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.
363
datasets available to search
ShareScore release 0.9.0
Dataset results
363 results for “Price”
Fig. 5 in Morphometric Analysis Of Trianchoratus Price & Berry, 1966 (Monogenea: Heteronchocleidinae) From Channa Spp. (Osteichthyes: Channidae) Of Peninsular Malaysia
Fig. 5. Fisher's linear discriminant analysis plots of the first three LD functions, which account for 65%, 21% and 14% of the total variation, respectively. Indicators: Trianchoratus malayensis (-); T. pahangensis (+); T. ophicephali (o); T. longianchoratus (l).
Fig. 8 in Morphometric Analysis Of Trianchoratus Price & Berry, 1966 (Monogenea: Heteronchocleidinae) From Channa Spp. (Osteichthyes: Channidae) Of Peninsular Malaysia
Fig. 8. PCA plot of Trianchoratus ophicephali with geographical origin of data indicated. The horizontal and vertical barplots indicate one-dimensional summary of the PC axes.
Results from the FLEX Model for the paper "Impact of variable electricity price on heat pump operated buildings"
<p>The sqlite database contains the results of the Flex model for the Austrian single family house building stock ( insert GITHUB LINK). The building stock is represented by 36 different representative building archetypes (“OperationScenario_Component_Building”). Each building is simulated in twice. In the "reference" mode the energy demand is simply met and indoor comfort is kept constant. In the "optimization" mode the indoor temperature can be varied and thermal storages are charged and discharged minimizing the households energy cost based on a variable electricity price. The sqlite database “Variable_Price_Paper” contains the results for the building stock without any storage implemented. In “Variable_Price_Paper_TS” all buildings have a 750l hot water buffer storage and a 400l DHW storage implemented. The sqlite files SFH_23/25/27 contain the results for a single building where the maximum inside room temperature was changed to 23, 25 and 27 °C respectively.</p> <p>Following columns were used for generating the results for the Paper:</p> <p>In the hourly results relevant parameters used in the publication were:</p> <ul> <li>ID_Scenario: each building simulated under a different electricity price has a unique scenario number. “OperationScenario” gives an overview of the scenarios.</li> <li>Grid: describes the electricity demand from the grid by the household.</li> </ul> <p>In the yearly results relevant parameters used in the publication were:</p> <ul> <li>ID_Scenario</li> <li>TotalCost: represent the yearly operation cost</li> <li>Grid: electricity demand summed up for the whole year</li> </ul> <p>5 different electricity prices are used for scenario generation. The first price is constant, “electricity_2” is the real time price from 2021 plus a hypothetical grid fee of 20cents/kWh. “electricity_3, electricity_4, electricity_5” are prices generated for 2030 for Austria with the Balmorel model. Their profiles can be found under “OperationScenario_EnergyPrice”.</p> <p> </p>
Evolution of the price of electricity and the renewable energy production in Spain
<p>The dataset contains the evolution of electricity prices in Spain for the period 2020-11-01 to 2022-10-31. The average energy prices (in MWh) as a function of the market, the produced energy (in MW), as well as the renewable energy produced (in MW) by type (wind, solar, hydroelectric, etc.) are provided with a granularity of hours for the period of time mentioned above.</p> <p>The data has been obtained from the webpage: <a href="https://www.esios.ree.es/es/">https://www.esios.ree.es/es/</a>.</p> <p><strong>Disclaimer: </strong>Express consent was provided by Red Eléctrica de España (source and proprietary of the data) to gather the data using web scraping under the framework of a practicum from the Master in Data Science from the Universitat Oberta de Catalunya (UOC). Under no circumstance do they support the reuse of the data. We express our intention to use the data for the purpose of the activity and decline any commercial interest in the use of the data extracted.</p> <p>The data is published under a license: <strong>CC BY-NC-SA 4.0.</strong></p>
Spain's transportation gas prices by gas station (Precio de los carburantes por estación de servicio en España)
<p>Transportation gas prices for more than 11,000 Spanish gas stations on 11-18-2022. It also includes detailed location information for each station.</p> <p>Precio de los carburantes en mas de 11.000 gasolineras en España a dia 18-11-2022. Tambien incluye informacion detallada sobre la localizacion de cada estacion de servicio </p>
Iphone-Ipad-Mac-Prices
<p>The dataset has 3 files:</p> <p>1. Prices from 20/11/21 of a list of Iphones, Ipads and Mac from all countries where the products are sold. This is a Dataset extracted by WebScraping from Apple website.</p> <p>2. FX rate from a list of countries (source numbeo.com, extracted by WebScraping)</p> <p>3. Monthly Average Prices from an list of countries (source numbeo.com, extracted by WebScraping)</p>
Data for: "Market Power and Price Exposure: Learning from Changes in Renewable Energy Regulation"
<p>Given the key role of renewable energies in current and future electricity markets, it is important to understand how they affect firms' pricing incentives in these markets. In this paper, we study whether renewables depress electricity market prices, and how this effect depends on their degree of market price exposure. Our theoretical analysis shows that paying renewables with fixed prices, rather than with market-based prices, is relatively more effective at curbing market power when the dominant electricity firms own large shares of the renewable capacity, and <em>vice-versa</em>. To test this prediction, our empirical analysis leverages several short-lived changes to renewable energy pricing mechanisms in the Spanish electricity market. In this context, we find that the switch from full price exposure to fixed prices caused a 2-4% reduction in the average price-cost markup.</p>
Replication package for: The Lost Capital Asset Pricing Model
<p>The package contains the codes and the data analysis files necessary to reproduce the figures and tables in Andrei, Cujean, and Wilson (forthcoming), "The Lost Capital Asset Pricing Model," Review of Economic Studies. Detailed instructions are also given about accessing the raw data.</p>
Food Pricing Data in Newfoundland and Labrador, Canada 2020-2021
<p>This dataset contains data for food prices on several key food items in the Canadian province of Newfoundland and Labrador collected using citizen science, from October 2020 to December 2021. Data were collected in different places in the province on different timelines, with some locations receiving regular biweekly data and others having a single date inputted. The goal of this dataset was to gain high-resolution temporal data on food pricing to see variations over time, place, stores, online vs in-person shopping, sales, and food items.</p> <p>This data is the basis of the report: Liboiron, Max, Willa Neilsen, Morgan Davidson, Sarah Crocker, Amanda Asiamah, Kaitlyn Hawkins, Brittany Marie Schaefer, Patricia Johnson-Castle, Kerri Claire Neil, Lynn Blackwood, Corinne Neil, Sarah Sauvé, and Charlotte Florian. (2023). <em>Comparative Food Pricing in Newfoundland and Labrador using Citizen Science, 2020-2021</em>. Civic Laboratory for Environmental Action Research (CLEAR). St. John’s: Memorial University. </p> <p>Report, figures, etc are available at <a href="https://civiclaboratory.nl/nl-food-pricing-project/%20">https://civiclaboratory.nl/nl-food-pricing-project/</a></p>
Dataset article "Demand-Response Control of Electric Storage Water Heaters Based on Dynamic Electricity Pricing and Comfort Optimization"
<p>"README-SupplementaryMaterial.txt" explains the information gathered in each csv files, and including the DHW consumption profiles generated, the hourly electricity pricing for 2022 (Spain), and the experimental data utilized for the validation of the model. </p>
Price and features of housing rentals in Spain as of April 2023.
<pre>Information on each housing rental advertisement each of the Spanish province capitals as of April 23.</pre>
Instances and detailed results for the whole testbed of "The Storage Location Assignment and Picker Routing Problem: A Generic Branch-Cut-and-Price Algorithm"
<p>This repository contains the instances and detailed results used for the computational experiments in the article "The Storage Location Assignment and Picker Routing Problem: A Generic Branch-Cut-and-Price Algorithm". Two sets of instances are used:</p> <p><br> The first set of instances comes from the paper "Integrating storage location and order picking problems in warehouse planning" authored by Allyson Silva, Leandro C. Coelho, Maryzam Darvish and Jacques Renaud.<br> https://doi.org/10.1016/j.tre.2020.102003<br> Their instances are available on the following website: https://www.leandro-coelho.com/slot-assignment-and-order-picking/</p> <p><br> The second set of instances comes from the paper "Storage assignment for newly arrived items in forward picking areas with limited open locations" authored by Xiaolong Guo, Ran Chen, Shaofu Du and Yugang Yu.<br> https://doi.org/10.1016/j.tre.2021.102359<br> The set of small instances is made available on this repository, with the kind permission of the authors.</p>
Activision stock price
<p>Activision stock price dataset includes historical prices beginning 2010 January to 2022 September.</p> <p> </p>
Dataset for "EuroMod: Modelling European power markets with improved price granularity"
<p>Raw and derived results to support the paper "EuroMod: Modelling European power markets with improved price granularity".</p> <p>Description and readme at <a href="https://github.com/carlamtmendes/EuroMod">https://github.com/carlamtmendes/EuroMod</a>.</p>
A rich dataset of hourly residential electricity consumption data and survey answers from the iFlex dynamic pricing experiment
<p>An experiment was conducted to understand if and how households change their power consumption in response to variable hourly electricity prices. The data were collected from several Norwegian regions, and various price signals were tested over two winter periods from early 2020 to spring 2021. The dataset includes hourly consumption data of all participating households and answers to three surveys about household characteristics such as electric appliances, living conditions, socio-demographic variables, and willingness to be flexible. Temperature data are added to the dataset from public sources. This comprehensive dataset can be used for in-depth analysis of household flexibility potential. Furthermore, subgroups, such as low-income households or highly electrified households with electricity as a primary heating source, can be investigated to enhance the understanding of how these are affected by variable power prices.</p> <p>The dataset is described in detail in an accompanying data article in Data in Brief: <a href="https://www.sciencedirect.com/science/article/pii/S2352340923006716">A rich dataset of hourly residential electricity consumption data and survey answers from the iFlex dynamic pricing experiment - ScienceDirect</a></p> <p>Supplementary figures containing the survey results are available here: <a href="../records/11580541">Supplementary result diagrams from household surveys on implicit demand response (zenodo.org)</a></p> <p>Survey answers in Norwegian are available here: <a href="https://zenodo.org/records/15063303">iFleks-prosjekt: Spørreundersøkelser med husholdninger og næringsliv om forbruksrespons på elektrisitetspriser</a></p>
Data for: Evaluating heterogeneity in household travel response to carbon pricing: a study focusing on small and rural communities
Open the record for dataset details and reuse information.
Assessing predictive performance of supervised machine learning algorithms for a diamond pricing model
Open the record for dataset details and reuse information.
2009 modeled electricity prices from HiGRID for the California grid
Open the record for dataset details and reuse information.
Data of correlation of COVID-19 cases/deaths and the Gold price
<p>The data was automatically computed by the tool https://doi.org/10.5281/zenodo.3741812 and shows the correlation between COVID-19 cases/deaths in a given time interval and the gold price in the same interval.</p> <p>The folder input_data contains the raw data that was used to produce this dataset.<br> The file TOOL_VERSION contains the version of the above reference tool that was used.</p>
Spatial Distribution of the International Food Prices: Unexpected Heterogeneity and Randomness
<p>Global <a href="https://www.sciencedirect.com/topics/agricultural-and-biological-sciences/food-prices">food prices</a> are typically analysed in a time-series framework. We complement this approach by focusing on the spatial <a href="https://www.sciencedirect.com/topics/economics-econometrics-and-finance/price-dispersion">price dispersion</a> of the country-pair bilateral trade in the international food trade network (<em>IFTN</em>), for ten relevant commodities. The main purposes are to verify if the <a href="https://www.sciencedirect.com/topics/economics-econometrics-and-finance/price-convergence">Law of One Price</a> (<em>LOP</em>) holds and to investigate the emergence of randomness in the price-formation mechanism.</p> <p>We distinguish between the “internal” variance, which indicates the magnitude of price discrimination, and the “external” variance, that is a measure of price dispersion. We find that, for some commodities, spatial price dispersion is remarkable and persistent over time (i.e., failure of the <em>LOP</em>) and that there exists a strict correlation between price spikes and peaks in spatial price variability.</p> <p>We test whether the price distribution can be replicated through a <a href="https://www.sciencedirect.com/topics/economics-econometrics-and-finance/stochastic-process">stochastic process</a> of extraction. Surprisingly, the actual distribution of prices, for several commodities, is well described by a random distribution. Then, the process of data aggregation is not neutral because the information at the micro-level scale might be lost at the macro-scale, due to the complexity of the <em>IFTN</em>. Finally, we discuss some possible economic explanations of these outcomes and the main methodological, environmental, and policy consequences.</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.