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.
8
datasets available to search
ShareScore release 0.9.0
Dataset results
8 results for “Coptis”
H. J. Andrews Experimental Forest site, station Andrews Watershed 3, study of plant cover of Coptis laciniata in units of percent on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from H. J. Andrews Experimental Forest (AND) contains plant cover of Coptis laciniata measurements in percent units and were aggregated to a yearly timescale.
H. J. Andrews Experimental Forest site, station Andrews Watershed 1, study of plant cover of Coptis laciniata in units of percent on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from H. J. Andrews Experimental Forest (AND) contains plant cover of Coptis laciniata measurements in percent units and were aggregated to a yearly timescale.
Composition of prokaryotic and viral community in continuously cropped field of Coptis chinensis Franch
<p>数据集,黄连连作田原核和病毒群落组成</p>
FIGURE 1 in A contribution to the Flora of North America: synonymy and lectotypification of Coptis laciniata (Ranunculaceae)
FIGURE 1. Holotype (OSC-0000899) of Coptis venosa (A) and lectotype (OSC-0000897) of Coptis laciniata (B). Reproduced with permission of the keeper of the Oregon State University Herbarium (OSC). http://oregondigital.org/digcol/herbarium/.
Supplementary material 1 from: Wang Y, Sun J, Wang J, Mao Q, Dong W, Yuan Q, Guo L, Huang L (2022) Coptis huanjiangensis, a new species of Ranunculaceae from Guangxi, China. PhytoKeys 213: 131-141. https://doi.org/10.3897/phytokeys.213.96546
Accession number of 23 sequenced or downloaded chloroplast genome in this study
Supplementary material 3 from: Wang Y, Sun J, Wang J, Mao Q, Dong W, Yuan Q, Guo L, Huang L (2022) Coptis huanjiangensis, a new species of Ranunculaceae from Guangxi, China. PhytoKeys 213: 131-141. https://doi.org/10.3897/phytokeys.213.96546
The photo of isotype stored at the CMMI with accession number HJ220124I01
Supplementary material 2 from: Wang Y, Sun J, Wang J, Mao Q, Dong W, Yuan Q, Guo L, Huang L (2022) Coptis huanjiangensis, a new species of Ranunculaceae from Guangxi, China. PhytoKeys 213: 131-141. https://doi.org/10.3897/phytokeys.213.96546
The photo of holotype stored at the CMMI with accession number HJ220124I02
The impact of Coptis chinensis Franch root rot on leaves
GEO Series GSE290673. Coptis chinensis. 9 samples. Type: Expression profiling by high throughput sequencing.
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.