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Auxiliary Euro-Calliope datasets: Spatio-temporal data representing national cooking demand and electric vehicle characteristic profiles in Europe
<p>Output generated by the <a href="https://github.com/RAMP-project/">RAMP engine</a> for use in the <a href="https://github.com/calliope-project/sector-coupled-euro-calliope">Sector-Coupled Euro-Calliope model</a>. The three datasets in this repository are described briefly here and in more detail in the accompanying README files. Each dataset has an hourly temporal resolution spanning the years 2000 - 2018 (inclusive) and a national spatial resolution spanning 26* - 28** countries in Europe. All datasets are dimensionless; only the profile shapes are used in Euro-Calliope.</p> <ul> <li>Cooking energy demand profiles (<em>ramp-cooking-profiles</em>): Profiles of heat energy demand for cooking in buildings in Europe, stochastically generated using the <a href="https://github.com/RAMP-project/RAMP">RAMP model</a> [1]. These profiles are used to distribute annual cooking energy demand in the Euro-Calliope workflow. This dataset covers 28 European countries**.</li> <li>Electric vehicle plug-in profiles (<em>ramp-ev-plugin-profiles</em>): Profiles of the percentage of parked electric vehicles, stochastically generated using the <a href="https://github.com/RAMP-project/RAMP-mobility">RAMP-Mobility model</a> [2]. These profiles are used in Euro-Calliope to define the maximum number of electric vehicles that could be plugged in and therefore available to be charged at any given time, assuming controlled (or "smart") charging. This dataset covers 26 European countries*.</li> <li>Electric vehicle energy consumption profiles (<em>ramp-ev-consumption-profiles</em>): Profiles of the electricity consumption of electric vehicles, stochastically generated using the <a href="https://github.com/RAMP-project/RAMP-mobility">RAMP-Mobility model</a> [2]. These profiles are aggregated in Euro-Calliope to provide a required percentage of total vehicle electricity demand that must be met in each month. This dataset covers 26 European countries*.</li> </ul> <p>* AUT, BEL, CHE, CZE, DEU, DNK, ESP, EST, FIN, FRA, GBR, HRV, HUN, IRL, ITA, LTU, LUX, LVA, NLD, NOR, POL, PRT, ROU, SVK, SVN, SWE</p> <p>** (*) + BGR, SRB</p> <p>*** ALB, MKD, GRC, CYP, BIH, MNE, ISL</p> <p>[1] Lombardi, Francesco, Sergio Balderrama, Sylvain Quoilin, and Emanuela Colombo. 2019. ‘Generating High-Resolution Multi-Energy Load Profiles for Remote Areas with an Open-Source Stochastic Model’. <em>Energy</em> 177 (June): 433–44. https://doi.org/10.1016/j.energy.2019.04.097.</p> <p>[2] Mangipinto, Andrea, Francesco Lombardi, Francesco Davide Sanvito, Matija Pavičević, Sylvain Quoilin, and Emanuela Colombo. 2022. ‘Impact of Mass-Scale Deployment of Electric Vehicles and Benefits of Smart Charging across All European Countries’. <em>Applied Energy</em> 312 (April): 118676. https://doi.org/10.1016/j.apenergy.2022.118676.</p>
Ensemble calculations of "98perc_sfcWindmax" from EURO-CORDEX data for Europe
<p><strong>Climate Index: </strong>98perc_sfcWindmax</p> <p><strong>Definition:</strong> Average of the annual 98<sup>th</sup> percentile of the daily maximum wind speed over a 30-year time-period.</p> <p><strong>Additional information:</strong> The dataset is based on an ensemble of EURO-CORDEX model simulations of daily maximum near-surface wind speed (sfcWindmax).</p> <p>Results (ensemble mean and ensemble standard deviation) are available for historical (1971-2000) and future (2011-2040, 2041-2070, 2071-2100) time periods and for the representative concentration pathways RCP2.6, RCP4.5 and RCP8.5.</p> <p>The EURO-CORDEX climate model simulations used are:</p> <ul> <li>SMHI-RCA4/ ICHEC-EC-EARTH, SMHI-RCA4/ MOHC-HadGEM2-ES</li> <li>CLMcom-CCLM4-8-17/ ICHEC-EC-EARTH, CLMcom-CCLM4-8-17/ MOHC-HadGEM2-ES</li> <li>DMI-HIRHAM5/ ICHEC-EC-EARTH</li> <li>KNMI-RACMO22E/ ICHEC-EC-EARTH, KNMI-RACMO22E/ MOHC-HadGEM2-ES</li> </ul>
Ensemble calculations of "Fmax" from EURO-CORDEX data for Europe
<p><strong>Climate Index: </strong>Fmax</p> <p><strong>Definition:</strong> Average of the annual maximum of the daily maximum wind speed over a 30-year time-period.</p> <p><strong>Additional information:</strong> The dataset is based on an ensemble of EURO-CORDEX model simulations of daily maximum near-surface wind speed (sfcWindmax).</p> <p>Results (ensemble mean and ensemble standard deviation) are available for historical (1971-2000) and future (2011-2040, 2041-2070, 2071-2100) time periods and for the representative concentration pathways RCP2.6, RCP4.5 and RCP8.5.</p> <p>The EURO-CORDEX climate model simulations used are:</p> <ul> <li>SMHI-RCA4/ ICHEC-EC-EARTH, SMHI-RCA4/ MOHC-HadGEM2-ES</li> <li>CLMcom-CCLM4-8-17/ ICHEC-EC-EARTH, CLMcom-CCLM4-8-17/ MOHC-HadGEM2-ES</li> <li>DMI-HIRHAM5/ ICHEC-EC-EARTH</li> <li>KNMI-RACMO22E/ ICHEC-EC-EARTH, KNMI-RACMO22E/ MOHC-HadGEM2-ES</li> </ul>
Augmented emission maps: the 1461 cc 81 kW Euro 6 diesel engine: update 1
<p>In order to enable the sharing of data the emission data for vehicles is standardized. The data exchange format contains all data that is applicable for a specific engine taxonomy code.</p> <p>This specific data set refers to the 1461 cc 81 kW Euro 6 diesel engine that has been applied in the several Renault, Nissan and Mercedes-Benz models (Kadjar, Megane, Scenic, Talisman, Captur, Clio, Kangoo; Qashqai, Juke, Pulsar, NV200; Citan).</p> <p>The standardized emission map has a “.map.txt” extension and is also human readable. The files starts with metadata which contains information about:</p> <ul> <li>the engine taxonomy code,</li> <li>total driven kilometers over which the data was gathered,</li> <li>total time in hours over which the data was gathered,</li> <li>the number of vehicles which were tested to create the emission map,</li> <li>the DOI (Digital Object Identifier) reference,</li> <li>Which emission maps are available in the file.</li> </ul> <p>The DOI 10.5281/zenodo refers to a meta-data document that provides the full description of the standardized emission map.</p>
Twitter Dataset for "Will You Take the Knee? Italian Twitter Echo Chambers' Genesis During EURO 2020"
<p>Echo chambers can be described as situations in which individuals encounter and interact only with viewpoints that confirm their own, thus moving, as a group, to more polarized and extreme positions. Recent literature mainly focuses on characterizing such entities via static observations, thus disregarding their temporal dimension. In this work, distancing from such a trend, we study, at multiple topological levels, echo chambers genesis related to the social discussions that took place in Italy during the EURO 2020 Championship. Our analysis focuses on a well-defined topic (i.e., BLM/racism) discussed on Twitter during a perfect temporally bound (sporting) event. Such characteristics allow us to track the rise and evolution of echo chambers in time, thus relating their existence to specific episodes.</p>
Dictionary of ENBIOS processors, Euro-Calliope inputs and ecoinvent .spold filenames
<p>Provides full details of ENBIOS structural processor structure, input sources from Euro-Calliope files, processor names and energy carrier details, and the names of the corresponding life cycle inventory (LCI) data files in ecoinvent .spold format. Note that the LCI .spold files referenced are those for the allocation at point of substitution (APOS) approach within version 3.8 of the ecoinvent database.</p> <p>New version (18 February 2022) includes new listings for biomass and coal as industrial fuels, as now included in ENBIOS base file.</p>
EURO-CORDEX Precipitation Intensity-Duration-Frequency Curves
<p>This dataset provides preliminary precipitation intensity-duration-frequency (IDF) values calculated from the <a href="https://cds.climate.copernicus.eu/datasets/projections-cordex-domains-single-levels">CMIP5 based EURO-CORDEX regional climate model simulations</a>. Values for the cities of Logroño, Spain; Gdynia, Poland; Milan Italy; and Athens Greece are provided for a historical and future period for the RCP 2.6, 4.5 and RCP 8.5 atmospheric greenhouse gas concentration scenarios for a total of 123 simulations.</p> <p>Technical Info</p> <p>The return period values are computed for exceedance periods of 2, 5, 10, 25, 50, 100, 200, and 500-years and durations of 3, 6, 12, and 24-hours using the generalized extreme value (GEV) distribution with the <a href="https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.genextreme.html">scipy.stats.genextreme </a>function from the Python SciPy library. Computations are performed from the output of a combination of 123 regional climate models (RCMs), global climate models (GCMs), climate change scenarios, and ensemble members. The historical data cover the period 1976 through 2005 and the future 2041 through 2070 for the RCP 2.6, 4.5 and 8.5 atmospheric greenhouse gas concentration scenarios. Included in the analysis, there are 39 unique RCM-GCM combinations with outputs from 48 historical, 15 RCP 2.6, 13 RCP 4.5, and 47 RCP 8.5 simulations.</p> <p>Data description: This dataset contains EURO CORDEX return period estimates computed for exceedance periods of 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-years and 3-, 6-, 12-, and 24-hour durations using the generalized extreme value (GEV) distribution. The data includes values based on outputs from a total of 123 simulation combinations, including 39 RCM–GCM configurations, three climate change scenario combinations for a historical period (1976-2005) and future period (2041-2070), and three ensemble members.</p> <p>Format:</p> <p>The format of this dataset is organized in one ZIP files: IDF_{Cityname}.zip. The zip file contains 48 csv files for each RCM-GCM combination and ensemble member that include IDFs for each available RCP scenario.</p>
Weather Regime definition for the Euro-Atlantic sector (Daily, DFJM, 1979-2018) used for ACDC-ESM
<p><strong>Weather Regime definition for the Euro-Atlantic sector at daily resolution from 1979-2018 for December to March in CSV format</strong></p> <p> </p> <p><strong>TL;DR</strong>: this is the weather regime assignment based the method as set out by Swinda K.J. Falkena in 'Revisiting the identification of wintertime atmosphericcirculation regimes in the Euro-Atlantic sector' (<a href="https://doi.org/10.1002/qj.3818">10.1002/qj.3818</a>). Daily data is provided for December to March for the period 1979-2018.</p> <p> </p> <p><strong>Method Description </strong><br> The weather regime assignment can be obtained by applying <em>k</em>-means clustering to the full field data of geopotential height data. Following the observed circulation in reanalysis data, the optimal number of clusters is six. By incorporating a weak persistence constraint in the clustering procedure the assignment is stabilized, without changing the weather regime occurrence rates.</p> <p>The six regimes used have been labelled to indicate atmospheric state. Due to their symmetry, a name (Atlantic Ridge (AR), North Atlantic Oscillation (NAO) and Scandinavian Blocking (SB)) and state (positive (+) and negative (-)) are used to label each of the six weather regimes. It should be noted that the naming convention used, does not imply that the weather associated with these six weather regimes is similar to a definition that uses four or two clusters to classify the weather.</p> <p>Full details on the method can be found in: Swinda K.J. Falkena, et al, 'Revisiting the identification of wintertime atmosphericcirculation regimes in the Euro-Atlantic sector' (DOI:<a href="https://doi.org/10.1002/qj.3818">10.1002/qj.3818</a>). The original implementation and source code can be found on gitHub via: <a href="https://github.com/SwindaKJ/Regimes_Public">github.com/SwindaKJ/Regimes_Public</a>.</p> <p> </p> <p><strong>Data structure description</strong><br> The file is provided in CSV (.csv) format with a semicolon (;) as separator. The first row stores the column labels. The columns contain the following:</p> <ul> <li>first column (or A) contains the valid-time <ul> <li>Label: datetime</li> <li>Contents represent time with text as [DD/MM/YYYY])</li> </ul> </li> <li>second column (or B) contains the assigned weather regime <ul> <li>Label: WR</li> <li>Contents represent the assigned cluster as an interger in the range [0,5]</li> <li>Meaning: 0="SB-", 1="AR+", 2="NAO-", 3="SB+", 4="NAO+", 5="AR-"</li> </ul> </li> </ul> <p> </p> <p><strong>DISCLAIMER</strong>: <em>the content of this dataset has been created with the greatest possible care. However, we invite to use the original assignement of weather regimes for critical applications and studies. </em></p>
Augmented emission maps: several petrol and diesel (Euro 5 - 6d-Temp) vehicle-specific augmented emission maps
<p>In order to enable the sharing of data the emission data for vehicles is standardized. The data exchange format contains all data that is applicable for a specific engine taxonomy code.</p> <p>The standardized emission map has a “.map.txt” extension and is also human readable. The files starts with metadata which contains information about:</p> <ul> <li>the engine taxonomy code,</li> <li>total driven kilometers over which the data was gathered,</li> <li>total time in hours over which the data was gathered,</li> <li>the number of vehicles which were tested to create the emission map,</li> <li>the DOI (Digital Object Identifier) reference,</li> <li>Which emission maps are available in the file.</li> </ul> <p>The DOI <a href="http://doi.org/10.5281/zenodo.4268034">10.5281/zenodo</a> refers to a meta-data document that provides the full description of the standardized emission map</p>
Ensemble calculations of "Tn10p" from EURO-CORDEX data for Europe
<p><strong>Climate Index: </strong>Tn10p</p> <p><strong>Definition:</strong> Average number of days that the daily minimum temperature is below the 10th percentile of daily minimum temperatures of a five day window.</p> <p><strong>Additional information:</strong> The dataset is based on an ensemble of EURO-CORDEX model simulations of daily near-surface maximum temperature. All ensemble members are bias-corrected against the gridded daily observational dataset E-OBS.</p> <p>Results (ensemble mean and standard deviation) are available for historical (1971-2000) and future (2011-2040, 2041-2070, 2071-2100) climate periods and for the representative concentration pathways RCP2.6, RCP4.5 and RCP8.5.</p> <p>The bias-corrected EURO-CORDEX climate model simulations used are:</p> <ul> <li>CLMcom-CCLM4-8-17/ICHEC-EC-EARTH, CLMcom-CCLM4-8-17/MOHC-HadGEM2-ES</li> <li>DMI-HIRHAM5/ICHEC-EC-EARTH</li> <li>KNMI-RACMO22E/ICHEC-EC-EARTH, KNMI-RACMO22E/MOHC-HadGEM2-ES</li> <li>SMHI-RCA4/ICHEC-EC-EARTH, SMHI-RCA4/MOHC-HadGEM2-ES</li> </ul>
Ensemble calculations of "Ice Days" from EURO-CORDEX data for Europe
<p><strong>Climate Index: </strong>Ice days</p> <p><strong>Definition:</strong> Number of days with daily maximum temperature below 0°C.</p> <p><strong>Additional information:</strong> The dataset is based on an ensemble of EURO-CORDEX model simulations of daily near-surface maximum temperature. All ensemble members are bias-corrected against the gridded daily observational dataset E-OBS.</p> <p>Results (ensemble mean and standard deviation) are available for historical (1971-2000) and future (2011-2040, 2041-2070, 2071-2100) climate periods and for the representative concentration pathways RCP2.6, RCP4.5 and RCP8.5.</p> <p>The bias-corrected EURO-CORDEX climate model simulations used are:</p> <ul> <li>CLMcom-CCLM4-8-17/ICHEC-EC-EARTH, CLMcom-CCLM4-8-17/MOHC-HadGEM2-ES</li> <li>DMI-HIRHAM5/ICHEC-EC-EARTH</li> <li>KNMI-RACMO22E/ICHEC-EC-EARTH, KNMI-RACMO22E/MOHC-HadGEM2-ES</li> <li>SMHI-RCA4/ICHEC-EC-EARTH, SMHI-RCA4/MOHC-HadGEM2-ES</li> </ul>
Ensemble calculations of "RX1day" from EURO-CORDEX data for Europe
<p><strong>Climate Index: </strong>RX1day</p> <p><strong>Definition:</strong> Greatest one-day precipitation amount.</p> <p><strong>Additional information:</strong> The dataset is based on an ensemble of EURO-CORDEX model simulations of daily near-surface maximum temperature. All ensemble members are bias-corrected against the gridded daily observational dataset E-OBS.</p> <p>Results (ensemble mean and standard deviation) are available for historical (1971-2000) and future (2011-2040, 2041-2070, 2071-2100) climate periods and for the representative concentration pathways RCP2.6, RCP4.5 and RCP8.5.</p> <p>The bias-corrected EURO-CORDEX climate model simulations used are:</p> <ul> <li>CLMcom-CCLM4-8-17/ICHEC-EC-EARTH, CLMcom-CCLM4-8-17/MOHC-HadGEM2-ES</li> <li>DMI-HIRHAM5/ICHEC-EC-EARTH</li> <li>KNMI-RACMO22E/ICHEC-EC-EARTH, KNMI-RACMO22E/MOHC-HadGEM2-ES</li> <li>SMHI-RCA4/ICHEC-EC-EARTH, SMHI-RCA4/MOHC-HadGEM2-ES</li> </ul>
Augmented emission maps: 1968 cc 55 kW Euro 6 diesel engine
<p>In order to enable the sharing of data the emission data for vehicles is standardized. The data exchange format contains all data that is applicable for a specific engine taxonomy code.</p> <p>This specific data set refers to the 1968 cc 55 kW Euro 6 diesel engine that has been applied in the Volkswagen Caddy.</p> <p>The standardized emission map has a “.map.txt” extension and is also human readable. The files starts with metadata which contains information about:</p> <ul> <li>the engine taxonomy code,</li> <li>total driven kilometers over which the data was gathered,</li> <li>total time in hours over which the data was gathered,</li> <li>the number of vehicles which were tested to create the emission map,</li> <li>the DOI (Digital Object Identifier) reference,</li> <li>Which emission maps are available in the file.</li> </ul> <p>The DOI 10.5281/zenodo refers to a meta-data document that provides the full description of the standardized emission map.</p>
Data of foreign exchange rates against the Euro
<p>The dataset is made up of a collection of the most recent information on the euro foreign exchange reference rates of 81 currencies published on the website https://datosmacro.expansion.com/divisas at the time of sampling (April 14, 2020).</p> <p>There is a list of 30 reference rates for each currency.</p> <p>The information on the time span of the exchange rates depends on each currency and covers the period from 2018 to 2020 (the most recent published information is collected).</p> <p>Below you can find a description of the attributes that make up the data set:</p> <ul> <li>"<strong>Tipo de cambio</strong>": description of the Euro / foreign exchange reference rate.</li> <li>"<strong>Fecha</strong>": date on which the exchange rate was recorded.</li> <li>"<strong>Cambio</strong>": value of the Euro / foreign exchange reference rate.</li> <li>"<strong>Var.%</strong>": percentage change from the previous recorded foreign exchange reference rate.</li> </ul> <p>File format is <strong>ISO 8859-15 (Latin-9)</strong>.</p> <p>File content: 2431 lines (the first one is the header).</p> <p>File delimiter: "<strong>;</strong>"</p> <p>End-of-line character: <strong>line feed</strong></p> <p> </p>
Augmented emission maps: 998 cc 74 kW Euro 6dT petrol engine
<p>In order to enable the sharing of data the emission data for vehicles is standardized. The data exchange format contains all data that is applicable for a specific engine taxonomy code.</p> <p>This specific data set refers to the 998 cc 74 kW Euro 6dT petrol engine that has been applied in the Ford Fiesta, Ecosport, Transit Courier.</p> <p>The standardized emission map has a “.map.txt” extension and is also human readable. The files starts with metadata which contains information about:</p> <ul> <li>the engine taxonomy code,</li> <li>total driven kilometers over which the data was gathered,</li> <li>total time in hours over which the data was gathered,</li> <li>the number of vehicles which were tested to create the emission map,</li> <li>the DOI (Digital Object Identifier) reference,</li> <li>Which emission maps are available in the file.</li> </ul> <p>The DOI <a href="http://doi.org/10.5281/zenodo.4268034">http://doi.org/10.5281/zenodo.4268034</a> refers to a updated meta-data document that provides the full description of the standardized emission map.</p>
Augmented emission maps: 1969 cc 140 kW Euro 6dT diesel engine
<p>In order to enable the sharing of data the emission data for vehicles is standardized. The data exchange format contains all data that is applicable for a specific engine taxonomy code.</p> <p>This specific data set refers to the 1969 cc 140 kW Euro 6dT diesel engine that has been applied in the Volvo XC40, V60, XC60, V90, and S90.</p> <p>The standardized emission map has a “.map.txt” extension and is also human readable. The files starts with metadata which contains information about:</p> <ul> <li>the engine taxonomy code,</li> <li>total driven kilometers over which the data was gathered,</li> <li>total time in hours over which the data was gathered,</li> <li>the number of vehicles which were tested to create the emission map,</li> <li>the DOI (Digital Object Identifier) reference,</li> <li>Which emission maps are available in the file.</li> </ul> <p>The DOI <a href="http://doi.org/10.5281/zenodo.4268034">http://doi.org/10.5281/zenodo.4268034</a> refers to a updated meta-data document that provides the full description of the standardized emission map.</p>
Augmented emission maps: 1950 cc 110 kW Euro 6c diesel engine
<p>In order to enable the sharing of data the emission data for vehicles is standardized. The data exchange format contains all data that is applicable for a specific engine taxonomy code.</p> <p>This specific data set refers to the 1950 cc 110 kW Euro 6c diesel engine that has been applied in the Mercedes E200D.</p> <p>The standardized emission map has a “.map.txt” extension and is also human readable. The files starts with metadata which contains information about:</p> <ul> <li>the engine taxonomy code,</li> <li>total driven kilometers over which the data was gathered,</li> <li>total time in hours over which the data was gathered,</li> <li>the number of vehicles which were tested to create the emission map,</li> <li>the DOI (Digital Object Identifier) reference,</li> <li>Which emission maps are available in the file.</li> </ul> <p>The DOI <a href="http://doi.org/10.5281/zenodo.4268034">http://doi.org/10.5281/zenodo.4268034</a> refers to a updated meta-data document that provides the full description of the standardized emission map.</p>
Augmented emission maps: 1596 cc 74 kW Euro 3 petrol engine
<p>In order to enable the sharing of data the emission data for vehicles is standardized. The data exchange format contains all data that is applicable for a specific engine taxonomy code.</p> <p>This specific data set refers to the 1596 cc 74 kW Euro 3 petrol engine that has been applied in the Ford.</p> <p>The standardized emission map has a “.map.txt” extension and is also human readable. The files starts with metadata which contains information about:</p> <ul> <li>the engine taxonomy code,</li> <li>total driven kilometers over which the data was gathered,</li> <li>total time in hours over which the data was gathered,</li> <li>the number of vehicles which were tested to create the emission map,</li> <li>the DOI (Digital Object Identifier) reference,</li> <li>Which emission maps are available in the file.</li> </ul> <p>The DOI <a href="http://doi.org/10.5281/zenodo.4268034">http://doi.org/10.5281/zenodo.4268034</a> refers to a updated meta-data document that provides the full description of the standardized emission map.</p>
Augmented emission maps: 2191 cc 110 kW Euro 6b diesel engine
<p>In order to enable the sharing of data the emission data for vehicles is standardized. The data exchange format contains all data that is applicable for a specific engine taxonomy code.</p> <p>This specific data set refers to the 2191 cc 110 kW Euro 6b diesel engine that has been applied in the Mazda.</p> <p>The standardized emission map has a “.map.txt” extension and is also human readable. The files starts with metadata which contains information about:</p> <ul> <li>the engine taxonomy code,</li> <li>total driven kilometers over which the data was gathered,</li> <li>total time in hours over which the data was gathered,</li> <li>the number of vehicles which were tested to create the emission map,</li> <li>the DOI (Digital Object Identifier) reference,</li> <li>Which emission maps are available in the file.</li> </ul> <p>The DOI <a href="http://doi.org/10.5281/zenodo.4268034">http://doi.org/10.5281/zenodo.4268034</a> refers to a updated meta-data document that provides the full description of the standardized emission map.</p>
Augmented emission maps: 1242 cc 48 kW Euro 4 petrol engine
<p>In order to enable the sharing of data the emission data for vehicles is standardized. The data exchange format contains all data that is applicable for a specific engine taxonomy code.</p> <p>This specific data set refers to the 1242 cc 48 kW Euro 4 petrol engine that has been applied in the Fiat Punto, Doblo.</p> <p>The standardized emission map has a “.map.txt” extension and is also human readable. The files starts with metadata which contains information about:</p> <ul> <li>the engine taxonomy code,</li> <li>total driven kilometers over which the data was gathered,</li> <li>total time in hours over which the data was gathered,</li> <li>the number of vehicles which were tested to create the emission map,</li> <li>the DOI (Digital Object Identifier) reference,</li> <li>Which emission maps are available in the file.</li> </ul> <p>The DOI <a href="http://doi.org/10.5281/zenodo.4268034">http://doi.org/10.5281/zenodo.4268034</a> refers to a updated meta-data document that provides the full description of the standardized emission map.</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.