) The relevance, biases, and importance of digitising opportunistic non-standardised collections: A case study in Iberian harvestmen fauna with BOS Arthropod Collection datasets (Arachnida, Opiliones). ZooKeys 404: 71-89. https://doi.org/10.3897/zookeys.404.6520
Figure 3 - Distribution of harvestmen records in the unplanned collection events. A Ischyropsalididae, Nemastomatidae and Phalangiidae B Scleromatidae and Trogulidae.
Figure 2 from: Torralba-Burrial A, Merino-Sáinz I, Anadón A (2014) The relevance, biases, and importance of digitising opportunistic non-standardised collections: A case study in Iberian harvestmen fauna with BOS Arthropod Collection datasets (Arachnida, Opiliones). ZooKeys 404: 71-89. https://doi.org/10.3897/zookeys.404.6520
Figure 2 - A diagram depicting the methodological design of this hybrid data paper. Harvestmen in the BOS Arthropod Collection (Merino-Sáinz et al. 2013c) have come from several sources: some from unplanned collection events and some from planned collections. For this hybrid data-paper, we compared the data subset of unplanned collection events with the subsets of harvestmen from planned collection events using monthly sampling (Merino-Sáinz and Anadón 2008, 2013), and the harvestmen of similar planned events in the same area (Rosa García et al. 2009a, b, 2010a, b). All of the subsets compared appear in light blue in the diagram.
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 5 from: Willemse L, Runnel V, Saarenmaa H, Casino A, Gödderz K (2020) Digitisation of private collections. Research Ideas and Outcomes 6: e57767. https://doi.org/10.3897/rio.6.e57767
Figure 5 Google Sheets approach.
Figure 4 from: Willemse L, Runnel V, Saarenmaa H, Casino A, Gödderz K (2020) Digitisation of private collections. Research Ideas and Outcomes 6: e57767. https://doi.org/10.3897/rio.6.e57767
Figure 4 The PlutoF module for GBIF publishing.
Figure 3 from: Willemse L, Runnel V, Saarenmaa H, Casino A, Gödderz K (2020) Digitisation of private collections. Research Ideas and Outcomes 6: e57767. https://doi.org/10.3897/rio.6.e57767
Figure 3 The PlutoF taxon occurrence management module.
Figure 1 from: Dixey K, Woodburn M, Hardy H, Livermore L, Smith VS (2020) Identification of provisional Centres of Excellence for digitisation of European natural science collections. Research Ideas and Outcomes 6: e57750. https://doi.org/10.3897/rio.6.e57750
Figure 1 Heat map matrix of Center of Excellence services versus organizational levels.
Figure 2 from: Tilley LJ, Woodburn M, Vincent S, Casino A, Addink W, Berger F, Bogaerts A, De Smedt S, French L, Islam S, Mergen P, Nivart A, Papp B, Petersen M, Santos C, Schiller EK, Semal P, Smith VS, Wiltschke K (2024) Systematic Design of a Natural Sciences Collections Digitisation Dashboard. Research Ideas and Outcomes 10: e118244. https://doi.org/10.3897/rio.10.e118244
Figure 2 CDD relational data model.
Figure 1 from: Tilley LJ, Woodburn M, Vincent S, Casino A, Addink W, Berger F, Bogaerts A, De Smedt S, French L, Islam S, Mergen P, Nivart A, Papp B, Petersen M, Santos C, Schiller EK, Semal P, Smith VS, Wiltschke K (2024) Systematic Design of a Natural Sciences Collections Digitisation Dashboard. Research Ideas and Outcomes 10: e118244. https://doi.org/10.3897/rio.10.e118244
Figure 1 A simplified conceptual view of the TDWG Collections Description data model.
Figure 3 from: Tilley LJ, Woodburn M, Vincent S, Casino A, Addink W, Berger F, Bogaerts A, De Smedt S, French L, Islam S, Mergen P, Nivart A, Papp B, Petersen M, Santos C, Schiller EK, Semal P, Smith VS, Wiltschke K (2024) Systematic Design of a Natural Sciences Collections Digitisation Dashboard. Research Ideas and Outcomes 10: e118244. https://doi.org/10.3897/rio.10.e118244
Figure 3 First page of the Pilot CDD showing a collection overview (Licence: CC-BY).
Figure 5 from: Popov D, Roychoudhury P, Hardy H, Livermore L, Norris K (2021) The Value of Digitising Natural History Collections. Research Ideas and Outcomes 7: e78844. https://doi.org/10.3897/rio.7.e78844
Figure 5 Components of the theory of change.
Figure 2 from: Saarenmaa H, Tegelberg R, Haapala J, Mononen T, Pajari M (2012) The development of a digitising service centre for natural history collections. ZooKeys 209: 75-86. https://doi.org/10.3897/zookeys.209.3119
Figure 2 - Selected windows of the digitisation workbench.
Figure 7 from: Flemons P, Berents P (2012) Image based Digitisation of Entomology Collections: Leveraging volunteers to increase digitization capacity. ZooKeys 209: 203-217. https://doi.org/10.3897/zookeys.209.3146
Figure 7 - Number of damaged specimens per month.
Figure 5 from: Flemons P, Berents P (2012) Image based Digitisation of Entomology Collections: Leveraging volunteers to increase digitization capacity. ZooKeys 209: 203-217. https://doi.org/10.3897/zookeys.209.3146
Figure 5 - Specimens digitised per month.
Figure 9 from: Flemons P, Berents P (2012) Image based Digitisation of Entomology Collections: Leveraging volunteers to increase digitization capacity. ZooKeys 209: 203-217. https://doi.org/10.3897/zookeys.209.3146
Figure 9 - Number of workstation hours per day.
Figure 1 from: Flemons P, Berents P (2012) Image based Digitisation of Entomology Collections: Leveraging volunteers to increase digitization capacity. ZooKeys 209: 203-217. https://doi.org/10.3897/zookeys.209.3146
Figure 1 - Database for entry of image metadata.
Figure 4 from: Flemons P, Berents P (2012) Image based Digitisation of Entomology Collections: Leveraging volunteers to increase digitization capacity. ZooKeys 209: 203-217. https://doi.org/10.3897/zookeys.209.3146
Figure 4 - Workstation hours per month.
Figure 3 from: Flemons P, Berents P (2012) Image based Digitisation of Entomology Collections: Leveraging volunteers to increase digitization capacity. ZooKeys 209: 203-217. https://doi.org/10.3897/zookeys.209.3146
Figure 3 - An example of a specimen and label image, in this case a hawk moth.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.