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.

138

datasets available to search

ShareScore release 0.7.1

Dataset results

138 results for “CH4”

Learn how ShareScore rates datasets ↗

zenodo40/100

TCOM-CH4: TOMCAT CTM and Occultation Measurements based daily zonal stratospheric methane profile dataset [1991-2021] constructed using machine-learning

Methodology:   he TOMCAT simulation was conducted at a T64L32 resolution, consistent with previous work by Dhomse et al. (2021, 2022), covering the period from 2000 to 2024. These simulations utilized ERA-5 reanalysis data. <h3>CH4 Profile Processing and Bias Correction</h3> Collocated CH4 profiles are organized into five distinct latitude bins: <ul> <li> NH polar: 90∘N - 50∘N </li> <li> NH mid-lat: 20∘N - 70∘N </li> <li> Tropics: 40∘S - 40∘N </li> <li> SH mid-lat: 70∘S - 20∘S </li> <li> SH polar: 90∘S - 50∘S </li> </ul> Initially, differences between TOMCAT and satellite measurements (primarily ACE-FTS data) are calculated for each zonal bin across 51 height levels (ranging from 10,km to 60,km). It is important to note that unlike previous versions that might have used both HALOE and ACE measurements, this version exclusively utilizes ACE-FTS data, which is why the dataset starts from 2000. Separate XGBoost regression models are then trained for these CH4 differences at each height level within a given latitude bin. These trained models are subsequently used to estimate CH4 bias corrections for all daytime TOMCAT grids (9132 days), specifically sampled at 1:30 PM local time at the equator. This yields grid-specific bias corrections that are applied to the original TOMCAT profiles. Height-resolved CH4 profile data are then interpolated onto 28 standard pressure levels (from 300,hPa to 0.1,hPa), using pressure levels directly from the TOMCAT grids. For overlapping latitude bins, values are averaged to ensure smoother fields near boundary regions. <h3>Data Files</h3> The dataset includes two files containing daily mean zonal mean CH4 profiles: <ul> <li> <code>zmch4_TCOM_hlev_T2Dz_2000-2024_V1.1.nc</code>: Contains height level data (10,km to 60,km). </li> <li> <code>zmch4_TCOM_plev_T2Dz_2000-2024_V1.1.nc</code>: Contains pressure level data (300,hPa to 0.1,hPa). </li> </ul> <h3>Reference Publication</h3> This methodology, incorporating only ACE-FTS data and various minor algorithmic developments, is based on the following publication: Dhomse, S. S. and Chipperfield, M. P.: Using machine learning to construct TOMCAT model and occultation measurement-based stratospheric methane (TCOM-CH4) and nitrous oxide (TCOM-N2O) profile data sets, Earth Syst. Sci. Data, 15, 5105–5120, <a title="null" href="https://doi.org/10.5194/essd-15-5105-2023">https://doi.org/10.5194/essd-15-5105-2023</a>, 2023.

opencc-by-4.0Nov 2022View details →

zenodo40/100

3D simulations of TRAPPIST-1e with varying CO2, CH4 and haze profiles [dataset]

Dataset of 3D simulations of TRAPPIST-1e with varying CO2, CH4 and haze profiles Using a 3D General Circulation Model, the Unified Model, we present results from simulations of a tidally locked TRAPPIST-1e with varying CO2 and CH4 gas concentrations, and their corresponding prescribed spherical haze profiles. Our results show that the presence of CO2 leads to a warmer atmosphere globally due to its greenhouse effect, with the increase of surface temperature on the day side surface up to ∼14.1 K, and on the night side up to ∼21.2 K. The presence of CH4 can lead to a peak in the change of surface temperature on the day side due to the balance of tropospheric warming and stratospheric cooling. A thin layer of haze, formed when CH4/CO2 = 0.1, leads to a day side warming of ∼4.9 K due to a change in the water vapour and cloud distribution. The haze reaches an optical threshold thickness when CH4/CO2 ∼0.4 beyond which the day side mean surface temperature does not vary much. The planet is more favourable to habitability (surface temperature above 273.15 K) when pCO2 is high, pCH4 is low and the haze layer is thin. The effect of CO2, CH4 and haze on the day side is similar to that for a rapidly-rotating planet. On the contrary, their effect on the night side depends on the wind structure and the wind speed in the simulation.

opencc-by-4.0Nov 2023View details →

zenodo40/100

Bayesian Analysis for Remote Biosignature Identification on exoEarths (BARBIE) III: Introducing the KEN; Data for CH4

We present all of the data across our SNR and abundance study for the molecule H2O for an exoEarth twin. The wavelength range is from 0.8-1.5 micron, with 25 evenly spaced 20%, 30%, and 40% bandpasses in this range. The SNR ranges from 3-20. We present the lower and upper wavelength per bandpass, the input CH4 value (abundance case), the retrieved CH4 value (presented as the log10(VMR)), the lower and upper limits of the 68% credible region (presented as the log10(VMR)), and the log-Bayes factor for CH4. For more information about how these were calculated, please see Bayesian Analysis for Remote Biosignature Identification on exoEarths (BARBIE) III: Introducing the KEN, accepted and currently available on arXiv.  To open this csv as a Pandas dataframe, use the following command: your_dataframe_name = pd.read_csv(f'zenodo_table.csv', dtype={'Input CH4': str})

opencc-by-4.0Sep 2024View details →

zenodo40/100

Data published in manuscript "Effects of reversal of water flow in an Arctic floodplain river on fluvial emissions of CO2 and CH4" by Castro-Morales et al.

This data is published in the manuscript: Castro-Morales, K., Canning, A., Körtzinger, A., Göckede, M., Küsel, K., et al. (2022). Effects of reversal of water flow in an Arctic floodplain river on fluvial emissions of CO2 and CH4. Journal of Geophysical Research: Biogeosciences, 127, e2021JG006485. <a href="https://doi.org/10.1029/2021JG006485">https://doi.org/10.1029/2021JG006485</a>. The data contains the water properties and gases data measured at a site in Ambolikha River, meteorological data measured at an eddy covariance tower located in the neighbor floodplain, and data from the analysis of dissolved organic matter in river water samples. The data was collected between 26 June, 2019 and 02 August, 2019. This folder contains four data files and the file "README_Data_access_Castro-Morales_etal_Ambolikha_River.txt" should be read before accessing the data. The authors recommend downloading Version 2.0 because it is the most up to date data. For questions contact the main and corresponding author Dr. Karel Castro-Morales at: karel.castro.morales@uni-jena.de

opencc-by-4.0Dec 2021View details →

zenodo40/100

CH4 isotopic signatures of emissions from oil and gas extraction sites in Romania

Dataset linked to the manuscript "CH4 isotopic signatures of emissions from oil and gas extraction sites in Romania", submitted to Elementa: Science of the Anthropocene. Abstract: Methane (CH4) emissions to the atmosphere from the oil and gas sector in Romania remain highly uncertain, despite their relevance for the European Union’s goals to reduce greenhouse gas emissions. Measurements of the isotopic composition of CH4 can be used for source attribution, which is important in top-down studies of emissions from extended areas. We performed isotope measurements of CH4 in atmospheric air samples collected from an aircraft (24 locations) and ground vehicles (83 locations), around oil and gas production sites in Romania, with focus on the Romanian Plain. Ethane to methane ratios (C2:C1) were derived at 412 locations of the same fossil fuel activity clusters. The resulting isotopic signals (δ13C and δ2H in CH4) covered a wide range of values, indicating mainly thermogenic gas sources (associated with oil production) in the Romanian Plain, mostly in Prahova county (δ13C from -67.8 to -22.4 per mille V-PDB; δ2H from -255 to -138 per mille V-SMOW) but also the presence of some natural gas reservoirs of microbial origin in Dolj, Ialomia, Prahova and likely Teleorman counties. The classification based on C2:C1 ratios was generally in agreement with the one based on CH4 isotopic composition, and confirmed the characterisation of the gas origin. In several cases, the CH4 enhancements sampled from the aircraft could directly be linked to the underlying production clusters using wind data. The combination of δ13C and δ2H signals determined on these samples confirm that the oil and gas production sector is the main source of CH4 emissions in the target areas.

opencc-by-4.0Oct 2021View details →

zenodo40/100

MIROC4-ACTM CH4 inversion fluxes (2000-2016)

This version of inversion is prepared by Dmitry Belikov, Chiba University. Results updated from Chandra et al. (Chandra et al., 2021) Methods detailed in Emissions from the Oil and Gas Sectors, Coal Mining and Ruminant Farming Drive Methane Growth over the Past Three Decades <a href="https://www.jstage.jst.go.jp/search/global/_search/-char/en?item=8&word=Naveen+CHANDRA">Naveen CHANDRA</a>, <a href="https://www.jstage.jst.go.jp/search/global/_search/-char/en?item=8&word=Prabir+K.+PATRA">Prabir K. PATRA</a>, <a href="https://www.jstage.jst.go.jp/search/global/_search/-char/en?item=8&word=Jagat+S.+H.+BISHT">Jagat S. H. BISHT</a>, <a href="https://www.jstage.jst.go.jp/search/global/_search/-char/en?item=8&word=Akihiko+ITO">Akihiko ITO</a>, <a href="https://www.jstage.jst.go.jp/search/global/_search/-char/en?item=8&word=Taku+UMEZAWA">Taku UMEZAWA</a>, <a href="https://www.jstage.jst.go.jp/search/global/_search/-char/en?item=8&word=Nobuko+SAIGUSA">Nobuko SAIGUSA</a>, <a href="https://www.jstage.jst.go.jp/search/global/_search/-char/en?item=8&word=Shinji+MORIMOTO">Shinji MORIMOTO</a>, <a href="https://www.jstage.jst.go.jp/search/global/_search/-char/en?item=8&word=Shuji+AOKI">Shuji AOKI</a>, <a href="https://www.jstage.jst.go.jp/search/global/_search/-char/en?item=8&word=Greet+JANSSENS-MAENHOUT">Greet JANSSENS-MAENHOUT</a>, <a href="https://www.jstage.jst.go.jp/search/global/_search/-char/en?item=8&word=Ryo+FUJITA">Ryo FUJITA</a>, <a href="https://www.jstage.jst.go.jp/search/global/_search/-char/en?item=8&word=Masayuki+TAKIGAWA">Masayuki TAKIGAWA</a>, <a href="https://www.jstage.jst.go.jp/search/global/_search/-char/en?item=8&word=Shingo+WATANABE">Shingo WATANABE</a>, <a href="https://www.jstage.jst.go.jp/search/global/_search/-char/en?item=8&word=Naoko+SAITOH">Naoko SAITOH</a>, <a href="https://www.jstage.jst.go.jp/search/global/_search/-char/en?item=8&word=Josep+G.+CANADELL">Josep G. CANADELL</a> DOI <a href="https://doi.org/10.2151/jmsj.2021-015">https://doi.org/10.2151/jmsj.2021-015</a>

opencc-by-4.0Mar 2022View details →

zenodo40/100

Electron Accepting Capacities of a wide variety of peat materials from around the Globe similarly explain CO2 and CH4 production

In peat soils the availability of terminal electron acceptors (TEAs), both inorganic and organic, largely determines the ratio of carbon dioxide to methane formation under waterlogged, anoxic conditions. The redox properties of peat organic matter and their relationship with anoxic carbon mineralization are yet only investigated for a limited amount of peat and reference materials, although electron accepting capacities of organic matter (EACOM) largely predominate over canonical inorganic TEAs in peatlands. To address this knowledge gap, we incubated 60 peat samples from four different depths of 15 sites located in five major peatland regions (including Germany, Sweden, Russia, France and Chile) distributed around the globe covering a variety of both bog and fen type samples and characterized their capacities to serve as electron acceptors for anaerobic carbon dioxide production. The dataset consists of a wide variety of recorded and calculated variables for a 56-day incubation of those samples. These variables include the formation and rates of methane, carbon dioxide, electron acceptor capacities and electron donator capacities at two different times, data on stable isotopes in delta notation (such as nitrogen, carbon and sulfur), molar element ratios for carbon/nitrogen, carbon/sulfur and nitrogen/phosphorus and elemental contents like silicon, phosphorus, sulfur, calcium and iron as well as specific fourier transformed infrared spectroscopy ratios regarding the ratios of polysaccharides and aromatic structures. The dataset was created mostly in 2019, with some additional measurements carried out in 2020 and 2021.

opencc-by-4.0Apr 2022View details →

zenodo40/100

TOMCAT model data & IASI satellite data of O3, CO, H2O, CH4 and OH/derived OH for 2010 and 2017

Monthly mean data of ozone (O3), carbon monoxide (CO), water vapour (H2O), methane (CH4) and the hydroxyl radical (OH) for 2010 and 2017. Model data is from the 3D chemical transport model TOMCAT (Chipperfield, 2006). Satellite observations are from the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp-A satellite and retrieved using schemes developed by the Rutherford Appleton Laboratory (RAL). The Ch4 is from RAL's CH4 retrieval scheme (Siddans et al. 2020) and the O3, CO and H2O retrievals are from the extended version of RAL’s Infrared and Microwave Sounding (IMS-extended) scheme (Pope et al. 2021).  Full description of the data can be found in Pimlott et al. (2022) (preprint: https://doi.org/10.5194/acp-2022-79) which has now been accepted for publication in ACP.

opencc-by-4.0Jul 2022View details →

zenodo40/100

Chamber flux data (CH4 , CO2) from Finland (1991 -1993) originally used in Nykänen et al. GBC, 12(1), 53 - 69, 1988,

Chamber flux (CH4 , CO2), temperature, water table and vegetaion data from Särkkä (62° 48'; 30° 58') and Lakkasuo (61° 47'; 24°16') from Finland (1991 -1993). These are natural and drained site data few decades after drainage nearby each other.  This data was originally used in following articles:  <table> <tbody> <tr> <td>Chamber measuremets CH4, CO2   </td> </tr> <tr> <td>Martikainen P.J., Nykänen H., Alm J. and Silvola J. 1995. Changes in fluxes of carbon dioxide, methane and nitrous oxide due to forest drainage of mire sites of different trophy. Plant and Soil 168/169: 571-577.</td> </tr> <tr> <td>Martikainen P.J., Nykänen H., Crill P. and Silvola J. 1993. Effect of a lowered water table on nitrous oxide fluxes from northern peatlands. Nature 366 (4): 51-53.</td> </tr> <tr> <td>Martikainen P.J., Nykänen H., Crill P. and Silvola J. 1993. The effect of changing water table on methane fluxes at two Finnish mire sites. Suo Mires and Peat 43: 237-240.</td> </tr> <tr> <td>Nykänen H., Alm J., Lang K., Silvola J. and Martikainen P.J. 1995. Emissions of CH4, N2O and CO2 from a virgin fen and a fen drained for grassland in Finland. Journal of Biogeography 22: 351-357.</td> </tr> <tr> <td>Descriptions: Nykänen H., Alm J., Silvola J. and Tolonen K., Martikainen P.J. 1998. Methane fluxes on boreal peatlands of different fertility and the effect of long-term experimental lowering of the water table on flux rates. Global Biogeochemical Cycles 12: 53-69.</td> </tr> </tbody> </table>

opencc-by-4.0Aug 2022View details →

zenodo40/100

Comparison of observation- and inventory- based CH4 emissions for eight large global emitters

CoCO2 (https://coco2-project.eu/) is a scientific collaborative effort funded by the H2020 European Commissions, grant number 958927. This synthesis has been originally based on data and country specific plots from previous VERIFY project, for the EU27: https://webportals.ipsl.fr/VERIFY/FactSheets, v1.28 and on the WP8 deliverable Reports D8.1 (https://coco2-project.eu/node/333), D8.2 (https://coco2-project.eu/node/360) and D8.3 (https://coco2-project.eu/index.php/node/406) from the CoCO2 project website. This dataset is updated after we received two review comments. Each spreadsheet contains the CH4 data behind the manuscript figures, both as time series, mean values and uncertainties (min, max ranges). Units are mentioned for each figure. For the gridded figures data should be asked directly from the data providers.

opencc-by-4.0Jul 2024View details →

zenodo40/100

Data-base of CH4 and ancillary data in the Belgian Coastal Zone (2017, 2018, 2019)

Data-base of CH4 and ancillary data (salinity, water temperature, chlorophyll-a concentration) in the Belgian Coastal Zone (2017, 2018, 2019)

opencc-by-4.0Oct 2019View details →

zenodo40/100

Techno Economic Analysis of Biogas Purification by Methane and Acetate Manufacturing CO2 to CH4 2024 SuppInfo

Techno Economic Analysis calculations for manuscript of Biogas Purification by Methane and Acetate Manufacturing to convert CO2 to CH4: Wastewater treatment plants have two persistent financial and energetic drains, the carbon dioxide content of biogas, which limits its commercial sale, and the presence of trace organics in the wastewater effluent, which damages the aquatic ecosystem. Biogas is a renewable methane resource that is underutilized due to the variable CO2 content (~40%). Biogas is energy intensive to purify and limited by the economy of scale (>8.85 GJ/hour) to large-scale purification methods, thus small-scale processes require development. Electrocatalytic microbes native to wastewater have been shown to convert CO2 to CH4 and acetate, however complete conversion of the CO2 content to CH4 is energy intensive. Here we show a low power bioelectrochemical fuel cell design to purify biogas to pipeline quality methane (98%), manufacture methane and/or acetate, and remove trace organics, using HCO3- as the transport charge carrier from dissolved CO2 from the biogas through an anion exchange membrane. This decreased the power required to separate CO2 from methane in biogas on a molar basis, resulting in a net energy recovery similar to current industrial systems. Magnesium anode use resulted in an energy positive system. Tests evaluated the influence of cathode potential on the current density, HCO3- ion flux and the rates and efficiencies of methane production, resulting in optimization at -0.7V vs Standard Hydrogen Electrode (SHE). A techno-economic analysis modeled a positive return on investment for scaled-up production to purify small biogas streams that are otherwise financially unrecoverable. Carbon sequestration by production of methane, acetate and solid fertilizers demonstrated profitable and energy efficient waste-to-resource conversion.

opencc-by-nc-4.0Aug 2024View details →

zenodo40/100

Soil and understory CO2 respiration, CH4, and N2O fluxes, tree biomass and litter, and soil carbon stock after a long-term N fertilization of a Scots pine forest in Finland

Data of forest soil respiration, soil and undestory respiration, CH4, and N2O fluxes, soil temperature and volumetric water content (Data_Karstula_GHG_temp.swc.csv), continuous soil temperature and moisture data (Data_Karstula_measured_temperature_2021_2023.csv, Data_Karstula_measured_moisture_2021_2023.csv), forest biomass and litter (Data_Karstula_total_biomass_litter.csv, Data_Karstula_measured_litter_2021_2023.csv), and soil C stocks (Data_Karstula_soc.csv) from the boreal Scots pine forest site Karstula after a long-term N fertilization in Finland (62°54'43.343"N; 24°34'16.021"E). The dataset is used for the publication "Tupek et al. : Lower sensitivity of microbial respiration to soil moisture after long-term N fertilization increases soil carbon retention in a Scots pine forest. 2024".

opencc-by-4.0Oct 2024View details →

zenodo40/100

Incubation data, CO2 and CH4 flux data and soil properties of thaw slump soils on Kurungnakh, Lena Delta in July 2016 and July 2019

CO2 and CH4 rates from incubations and potential fluxes: This dataset contains rates of CO2 and CH4 production and the potential CO2 and CH4 emission rates calculated from these incubation fluxes in situ CO2 and CH4 chamber fluxes: This dataset contains CO2 and CH4 fluxes measured with closed chambers from different sites on Kurungnakh in July 2016 and July 2019 simulated soil temperature and modelled CO2 fluxes: This dataset contains daily mean soil temperature data simulated with JSBACH for 2016 and the annual CO2 fluxes simulated with a Q10 model and the Introductory Carbon Balance Model (ICBM) thaw depth, TOC in active layer, soil temperature 2016: This dataset contains the thaw depth, TOC pools in the active layer and the soil temperature during the measurement period in July 2016 thaw depth, TOC in active layer, soil temperature 2019: This dataset contains the thaw depth, TOC pools in the active layer and the soil temperature during the measurement period in July 2019

opencc-by-4.0Oct 2021View details →

zenodo40/100

N2O and CH4 fluxes/concentrations reported in Krauss et al. 2017

The two data sheets: A) Kraussetal_2017_N2O-CH4_Gas_concentration_per_Sampling B) Kraussetal_2017_N2O-CH4_Fluxes contain greenhouse gas concentrations and fluxes published in Krauss, M., Ruser, R., Müller, T., Hansen, S., Mäder, P., Gattinger, A. (2017) Impact of reduced tillage on greenhouse gas emissions and soil carbon stocks in an organic grass-clover ley - winter wheat cropping sequence. Agriculture, Ecosystems & Environment, 239, p. 324-333 Detailed description about the sampling campaign, the trial and the calculation procedures can be found in the publication. Details about the data structure can be found in a README sheet in the data file.

opencc-by-4.0Nov 2018View details →

zenodo40/100

Data-set of the partial pressure of CO2, dissolved concentrations of CH4, N2O, NO3-, NO2- and NH4+, specific conductivity and water temperature in the rivers and streams of the Napo River basin in Ecuador (2018, 2019, 2020, 2021)

Data-set consists of two files: - data_ghgs.xlsx : Time-stamped and georeferenced data-set of the partial pressure of CO2 (pCO2 in ppm), dissolved CH4 concentration (CH4 in nmol/L), dissolved N2O concentration (N2O in nmol/L), specific (Sp.) conductivity (in µS/cm), water temperature (in °C), dissolved nitrate concentration (NO3- in µmol/L), dissolved nitrite concentration (NO2- in µmol/L), and dissolved ammonia concentration (NH4+ in µmol/L) in the rivers and streams of the Napo River basin in Ecuador (October 2018 and 2019, January 2019 and 2020, April 2019 and 2021, July 2019 and 2020). Gas measurements were made by headspace equilibration directly in the field with a infra-red gas analyser for CO2 and in the lab with a gas chromatograph for CH4 and N2O. NO3-, NO2- and NH4+ were measured with standard colometric procedures. Sampling and analytical protocols are provided here <a href="https://doi.org/10.5194/bg-16-3801-2019">https://doi.org/10.5194/bg-16-3801-2019</a> - RiverATLAS.xlsx: hydro-environmental data for the sampled streams extracted from RiverATLAS (https://www.nature.com/articles/s41597-019-0300-6). Data codes and units are available here: https://data.hydrosheds.org/file/technical-documentation/HydroATLAS_TechDoc_v10_1.pdf First column of each of the two files provides station ID allowing to merge both data-sets.

opencc-by-4.0May 2022View details →

zenodo40/100

Montly flux of TPM, CO2, CO and CH4 for the south of the Amazon Basin during 2020, 2021 and 2022.

Base de dados da emissão média mensal do fluxo dos materiais TPM, CO2, CO e CH4 para o sul da Bacia Amazônica durante os anos 2020,2021 e 2022. Gerada a partir dos dados do instrumento ABI a bordo do satélite GOES-East, dos coeficientes de emissão do inventário FEER e fatores de emissão específicos do bioma de floresta tropical.   Database of the monthly average emission flux of the materials TPM, CO2, CO, and CH4 for the southern Amazon Basin during the years 2020, 2021, and 2022. Generated from data obtained by the ABI instrument on board the GOES-East satellite, using emission coefficients from the FEER inventory and biome-specific emission factors for tropical forests.

opencc-by-4.0Aug 2023View details →

dryad40/100

Modelling system for computing the tropospheric O3 and CH4 perturbations from South Korean Emissions (KORUS-AQ period)

Open the record for dataset details and reuse information.

publicJan 2026View details →

edi40/100

CH4 Uptake by Forest Soils at two sites in the Northeastern US

Soil to atmosphere net CH4 fluxes were measured at two different sites in order to assess the long term effects of environmental change on soil CH4 uptake. This data set includes samples collected between 1998-2016 at the Baltimore Ecosystem Study, MD and Hubbard Brook Experimental Forest, NH from 2002-2015. These data were assembled and are published here in support of the following paper: Ni, X. and P.M. Groffman. 2018. Decines in methane uptake in forest soils. Proceedings of the National Academies of Science of the United States of America: www.pnas.org/cgi/doi/10.1073/pnas.1807377115. This datset is a derived from two datasets in this same repository: Groffman P. 2017. Soil atmosphere fluxes of carbon dioxide, nitrous oxide and methane. Environmental Data Initiative. https://doi.org/10.6073/pasta/d2d727c9638c0fc23bd5be55a767cfb5 Groffman P. 2016. Forest soil:atmosphere fluxes of carbon dioxide, nitrous oxide and methane at the Hubbard Brook Experimental Forest, 1997- present. Environmental Data Initiative. https://doi.org/10.6073/pasta/9d017f1a32cba6788d968dc03632ee03.

openCC (other)Jul 2018View details →

zenodo36/100

Dataset: Ideas and perspectives: patterns of soil CO2, CH4, and N2O fluxes along an altitudinal gradient - a pilot study from an Ecuadorian neotropical montane forest

These datasets contain data from (i) soil CO2, CH4, and N2O flux measurements (ii) physicochemical soil properties, and (iii) soil temperature and moisture of four tropical forests located on the western flanks of the Andes in northern Ecuador. A manuscript using these datasets has been submitted to Biogeosciences under the title: "Ideas and perspectives:  patterns of soil CO2, CH4, and N2O fluxes along an altitudinal gradient - a pilot study from an Ecuadorian neotropical montane forest".

opencc-by-4.0Jan 2021View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated 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.

allen-brain-atlas

neuroscienceopenDocumentation, web resources, and API references are available online.

Last verified 2026-04-30Open record

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.

abode-home-cage

behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.

Last verified 2026-04-30Open record

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.

dandi-nwb

electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.

Last verified 2026-04-30Open record

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.

ibl

behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.

Last verified 2026-04-29Open record

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.

openneuro

neuroscienceopenPublished datasets are available on demand over the internet.

Last verified 2026-04-29Open record