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.
863
datasets available to search
ShareScore release 0.7.1
Dataset results
863 results for “chemistry”
North Temperate Lakes LTER: Groundwater Chemistry 1984 - current
Water chemistry is measured annually in 11 monitoring wells to characterize regional groundwater chemistry in the Trout Lake area. The chemical parameters measured include pH, conductivity, total alkalinity, disolved inorganic and organic carbon, total nitrogen, nitrae, ammonia, total phosphorus, calcium, magnesium, soium, potassium, chloride, sulfate, iron, manganese, total silica and dissolved reactive silica. Chemical data areavailable at a quarterly sampling frequency for some years. In addition (see related data set - Groundwater Level), water levels in 37 monitoring wells are measured several times per year. The wells are scattered throughout the Trout Lake hydrological basin and the data are used to calibrate and test regional groundwater flow models. Sampling Frequency: annually - with some earlier data from quarterly sampling Number of sites: 11
North Temperate Lakes LTER: Northern Highlands Stream Chemistry Survey 2006
We compared regional patterns in lake and stream biogeochemistry in the Northern Highlands Lake District (NHLD), Wisconsin, USA to ask how regional biogeochemistry differs as a function of the type of ecosystem considered (i.e., lakes versus streams); if lake-stream comparisons reveal regional patterns and processes that are not apparent from studies of a single ecosystem type; and if characteristics of streams and lakes scale similarly. Fifty-two streams were sampled using a stratified random design to determine regional distribution of 21 water chemistry variables during summer baseflow conditions. Sampling Frequency: once per site Number of sites: 52
Spatial variability in water chemistry of four Wisconsin aquatic ecosystems - High speed limnology Environmental Science and Technology datasets
Advanced sensor technology is widely used in aquatic monitoring and research. Most applications focus on temporal variability, whereas spatial variability has been challenging to document. We assess the capability of water chemistry sensors embedded in a high-speed water intake system to document spatial variability. We developed a new sensor platform to continuously samples surface water at a range of speeds (0 to > 45 km hr-1) resulting in high-density, meso-scale spatial data. Here, we archive data associated with an Environmental Science and Technology publication. Data include a single spatial survey of the following aquatic ecosystems: Lake Mendota, Allequash Creek, Pool 8 of the Upper Mississippi River, and Trout Bog. Data have been provided in three formats (raw, hydraulic-corrected, and tau-corrected).
Mississippi River spatial water chemistry Environmental Research Letters datasets
We mapped surface water chemistry along the entire length of the Upper Mississippi River (UMR) to understand spatial patterns in nitrate sources and processing. We used a sensor-based and boat-mounted sensing platform to continuously measure underway water chemistry. Measurements were linked with global positioning systems (GPS) to create maps of surface water chemistry. Here, we archive data associated with an Environmental Research Letters publication (Loken et al. 2018). Data include a single spatial survey of the entire length of the UMR (Minneapolis, Minnesota to Cairo, Illinois) in August 2015 and repeat surveys in Navigation Pool 8 (located near La Crosse, WI). Data have been provided in three formats (raw, hydraulic-corrected, and tau-corrected). Additionally, we archive laboratory chemistry data from water samples collected during the project. Sites include a range of main channel, backwaters, and tributaries. Water chemistry samples were analyzed at the North Temperate Lakes - Long Term Ecological Research facility and linked with underway sensor measurements.
Columbia River spatial water chemistry
We mapped surface water chemistry along a ~600 km segment of the Columbia River. We used a sensor-based and boat-mounted sensing platform to continuously measure underway water chemistry. Measurements were linked with global positioning systems (GPS) to create maps of surface water chemistry. Data were collected over 6 days in July 2018 and include a single longitudinal survey of the Columbia River. Data have been provided in three formats (raw, hydraulic-corrected, and tau-corrected). Additionally, we archive laboratory chemistry data from water samples collected during the project. Sites include a range of main channel, backwaters, and tributaries. Water chemistry samples were analyzed at the North Temperate Lakes - Long Term Ecological Research facility and linked with underway sensor measurements.
Spatial surface water chemistry of Lake Mendota with FLAMe: 2014-2016
We mapped surface water chemistry in Lake Mendota 39 times between 2014 and 2016. We used a sensor-based and boat-mounted sensing platform to continuously measure underway water chemistry. Measurements were linked with global positioning systems (GPS) to create maps of surface water chemistry. Data have been provided in three formats (raw, hydraulic-corrected, and tau-corrected). Dataset is used for the publication, "Large spatial and temporal variability of carbon dioxide and methane in a eutrophic lake", https://doi.org/10.1029/2019JG005186
North Temperate Lakes LTER Regional Survey Water Chemistry 2015 - current
The Northern Highlands Lake District (NHLD) is one of the few regions in the world with periodic comprehensive water chemistry data from hundreds of lakes spanning almost a century. Birge and Juday directed the first comprehensive assessment of water chemistry in the NHLD, sampling more than 600 lakes in the 1920s and 30s. These surveys have been repeated by various agencies and we now have data from the 1920s (UW), 1960s (WDNR), 1970s (EPA), 1980s (EPA), 1990s (EPA), and 2000s (NTL). The 28 lakes sampled as part of the Regional Lake Survey have been sampled by at least four of these regional surveys including the 1920s Birge and Juday sampling efforts. These 28 lakes were selected to represent a gradient of landscape position and shoreline development, both of which are important factors influencing social and ecological dynamics of lakes in the NHLD. This long-term regional dataset will lead to a greater understanding of whether and how large-scale drivers such as climate change and variability, lakeshore residential development, introductions of invasive species, or forest management have altered regional water chemistry. The regional lakes survey in 2015 followed the standard LTER protocol for standard water chemistry and biology. Samples were taken as close to solar noon as possible. Seven lakes had replicates performed, which were chosen at random.
Unveiling the potential of redox chemistry to form size tunable, high index silicon particles
<p>In the present work, the effect of changing the precursor ratio of silicon between sodium silicde and a hexacoordinated silicon complex to form various sizes of particles is studied. TEM images show the size difference between particles produced with different ratios. Particles produced with a 1:1 ratio are 45 nm in diameter and up to a 1:4 precursor ratio is used to make 230 nm particles. X-ray diffraction patterns confirm the presence of crystalline silicon for all sizes, while Raman spectroscopy shows how different degree of oxidation occurs thanks to different particle sizes, shifting the Raman peak. The surface chemistry is also studied to evidence the growth mechanism.</p>
Marcell Experimental Forest chemistry of surface water draining the S2 catchment, 1986 - ongoing
This data set is a record since 1986 of chemistry for surface water draining the S2 catchment at the Marcell Experimental Forest (MEF) in Itasca County, Minnesota. Unfiltered water is usually collected every one or two weeks as part of the long-term monitoring program of the S2 catchment. Some samples were collected more often for various other studies and are included in this data set. Samples are routinely measured for pH, specific conductivity, anions (chloride, sulfate), cations (calcium, magnesium, potassium, sodium, aluminum, iron, manganese, strontium), silicon, nutrients (ammonium, nitrate+nitrite, soluble reactive phosphorus, total nitrogen, total phosphorus), and total organic carbon. Occasionally, stable water and mercury isotopes as well as concentrations of dissolved organic carbon (DOC), bacterial respiration of dissolved organic matter, biodegradable DOC (BDOC), ferrous and ferric iron, total mercury (filtered or unfiltered), methylmercury (filtered or unfiltered), and lead were measured. Ultraviolet (UV) absorbance, a measure of water color or dissolved organic matter optical properties, was also measured for some samples. More solutes and values will be added as additional metadata are documented (pre-1986 to 1992), water samples are collected and analyzed (concentrations and isotopes), or archived water samples are analyzed for stable water isotopes. The MEF is operated and maintained by the USDA Forest Service, Northern Research Station.
IISD Experimental Lakes Area: Chemistry of LTER Lakes, 1968-2024
The IISD Experimental Lakes Area (IISD-ELA) Chemistry of LTER Lakes data package provides lake chemistry data from five reference lakes in northwestern Ontario, Canada for the years 1968-2024. This data package includes both tabular data and metadata files. The chemistry data includes the analysis of physical, nutrient, biological, inorganic, and organic parameters for long-term ecological research across lakes 114, 224, 239, 373, and 442. The dataset contains a row for each parameter measured at a specific date, lake, and depth (integrated layer or profile level). Metadata in this data package include a table of location coordinates and record counts and a PDF information sheet. The table of coordinates and counts is useful to know where the lakes and specific sampling sites are located and as an overview of data availability per lake (Lake 239 has the longest and most consistent data record). The info sheet provides additional metadata details about the dataset, including background and uses of the datasets, a data dictionary, diagrams, descriptions of methods and instruments, and additional references. The info sheet also contains a table that lists chemical parameter names and metadata used in this EDI repository alongside their equivalencies in the DataStream repository to help understand differences in naming conventions between the two parallel repository data packages. This data package is ongoing—updates will be provided as data are collected from these lakes in subsequent years. If data are not present here for a specific IISD-ELA lake that you are interested in, please get in touch with us. The data in this chemistry data package on EDI are also published in parallel at the Lake Winnipeg DataStream repository (https://doi.org/10.25976/fq3n-8207). The differences between the two are: the formatting of data and metadata (particularly how integrated sample information is organized across columns, and the differing chemical parameter names and metadata explai
Code for Random Forest models that predict pharmaceutical and water chemistry measurements in Baltimore Ecosystem Study streams
This file contains code to model the relationship between the water chemistry measurements and discharge measured as part of BES routine sampling and the pharmaceuticals measured in WY 2018. We use Random Forest models to predict 1) total (i.e., summed) concentration of the pharmaceuticals for which we screened, 2) total nutrient concentrations (TN & TP), 3) whether or not the antibiotic trimethoprim was detected in a given sample, and 4) whether or not nitrate and TP were above or below environmentally-relevant threshold concentrations. We also use RF models to predict N and P concentrations over a longer period, in order to compare models for nutrients to pharma. Code and analyses here rely on data processed in the file "BESPharma_WY2018.Rmd", published on EDI (doi:10.6073/pasta/610cb67fcbc8982c2af8ed946dce8ea5) and BES water chemistry data published on EDI (doi:10.6073/pasta/ce7f30e6013e003bfe28c5fd7d4aed23 )
Great Bay Estuary, NH/ME, Box Model Water Chemistry, Flow, Precipitation, and Seagrass Coverage Data, 2008 - 2023.
This data repository contains compiled surface water (tributary and estuarine), wet deposition, and wastewater effluent chemistry, along with discharge, precipitation totals, and monthly effluent flows necessary for the completion of solute budgets for Great Bay, a subregion of Great Bay Estuary, NH/ME, USA. These datasets are part of on-going monitoring programs in the Great Bay Estuary and Lamprey River Hydrological Observatory. A subset of the monitoring data for the 2008 to 2023 period was compiled. The tributary and estuarine monitoring data were requested from the NH Department of Environmental Services Environmental Monitoring Database as part of the Tidal Tributary and Estuary Water Quality Monitoring Programs. The wet deposition chemistry record is maintained as part of the Lamprey River Hydrologic Observatory. Wastewater effluent chemistry was downloaded from the EPA's Enforcement and Compliance History Online Database. The annual (1996 - 2023) seagrass coverage dataset for Great Bay Estuary reflects coverage of Zostera marina seagrass only and was compiled from annual monitoring reports. Mean daily instantaneous discharge data for the three tidal tributaries used in the load calculations are available from the USGS National Water Information System. Hourly precipitation volume data for the Durham, NH SSW station are available from the NCDC U.S. Climate Reference Network, with minor hourly gaps filled using the University of New Hampshire Durham weather station (https://www.weather.unh.edu).
High-frequency time series of inorganic carbon chemistry in the Upper Clark Fork River (Montana, USA) during the summer of 2021.
This dataset was collected in the Upper Clark Fork River, MT from July to August in 2021. The dataset contains high-frequency measurements of dissolved oxygen, alkalinity, partial pressure of carbon dioxide and other environmental variables.
Water chemistry time series for Beaverdam Reservoir, Carvins Cove Reservoir, Falling Creek Reservoir, Gatewood Reservoir, and Spring Hollow Reservoir in southwestern Virginia, USA 2013-2024
Depth profiles of dissolved organic and inorganic carbon and total and dissolved nitrogen and phosphorus were sampled from 2013-2024 in five drinking water reservoirs in southwestern Virginia, USA. The five drinking water reservoirs are: Beaverdam Reservoir (Vinton, Virginia), Carvins Cove Reservoir (Roanoke, Virginia), Falling Creek Reservoir (Vinton, Virginia), Gatewood Reservoir (Pulaski, Virginia), and Spring Hollow Reservoir (Salem, Virginia). Beaverdam, Carvins Cove, Falling Creek, and Spring Hollow Reservoirs are owned and operated by the Western Virginia Water Authority as primary or secondary drinking water sources for Roanoke, Virginia, and Gatewood Reservoir is a drinking water source for the town of Pulaski, Virginia. The dataset consists of depth profiles of water chemistry samples measured at the deepest site of each reservoir adjacent to the dam. Additional water chemistry samples were collected at a gauged weir on Falling Creek Reservoir's primary inflow tributary, as well as multiple upstream, inflow, and outflow sites at Falling Creek Reservoir 2014-2024 and Beaverdam Reservoir in 2019, 2020, and 2022. Inflow sites at Carvins Cove Reservoir were sampled from 2020-2024, and additional within-reservoir sites were sampled in 2021-2024. The water column samples at Falling Creek Reservoir and Beaverdam Reservoir were collected approximately fortnightly from March-April, weekly from May-October, and monthly from November-February. Water column samples at Carvins Cove Reservoir were collected approximately fortnightly from May-August in most years, and approximately fortnightly from 2014-2016 in Gatewood and Spring Hollow Reservoirs, though sampling frequency and duration varied among reservoirs and years. A few additional samples collected in 2025 from Falling Creek Reservoir and Carvins Cove Reservoir are included in this dataset as they were analyzed with 2024 samples.
Nutrient amendment effects on phytoplankton, water chemistry, and cyanotoxins in the 2018 Large-Scale Mesocosm Experiment at the University of Kansas Field Station
This dataset includes water physicochemical parameters, phytoplankton community composition, and cyanobacteria metabolites collected during a 21-day nutrient amendment experiment conducted from 23 July to 13 August 2018 at the University of Kansas Biological Station, Lawrence, KS, United States (39.049674°N, 95.190777°W). The experiment was performed using 18 large-scale, closed-bottom fiberglass tanks (volume: 11,000 L; height: 1.25 m; diameter: 3 m). Three tanks served as ambient controls (CON), while the others received one of the following nutrient treatments: nitrogen only (280 µM) as either ammonium chloride (NH4) or sodium nitrate (NO3); nitrogen (280 µM) plus phosphorus (200 µM) as either ammonium chloride + dipotassium phosphate (NHP) or sodium nitrate + dipotassium phosphate (NOP); and phosphorus only (200 µM) as dipotassium phosphate (P). Each tank received an initial nutrient dose on Day 0.5, followed by weekly additions of 20% of the initial amendment to maintain treatment conditions. All data were quality controlled to correct basic errors and to remove measurements outside the manufacturer’s standard operational ranges.
Summer water chemistry, high frequency sensors, zooplankton and benthic macroinvertebrate community composition, periphyton, fish, and macrophyte biomass, along with lake metabolism and greenhouse gas dynamics in six experimental ponds in central Iowa, USA (2020)
This data product contains physical, chemical, and biological data ranging from the minute to daily to weekly scale in six artificial ponds (400 square meter surface area, 2m depth) in central Iowa (USA) 2020. Ponds were paired into three sets of treatment and reference with treatment ponds receiving two nutrient pulses designed to increase ambient phosphorus concentrations ~ 3 - 5%. Nitrogen and phosphorus were added as NH4NO3 and H3PO4, respectively, at a 24:1 molar ratio. The first nutrient pulse occurred on Julian day of year (DOY) 176 corresponding to a 3% increase and the second nutrient pulse occurred on DOY 211 to a 5% increase. Each treatment-reference set had a different food web structure established ranging between low, intermediate, and high complexity based on trophic connectivity and food chain length. Added to this data package is a document titled "2020 Iowa State University Horticultural Farm Experimental Ponds Nutrient Addition Experiment". For experimental set up, context, and a summary table of the data tables archived herein with available variables please review this document. It is added to aid in successful interpretation and to increase ease-of-use. Please email Tyler Butts (tyler.james.butts@gmail.com) for any and all questions regarding context or use of this dataset!
Stream metabolism estimates and surface water chemistry in Glenbrook Creek (NV) and Blackwood Creek (CA) in the Lake Tahoe Basin, 2021-2024
The goal of this project was to develop a process-based understanding of how in-stream productivity and nitrogen dynamics respond to hydroclimatic volatility. We used a combined approach of high-frequency sensor deployment and maintenance, ecosystem metabolism modeling, and routine monitoring of water chemistry and other parameters. The data we collected as part of this project demonstrate how variable ecosystem productivity is in time and space in within and among mountain streams. Although maintenance of the sensor arrays during the exceptionally wet winter of 2023 was challenging, we were able to estimate a time series of stream metabolism within the upper and lower reaches of two streams with different basin characteristics and through hydroclimatic conditions (2021 to 2024). Throughout this project we: 1. We generated four years of daily estimates of ecosystem metabolism (gross primary productivity, ecosystem respiration, and net ecosystem productivity) from upper and lower reach stations on both the east and west shores of the Lake Tahoe Basin. 2. We measured ammonium (NH4+) and nitrate (NO3-) concentrations in surface water and sediment samples from both Glenbrook and Blackwood creeks. 3. We modeled nitrogen supply and demand dynamics at each reach location. See this git code repository for project analysis: https://github.com/kellyloria/Mountain-stream-biogeochem-and-productivity.
Arctic LTER Streams Chemistry Toolik Field Station, Alaska 1978 to 2019.
Since 1983, the Streams Project at the Toolik Field Station has monitored physical, chemical, and biological parameters in a 5-km, fourth-order reach of the Kuparuk River near its intersection with the Dalton Highway and the Trans-Alaska Pipeline. In 1989, similar studies were begun on a 3.5-km, third-order reach of a second stream, Oksrukuyik Creek. In each river, physical conditions (such as discharge and temperature), nutrient levels, primary production, insects, and fishes are monitored throughout the summer. Also, we conduct experimental fertilization of the Kuparuk River and Oksrukuyik Creek to determine the effects of added phosphorus and nitrogen on primary productivity, insect communities, and fish growth in arctic rivers. The Oksrukuyik Creek has not been fertilized since 1996. The Kuparuk River received phosphorus additions from 1983 through 2016. Station sites are relative distance from the original nutrient drippers for both the Kuparuk and Oksrukuyik. Kuparuk stations include sites in a reference, recovery, and fertilized reach. Reaches were defined based on the location of nutrient addition (see methods).
Bonanza Creek LTER: Stream water chemistry from 2001 to Present in the Caribou Poker Creek Research Watershed near Fairbanks, Alaska
The hydrogeochemistry of nine streams in the Caribou-Poker Creeks Research Watershed (CPCRW) during the summers of 2002-2006. In summer 2005, Boston Creek, which is located ca. 20 km east of the CPCRW was sampled. The Boston Creek watershed was extensively burned during the Boundary Fire of 2004. Samples were analyzed for Ca, Mg, Na, K, NH4+, Si, Cl, NO3, SO4, DOC, TDN, DIC, SUVA, pH and conductivity.
Mangrove Soil Chemistry Shark River Slough and Taylor Slough, Everglades National Park (FCE), from December 2000 to May 23, 2002
Physicochemical variables in soils from stations SRS-4-6 and TS/Ph6-8 were sampled in the period December 2000-May 2002. Salinity, temperature, pH, Redox, and sulfide concentrations were measured in 4 stations (sampling units) located in adjacent 10 x 10 m plots (in a 20 x 20 m block). Statistical analyses are in progress.
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.