Lidar / Raw Data
This dataset contains raw data from the WFIP3 NANT site UTD Halo XR Lidar.
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This dataset contains raw data from the WFIP3 NANT site UTD Halo XR Lidar.
This dataset contains raw data from the WFIP3 site NANT UTD Alphasense N3 OPC.
This dataset contains raw NREL Thermodynamic profiler (Assist II-12) data from the WFIP3 CACO site.
This dataset contains raw data from the WFIP3 site NANT UTD Alphasense N3 OPC colocated with the UTD 200S scanning lidar.
This dataset contains ERCOT plant-level wind power production data at a 15-minute time resolution. Data at ERCOT are called 60-Day SCED Disclosure Report; data product number NP3-965-ER. Raw data are in local time. DST is handled as "skip hour" (12a, 1a, 3a,...) in spring, "extra hour" (12a, 1a, 2a, 2a, 3a,...) in fall.
The dataset contains raw data from the ground-based NLR profiling lidar (Windcube v2.1) at FC Site 4.0. Two data types are included here: 1) STA files, which have 10-minute average data, and 2) RTD files, which have real-time data, at about 1 Hz resolution.
This dataset contains raw lidar data from ground-based NLR Halo XR+235.
This dataset contains raw and summary data from the ASSIST II.
This dataset contains raw lidar data from the ground-based NLR Halo XR+ 200.
This dataset contains raw lidar data from the ground-based NLR Halo XR+ 200.
This dataset contains raw lidar data from ground-based NLR Halo XR+ 199.
This dataset contains raw data from the laser disdrometer at ASIT. The disdrometer measures droplet size distribution, hydrometer type, and precipitation rate.
This dataset contains raw data from the laser disdrometer at ASIT. The disdrometer measures droplet size distribution, hydrometer type, and precipitation rate.
This dataset contains raw data collected by sentinel buoy 5 during the WFIP3 project period at the WFIP3 location. It was deployed on 7/9/2024 12:15Z and is still currently deployed.
This dataset contains the raw LC-MS data of metabolites extracted from I. orientalis strains.
The building management system in Building 59 is monitoring and archiving building-level electricity usage, HVAC and lighting system states (e.g., setpoint, temperature, flow rate, pressure), indoor environmental conditions (air temperature, relative humidity, CO2), on-site weather (air temperature, relative humidity), and especially occupant counts as well as other metrics such as Wi-Fi signal. This dataset could support multiple use cases, such as model predictive control and occupant related demand management. Raw data.
The raw bulk metagenomic data were trimmed and de-novo assembled. The assemblies were screened for viral contigs (by virsorter2, Deepvirfinder, VIBRANT, checkV) and binned to generate MAGs that were further refined by Hi-C read links.
The raw Hi-C metagenomic data were trimmed and aligned to the de-novo assemblies obtained from the paired shotgun metagenomes following the Hi-C kit manufacturer's recommendations (https://phasegenomics.github.io/2019/09/19/hic-alignment-and-qc.html). The contig-contig links or Hi-C links were quality-filtered for the identification of virus-host pairs.