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ShareScore release 0.9.0
Dataset results
14 results for “2011-2014”
Temporal patterns of leaf litter inputs into a stream over a four-year period (2011-2014), Arbúcies, Catalonia, Spain.
Data based on estimations of leaf litter inputs from riparian trees into a stream reach over a 4 years period (2011-2014). Data was collected in Arbucies, Barcelona is a forested stream with no human pressure (i.e., pristine). Data contains values from 4 riparian tree species: AL (alder), AS (ash), BL (Black Locust) and BP (Black Poplar). Units are in mg. Estimations were extracted from sampling leaf litter input into the stream during the study period (30 samplings per year) and fitting Gaussian-type models (P<0.001, r2>0.60). Data also includes daily-basis discharge flow estimations based on discrete measure of flow using salt dilution technique and water level sensor data.
SBC LTER: Ocean: Time-series: Mid-water SeaFET and CO2 system chemistry at Alegria (ALE), 2011-2014
Calibrated pH (Total scale, SeaFET sensor) data was collected from Alegria in the Santa Barbara Channel (site ID: ALE) along with in situ temperature and associated carbonate chemistry parameters. The SeaFET instrument is located about 4 meters from the surface, with other moored instruments. Associated carbonate chemistry parameters were calculated with the CO2calc programs from USGS, and include: partial pressure and fugosity of CO2, concentrations of bicarbonate, carbonate and hyrdroxide ion, Omega (saturation state) of calcite and aragonite. Data have been interpolated to a 20 minute time interval for compatibility with other SBC LTER moored instrument data. Data coverage is 2011-06-21 to 2014-01-07.The update of this dataset was terminated in 2019. All data from this site have been concatenated with the pH data from the other sites and merged into one data package: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sbc&identifier=6005
State level income distributions for net income deciles for the US for historical years (2011-2014) and projections for different SSP scenarios (2015-2100)
<p>This dataset is documented in this manuscript here- https://iopscience.iop.org/article/10.1088/1748-9326/acf9b8/meta</p> <p>Income distributions are a growing area of interest in the examination of equity impacts brought on by climate change and its responses. We project US state level income distributions using a PCA-based approach, applying a downscaled version of the approach employed by Narayan et al. (2022, in-prep). A state-level dataset had to be synthesized and projected based on existing sources. We apply a PC-based model to our derived state-level dataset, employing projected GINI’s from the SSP scenarios. We produce projected income distribution by income decile for three SSPs to year 2100. For the purpose of the projections, we developed a consistent set of tax adjusted net income deciles for all states from 2011 to 2014. This dataset was used for initialization of the projections and for validation.</p> <p>If/when using this dataset, please cite this paper- https://iopscience.iop.org/article/10.1088/1748-9326/acf9b8/meta</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>
DMSP F15/F16/F18 2011-2014 Binned Poynting Flux Data
<p>This dataset, created using the <a href="https://github.com/lkilcommons/esabin">esabin</a> Python library, comprises 9 spacecraft-years of electrodynamics measurements from Defense Meteorology Satellite Program F15, F16 and F18 spacecraft. <strong>Users of this data should prefer files which do not contain 'idm_only' in their filenames, as these do not use both components of DMSP ion drift vector measurements.</strong> They are included here to support reproducibility of a upcoming publication.</p> <p>The HDF5 files herein organize this data in equal area bins in magnetic coordinates. Each Group in the files represents one bin. Each Dataset contains the data for one crossing of that bin by a DMSP spacecraft. The name of each Dataset is the approximate time of the crossing as Julian date. Hourly NASA OMNIWeb solar wind and geomagnetic activity parameters are included as attributes for each Dataset.</p> <p>The electrodynamic parameters herein are magnetic perturbation (dB), electric field (E) and ion drift velocity (V). These quantities are scaled from satellite altitude (~850 km) where they were observed to ionospheric altitude (~110 km) using Modified Magnetic Apex coordinates. In the filenames, 'e' represents magnetic eastward and 'n' represents magnetic northward. Also included are geomagnetic-main-field-aligned Poynting flux also scaled to 110km altitude (files with 'poynting' in the name).</p>
Net N Mineralization Rates in Peat From N-Addition Plots in an Alberta Peatland, 2011-2014
Development of the oil sands has led to increasing atmospheric N deposition, with values as high as 17 kg N ha-1 yr-1; regional background levels <2 kg N ha-1 yr-1. Bogs, being ombrotrophic, may be especially susceptible to increasing N deposition. To examine responses to N deposition, over five years, we experimentally applied N (as NH4NO3) to a bog near Mariana Lakes, Alberta, at rates of 0, 5, 10, 15, 20, and 25 kg N ha-1 yr-1, plus controls (no water or N addition). From 2011 through 2014, we quantified net N mineralization in each plot using the in situ buried polyethylene bag technique. Concentrations of initial KCl-extractable NH4 +-N, NO3 --N, and DIN in the top 10 cm of peat were unaffected by N inputs. We hypothesized that as N deposition increases to a level that exceeds the capacity of the bog vegetation to take up N, net N mineralization in surface peat would be inhibited by higher NH4 +-N availability, net nitrification would be stimulated by higher NH4 +-N availability (cf. McGill and Cole 1981, Robertson and Groffman 2015), and concentrations of DIN in porewater at the top of the water table would increase, as DIN bypasses interception by the ground layer vegetation. None of these hypotheses was supported. Experimentally added NH4 +-N and NO3 --N apparently appear to be rapidly immobilized. This immobilization prevents experimentally added DIN from moving downward through the peat to the bog water table.
Net N mineralization rates in peat from N-Addition plots in an Alberta Poor Fen, 2011-2014
Development of the oil sands has led to increasing atmospheric N deposition, with values as high as 17 kg N ha-1 yr-1; regional background levels <2 kg N ha-1 yr-1. To examine responses to N deposition, over five years, we experimentally applied N (as NH4NO3) to a poor fen near Mariana Lake, Alberta, at rates of 0, 5, 10, 15, 20, and 25 kg N ha-1 yr-1, plus controls (no water or N addition). From 2011 through 2014, we quantified net N mineralization in each plot using the in situ buried polyethylene bag technique. Concentrations of initial KCl-extractable NH4+-N, NO3--N, and DIN in the top 10 cm of peat were unaffected by N inputs. We hypothesized that as N deposition increases to a level that exceeds the capacity of the fen vegetation to take up N, net N mineralization in surface peat would be inhibited by higher NH4+-N availability, net nitrification would be stimulated by higher NH4+-N availability, and concentrations of DIN in porewater at the top of the water table would increase, as DIN bypasses interception by the ground layer vegetation. None of these hypotheses was supported. Experimentally added NH4+-N and NO3--N apparently appear to be rapidly immobilized. This immobilization prevents experimentally added DIN from moving downward through the peat to the bog water table.
Summer water temperature and light measurements in Hog Island Bay, VA 2011-2014
This dataset contains water temperature and crude light measurements taken every 15 minutes for locations within the seagrass set-aside area in Hog Island Bay. Measurements are made in the summer when temperature maxima are expected to occur. Only temperature data is available for 2011 and early 2012. No sampling was done in 2013.
The Gold OA Landscape 2011-2014
<p>Dataset used for The Gold OA Landscape 2011-2014 (http://www.lulu.com/content/paperback-book/the-gold-oa-landscape-2011-2014/17264390). One row for each journal in the Directory of Open Access Journals as of June 15, 2015 that I was able to analyze fully, including grades and subgrades, article counts for 2014, 2013, 2012 and 2011, article processing charges (if any), broad subject and area, and country. In all, 9,824 journal rows. The second worksheet describes the data elements.</p>
Snow cover simulations and avalanche dynamics simulations for the area of Davos, Switzerland (2011-2014)
<p>Alpine3D model simulations of the snow cover at 100m resolution for the area surrounding Davos for the period October 2010 to September 2014.</p> <p>Avalanche dynamics simulations using the RAMMS-Extended model of 169 selected avalanches in the same period, using initial conditions as simulated by the Alpine3D model.</p> <p>This dataset belongs to:</p> <p>Wever, N., Vera Valero, C., and Techel, F. (2018): <em>Coupled snow cover and avalanche dynamics simulations to evaluate wet snow avalanche activity</em>, J. Geophys. Res. Earth Surf., 123, 1772–1796 <a href="https://doi.org/10.1029/2017JF004515">doi: 10.1029/2017JF004515.</a></p>
Plasmablast Trafficking and Antibody Response in Influenza Vaccination (SLVP021 2011-2014)
ClinicalTrials.gov study NCT02141581. IPD Sharing: YES. Countries: 1. Publications: 3.
Scraped Data BikeMI 2011-2014
<p>Scraped BikeMI (Milan, Italy, bike sharing) data, year 2011-2014</p> <p>CSV file</p> <p>fields are:</p> <p>date (YYMMDDHHMM) : location name : bikes : free slots (if 0 the station is full)</p> <p>field separator is ":"</p>
Managing Dysexecutive Syndrome (DS): CIHR 2011-2014
ClinicalTrials.gov study NCT01414348. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Ministry of Environment of Québec (2011-2014) web archive collection derivatives
<p>Web archive derivatives of the Ministry of Environment of Québec (2011-2014) collection from the <a href="https://www.banq.qc.ca/accueil/">Bibliothèque et Archives nationales du Québec</a>. The derivatives were created with the <a href="https://github.com/archivesunleashed/aut/">Archives Unleashed Toolkit</a>. Merci beaucoup BAnQ!</p> <p>These derivatives are in the <a href="https://parquet.apache.org/">Apache Parquet format</a>, which is a <a href="http://en.wikipedia.org/wiki/Column-oriented_DBMS">columnar storage</a> format. These derivatives are generally small enough to work with on your local machine, and can be easily converted to Pandas DataFrames. See <a href="https://github.com/archivesunleashed/notebooks/blob/master/parquet_pandas_example.ipynb">this</a> notebook for examples.</p> <p><strong>Domains</strong></p> <pre><code class="language-java">.webpages().groupBy(ExtractDomainDF($"url").alias("url")).count().sort($"count".desc)</code></pre> <p>Produces a DataFrame with the following columns:</p> <ul> <li>domain</li> <li>count</li> </ul> <p><strong>Web Pages</strong></p> <pre><code class="language-java">.webpages().select($"crawl_date", $"url", $"mime_type_web_server", $"mime_type_tika", RemoveHTMLDF(RemoveHTTPHeaderDF(($"content"))).alias("content"))</code></pre> <p>Produces a DataFrame with the following columns:</p> <ul> <li>crawl_date</li> <li>url</li> <li>mime_type_web_server</li> <li>mime_type_tika</li> <li>content</li> </ul> <p><strong>Web Graph</strong></p> <pre><code class="language-java">.webgraph()</code></pre> <p>Produces a DataFrame with the following columns:</p> <ul> <li>crawl_date</li> <li>src</li> <li>dest</li> <li>anchor</li> </ul> <p><strong>Image Links</strong></p> <pre><code class="language-java">.imageLinks()</code></pre> <p>Produces a DataFrame with the following columns:</p> <ul> <li>src</li> <li>image_url</li> </ul> <p><a href="https://github.com/archivesunleashed/aut-docs/blob/master/current/binary-analysis.md#binary-analysis"><strong>Binary Analysis</strong></a></p> <ul> <li>Audio</li> <li>Images</li> <li>PDFs</li> <li>Presentation program files</li> <li>Spreadsheets</li> <li>Text files</li> <li>Videos</li> <li>Word processor files</li> </ul>
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.