Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
3,507
datasets available to search
ShareScore release 0.9.0
Dataset results
3,507 results for “Species identification”
FIGURE 26 in Gobies (Teleostei: Gobiidae) of the oldest and deepest Caspian Sea sub-basin: an evidence-based annotated checklist and a key for species identification
FIGURE 26. Ponticola cyrius. Kura River at Yalnýzçam, northeastern Turkey. Photo by C. Kaya.
FIGURE 24 in Gobies (Teleostei: Gobiidae) of the oldest and deepest Caspian Sea sub-basin: an evidence-based annotated checklist and a key for species identification
FIGURE 24. Neogobius melanostomus. Off Anzali, Gilan Province, Iran.
FIGURE 20 in Gobies (Teleostei: Gobiidae) of the oldest and deepest Caspian Sea sub-basin: an evidence-based annotated checklist and a key for species identification
FIGURE 20. Mesogobius nonultimus. ZM-CBSU S036-1, 126 mm SL, off Anzali, Gilan Province, Iran.
FIGURE 19 in Gobies (Teleostei: Gobiidae) of the oldest and deepest Caspian Sea sub-basin: an evidence-based annotated checklist and a key for species identification
FIGURE 19. Knipowitschia longecaudata. Off Anzali, Gilan Province, Iran.
FIGURE 14 in Gobies (Teleostei: Gobiidae) of the oldest and deepest Caspian Sea sub-basin: an evidence-based annotated checklist and a key for species identification
FIGURE 14. Benthophilus pinchuki. ZM-CBSU S005-1, 61.1 mm SL, off Anzali, Gilan Province, Iran.
FIGURE 10 in Gobies (Teleostei: Gobiidae) of the oldest and deepest Caspian Sea sub-basin: an evidence-based annotated checklist and a key for species identification
FIGURE 10. Benthophilus granulosus. ZM-CBSU S006-1, 33.3 mm SL, off Anzali, Gilan Province, Iran.
FIGURE 3 in Gobies (Teleostei: Gobiidae) of the oldest and deepest Caspian Sea sub-basin: an evidence-based annotated checklist and a key for species identification
FIGURE 3. Endemic, native, and exotic gobiid species of the South Caspian Sea sub-basin.
FIGURE 23 in Gobies (Teleostei: Gobiidae) of the oldest and deepest Caspian Sea sub-basin: an evidence-based annotated checklist and a key for species identification
FIGURE 23. Neogobius caspius. Talar, Babolsar, Mazandaran Province, Iran (Zarei et al. 2021).
FIGURE 4 in Gobies (Teleostei: Gobiidae) of the oldest and deepest Caspian Sea sub-basin: an evidence-based annotated checklist and a key for species identification
FIGURE 4. Number of gobiid species from the South Caspian Sea sub-basin in each ecological group.
FIGURE 12 in Gobies (Teleostei: Gobiidae) of the oldest and deepest Caspian Sea sub-basin: an evidence-based annotated checklist and a key for species identification
FIGURE 12. Benthophilus leobergius. ZM-CBSU S037-1, 64.2 mm SL, off Anzali, Gilan Province, Iran.
FIGURE 2 in Gobies (Teleostei: Gobiidae) of the oldest and deepest Caspian Sea sub-basin: an evidence-based annotated checklist and a key for species identification
FIGURE 2. Species richness of gobiid genera in the South Caspian Sea sub-basin.
FIGURE 9 in Gobies (Teleostei: Gobiidae) of the oldest and deepest Caspian Sea sub-basin: an evidence-based annotated checklist and a key for species identification
FIGURE 9. Benthophilus baeri. ZM-CBSU S002-14, 54.8 mm SL; Off Anzali, Gilan Province, Iran.
Supplementary material 6 from: Boroni NL, Lobo LS, Romano PSR, Lessa G (2017) Taxonomic identification using geometric morphometric approach and limited data: an example using the upper molars of two sympatric species of Calomys (Cricetidae: Rodentia). Zoologia 34: 1-11. https://doi.org/10.3897/zoologia.34.e19864
PCA with Calomys terrer and C. expulsus : Data type: statistical data
Supplementary material 5 from: Boroni NL, Lobo LS, Romano PSR, Lessa G (2017) Taxonomic identification using geometric morphometric approach and limited data: an example using the upper molars of two sympatric species of Calomys (Cricetidae: Rodentia). Zoologia 34: 1-11. https://doi.org/10.3897/zoologia.34.e19864
Tests for normality, hornoscedasticity and homogeneity : Data type: statistical data
Supplementary material 4 from: Boroni NL, Lobo LS, Romano PSR, Lessa G (2017) Taxonomic identification using geometric morphometric approach and limited data: an example using the upper molars of two sympatric species of Calomys (Cricetidae: Rodentia). Zoologia 34: 1-11. https://doi.org/10.3897/zoologia.34.e19864
Protocol for testing error in the digitalization : Data type: statistical data
Supplementary material 3 from: Boroni NL, Lobo LS, Romano PSR, Lessa G (2017) Taxonomic identification using geometric morphometric approach and limited data: an example using the upper molars of two sympatric species of Calomys (Cricetidae: Rodentia). Zoologia 34: 1-11. https://doi.org/10.3897/zoologia.34.e19864
Specimens of the wear category class 2 : Data type: species data
Supplementary material 2 from: Boroni NL, Lobo LS, Romano PSR, Lessa G (2017) Taxonomic identification using geometric morphometric approach and limited data: an example using the upper molars of two sympatric species of Calomys (Cricetidae: Rodentia). Zoologia 34: 1-11. https://doi.org/10.3897/zoologia.34.e19864
Wear categories : Data type: measurement
Supplementary material 1 from: Boroni NL, Lobo LS, Romano PSR, Lessa G (2017) Taxonomic identification using geometric morphometric approach and limited data: an example using the upper molars of two sympatric species of Calomys (Cricetidae: Rodentia). Zoologia 34: 1-11. https://doi.org/10.3897/zoologia.34.e19864
Alisphenoid strut : Data type: multimedia
Figure 3 from: Boroni NL, Lobo LS, Romano PSR, Lessa G (2017) Taxonomic identification using geometric morphometric approach and limited data: an example using the upper molars of two sympatric species of Calomys (Cricetidae: Rodentia). Zoologia 34: 1-11. https://doi.org/10.3897/zoologia.34.e19864
Figure 3 - PCA showing the individual projections of Calomys sp., C. expulsus and C. tener in the two major axis (PC1 28.7%, PC2 12.3% of the variance). The wireframes illustrate shape differences between most different specimens: CE 09, CT 05, CT 02, and SP 11. Black circles: C. expulsus; Gray triangle: C. tener; Black square: Calomys sp. identified as C. expulsus; Gray square: Calomys sp. identified as C. tener; Gray triangle with black edge: specimen CT 02; Stars: mean shape for each species.
Figure 7 from: Boroni NL, Lobo LS, Romano PSR, Lessa G (2017) Taxonomic identification using geometric morphometric approach and limited data: an example using the upper molars of two sympatric species of Calomys (Cricetidae: Rodentia). Zoologia 34: 1-11. https://doi.org/10.3897/zoologia.34.e19864
Figure 7 - Pooled regression within the two species, between shape (dependent variable) and centroid size (independent variable). Black circles: C. expulsus; Gray triangle: C. tener; Black square: Calomys sp. identified as C. expulsus; Gray square: Calomys sp. identified as C. tener.
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.