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Figure 3 from: Blagoderov V, Kitching I, Livermore L, Simonsen T, Smith V (2012) No specimen left behind: industrial scale digitization of natural history collections. ZooKeys 209: 133-146. https://doi.org/10.3897/zookeys.209.3178
Figure 3 - Metadata Creator software: a–c working areas a drawer image b specimen records c annotation fields d tool selector e unique IDs.
Figure 2 from: Nelson G, Paul D, Riccardi G, Mast A (2012) Five task clusters that enable efficient and effective digitization of biological collections. ZooKeys 209: 19-45. https://doi.org/10.3897/zookeys.209.3135
Figure 2 - Specimen image capture. Fossil specimen imaging, specimen label imaging. Two very different imaging set-ups. Yale Peabody Museum, University of Kansas - Entomology.
Figure 1 from: Blagoderov V, Kitching I, Livermore L, Simonsen T, Smith V (2012) No specimen left behind: industrial scale digitization of natural history collections. ZooKeys 209: 133-146. https://doi.org/10.3897/zookeys.209.3178
Figure 1 - SatScan imaging: a SatScan machine b specimens being imaged c individual frames aligned d fragment of a stitched image; final resolution of the stitched image ~11 lines/mm.
Figure 1 from: Nelson G, Paul D, Riccardi G, Mast A (2012) Five task clusters that enable efficient and effective digitization of biological collections. ZooKeys 209: 19-45. https://doi.org/10.3897/zookeys.209.3135
Figure 1 - Pre-digitization specimen curation and staging. Preparing barcodes and imaging labels, affixing barcodes, updating taxonomy. L to R: University of Kansas – Entomology, New York Botanical Garden and Yale Peabody Museum.
Figure 8 from: Mantle B, LaSalle J, Fisher N (2012) Whole-drawer imaging for digital management and curation of a large entomological collection. ZooKeys 209: 147-163. https://doi.org/10.3897/zookeys.209.3169
Figure 8 - Whole-drawer image of dragonfly specimens used for a pilot study investigating the error associated with direct and indirect measures of morphological characters, such as wing length.
Figure 2 from: Blagoderov V, Kitching I, Livermore L, Simonsen T, Smith V (2012) No specimen left behind: industrial scale digitization of natural history collections. ZooKeys 209: 133-146. https://doi.org/10.3897/zookeys.209.3178
Figure 2 - Image based digitization workflow consisting of four stages: Imaging, Metadata capture, Institutional databading and Publication.
Figure 5 from: Nelson G, Paul D, Riccardi G, Mast A (2012) Five task clusters that enable efficient and effective digitization of biological collections. ZooKeys 209: 19-45. https://doi.org/10.3897/zookeys.209.3135
Figure 5 - Electronic data capture. Entering data straight from the specimen label into the database. New York Botanical Garden.
Figure 5 from: Mantle B, LaSalle J, Fisher N (2012) Whole-drawer imaging for digital management and curation of a large entomological collection. ZooKeys 209: 147-163. https://doi.org/10.3897/zookeys.209.3169
Figure 5 - Inset from previous figure (Figure 4). Label data attached to small specimens is often almost completely readable. Therefore, specimen metadata could be extracted and digitised using specialised character recognition software.
Figure 6 from: Mantle B, LaSalle J, Fisher N (2012) Whole-drawer imaging for digital management and curation of a large entomological collection. ZooKeys 209: 147-163. https://doi.org/10.3897/zookeys.209.3169
Figure 6 - Specimen with QR Code containing label data. A smart phone with the appropriate software can read and access the label data for this specimen from the image.
Figure 7 from: Mantle B, LaSalle J, Fisher N (2012) Whole-drawer imaging for digital management and curation of a large entomological collection. ZooKeys 209: 147-163. https://doi.org/10.3897/zookeys.209.3169
Figure 7 - Ultra high-resolution image of Buforaniidae grasshoppers (Orthoptera) from the ANIC. Note that the specimens are arranged by species, and then by the State from which they were collected. In this example, Northern Territory specimens are pinned in the first and second columns, followed by Queensland specimens in columns three and four. The online version of this image is viewable at Morphbank-ALA.
Figure 4 from: Mantle B, LaSalle J, Fisher N (2012) Whole-drawer imaging for digital management and curation of a large entomological collection. ZooKeys 209: 147-163. https://doi.org/10.3897/zookeys.209.3169
Figure 4 - Whole-drawer image of unsorted Hemiptera specimens with identifications provided by a remotely located expert, Dr Murray Fletcher. This drawer was subsequently re-curated according to the identifications, with specimens accessioned into the appropriate locations within the ANIC Hemiptera collection. See Appendix 1 for full list of remote identifications.
Figure 1 from: Wheeler Q, Bourgoin T, Coddington J, Gostony T, Hamilton A, Larimer R, Polaszek A, Schauff M, Solis A (2012) Nomenclatural benchmarking: the roles of digital typification and telemicroscopy. ZooKeys 209: 193-202. https://doi.org/10.3897/zookeys.209.3486
Figure 1 - Three-part strategy to (a) avoid further growth of backlog by digitizing all new species, (b) rapidly create 3D e-types for all existing species, and (c) open access to types for experts to facilitate their nomenclatural decision-making while simultaneously expanding and enhancing comprehensiveness of digital images of informative characters of type specimens. All images should be available through an open access public "Global e-Type Archive," whether managed by ZooBank or a community-level organization.
Figure 2 from: Wheeler Q, Bourgoin T, Coddington J, Gostony T, Hamilton A, Larimer R, Polaszek A, Schauff M, Solis A (2012) Nomenclatural benchmarking: the roles of digital typification and telemicroscopy. ZooKeys 209: 193-202. https://doi.org/10.3897/zookeys.209.3486
Figure 2 - Two ROBOT(E) remotely operable digital imaging systems designed to allow taxonomists to examine, manipulate, and digitally photograph type specimens through a Web connection. Three such instruments are being deployed to major insect collections in Washington, London, and Paris. A prototype instrument remains with the IISE for testing and development purposes. PHOTO: Courtesy of Erik Holsinger, Arizona State University.
Figure 4 from: Dietrich C, Hart J, Raila D, Ravaioli U, Sobh N, Sobh O, Taylor C (2012) InvertNet: a new paradigm for digital access to invertebrate collections. ZooKeys 209: 165-181. https://doi.org/10.3897/zookeys.209.3571
Figure 4 - Image of multiple pinned insect specimens in unit tray (left) and same specimens segmented into separate files (right) using customized ImageJ image processing protocol.
Figure 2 from: Schmidt S, Balke M, Lafogler S (2012) DScan – a high-performance digital scanning system for entomological collections. ZooKeys 209: 183-191. https://doi.org/10.3897/zookeys.209.3115
Figure 2 - Partial drawer images taken at the same position using three different file formats: captured as JPEG (a), captured as TIFF (b), and TIFF converted from RAW (c). A high resolution version of the image is available under media.zsm-entomology.de/suppl/zookeys_mass_digitisation_volume/Fig_2.png
Figure 3 from: Dietrich C, Hart J, Raila D, Ravaioli U, Sobh N, Sobh O, Taylor C (2012) InvertNet: a new paradigm for digital access to invertebrate collections. ZooKeys 209: 165-181. https://doi.org/10.3897/zookeys.209.3571
Figure 3 - Current version of InvertNet's Medici multimedia semantic content management system interface, accessible from InvertNet digital collections tab on homepage, showing taxonomic tree, drag and drop file upload space, and zoomable user interface for viewing gigapixel images.
Figure 1 from: Schmidt S, Balke M, Lafogler S (2012) DScan – a high-performance digital scanning system for entomological collections. ZooKeys 209: 183-191. https://doi.org/10.3897/zookeys.209.3115
Figure 1 - Schematic drawing of the DScan system. Flashes (not shown) are placed inside the scanner.
Figure 1 from: Dietrich C, Hart J, Raila D, Ravaioli U, Sobh N, Sobh O, Taylor C (2012) InvertNet: a new paradigm for digital access to invertebrate collections. ZooKeys 209: 165-181. https://doi.org/10.3897/zookeys.209.3571
Figure 1 - A set of three-dram vials scanned using a color flatbed scanner showing the front (left) and back (right) of the same set of vials. Note that the position of empty spacer vials (e.g., sixth from top in middle column) is the same, but inverted, in the two images because the vial racks are flipped vertically between scans. This relatively quick and inexpensive procedure exposes at least some label data for subsequent capture and reveals the general condition of specimens.
Figure 3 from: Mantle B, LaSalle J, Fisher N (2012) Whole-drawer imaging for digital management and curation of a large entomological collection. ZooKeys 209: 147-163. https://doi.org/10.3897/zookeys.209.3169
Figure 3 - A whole-drawer image displayed in MorphbankALA for online for viewing, editing and download. Image properties: 17,003x16,425 pixels, 30 MB (JPEG), and 464 MB (LZW compressed TIFF).
Figure 2 from: Mantle B, LaSalle J, Fisher N (2012) Whole-drawer imaging for digital management and curation of a large entomological collection. ZooKeys 209: 147-163. https://doi.org/10.3897/zookeys.209.3169
Figure 2 - Workflow process in ANIC to Digitise whole drawers of insects and load images into Morphbank-ALA
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
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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.