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.
12
datasets available to search
ShareScore release 0.9.0
Dataset results
12 results for “mineral exploration”
Supplement for Drone-based magnetic and multispectral surveys to develop a 3D model for mineral exploration at Qullissat, Disko Island, Greenland
<p>Supplement to Jackisch et al., 2021: Drone-based magnetic and multispectral surveys to develop a 3D model for mineral exploration at Qullissat, Disko Island, Greenland.</p> <p><a href="https://se.copernicus.org/articles/13/793/2022/se-13-793-2022.html">https://se.copernicus.org/articles/13/793/2022/se-13-793-2022.html</a></p> <p>Data set contains 3D model in dxf file, additional images, selected handheld spectra.</p> <p>Publication summary:</p> <p>We integrate UAS-based magnetic and remote sensing mineral exploration data with legacy exploration data of a Ni-Cu-PGE prospect on Disko Island, West Greenland. The basalt unit has a complex magnetization, and we use a 3D magnetic vector inversion on the UAS magnetics to estimate magnetic properties and spatial dimensions of the mineralized unit. Our 3D modelling reveals a horizontal sheet and a strong remanent magnetization component. We highlight the advantage of UAS in rugged terrain.</p> <p> </p>
A LCT Pegmatite Spectral Library of the Aldeia spodumene deposit: contributes to mineral exploration
<p>Studies focused on methodologies for locating and prospecting Li-Cs-Ta (LCT) pegmatites are increasingly relevant, given their importance for the energy market in a scenario where new sources need to be identified. Considering the inherent costs of field campaigns to identify targets <em>in situ</em>, this study presents alternatives, focusing on a preliminary evaluation of the spectral signature of targets at a specific site to serve as an added value for future exploration studies. Moreover, such spectral and remote sensing-based approaches help to decrease the impacts of early stages of exploration due to their less invasive nature.</p> <p>Therefore, we present a spectral library built with empirical data available for public use, focusing on Lithium minerals and pegmatites of the Barroso pegmatite field (Portugal), one of the largest hard-rock European Lithium deposits, built within the scope of the INOVMINERAL4.0 project (<a href="https://inovmineral.pt/">https://inovmineral.pt/</a>).</p>
Figure 6 in How many metazoan species live in the world's largest mineral exploration region?
Figure 6. UpSet plot of all CCZ species (named and unnamed species combined) at regional scales (A and B) Top bars show total species shared or independent, intersecting with region in the lower panel (species independent per region correlate to a ''dot'' or shared between region to a ''dash'' connecting the regions). Side bars show total species per region. (A): all species by region, (B), all species in contract areas and reserved areas pooled versus those in APEIs pooled. See also Data S3 and S4.
Figure 5 in How many metazoan species live in the world's largest mineral exploration region?
Figure 5. Species and family diversity in the Clarion-Clipperton (A–D) Diversity estimators (solid line, rarefaction; dashed line, extrapolation): (A) Chao1 species diversity 6,233 (+/¯82 SE); N = 112,428 ind., S(obs) = 4,716; extrapolation maximum sample size: 224,858 ind; (B) Chao2 species diversity 7,620 (+/¯132 SE); N = 1,668 samples; S(obs) = 4,779, extrapolation maximum sample size, 3,336 samples. Family diversity estimators: (C) Chao1 family diversity 469 (+/¯18 SE); N = 70,597 ind., F(obs) = 406; extrapolation maximum. N: 141,194 ind.; (D) Chao2 family diversity 544 (+/¯24 SE); N = 2,179 samples; F(obs) = 423; extrapolation maximum N: 4,358 samples. See also Table 1, Figures S1–S3, and Data S3 and S4.
Figure 3 in How many metazoan species live in the world's largest mineral exploration region?
Figure 3. Fauna from the CCZ (A–J) All fauna are species described from the region and illustrating a range of phyla and size classes, (A) the sea cucumber, Psychropotes dyscrita (Clark, 1920),32 commonly known as the ''gummy squirrel'' (scale bar: 5 cm); (B) the primnoid coral Abyssoprimnoa gemina Cairns, 201539 (scale bar: 5 mm, note the rights to this image are owned by Springer Nature who have granted permission for reuse); (C) the antipatharian coral, Abyssopathes anomala Molodtsova & Opresko, 201731 (scale bar: 2 cm); and (D) the hexactinellid sponge, Sympagella clippertonae Herzog, Amon, Smith & Janussen, 2018.40 (scale bar: 1 cm). Row 2, (E) the cyclostomatid bryozoan, Pandanipora helix Grischenko, Gordon & Melnik, 201830 (scale bar: 500 Mm); (F) the isopod, Macrostylis metallicola Riehl & De Smet, 20207 (scale bar: 0.2 mm); (G) the polychaete, Neanthes goodayi Drennan, Wiklund, Rabone,Georgieva,Dahlgren & Glover, 202127; and (H) the mollusc, Ledella knudseni J. D. Taylor & Wiklund, 201735 (scale bar: 0.5 mm). Row 3, (I) the nematode, Odetenema gesarae Bezerra, Pape, Hauquier & Vanreusel, 202136 (scale bar: 100 Mm); (J) the kinorhynch, Meristoderes taro Sánchez, Pardos & Martínez Arbizu, 201933 (scale bar: 10 Mm); the loriciferan, Fafnirloricus polymetallicus Fujimoto, 202034 (scale bar: 100 Mm), and the copepod, Siphonis aurreus Mercado-Salas, Khodami & Martínez Arbizu, 201928 (scale bar: 100 Mm). All authors provided permission for reuse of plates (please see Acknowledgments).
Figure 2 in How many metazoan species live in the world's largest mineral exploration region?
Figure 2. Rates of species descriptions in the CCZ; proportion of species diversity in the CCZ that is undescribed (A) Rates of new descriptions and publications in the CCZ. Cumulative totals of new taxa (families, genera, and species combined) and new species described from the CCZ and taxonomic publications per year, over the period 1980–2022. Yearly totals of new descriptions also shown. (B) Proportion of recorded benthic metazoan diversity from the CCZ that is undescribed: named species recorded in red (both those described from the CCZ and elsewhere), unnamed species shown in blue (''unassigned'' are records not identified to phyla). Depictions of some of the new CCZ species by phyla: Annelida, Neanthes goodayi Drennan, Wiklund, Rabone, Georgieva, Dahlgren & Glover, 202127; Arthropoda, Siphonis aurreus Mercado-Salas, Khodami & Martínez Arbizu, 201928; Brachiopoda, Oceanithyris juveniformis Bitner & Zezina, 201329; Bryozoa, Pandanipora helix Grischenko, Gordon & Melnik, 201830; Cnidaria, Abyssopathes anomala Molodtsova & Opresko, 201731; Echinodermata, Psychropotes dyscrita (Clark, 1920)32; Kinorhyncha, Meristoderes taro Sánchez, Pardos & Martínez Arbizu, 201933; Loricifera, Fafnirloricus polymetallicus Fujimoto, 202034; Mollusca, Ledella knudseni J. D. Taylor & Wiklund, 201735; Nematoda, Odetenema gesarae Bezerra, Pape, Hauquier & Vanreusel, 202136; Porifera, Chaunoplectella megapora Wang, Zhang, Lu & Wang, 201837; and Tardigrada, Moebjergarctus clarionclippertonensis Bai, Wang, Zhou, Lin, Meng & Fontoura, 2020.38 See also Data S1 and S2 and Table S1.
Figure 1 in How many metazoan species live in the world's largest mineral exploration region?
Figure 1. All geolocated published records of benthic metazoa from the literature and databases Areas of Particular Environmental Interest (APEIs) and exploration mining contract areas, both active and reserved, are shown in outline. The type localities of all species described from the CCZ to date are also shown (185 in total). Background layer: the GEBCO Grid, 2022. See also Figures S4–S6, the key resources table, and supplemental information.
Figure 4 in How many metazoan species live in the world's largest mineral exploration region?
Figure 4. Phylum-level composition of CCZ and global benthic metazoan checklists Relative abundance of phyla in the CCZ Checklist— named/known species (Data S1); the CCZ unnamed species list (Data S2); and all global deep-sea metazoan species recorded in WoRDSS (World Register of Deep-Sea Species)44 on 1st January, 2023.
Biodiversity, biogeography, and connectivity of polychaetes in the world's largest marine minerals exploration frontier
<p>The abyssal Clarion-Clipperton Zone (CCZ), Pacific Ocean, is an area of commercial importance owing to the growing interest in mining high-grade polymetallic nodules at the seafloor for battery metals. Research into the spatial patterns of faunal diversity, composition, and population connectivity is needed to better understand the ecological impacts of potential resource extraction. Here, a DNA taxonomy approach is used to investigate regional-scale patterns of taxonomic and phylogenetic alpha and beta diversity, and genetic connectivity, of the dominant macrofaunal group (annelids) across a 6 million km<sup>2</sup> region of the abyssal seafloor. We used a combination of new and published barcode data to study 1866 polychaete specimens using molecular species delimitation. Both phylogenetic and taxonomic alpha and beta diversity metrics were used to analyse spatial patterns of biodiversity. Connectivity analyses were based on haplotype distributions for a subset of the studied taxa. DNA taxonomy identified 291–314 polychaete species from the COI and 16S datasets respectively. Taxonomic and phylogenetic beta diversity between sites were relatively high and mostly explained by lineage turnover. Over half of pairwise comparisons were more phylogenetically distinct than expected based on their taxonomic diversity. Connectivity analyses in abundant, broadly distributed taxa suggest an absence of genetic structuring driven by geographical location. Species diversity in abyssal Pacific polychaetes is high relative to other deep-sea regions. Results suggest that environmental filtering, where the environment selects against certain species, may play a significant role in regulating spatial patterns of biodiversity in the CCZ. A core group of widespread species have diverse haplotypes but are well connected over broad distances. Our data suggest that the high environmental and faunal heterogeneity of the CCZ should be considered in policy decisions such as designating protected areas.</p>
Biodiversity, biogeography, and connectivity of polychaetes in the world's largest marine minerals exploration frontier
Open the record for dataset details and reuse information.
Geodiversity index of the proposed opening area for deep-sea mineral explorations in Norway.
<p>Dataset containing sub-indexes of bathymetry, seafloor roughness, geomorphology and sediment thickness as well as a geodiversity index of the proposed opening area for deep-sea mineral explorations in het Norwegian Sea. </p>
Dataset related to publication "Active hyperspectral sensing (AHS) applications for mineral deposit exploration"
<p>Dataset related to publication "Active hyperspectral sensing (AHS) applications for mineral deposit exploration"</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.