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275 results for “Data storage”
The Global and National Energy Systems Techno-Economic (GNESTE) Database: Economic and performance data for battery storage in current and future electricity systems
<p><span><span>Here, we </span><span>present a</span><span> database </span><span>which collates </span><span>historical, </span><span>current</span><span>,</span><span> and future </span><span>cost and performance</span><span> data</span> <span>and </span><span>assumption</span><span>s</span> <span>for </span></span><span><span>battery energy storag</span><span>e </span><span>systems</span></span><span> <span>from</span><span> the open literature. </span></span><span><span>Battery energy storage is the fastest growing form of power system </span><span>flexibility, and</span><span> will be critical to integrating large shares of variable renewable energy.</span></span><span> <span>The data are </span><span>global in scope but with </span><span>regional and national</span> <span>specificity</span><span>, </span><span>cover</span><span>s</span><span> the years 2015 t</span><span>hrough </span><span>to 2050, </span><span>and </span><span>span</span> </span><span><span>671</span></span><span><span> datapoints from </span></span><span><span>18</span></span><span><span> sources</span><span>.</span> </span></p> <p><span><span>The database </span><span>enables modellers to select and justify</span> <span>model input data and </span><span>provides </span><span>a </span><span>benchmark for comparing assumptions and projections to </span><span>other source</span><span>s</span><span> across the </span><span>literature</span> <span>to </span><span>validate</span><span> model inputs and outputs</span><span>.</span> <span>It is designed to be easily updated with </span><span>new sources of</span><span> data, ensuring its utility</span><span>, comprehensiveness,</span><span> and broad applicability over time.</span></span><span> </span>Technoeconomic data on utility-scale batteries was collected from websites, reports, academic articles and databases of national and international organisations.</p>
[Data set]for publication Acidification of Strawberry Puree Affects Color and Volatile Characteristics during Storage
<p>Color degradation of strawberry-based products negatively affects consumer acceptance of these products. To improve the color stability of strawberry puree during storage, an acidification step (pH 1.5 and 2.5) prior to pasteurization was performed and quality changes of strawberry puree during storage (35 °C, 40 days) were monitored. Acidification prior to pasteurization resulted in an improved color and anthocyanin stability. However, the volatile fraction of strawberry puree was negatively influenced by acidification of the puree. Low acidic conditions (pH 1.5) resulted in the hydrolysis of esters, oxidation of terpene oxides, and acid-catalyzed reactions of terpene alcohols during storage. The volatile fraction of strawberry puree stored at pH 2.5 and 3.5 (the latter being the original strawberry puree) were more similar. Furthermore, after 4 days of storage, the pH of the acidified purees was brought back to the natural pH of the system (3.5) and subsequently thermally treated and stored. During this second storage, color showed a slightly faster degradation rate in those purees that were previously acidified, whereas anthocyanins exhibited similar trends suggesting that the advantage of acidification to preserve color would be beneficial after thermal processing, but more limited during storage of the regenerated product (second storage).</p>
Data Storage for Baylis and Boomhower (2022): Fire Characteristics, Expenditures, and Other Miscellaneous Datasets
<pre># Description Zenodo data storage for large, non-proprietary data used in "The Economic Incidence of Wildfire Suppression in the United States", by Patrick Baylis and Judson Boomhower. Main OpenICPSR repository (contains code and main README.txt): https://www.openicpsr.org/openicpsr/workspace?goToPath=/openicpsr/144601 # Contents This storage mirrors the following offline directories used in the code. Each .tar file contains a directory of the same name. To replicate the existing code, users should decompress each directory into raw/, following the structure used in the code. (Note: as described in the main README, running most of the code requires access to proprietary data which is not included in this storage). ## Resulting directory structure To be consistent with the original source code, included the .tar files should be decompressed into the following directory structure within the directory designated by the RAW global in 01_Code/globals.R in the main reposistory. raw/calfire/ raw/census/county-tract/ raw/census/income/ raw/census/populated_places raw/gacc/ raw/geo/ raw/gpw/ raw/hpi/ raw/incidents/CalFire/ raw/incidents/FAMWEB/ raw/incidents/InteriorDepartment/ raw/incidents/FEMA/ raw/incidents/KCFAST/ raw/MTBS/ raw/nifc/ raw/preparedness-spending/doi/ raw/preparedness-spending/usfs/ raw/roads/ raw/USFS/ raw/whp/ raw/wui/</pre>
Data Storage for Baylis and Boomhower (2022): LANDFIRE Aspect, Elevation, Slope, and Anderson 13 Fuel Models
<pre># Description Zenodo data storage for large, non-proprietary data used in "The Economic Incidence of Wildfire Suppression in the United States", by Patrick Baylis and Judson Boomhower. Main OpenICPSR repository (contains code and main README.txt): https://www.openicpsr.org/openicpsr/workspace?goToPath=/openicpsr/144601 # Contents This storage mirrors the following offline directories used in the code. Each .tar file contains a directory of the same name. To replicate the existing code, users should decompress each directory into raw/, following the structure used in the code. (Note: as described in the main README, running most of the code requires access to proprietary data which is not included in this storage). ## Resulting directory structure To be consistent with the original source code, included the .tar files should be decompressed into the following directory structure within the directory designated by the RAW global in 01_Code/globals.R in the main reposistory. LANDFIRE/Aspect/ LANDFIRE/DEM_Elevation/ LANDFIRE/Slope/ LANDFIRE/US_140FBFM13_12052016/</pre>
Storage Technologies Costs - Support File for Data Manipulation Starter Data Kits
<p>This file can be used to manipulate the storage technologies cost data for the Starter Data Kits. </p>
Data and code for publication: A simple preparation protocol for shipping and storage of tissue sections for laser ablation-inductively coupled plasma-mass spectrometry imaging
<p>Data & Code release for publication:</p> <p>Rebecca Buchholz, Sebastian Krossa, Maria K Andersen, Michael Holtkamp, Michael Sperling, Uwe Karst, May-Britt Tessem, A simple preparation protocol for shipping and storage of tissue sections for laser ablation-inductively coupled plasma-mass spectrometry imaging, <em>Metallomics</em>, Volume 14, Issue 3, March 2022, mfac013, <a href="https://doi.org/10.1093/mtomcs/mfac013">https://doi.org/10.1093/mtomcs/mfac013</a></p> <p>Python code for LA ICP MS imaging data segmentation</p> <p>Code & Data also on <a href="https://github.com/sekro/la-icp-msi_segmentation">github</a></p> <p>Thresholding based segmentation of LA-ICP-MS imaging data</p> <p>Description</p> <p><a href="https://github.com/sekro/la-icp-msi_segmentation/blob/master/src/main.py">src/main.py</a> - run this to process LA ICP MS data in data folder - generates matplotlib.figures - project specific setup <a href="https://github.com/sekro/la-icp-msi_segmentation/blob/master/src/laicpms_data_handler.py">src/laicpms_data_handler.py</a> - contains object to import, handle and segment (shimadzu) raw data</p> <p>Dependencies</p> <p>Python 3.8.1 or newer</p> <p>For packages see <a href="https://github.com/sekro/la-icp-msi_segmentation/blob/master/requirements.txt">requirements.txt</a></p> <p>Data</p> <p>LA-ICP-MS imaging data of human prostate tissue of the elements Zn, Fe & P. Details on data generation & collection in <a href="https://doi.org/10.1093/mtomcs/mfac013">publication</a>. LA-ICP-MS imaging data as plain text files (comma-separated values)</p> <ul> <li>Condition 1 = fresh frozen (FF)</li> <li>Condition 2 = room temperature vacuum dried and sealed (RTV)</li> <li>Condition 3 = formalin fixed (FFix)</li> <li>Condition 4 = formalin fixed, paraffin sealed (FFPS)</li> </ul> <p>3 replicate sectioning sets named A, B, C</p> <p>File-naming: LA_Data_CISN1.csv, where I = [1, 2, 3, 4] is indicating the condition used and N = [A, B, C] is indicating the replicate set</p> <p>License</p> <p>Data</p> <p>CC-BY 4.0 - respective <a href="https://github.com/sekro/la-icp-msi_segmentation/blob/master/data/LICENSE">LICENSE</a> file in data folder</p> <p>Source code</p> <p>MIT - respective <a href="https://github.com/sekro/la-icp-msi_segmentation/blob/master/src/LICENSE">LICENSE</a> file in src folder</p>
Fluid Transport and Storage in the Cascadia Forearc inferred from Magnetotelluric Data
<p>The 3D electrical resistivity model derived from magnetotelluric data inversion. The model file is in netCDF format, which can be viewed using any standard netCDF plotting tools (e.g. <a href="https://www.giss.nasa.gov/tools/panoply/">Panoply</a>).</p>
Data from: Pop‐off data storage tags reveal niche partitioning between native and non‐native predators in a novel ecosystem
1. Niche partitioning might be predicted to be particularly dynamic in 'novel ecosystems' characterized by human-altered environmental conditions and biological invasions. Restoration efforts for native species in such systems can be informed by detailed characterization of niche partitioning. 2. In Lake Ontario, fishery management agencies have been engaged in a long-term struggle to restore native top predators including lake trout (Salvelinus namaycush). Meanwhile, management agencies continue to stock non-native species like Chinook salmon (Oncorhynchus tshawytscha) into the lake to support a recreational fishery and to help control the abundance of a non-native forage fish, the alewife (Alosa pseudoharengus). 3. We used pop-off data storage tags to study fine scale (9.1M lines of data from 22 animals) behaviour and habitat use by lake trout (native) and Chinook salmon (non-native) in Lake Ontario in terms of depth and temperature, recorded at ≤70 s intervals for periods of up to 12 months. 4. Chinook salmon occupied warmer and shallower waters during summer than did lake trout, and their niche breadth was wider. They achieved greater niche breadth in part because they were much more active vertically, cumulatively traveling 103±1 m hour-1 during summer (model-estimated median), whereas most lake trout were relatively inactive vertically (7±1 m hour-1). In each of our analyses, there was more inter-individual variation among lake trout than among Chinook salmon, driven by some lake trout that spent considerable time making forays into warmer, shallower waters. 5. Synthesis and applications. Our results illustrate the different foraging tactics used by two species in the Great Lakes and reflect their distinct life histories. Vertical and thermal niche partitioning between Chinook salmon and lake trout helps to explain how these species can co-exist in a multi-species fishery even while having substantial overlap in diet. The diversity of behaviours exhibited here by native lake trout have likely helped them persist during dramatic changes to the forage base in recent decades; that flexibility could help underlie their long-term prospects for restoration during future changes to the ecosystem.
Supplementary data to: Climate change threatens terrestrial water storage over the Tibetan Plateau
<p>This data archive includes the boundary of the Tibetan Plateau (TP) and river basins, and projected changes in terrestrial water storage by the mid-21<sup>st</sup> century (up to 2060). The boundary of the TP and river basins is in the shapefile (.shp) format, and all other processed data are in the geotiff (.tif) format. Please see Readme for more data information. For calculation details please see the publication.</p>
Data from: Treated like dirt: Robust forensic and ecological inferences from soil eDNA after challenging sample storage
<p>We investigated the effect of storage duration and conditions on the assessment of the soil biota with eDNA metabarcoding. We extracted eDNA from freshly collected soil samples and again from the same samples after storage under contrasting temperature conditions and contrasting exposure (open/closed tubes). We used four different primer sets targeting bacteria, fungi, protists (cercozoans), and general eukaryotes. <span>W</span>e quantified differences in richness, evenness, and community composition. Subsequently, we tested whether we could correctly infer habitat type and original sample identity after storage using a large reference dataset.</p> <p>This repository contains the un-demultiplexed fastq sequences.</p>
Data for Novel Approach to Quantify Sediment Transfer and Storage in Rivers with Feldspar Single-Grain pIRIR
<p>Raw data of feldspar post infra-red infra-red (pIRIR) stimulated luminescence signal from modern sand from New Zealand rivers (Rakaia, six samples; Waimakariri, height samples) used in the paper Guyez et al. (2022) submitted to JGR: Earth Surface. The samples were collected in February 2020 by S. Bonnet and A. Guyez. They were measured in the Netherlands Center for Luminescence dating (Wageningen University and Research). </p>
Data used for the article "Global evaluation of the dry gets drier and wet gets wetter paradigm from terrestrial water storage changes perspective".
<p>This is the data used in the HESS paper "Global evaluation of the dry gets drier and wet gets wetter paradigm from terrestrial water storage changes perspective".</p>
Supporting data for "Granularity of model input data impacts estimates of carbon storage in soils"
<p>The exchange of carbon between the soil and the atmosphere is an important factor in climate change. Soil organic carbon (SOC) storage is sensitive to land management, soil properties, and climatic conditions, and these data serve as key inputs to computer models projecting SOC change. Farmland has been identified as a sink for atmospheric carbon, and we have previously estimated the potential for SOC sequestration in agricultural soils in Vermont, USA using the Rothamsted Carbon Model. However, fine spatial-scale (high granularity) input data are not always available, which can limit the skill of SOC projections. For example, climate projections are often only available at scales of 10s to 100s of km2. To overcome this, we use a climate projection dataset downscaled to <1 km2 (~18,000 cells). We compare SOC from runs forced by high granularity input data to runs forced by aggregated data averaged over the 11,690 km2 study region. We spin up and run the model individually for each cell in the fine-scale runs and for the region in the aggregated runs factorially over three agricultural land uses and four Global Climate Models. </p> <p>In this repository are the downscaled climate input data that drive the RothC model, as well as the model outputs for each GCM.</p>
Dataset: Data Storage Corporation (DTST) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: Data Storage Corporation (DTSTW) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Fig. 1 in Data storage and data re-use in taxonomy-the need for improved storage and accessibility of heterogeneous data
Fig. 1 (a) Sp_ci_s d_scriptions p_r d_cad_ in s_l_ct_d major groups of organisms (bas_d on data _xtract_d from th_ Int_rnational Plant Nam_s Ind_x (https://www.ipni.org/) for plants, MycoBank (http://www. mycobank.org/) for fungi, Ind_x of Organism Nam_s (http://www. organismnam_s.com/) for ins_cts, and compil_d from various databas_s for v_rt_brat_s: Eschm_y_r Catalog for fish_s (https://www.calacad_my. org/sci_ntists/proj_cts/_schm_y_rs-catalog-of-fish_s), th_ Amphibian Sp_ci_s of th_ World for amphibians (http://r_s_arch.amnh.org/vz/ h_rp_tology/amphibia/), R_ptil_ Databas_ for r_ptil_s (http://www. r_ptil_-databas_.org/), Howard and Moor_ Databas_ (https://www. howardandmoor_.org/) for birds, and ASM Mammal Div_rsity Databas_ (https://mammaldiv_rsity.org/) for mammals, all acc_ss_d in April 2019. Not_ that data for fungi and v_rt_brat_s r_f_r to curr_ntly acc_pt_d sp_ci_s nam_s only wh_r_as ins_ct data also includ_ synonyms and subsp_ci_s, and contain data gaps for s_v_ral d_cad_s in th_ nin_t__nth c_ntury; for all taxa, th_ low valu_s obtain_d for th_ last
Tsunamis due to ice masses: Different calving mechanisms and linkage to landslide-tsunamis - Data storage report
<p>Land ice melt and retreat is one of the most visible effects of climate change and contributes ≈1.5 mm/year to global sea-level rise (SLR) of a total of ≈2.7 mm/year. Global warming results in the shrinking of ice masses in most ice covered regions in the World, particularly in the Alps and in Greenland and the Greenlandic mass loss is estimated at –269 ±51 Gt/year. A significant part of this mass loss is through the detachment of icebergs at glacier fronts in a mechanism called iceberg calving. Such iceberg impacting into a water body generate tsunamis, such called "iceberg-tsunamis". Such an iceberg-tsunami reached a height of 50 m at the Eqip Sermia outlet glacier in 2014. These tsunamis pose a considerable hazard for the local community, the fishing industry and the increasing number of tourists in ice covered areas. Several iceberg calving mechanisms have been proposed including fall, over-turning and capsizing. Reliable guidance on the upper limit of iceberg-tsunami heights are currently unavailable. A main reason for this limited understanding is that reliable field data are rare, such that laboratory tests complemented with numerical simulations are important to advance this research field. This was the aim of this HYDRALAB+ funded study. The wave features (height, length, velocity) caused by icebergs in function of the iceberg calving mechanisms (fall, over-turning, capsizing), as well as the mass volume and kinematics, were modelled in unique large-scale experiments. This minimised both scale effects and wave reflection. The attached file is an HYDRALAB+ standard Data Storage Report about these experiments.</p>
SparBOFWEC Spar Buoy for Offshore Floating Wind Energy Conversion - Data Storage Report
<p>The present work describes the experiences gained from the design methodology and operation of a 3D physical model experiment aimed to investigate the dynamic behaviour of a spar buoy (SB) off-shore floating wind turbine (WT) under different wind and wave conditions. The physical model tests have been performed at Danish Hydraulic Institute (DHI) off-shore wave basin within the European Union-Hydralab+ Initiative, in April 2019. The floating WT model has been subjected to a combination of regular and irregular wave attacks and wind loads.</p>
Data Storage Report. RODBreak - Wave run-up, overtopping and damage in rubble-mound breakwaters under oblique extreme wave conditions due to climate change scenarios
<p>Wave breaking / run-up / overtopping and their impact on the stability of rubble-mound breakwaters (both at trunk and roundhead) are not adequately characterized yet for climate change scenarios. The same happens with the influence of high-incidence angles on such phenomena.</p> <p>To study these phenomena a stretch of a rubble-mound breakwater (head and part of the adjoining trunk, with a slope of 1(V):2(H)) was built in the wave basin of the LUH, The trunk of the breakwater was 7.5 m long and the head had the same cross section as the exposed part of breakwater. The model was 9.0 m long, 0.82 m high and 3.0 m wide. The angle between the longitudinal axis of the breakwater and the tank wall was 70º. Two types of armour elements (rock and Antifer cubes) were tested.</p> <p>60 tests were carried out in this experiment to assess, under extreme wave conditions (wave steepness of 0.055) with different incidence wave angles (from 40º to 90º), the structure behaviour in what concerns wave run-up, wave overtopping and damage progression of the armour layer.</p> <p>The report describes the data collected in those tests as well as how such data is stored.</p>
HY+_HSVA‐06_UNIS - Data Storage Report
<p>Data Storage Report<br>Bending rheology of floating saline ice and wave damping – Waves in Ice; BRWD-Waves in Ice<br>Large Ice Model Basin (LIMB), Hamburg Ship Model Basin</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.