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Dataset results
428 results for “data standards”
Standardized NEON organismal data (neonDivData)
To standardize NEON organismal data for major taxonomic groups, we first systematically reviewed NEON’s documentations for each taxonomic group. We then discussed as a group and with NEON staff to decide how to wrangle and standardize NEON organismal data. See Li et al. 2022 for more details. All R code to process NEON data products can be obtained through the R package ‘ecocomDP’. Once the data are in ecocomDP format, we further processed them to convert them into long data frames with code on Github (https://github.com/daijiang/neonDivData/tree/master/data-raw), which is also archived here.
Precipitation data from a standard can rain gauge at the LTER weather station, Jornada Basin, southern New Mexico, USA, 1992-ongoing
This data package contains precipitation measurements collected from a "dipstick" rain gauge (NOAA standard can type) at the LTER Weather Station in the Jornada Basin, southern New Mexico, USA. The primary purpose of this data set is to validate the LTER Weather Station tipping bucket rain gauge data. The dipstick rain gauge (DSRG) data is measured at least weekly during scheduled maintenance trips to the LTER Weather Station to maintain the evaporation pan water levels. During the summer months this may be twice a week. Additionally, DSRG data is collected after any rain event that requires the collection of the Wetfall/Dryfall precipitation buckets which are located about 10 meters from the DSRG. This is usually any amount greater than 0.02 inches. DSRG data is also collected after very small events when personnel are in the vicinity. Rain gauge records at this gauge began in 1992 and the study is ongoing.
Standard meteorology and ancillary data from the Tromble Weir experimental watershed tower at the Jornada Basin LTER site, 2010-ongoing
This data package contains 30-minute standard meteorology and ancillary data collected at an eddy covariance tower in the Tromble Weir Watershed area of the Jornada Basin in southern New Mexico, USA. These data are used to quantify the water and energy balances in a small experimental watershed, including observational studies to calculate groundwater recharge as a water balance residual, to build relations between soil moisture state and ET flux, and to quantify land-atmosphere interactions and improve our understanding of the eddy covariance method. Additionally, they have been used in modeling studies as a validation of model performance. This file presents the ancillary data collected at the eddy covariance tower, excluding the 20Hz flux measurements that are archived at AmeriFlux (site US-Jo2; http://ameriflux.lbl.gov/sites/siteinfo/US-Jo2). This includes soil moisture and temperature at 4 depths, air temperature and pressure, humidity and vapor pressure, ground heat flux, incoming and outgoing longwave and shortwave radiation, photosynthetically active radiation for a subset of the study period, and surface soil temperature. Instrument descriptions and detailed procedures are found in the references listed in the Methods section of this package. This is an ongoing dataset that will be updated annually.
FTICR MS data for standards and mixtures for quantitative peak intensity investigation
<p>This upload contains raw (Bruker .d format) FTICR mass spectrometry data (direct infusion, negative mode ESI) for standards in different mixtures and matrices for the purposes of investigating the (non)quantitative nature of the data. <br>Processed data (Excel format), and Python scripts used for data processing are also included. </p> <p>Note - the Python scripts used CoreMS version prior to V2.0 for analysis - to re-run these scripts with a more recent release likely requires syntax updates. </p>
Data for: A tool based on the Industry Foundation Classes standard for dynamic data collection and automatic generation of Building Automation Control Networks
<p>This dataset shows the results obtained for a case study at TRL4 for the research paper title <em><strong>A tool based on the Industry Foundation Classes standard for dynamic data collection and automatic generation of Building Automation Control Networks</strong></em>, with DOI: https://doi.org/10.1016/j.jobe.2023.107625</p> <p>This dataset is an enhanced IFC (Industry Foundation Classes) file with the creation of the BACN (Building Automation Control Network). This IFC file includes the devices created automatically by the BACN2BIM tool (developed by CARTIF Technology Centre) for the case study validated at TRL4. The original IFC was obtained from the Institute for Automation and Applied Informatics (IAI) / Karlsruhe Institute of Technology (KIT) https://www.ifcwiki.org/images/e/e3/AC20-FZK-Haus.ifc, under an unrestricted license, as served as one of the case studies for this research.</p> <p>*Depending on the IFC viewer used, the included sensors may not be represented correctly. In this case, it is recommended to try with another IFC viewer, for example xBIM explorer https://docs.xbim.net/downloads/xbimxplorer.html or BimCollab Zoom Free https://www.bimcollab.com/en/support/downloads/</p>
SGS-LTER Standard Production Data: 1983-2008 Annual Aboveground Net Primary Production on the Central Plains Experimental Range, Nunn, Colorado, USA 1983-2008, ARS Study Number 6 (Reformatted to the ecocomDP Design Pattern)
This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-sgs/700/1. The abstract below was extracted from the Level 0 data package and is included for context: This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. The objective of the long-term ANPP study is to monitor long-term net above ground primary production of the shortgrass steppe community by species. There are 6 sites: ridgetop (ridge), midslope (mid), swale, ESA (replicate 1 not 2), Section 25 (SEC 25), and owl-creek (OC). Each site is located in a different landscape position or soil type on the shortgrass steppe and may be grazed or not. Ridgetop, midslope and swale are grazed and are sampled along a catena. Section 25 is grazed and is located in an upload grassland. ESA is an ungrazed upland grassland an is the control from the Ecosystem Stress Area experiment. Owl Creek is ungrazed and is located in the lowland along the owl creek drainage. There are 3 transects with 5 plots in each transect. Plots in the grazed locations are protected by cages. Because this is a monitoring effort, true replicates across the landscape are not
Capture data for sharks caught in standardized drumline fishing in Shark Bay, Western Australia, with accompanying abiotic data, from February 2008 to July 2014.
This dataset provides data on large sharks captured during standardized drumline fishing and is used to monitor shark catch rates, sex ratios and size distributions in Shark Bay.
Capture data for sharks caught in standardized drumline fishing in Shark Bay, Western Australia, with accompanying abiotic data, from January 2012 to April 2014.
This file provides data on standardized drumline fishing effort (gear deployment data) targeting large elasmobranchs in Shark Bay, Western Australia between 2012 and 2014
Monthly precipitation data from a network of standard gauges at the Jornada Experimental Range (Jornada Basin LTER) in southern New Mexico, January 1916 - ongoing
This ongoing dataset contains monthly precipitation measurements from a network of standard can rain gauges at the Jornada Experimental Range in Dona Ana County, New Mexico, USA. Precipitation physically collects within gauges during the month and is manually measured with a graduated cylinder at the end of each month. This network is maintained by USDA Agricultural Research Service personnel. This dataset includes 39 different locations but only 29 of them are current. Other precipitation data exist for this area, including event-based tipping bucket data with timestamps, but do not go as far back in time as this dataset.
Data relating to Clyne et al. Quality, scope and reporting standards of randomised controlled trials in Irish Health Research: an observational study
<p>Data relating to the study reported in the paper "Quality, scope and reporting standards of randomised controlled trials in Irish Health Research: an observational study".</p>
Fast MLE and Supervised Classification for the Beta-Liouville Multinomial -- Gold Standard Data
<p>Gold standard datasets used in the publication Fast Maximum Likelihood Estimation and Supervised Classification for the Beta-Liouville Multinomial. Datasets were prepared by Cardoso-Cachopo (2007).</p>
Clumped Isotope Data from Gar Scale Bioapatite Samples and Lab Standards
<p>We measured the clumped isotope, Δ<sub>47</sub>, composition of the carbonate in the bioapatite of modern gar scales from 19 specimens collected from eight locations in North America, with mean water temperatures ranging from 11.3 to 27.0 °C. Samples were reacted at 90 °C and standards were reacted at both 25 °C and 90 °C. Samples and standards were run on a MAT 253 dual-inlet gas-source isotope ratio mass spectrometer (Thermo Scientific, USA) housed at the Yale University Analytical and Stable Isotope Center. Raw data was processed using the most up-to-date methods (Petersen et al., 2019). Our sample reproducibility was 0.021‰ (1 SD). Our standards included cylinder CO<sub>2 </sub>(Airgas, USA), CO<sub>2</sub> equilibrated with water at 25 °C and 50 °C, Carrara marble, and the ETH carbonate anchors. Δ<sub>47</sub> data is presented as ‰, InterCarb-Carbon Dioxide Equilibrium Scale (I-CDES) 90 °C for samples and standards reacted at 90 °C and I-CDES 25 °C for standards reacted at 25 °C.</p> <p> </p> <p>We use modern climate data from Daymet V4 (Thornton et al., 2022). We convert variable water temperatures into an effective temperature <em>T</em><sub>e</sub>, which accounts for the influence of temperature on growth rate. <em>T</em><sub>e</sub> for our gar samples ranges from 13.8 to 27.1 °C. We used this dataset to create a new calibration relating temperature to the Δ<sub>47</sub> in gar scale bioapatite. The resulting calibration curve is: Δ<sub>47</sub> = (0.1206 ± 0.0171) x 10<sup>6</sup>/<em>T</em><sub>e</sub><sup>2</sup> – (0.7429 ± 0.0587) (1 SE), with <em>R</em><sup>2</sup> = 0.75.</p>
SCALE-WIN19 Standard CTD Rosette Data
<p>The files here contain the standard CTD bottle and sensor files for the SCALE Winter Cruise. </p> <p>Oxygen sensor data is now included - except for stations PUZ, SAZ2, GT1, GTE, GT1, MIZ1 and MIZ2.</p> <p>For notes on how the data was processed please refer to the SCALE CTD Processing Report.</p> <p> </p> <table style="border-collapse: collapse; width: 100%; height: 156.75px;"><colgroup><col style="width: 50%;"><col style="width: 50%;"></colgroup> <tbody> <tr style="height: 19.5938px;"> <td style="height: 19.5938px;"><strong>Variable</strong></td> <td style="height: 19.5938px;"><strong>Units</strong></td> </tr> <tr style="height: 19.5938px;"> <td style="height: 19.5938px;">Temperature</td> <td style="height: 19.5938px;">degrees C</td> </tr> <tr style="height: 19.5938px;"> <td style="height: 19.5938px;">Conductivity</td> <td style="height: 19.5938px;">S/m</td> </tr> <tr style="height: 19.5938px;"> <td style="height: 19.5938px;">Salinity</td> <td style="height: 19.5938px;">PSU</td> </tr> <tr style="height: 19.5938px;"> <td style="height: 19.5938px;">Oxygen in situ/Oxygen theoretical/AOU</td> <td style="height: 19.5938px;">mL/L</td> </tr> <tr style="height: 19.5938px;"> <td style="height: 19.5938px;">Oxygen Saturation</td> <td style="height: 19.5938px;">%</td> </tr> <tr style="height: 19.5938px;"> <td style="height: 19.5938px;">Density</td> <td style="height: 19.5938px;">kg/m3</td> </tr> <tr style="height: 19.5938px;"> <td style="height: 19.5938px;">Chlorophyll</td> <td style="height: 19.5938px;">mg/m3</td> </tr> <tr> <td>Beam Transmission</td> <td>%</td> </tr> <tr> <td>Beam Attenuation</td> <td>m</td> </tr> </tbody> </table>
Data from PV module energy rating standard IEC 61853-3 intercomparison
<p>This is the data from PV module energy rating standard IEC 61853-3 intercomparison.</p> <p>Details can be found in:</p> <p>M. R. Vogt, S. Riechelmann, A. M. Gracia-Amillo, A. Driesse, A. Kokka, K. Maham, P. Kärhä, R. Kenny, C. Schinke, K. Bothe, J. C. Blakesley, E. Music, F. Plag, G. Friesen, G. Corbellini, N. Riedel-Lyngskær, R. Valckenborg, M. Schweiger, W. Herrmann, „PV module energy rating standard IEC 61853-3 intercomparison and best practice guidelines for implementation and validation”, accepted IEEE JPV. DOI (identifier) 10.1109/JPHOTOV.2021.3135258</p>
Example subjects for Mobilise-D data standardization
<p>Standardized data from Mobilise-D participants (YAR dataset) and pre-existing datasets (ICICLE, MSIPC2, Gait in Lab and real-life settings, MS project, UNISS-UNIGE) are provided in the shared folder, as an example of the procedures proposed in the publication "Mobility recorded by wearable devices and gold standards: the Mobilise-D procedure for data standardization" that is currently under review in Scientific data. Please refer to that publication for further information. Please cite that publication if using these data. </p> <p>The code to standardize an example subject (for the ICICLE dataset) and to open the standardized Matlab files in other languages (Python, R) is available in github (https://github.com/luca-palmerini/Procedure-wearable-data-standardization-Mobilise-D).</p>
Mapping Across OpenAIRE And Argos Data Models And The DMP Common Standard
<p>This is the outcome of the mapping activity across the data models of Argos and the OpenAIRE Research Graph and the RDA DMP Common Standard.</p>
Improving Methods to Measure Comparable Mortality by Cause - Gold Standard Verbal Autopsy Data 2011-2014
<p>These data were collected and compiled as part of the Improving Methods to Measure Comparable Mortality by Cause (IMMCMC) project, funded by Australia's National Health and Medical Research Council (NHMRC). Verbal autopsies (VAs) were conducted between 2011 and 2014 in three sites: Bohol, Philippines; Chandpur and Comila Districts, Bangladesh; and Central and Eastern Highlands Provinces, Papua New Guinea. Diagnostic criteria and cause lists similar to those employed in the Population Health Metrics Research Consortium (PHMRC) study were used to identify gold standard (GS) deaths. This study added 3512 deaths (2491 adults, 320 children, and 701 neonates) to the GS VA database created from the PHMRC study. This dataset contains the combined PHMRC and IMMCMC data for an updated GS VA database.</p>
Section 5.1 "Task Area 1: Image (meta)data formats and standardization)" Figure 8
<p>Figure 8. A FAIR-IO bundle combines the necessary acquisition and provenance metadata together with multi-resolution, chunked binary data in a single cloud-compatible format for simplified sharing and re-use.</p> <p>from NFDI Grant Application, "<strong>National Research Data Infrastructure for Microscopy and Bioimage Analysis</strong>" (NFDI4BIOIMAGE)</p>
Data associated with "Developing a standardized but extendable framework to increase the findability of infectious disease datasets"
<p><strong>Data associated with "Developing a standardized but extendable framework to increase the findability of infectious disease datasets"</strong></p> <p> </p> <p>Includes:</p> <ul> <li>NIAID Dataset schema</li> <li>NIAID ComputationalTool schema</li> <li>Crosswalk between NIAID schemas and common schemas</li> <li>Survey of Schema.org-compliant repositories</li> </ul> <p><br> The open access movement and scientific reproducibility concerns have led the biomedical research community to embrace efforts to make scientific datasets openly accessible. While many datasets are now available, there are still challenges in ensuring that they are Findable, Accessible, Interoperable, and Reusable (FAIR). To improve the FAIRness of datasets, we evaluated dataset repositories for compliance with Schema.org standards – a collection of standards developed to increase metadata searchability across the internet. Adoption of the Schema.org Dataset standard was highly variable in biomedical research datasets, and the standard omitted many desirable metadata fields. We customized the Schema.org Dataset standard to catalog datasets collected across a Systems Biology research consortium consisting of 15 Centers. We developed a reusable process for creating a schema which is interoperable with other standards, but still extendable and customizable to a particular context. Here, we describe our process along with the associated gains in FAIRness, and discuss ongoing challenges with dataset discoverability – the first step to ensure that the vast amount of open data published by the research community is reused to its maximum value.</p>
Data for: BetaScan2: Standardized Statistics to Detect Balancing Selection Utilizing Substitution Data
<p>Genome-wide scan using BetaScan2 in 1KG populations report in:</p> <p><a href="https://pubmed.ncbi.nlm.nih.gov/32011695/">BetaScan2: Standardized Statistics to Detect Balancing Selection Utilizing Substitution Data.</a></p> <p>Siewert KM, Voight BF.Genome Biol Evol. 2020 Feb 1;12(2):3873-3877. doi: 10.1093/gbe/evaa013.</p> <p>PMID: 32011695 </p> <p>Code available at: https://github.com/ksiewert/BetaScan</p>
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.