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95 results for “digitized collection”
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
Figure 2 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 2 - Current HUBzero-based InvertNet homepage showing top menu bar with content areas accessible to registered users.
Figure 3 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 3 - Enlargements of drawer images from Fig. 1 to show quality differences between image file formats. Each of the three specimens was captured in JPEG (a, d, g), TIFF (b, e, h), and RAW (c, f, i). A high resolution version of the image is available under media.zsm-entomology.de/suppl/zookeys_mass_digitisation_volume/Fig_3.png
Digital Auscultation Test - IPF Data Collection
ClinicalTrials.gov study NCT03503188. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Remote Digital Physiologic Data Collection in Cancer: An MSK Registry Protocol
ClinicalTrials.gov study NCT05390827. IPD Sharing: YES. Countries: 1. Publications: 0.
Carestream Digital Radiography Long Length Imaging Software Data Collection Protocol
ClinicalTrials.gov study NCT01592435. IPD Sharing: NO. Countries: 1. Publications: 0.
Data from: A survey of digitized data from U.S. fish collections in the iDigBio data aggregator
Open the record for dataset details and reuse information.
Figure 6 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 6 - Dominant Digitization Workflows Observed.
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.
Figure 8 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 8 - Number of specimens digitised per workstation hour.
Figure 2 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 2 - A digitising workstation.
Figure 4 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 4 - Automatic numbering of specimens using ImageJ. For details see text.
Figure 6 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 6 - Average number of specimens per workstation hour by month.
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.