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.
136
datasets available to search
ShareScore release 0.7.1
Dataset results
136 results for “trend analysis”
Figure 9 in Morphometric analysis of Eocene nummulitids in western and central Cuba: taxonomy, biostratigraphy and evolutionary trends
Figure 9. Distribution of larger benthic foraminifera (LBF) in the Angelita Quarry section, western Cuba.
Figure 6 in Morphometric analysis of Eocene nummulitids in western and central Cuba: taxonomy, biostratigraphy and evolutionary trends
Figure 6. Stratigraphical ranges of the nummulitid species from the Cuban sections and their correlation with the standard planktonic zones. A, Pearson et al. (2006); B, Berggren et al. (1995); C, Martini (1971); D, Agnini et al. (2014).
Figure 5. Ordinations and discriminant analysis. A in Morphometric analysis of Eocene nummulitids in western and central Cuba: taxonomy, biostratigraphy and evolutionary trends
Figure 5. Ordinations and discriminant analysis. A, two-dimensional ordination of studied specimens; genera are separated by different shapes (squares = Operculinoides; polygons = Palaeonummulites; triangles = Heterostegina). B, three-dimensional ordination of the studied specimens emphasizes the variation in the third component, highlighting the differentiation between Heterostegina sp. indet. and Operculinoides. C, discriminant analysis of Heterostegina species and Operculinoides or Palaeonummulites species; parameters are sorted in order of their importance as discriminators.
Figure 2 in Morphometric analysis of Eocene nummulitids in western and central Cuba: taxonomy, biostratigraphy and evolutionary trends
Figure 2. Measurements of characters in equatorial section. A, embryonic apparatus; B, marginal test spiral; C, chamber measurements; D, example individual, Operculinoides floridensis, specimen 98LC-1H-648.
Figure 1. A in Morphometric analysis of Eocene nummulitids in western and central Cuba: taxonomy, biostratigraphy and evolutionary trends
Figure 1. A, schematic tectonic map of western and central Cuba (after Iturrlade-Vinent 1994), with locations of the stratigraphical sections and samples. B, stratigraphical relations of Eocene units in western and central Cuba, slightly modified from Garćıa-Delgado & Torres-Silva (1997); stratigraphical ranges of the studied sections: A, 98LC-2; B, 98LC-1; C, LM-52; D, NOR-UN; E, 98MT-1; F, E-126; G, CA-215.
Figure 3. A in Morphometric analysis of Eocene nummulitids in western and central Cuba: taxonomy, biostratigraphy and evolutionary trends
Figure 3. A, two-dimensional ordination of studied specimens; colours accord with the results of the K-means cluster analysis. Numbers indicate the measured type material: 1, Nummulites stritoreticulatus, holotype; 2, N. macgillavry (from Butterlin 1981); 3, Operculinoides trinitatensis, holotype; 4, O. spiralis, holotype; 5. O. kugleri, holotype; 6, N. trinitatensis (from Butterlin 1961); 7, O. willcoxi (from Barker 1939); 8, O. willcoxi (from Cole 1941); 9, O. floridensis (from Frost & Langenheim 1974); 10, O. floridensis (from Cole 1941); 11, O. floridensis (from Cole 1941); 12, O. soldadensis (from Vaughan & Cole 1941); 13, O. suteri (from Caudri 1996); 14, N. floridensis (from Butterlin 1961). B, three-dimensional ordination of the studied specimens emphasizes the variation in the third component, highlighting the differentiation between Nummulites from 98LC-2 and Palaeonummulites from 98LC-1. C, discriminant analysis between the interpreted species: Nummulites striatoreticulatus, Palaeonummulites trinitatensis, Operculinoides floridensis and Operculinoides soldadensis; parameters are sorted in order of their importance as discriminators.
Figure 16 in Morphometric analysis of Eocene nummulitids in western and central Cuba: taxonomy, biostratigraphy and evolutionary trends
Figure 16. Operculinoides floridensis (Heilprin). A–C, Loma Candelaria; A, 98LC-1-651; B, 98LC-1-667; C, 98LC-1-815. D, E, Loma Viǵıa; D, CA-216-F3-16; E, CA-216-D1a. F, Loma El Santo, CA-215-852. G, Loma Jabaco, LM-52-759. H, Angelita Quarry, 98MT-1. A–D, F and G are A forms in equatorial section; E and F are A forms in axial section.
Unveiling Mexico City's Airbnb Market Trends: A Data Analysis Exploration.
<p>The present document focuses on analyzing, exploring and visualizing data from the Airbnb market in Mexico City using tools such as Python. The data used for this work was cleaned and prepared to extract relevant insights and relations between popular locations, occupancy rate, and reviews (classified into positive or negative using BERT) of accommodations and market trends. The results obtained provide an in-depth insight into the Airbnb market in Mexico City and may be valuable for property owners to make an informed decision in their dynamic pricing strategy.</p>
Fig 9. Top 10 in Publishing trends and productivity in insect taxonomy from 1946 through 2012 based on an analysis of the Zoological Record for four species-rich families
Fig 9. Top 10 of most utilized journals from 1946 to 2012. A. Cicadellidae. B. Miridae. C. Pyralidae. D. Staphylinidae.
Fig 6 in Publishing trends and productivity in insect taxonomy from 1946 through 2012 based on an analysis of the Zoological Record for four species-rich families
Fig 6 (continued from previous page). Number of total articles and co-authored articles from 1946 to 2012. A. Cicadellidae. B. Miridae. C. Pyralidae. D. Staphylinidae.
Fig 6 in Publishing trends and productivity in insect taxonomy from 1946 through 2012 based on an analysis of the Zoological Record for four species-rich families
Fig 6 (continued on next page). Number of total articles and co-authored articles from 1946 to 2012. A. Cicadellidae. B. Miridae. C. Pyralidae. D. Staphylinidae.
Fig 5 in Publishing trends and productivity in insect taxonomy from 1946 through 2012 based on an analysis of the Zoological Record for four species-rich families
Fig 5 (continued on next page). Number of articles published by continent (Europe, North America, South America, Africa, Asia and Australia) between 1946 and 2012. A. Cicadellidae. B. Miridae. C. Pyralidae. D. Staphylinidae.
Fig 2 in Publishing trends and productivity in insect taxonomy from 1946 through 2012 based on an analysis of the Zoological Record for four species-rich families
Fig 2. Average new species described per article (Cicadellidae, Miridae, Pyralidae and Staphylinidae combined) from 1946 to 2012.
Fig 1 in Publishing trends and productivity in insect taxonomy from 1946 through 2012 based on an analysis of the Zoological Record for four species-rich families
Fig 1. Time series of newly described species for the families Cicadellidae, Miridae, Pyralidae and Staphylinidae between 1946 and 2012. A. Number of new species. B. Number of articles with new species.
Fig 4 in Publishing trends and productivity in insect taxonomy from 1946 through 2012 based on an analysis of the Zoological Record for four species-rich families
Fig 4. Total and average article length for for papers on the four families of Cicadellidae, Miridae, Pyralidae and Staphylinidae between 1946 and 2012.
Fig 3 in Publishing trends and productivity in insect taxonomy from 1946 through 2012 based on an analysis of the Zoological Record for four species-rich families
Fig 3. Average page length of new species descriptions (Cicadellidae, Miridae, Pyralidae and Staphylinidae combined) between 1946 and 2012.
Fig 5 in Publishing trends and productivity in insect taxonomy from 1946 through 2012 based on an analysis of the Zoological Record for four species-rich families
Fig 5 (continued from previous page). Number of articles published by continent (Europe, North America, South America, Africa, Asia and Australia) between 1946 and 2012. A. Cicadellidae. B. Miridae. C. Pyralidae. D. Staphylinidae.
Figures 5a–f in Trapping Records of Fruit Fly Pest Species (Diptera: Tephritidae) on Oahu (Hawaiian Islands): Analysis of Spatial Population Trends
Figures 5a–f. Mean (± S.E.) captures in different habitats for B. cucurbitae in cuelure and torula yeast (a, b), B. dorsalis in methyl eugenol and torula yeast (c, d) and C. capitata in trimedlure and torula yeast (e, f) traps. Units are flies per trap per day in male lure and per week in torula yeast traps.
Trend surface analysis of the 300 Years-Before Present stratigraphic horizon and the Holocene/Pleistocene boundary of the Virginia Coast Reserve
This data set contains sediment grain-size distribution and organic matter data obtained from thirty vibracore samples collected along transects crossing Hog Island Bay, VA prior to 1997. Â Analysis was conducted at various depths along each core.
Research trends in stable isotope analysis: a revision on unconsolidated intertidal ecosystems Supplementary Material 2
<p>Supplementary material corresponding to document "Research trends in stable isotope analysis: a revision on unconsolidated intertidal ecosystems".</p>
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.