https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
Dataset Containing 173 College Common Data Sets
Contains Common Data Sets for the Following Schools:
New York University had around 27,247 international students studying there in the academic year 2023/24, making it the most popular university for international students in the United States. NYU was followed by Northeastern University with 21,023 international students and Columbia University, which hosted 20,321 international students.
The COVID Information Commons (CIC) is an open website portal and community to facilitate knowledge-sharing and collaboration across various COVID research efforts, funded by the NSF Convergence Accelerator and the  NSF Technology, Innovation and Partnerships Directorate. The CIC serves as an open resource for researchers, students, and decision-makers from academia, government, not-for-profits and industry to identify collaboration opportunities, to leverage each other's research findings, and to accelerate the most promising research to mitigate the broad societal impacts of the COVID-19 pandemic. The CIC was developed as a collaborative proposal led by the Northeast Big Data Innovation Hub, hosted by Columbia University, in collaboration with the Midwest Big Data Innovation Hub, South Big Data Innovation Hub, and West Big Data Innovation Hub. It was funded by the NSF Convergence Accelerator (NSF #2028999) in May 2020 and launched in July 2020. The initial focus of the CIC website ..., The NSF and NIH funded COVID related awards corpus in the CIC was collected primarily from NSF and NIH via APIs. Further information has been collected directly from researchers, who filled out an online form to enhance the descriptions. The dataset has been cleaned and enhanced by automated processing, using custom scripts to remove invalid characters, and standardize names of funding agency divisions., , # COVID Information Commons Archive
This archive is a snapshot of the COVID Information Commons (CIC). The CIC is a live database that records information about COVID-19 researchers and their projects.
The snapshot of the CIC contains the following files, each listed with a description of the fields it contains:
cic_people_export.json -- Researchers who have studied aspects of COVID-19. All information known about the researchers in CIC, except email addresses, which have been filtered out for privacy purposes. Some researchers have minimal information, as CIC may only know their name via a reference in a grant description. Other people have more complete records, if they have provided additional information to the CIC.
This collection holds the Lowered Acoustic Doppler Current Profile (LADCP) estimates of ocean currents collected for the Global Ocean Ship-based Hydrographic Investigations Program (GO-SHIP). GO-SHIP brings together scientists with interests in physical oceanography, the carbon cycle, marine biogeochemistry and ecosystems, and other users and collectors of ocean interior data, and coordinates a network of globally sustained hydrographic sections as part of the global ocean/climate observing system including physical oceanography, the carbon cycle, marine biogeochemistry and ecosystems. To understand the ocean currents through the water column, LADCPs are employed. LADCPs estimate deep ocean absolute currents and shear. LADCP specialists of the University of Hawaii (UH) and the Lamont-Doherty Earth Observatory (LDEO) serve as the conduit to integrate LADCP data from international sources into a common database in support of GO-SHIP. LADCP data in this collection begin in 2015 with 1-2 cruises per year, which revisit World Ocean Circulation Experiment (WOCE) transect lines across the major ocean basins. Files within each granule of the collection consist of either ASCII text or NetCDF formats for the science-ready data, though there are some proprietary formats for the raw data directories, which are included to give advanced users the opportunity to reprocess the set. ADCPs use the Doppler shift of an outgoing frequency along a beam to return measured velocity along that beam. ADCPs typically have 4 beams, allowing measurement of velocity in 3 dimensions, in bins of varying distances from the transducer head. In this application, the ADCP is mounted on a Conductivity-Temperature-Depth (CTD) rosette frame and lowered along with the rest of the package, hence called Lowered ADCP ("LADCP"). The goal is to determine water velocities to the full depth of the ocean for each LADCP deployment. Ocean velocities are very small (few cm/s), especially in the deep water. The package is typically lowered or raised at 1m/s for much of the water column, creating a challenging data processing situation. Lowered ADCP data requires ancillary information to calculate ocean velocities and turbulence parameters. Ancillary measurements included in the submission package include Conductivity, Temperature, Depth, at 24Hz, with 1Hz position, and shipboard ADCP data. For the NCEI archive of GO-SHIP LADCP, three levels are defined: 1) Level-0, raw LADCP and ancillary data streams of the down- and up-cast, 2) Level-1, processed LADCP and ancillary data streams for the down-, up-, and averaged cast, and 3) Level-2 science-ready subset of select parameters. Presently only Levels 0 and 1 will be archived since work continues for defining error associated with Level 3. There is one processed file per station cast. The ancillary streams of Level-1 are the basic oceanographic variables of interest, and may also include a variety of additional fields associated with the processing.
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https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
Dataset Containing 173 College Common Data Sets
Contains Common Data Sets for the Following Schools: