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855 results for “model system”
Viet Nam Technology Catalogue - Technology data input for power system modelling in Viet Nam
<p>Today, innovations and technology improvements within renewable energy are taking place at a very rapid pace. Long-term energy planning is very dependent on cost and performance of future energy producing technologies.<br> This technology catalogue provides estimates of costs and performance for a wide range of power producing technologies, thereby building one of the key inputs to good energy planning in Vietnam.<br> Due to the multi-stakeholder involvement in the data collection process, the technology catalogue contains data that have been scrutinised and discussed by a broad range of relevant stakeholders including the Ministry of Industry and Trade – MOIT, Vietnam Electricity – EVN, independent power producers, local and international consultants, organizations, associations and universities. This is essential because a main objective is to produce a technology catalogue which is well anchored amongst all stakeholders.<br> The technology catalogue will assist the long-term energy modelling in Vietnam and support government institutions, private energy companies, think tanks and others with a common and broadly recognized set of data for electricity producing technologies in Vietnam in the future.</p>
data set related to article A Nervous System-Specific Model of Creatine Transporter Deficiency Recapitulates the Cognitive Endophenotype of the Disease: a Longitudinal Study
<p>This record contains raw data related to article A Nervous System-Specific Model of Creatine Transporter Deficiency Recapitulates the Cognitive Endophenotype of the Disease: a Longitudinal Study</p>
Tutorial Data Bundle for PyPSA-Eur: An Open Optimisation Model of the European Transmission System
<p><strong>PyPSA-Eur</strong> is an open model dataset of the European power system at the transmission network level that covers the full ENTSO-E area. It can be built using the code provided at <a href="https://github.com/PyPSA/PyPSA-eur">https://github.com/PyPSA/PyPSA-eur</a>.</p> <p><strong>It contains</strong> alternating current lines at and above 220 kV voltage level and all high voltage direct current lines, substations, an open database of conventional power plants, time series for electrical demand and variable renewable generator availability, and geographic potentials for the expansion of wind and solar power.</p> <p><strong>Not all data dependencies</strong> are shipped with the <a href="https://github.com/PyPSA/PyPSA-eur">code repository</a>, since git is not suited for handling large changing files. Instead we provide separate <strong>data bundles</strong> to be downloaded and extracted as noted in the <a href="https://pypsa-eur.readthedocs.io/en/latest/installation.html">documentation</a>.</p> <p>This is the <strong>lightweight</strong> data bundle to be used for the <a href="https://pypsa-eur.readthedocs.io/en/latest/tutorial.html">PyPSA-Eur tutorial</a>. It excludes large bathymetry and natural protection area datasets.</p> <p>While the <a href="https://github.com/PyPSA/PyPSA-eur">code</a> in PyPSA-Eur is released as free software under the <a href="https://www.gnu.org/licenses/gpl-3.0.en.html">GPLv3</a>, <strong>different licenses and terms of use</strong> apply to the various input data, which are summarised and linked below:</p> <p><strong>corine/*</strong></p> <ul> <li>CORINE Land Cover (CLC) database</li> <li><strong>Source:</strong> <a href="https://land.copernicus.eu/pan-european/corine-land-cover/clc-2012/">https://land.copernicus.eu/pan-european/corine-land-cover/clc-2012/</a></li> <li><strong>Extract from Terms of Use:</strong></li> </ul> <blockquote> <p>Access to data is based on a principle of full, open and free access as established by the Copernicus data and information policy Regulation (EU) No 1159/2013 of 12 July 2013. This regulation establishes registration and licensing conditions for GMES/Copernicus users and can be found here. Free, full and open access to this data set is made on the conditions that:</p> <ul> <li> <p>When distributing or communicating Copernicus dedicated data and Copernicus service information to the public, users shall inform the public of the source of that data and information.</p> </li> <li> <p>Users shall make sure not to convey the impression to the public that the user's activities are officially endorsed by the Union.</p> </li> <li> <p>Where that data or information has been adapted or modified, the user shall clearly state this.</p> </li> <li> <p>The data remain the sole property of the European Union. Any information and data produced in the framework of the action shall be the sole property of the European Union. Any communication and publication by the beneficiary shall acknowledge that the data were produced “with funding by the European Union”.</p> </li> </ul> </blockquote> <ul> <li><a href="https://land.copernicus.eu/pan-european/corine-land-cover/clc-2012?tab=metadata">https://land.copernicus.eu/pan-european/corine-land-cover/clc-2012?tab=metadata</a></li> </ul> <p><strong>eez/*</strong></p> <ul> <li>World exclusive economic zones (EEZ)</li> <li><strong>Source:</strong> <a href="http://www.marineregions.org/sources.php#unioneezcountry">http://www.marineregions.org/sources.php#unioneezcountry</a></li> <li><strong>Extract from Terms of Use:</strong></li> </ul> <blockquote> <p>Marine Regions’ products are licensed under CC-BY-NC-SA. Please contact us for other uses of the Licensed Material beyond license terms. We kindly request our users not to make our products available for download elsewhere and to always refer to marineregions.org for the most up-to-date products and services.</p> </blockquote> <ul> <li><a href="http://www.marineregions.org/disclaimer.php">http://www.marineregions.org/disclaimer.php</a></li> </ul> <p><strong>naturalearth/*</strong></p> <ul> <li>World country shapes</li> <li><strong>Source:</strong> <a href="https://www.naturalearthdata.com/downloads/10m-cultural-vectors/10m-admin-0-countries/">https://www.naturalearthdata.com/downloads/10m-cultural-vectors/10m-admin-0-countries/</a></li> <li><strong>Extract from Terms of Use:</strong></li> </ul> <blockquote> <p>All versions of Natural Earth raster + vector map data found on this website are in the public domain. You may use the maps in any manner, including modifying the content and design, electronic dissemination, and offset printing. The primary authors, Tom Patterson and Nathaniel Vaughn Kelso, and all other contributors renounce all financial claim to the maps and invites you to use them for personal, educational, and commercial purposes.</p> <p>No permission is needed to use Natural Earth. Crediting the authors is unnecessary.</p> </blockquote> <ul> <li><a href="http://www.naturalearthdata.com/about/terms-of-use/">http://www.naturalearthdata.com/about/terms-of-use/</a></li> </ul> <p><strong>NUTS_2013_60M_SH/*</strong></p> <ul> <li>Europe NUTS3 regions</li> <li><strong>Source:</strong> <a href="https://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/administrative-units-statistical-units">https://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/administrative-units-statistical-units</a></li> <li><strong>Extract from Terms of Use:</strong></li> </ul> <blockquote> <p>In addition to the general copyright and licence policy applicable to the whole Eurostat website, the following specific provisions apply to the datasets you are downloading. The download and usage of these data is subject to the acceptance of the following clauses:</p> <ol> <li> <p>The Commission agrees to grant the non-exclusive and not transferable right to use and process the Eurostat/GISCO geographical data downloaded from this page (the "data").</p> </li> <li> <p>The permission to use the data is granted on condition that: the data will not be used for commercial purposes; the source will be acknowledged. A copyright notice, as specified below, will have to be visible on any printed or electronic publication using the data downloaded from this page.</p> </li> </ol> </blockquote> <ul> <li><a href="https://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/administrative-units-statistical-units">https://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/administrative-units-statistical-units</a></li> <li><a href="https://ec.europa.eu/eurostat/about/policies/copyright">https://ec.europa.eu/eurostat/about/policies/copyright</a></li> </ul> <p><strong>ch_cantons.csv</strong></p> <ul> <li>Mapping between Swiss Cantons and NUTS3 regions</li> <li><strong>Source:</strong> <a href="https://en.wikipedia.org/wiki/Data_codes_for_Switzerland">https://en.wikipedia.org/wiki/Data_codes_for_Switzerland</a></li> <li><strong>Extract from Terms of Use:</strong></li> </ul> <blockquote> <p>Creative Commons Attribution-ShareAlike 3.0 Unported License</p> </blockquote> <ul> <li><a href="https://en.wikipedia.org/wiki/Data_codes_for_Switzerland">https://en.wikipedia.org/wiki/Data_codes_for_Switzerland</a></li> </ul> <p><strong>EIA_hydro_generation_2000_2014.csv</strong></p> <ul> <li>Hydroelectricity generation per country and year</li> <li><strong>Source:</strong> <a href="https://www.eia.gov/beta/international/data/browser/#/?pa=000000000000000000000000000000g&c=1028i008006gg6168g80a4k000e0ag00gg0004g800ho00g8&ct=0&ug=8&tl_id=2-A&vs=INTL.33-12-ALB-BKWH.A&cy=2014&vo=0&v=H&start=2000&end=2016">https://www.eia.gov/beta/international/data/browser/#/?pa=000000000000000000000000000000g&c=1028i008006gg6168g80a4k000e0ag00gg0004g800ho00g8&ct=0&ug=8&tl_id=2-A&vs=INTL.33-12-ALB-BKWH.A&cy=2014&vo=0&v=H&start=2000&end=2016</a></li> <li><strong>Extract from Terms of Use:</strong></li> </ul> <blockquote> <p>Public domain and use of EIA content: U.S. government publications are in the public domain and are not subject to copyright protection. You may use and/or distribute any of our data, files, databases, reports, graphs, charts, and other information products that are on our website or that you receive through our email distribution service. However, if you use or reproduce any of our information products, you should use an acknowledgment, which includes the publication date, such as: "Source: U.S. Energy Information Administration (Oct 2008)."</p> </blockquote> <ul> <li><a href="https://www.eia.gov/about/copyrights_reuse.php">https://www.eia.gov/about/copyrights_reuse.php</a></li> </ul> <p><strong>hydro_capacities.csv</strong></p> <p>Hydroelectricity generation and storage capacities</p> <ul> <li><strong>Source:</strong> <ul> <li> <p>A. Kies, K. Chattopadhyay, L. von Bremen, E. Lorenz, D. Heinemann, RESTORE 2050 Work Package Report D12: Simulation of renewable feed-in for power system studies., Tech. rep., RESTORE 2050 (2016).</p> </li> <li> <p>B. Pfluger, F. Sensfuß, G. Schubert, J. Leisentritt, Tangible ways towards climate protection in the European Union (EU Long-term scenarios 2050), Fraunhofer ISI. <a href="https://www.isi.fraunhofer.de/content/dam/isi/dokumente/ccx/2011/Final_Report_EU-Long-term-scenarios-2050.pdf">https://www.isi.fraunhofer.de/content/dam/isi/dokumente/ccx/2011/Final_Report_EU-Long-term-scenarios-2050.pdf</a></p> </li> </ul> </li> </ul> <p><strong>je-e-21.03.02.xls</strong></p> <ul> <li>Population and GDP data for Swiss Cantons</li> <li><strong>Source:</strong> <a href="https://www.bfs.admin.ch/bfs/en/home/news/whats-new.assetdetail.7786557.html">https://www.bfs.admin.ch/bfs/en/home/news/whats-new.assetdetail.7786557.html</a></li> <li><strong>Extract from Terms of Use:</strong></li> </ul> <blockquote> <p>Information on the websites of the Federal Authorities is accessible to the public. Downloading, copying or integrating content (texts, tables, graphics, maps, photos or any other data) does not entail any transfer of rights to the content.</p> <p>Copyright and any other rights relating to content available on the websites of the Federal Authorities are the exclusive property of the Federal Authorities or of any other expressly mentioned owners.</p> <p>Any reproduction requires the prior written consent of the copyright holder. The source of the content (statistical results) should always be given. Anyone who intends on using statistical results for commercial purposes or gain must obtain an authorisation pursuant to Art. 13 of the Fee Ordinance and is liable to pay an indemnity. Please contact the FSO for this purpose.</p> </blockquote> <ul> <li><a href="https://www.bfs.admin.ch/bfs/en/home/fso/swiss-federal-statistical-office/terms-of-use.html">https://www.bfs.admin.ch/bfs/en/home/fso/swiss-federal-statistical-office/terms-of-use.html</a></li> <li><a href="https://www.bfs.admin.ch/bfs/de/home/bfs/oeffentliche-statistik/copyright.html">https://www.bfs.admin.ch/bfs/de/home/bfs/oeffentliche-statistik/copyright.html</a></li> </ul> <p><strong>nama_10r_3gdp.tsv.gz</strong></p> <ul> <li>Gross domestic product (GDP) by NUTS3 region</li> <li><strong>Source:</strong> <a href="http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=nama_10r_3gdp&lang=">http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=nama_10r_3gdp&lang=</a></li> <li><strong>Extract from Terms of Use:</strong></li> </ul> <blockquote> <p>Eurostat has a policy of encouraging free re-use of its data, both for non-commercial and commercial purposes. All statistical data, metadata, content of web pages or other dissemination tools, official publications and other documents published on its website, with the exceptions listed below, can be reused without any payment or written licence provided that:</p> <ul> <li> <p>the source is indicated as Eurostat;</p> </li> <li> <p>when re-use involves modifications to the data or text, this must be stated clearly to the end user of the information.</p> </li> </ul> <p>Exceptions</p> <ul> <li> <p>The permission granted above does not extend to any material whose copyright is identified as belonging to a third-party, such as photos or illustrations from copyright holders other than the European Union. In these circumstances, authorisation must be obtained from the relevant copyright holder(s).</p> </li> <li> <p>Logos and trademarks are excluded from the above mentioned general permission, except if they are redistributed as an integral part of a Eurostat publication and if the publication is redistributed unchanged.</p> </li> <li> <p>When reuse involves translations of publications or modifications to the data or text, this must be stated clearly to the end user of the information. A disclaimer regarding the non-responsibility of Eurostat shall be included.</p> </li> </ul> </blockquote> <ul> <li><a href="https://ec.europa.eu/eurostat/about/policies/copyright">https://ec.europa.eu/eurostat/about/policies/copyright</a></li> </ul> <p><strong>nama_10r_3popgdp.tsv.gz</strong></p> <ul> <li>Population by NUTS3 region</li> <li><strong>Source:</strong> <a href="http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=nama_10r_3popgdp&lang=en">http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=nama_10r_3popgdp&lang=en</a></li> <li><strong>Extract from Terms of Use:</strong></li> </ul> <blockquote> <p>Eurostat has a policy of encouraging free re-use of its data, both for non-commercial and commercial purposes. All statistical data, metadata, content of web pages or other dissemination tools, official publications and other documents published on its website, with the exceptions listed below, can be reused without any payment or written licence provided that:</p> <ul> <li> <p>the source is indicated as Eurostat;</p> </li> <li> <p>when re-use involves modifications to the data or text, this must be stated clearly to the end user of the information.</p> </li> </ul> <p>Exceptions</p> <ul> <li> <p>The permission granted above does not extend to any material whose copyright is identified as belonging to a third-party, such as photos or illustrations from copyright holders other than the European Union. In these circumstances, authorisation must be obtained from the relevant copyright holder(s).</p> </li> <li> <p>Logos and trademarks are excluded from the above mentioned general permission, except if they are redistributed as an integral part of a Eurostat publication and if the publication is redistributed unchanged.</p> </li> <li> <p>When reuse involves translations of publications or modifications to the data or text, this must be stated clearly to the end user of the information. A disclaimer regarding the non-responsibility of Eurostat shall be included.</p> </li> </ul> </blockquote> <ul> <li><a href="https://ec.europa.eu/eurostat/about/policies/copyright">https://ec.europa.eu/eurostat/about/policies/copyright</a></li> </ul> <p><strong>time_series_60min_singleindex_filtered.csv</strong></p> <ul> <li>ENTSO-E hourly per-country load profiles</li> <li><strong>Source:</strong> <a href="https://data.open-power-system-data.org/time_series/2019-06-05/time_series_60min_singleindex.csv">https://data.open-power-system-data.org/time_series/2019-06-05/time_series_60min_singleindex.csv</a></li> <li><strong>Extract from Terms of Use:</strong></li> </ul> <blockquote> <p>Attribution in Chicago author-date style should be given as follows: "Open Power System Data. 2019. Data Package Time series. Version 2019-06-05. <a href="https://doi.org/10.25832/time_series/2019-06-05">https://doi.org/10.25832/time_series/2019-06-05</a>. (Primary data from various sources, for a complete list see URL)."</p> </blockquote> <ul> <li><a href="https://data.open-power-system-data.org/time_series/2019-06-05/README.md">https://data.open-power-system-data.org/time_series/2019-06-05/README.md</a></li> </ul>
Groundwater model outputs for coastal aquifer system
<p>Model outputs for 9 predevelopment coastal groundwater models, and one development scenario for each of these models. This data has been used to generate results for a manuscript which has been submitted for publication.</p>
The INMCM-4.8 Earth system model data used in the paper by Guryanov V.V. et al. entitled ''The present-day and future lightning frequency as simulated by four CMIP6 models'
<p>The INMCM-4.8 Earth system model data used in the paper by Guryanov V.V. et al. entitled ''The present-day and future lightning frequency as simulated by four CMIP6 models'</p>
Post-processed SAM (System for Atmospheric Modeling) simulation output for "Tipping to an Aggregated State by Mesoscale Convective Systems"
<p>Statistics output files for all variables, for a select number of SAM (System for Atmospheric Modeling v. 6.11) simulation runs used in the study "Tipping to an Aggregated State by Mesoscale Convective Systems". The following simulations are included: DIU, OCEAN, DIU2OCEAN branch A1, DIU2OCEAN branch A2.</p>
Data bundle for powerd-data: A transparent and reproducible data processing pipeline for energy system modeling based on egon-data
<div> <p><strong>powerd-data</strong> provides a transparent and reproducible open data based data processing pipeline for generating data models suitable for energy system modeling. Is is a fork from the open-source tool <strong>egon-data</strong>. </p> <p>powerd-data and egon-data retrieve and process data from several different external input sources. As not all data dependencies can be downloaded automatically from external sources, we provide a data bundle to be downloaded by egon-data.</p> <p>The following data sets are part of the available data bundle:</p> <ol> <li>district_heating_shares: <ul> <li>Assumed district heating share for all European countries in 2050</li> <li>Source: Own representation</li> <li>License: Attribution 4.0 International (CC BY 4.0)</li> </ul> </li> <li>egon_demandregio_cts_ind:<br> <ul> <li>Industrial and CTS demands per branch and NUTS3 region in Germany for the year 2050</li> <li>Source: egon-data, based on data from DemandRegio disaggregator tool</li> <li>License: Data license Germany – © FfE 2019, © Statistisches Bundesamt (Destatis), 2008-2017 – version 2.0</li> </ul> </li> <li>industrial_gas_demand: <ul> <li>This folder contains 5 files. The files CH4_for_industry_eGon100RE.json, CH4_for_industry_eGon2035.json, H2_for_industry_eGon100RE.json and H2_for_industry_eGon2035.json contain the industrial hourly demands for hydrogen and methane in NUTS3 resolution for the scenarios eGon100RE and eGon2035. The file region_corr.json provides information that make it possible to correlate each load to a geographical position.</li> <li>License: Attribution 4.0 International (CC BY 4.0) © FfE, eXtremOS Project</li> </ul> </li> </ol> <p> </p> </div>
Displacement time series from Foamquake and Gelquake in single- and double asperity configurations: Supplementary material to "Scaled seismotectonic models of megathrust seismic cycles through the lens of dynamical system theory"
<p><span>This dataset includes displacement data from 4 experiments performed with Foamquake and Gelquake (Mastella et al. 2022, Corbi et al., 2013), two scaled seismotectonic models reproducing the megathrust seismic cycle running at the Laboratory of Experimental Tectonics LET (Univ. Roma Tre). These models enable the generation of hundreds of quasi-periodic cycles of stress accumulation and sudden release through the spontaneous nucleation of frictional instabilities within one or many analog seismic asperities. Models are monitored by the means of a high-resolution top-view monitoring camera acquiring images at 7.5 and 50 frames per second for Gelquake and Foamquake, respectively. This dataset has been created with particle image velocimetry (PIV, using MatPIV (Sveen 2004)) through the cross-correlation between consecutive images. The PIV provides us with velocity field time series. These are integrated to obtain displacement time series. From the whole model surface, in each experiment we selected data from a cross-section striking parallel to the trench and located at the downdip center of the asperities. Cross sections are discretized in 28 and 29 target points in Gelquake and Foamquake, respectively. </span></p> <p><span>Displacement time series have been normalized to zero mean and unit variance to ensure the same level of magnitude for comparison between different experiments. Linear and second order polynomial trends have been removed to make the stick-slip confined in a given range and avoid non-stationary behavior. Time series data are not passed through filters (e.g., smoothing or moving average).</span></p> <p><span>Filename informs about the nature of the analog upper plate (i.e., foam and gel) and geometrical configuration of asperities (i.e., mono and twin). Together with individual files for each experiment, this dataset includes a Matlab script (i.e., all_timeseries.m) that allows visualization of displacement time series from individual target points. </span></p> <p><span>This dataset is supplementary to the paper in SEISMICA "Scaled seismotectonic models of megathrust seismic cycles through the lens of dynamical system theory” by Corbi et al. (2024), where detailed descriptions of models and experimental results can be found.</span></p>
Demo-Dataset for publication "FAIR workflows in Earth system modelling: a use case with semantic data management"
<p>This demodataset is intended to be used to test the workflow described in the publication by Lennartz & Schlemmer "FAIR workflows in Earth System modelling: a use case with semantic data management". It contains example model output for an arbitrary biogeochemical model tracer (here: dissolved organic carbon, DOC) from an ocean model as a 4-dimensional dataset (latitude, longitude, depth, time), the corresponding grid point locations as well as a textfile specifying parameter inputs for the model. The file structure is adapted for seamless integration into the workflow described in Lennartz & Schlemmer, which builds on the open source semantic research data management system LinkAhead. The dataset contains the following structure: The folder DataAnalysis stores data required for data analysis, such as the grid point locations in the file TMM_grid_v2018a.mat. The folder SimulationData stores model output in the folder 2022_TMM, containing the parameter input file nl_in.txt and the model output TR_monthly.mat. Related instructions can be accessed here: https://gitlab.com/salexan/fairworkflows-demodataset .</p>
Dataset related to "Material recycling in energy system modeling: a review and showcase"
<p>This dataset has been generated and used for the publication:</p> <blockquote> <p>Zwickl-Bernhard, S., 2024. Material recycling in energy system modeling: a review and showcase. ... DOI: ...</p> </blockquote> <p>The corresponding code is published on *Github. #add link after publication</p> <p>The dataset includes:</p> <ol> <li>Compiled data for manufacturing costs of Solar Modules and Wind Turbines in the EU (manufacturing costs in the EU.xlsx)</li> <li>Compiled data for modified prices (modified prices.xlsx)</li> <li>Additional Data (scalars.xlsx)</li> <li>Sources (sources.txt)</li> <li>Compiled data for yearly capacity of Solar Modules and Wind Turbines (vectors_capacity.xlsx)</li> <li>Compiled data for yearly costs of Solar Modules and Wind Turbines (vectors_costs.xlsx)</li> <li>Compiled data for yearly manufacturing costs of Solar Modules and Wind Turbines (vectors_manufacturing.xlsx)</li> </ol>
Datasets of protein models from plasmids containing conjugative Type 4 Secretion Systems
<p>In the connected article, we have created a database of all modelled protein structures encoded on plasmids that contain conjugative type 4 secretion systems. In this deposition, you will find zip files of all structures modelled by AlphaFold, as well as the ones that were modelled using EMS fold. Further, there the csv file containing the DeepFRI output, as well as a fasta file containing the sequences of the plasmids.</p> <p>The AlphaFold and ESM databases contain the structural models of the curated/triaged proteins, as described in the paper.</p> <p> </p>
Dataset for manuscript "Gaps in our understanding of ice-nucleating particle sources exposed by global simulation of the UK Earth System Model"
<p>Datasets and Jupyterlab python script for plotting all figures relevant to the mansucript "Gaps in our understanding of ice-nucleating particle sources exposed by global simulation of the UK Earth System Model" by Herbert et al.</p> <p>https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1538/</p> <p>Data needs to be unzipped and paths (input and output) updated in the jupyterlab python script.</p> <p> </p>
A Model-Driven, Metrics-Based Approach to Assessing Support for Quality Aspects in MLOps System Architectures: Replication Package
<div> <p><strong>Title:</strong> A Model-Driven, Metrics-Based Approach to Assessing Support for Quality Aspects in MLOps System Architectures: Replication Package</p> <p><strong>Authors:</strong> Stephen John Warnett; Uwe Zdun</p> <p><strong>About:</strong> This is the replication package artefact for the paper entitled "A Model-Driven, Metrics-Based Approach to Assessing Support for Quality Aspects in MLOps System Architectures".</p> <p><strong>Paper Abstract:</strong> In machine learning (ML) and machine learning operations (MLOps), automation serves as a fundamental pillar, streamlining the deployment of ML models and representing an architectural quality aspect. Support for automation is especially relevant when dealing with ML deployments characterised by the continuous delivery of ML models. Taking automation in MLOps systems as an example, we present novel metrics that offer reliable insights into support for this vital quality attribute, validated by ordinal regression analysis. Our method introduces novel, technology-agnostic metrics aligned with typical Architectural Design Decisions (ADDs) for automation in MLOps. Through systematic processes, we demonstrate the feasibility of our approach in evaluating automation-related ADDs and decision options. Our approach can itself be automated within continuous integration/continuous delivery pipelines. It can also be modified and extended to evaluate any relevant architectural quality aspects, thereby assisting in enhancing compliance with non-functional requirements and streamlining development, quality assurance and release cycles.</p> </div>
Scenario-tree model to estimate the sensitivity of a surveillance system for classical scrapie
<p>The supplementary files to the EFSA's scientific report on the "Evaluation of the application of Slovenia to be recognised as having a negligible risk of classical scrapie" include:</p> <p>R code of the scenario-tree model to estimate the sensitivity of the surveillance system of sheep and goats for scrapie in Slovenia.</p> <p>Read-me file with information and instructions on how to rum the model </p> <p>Input data from Slovenia. Surveillance data to be analysed usgin the model.</p>
Systemic inflammation accelerates neurodegeneration in a rat model of Parkinson's disease overexpressing human alpha synuclein
<p><span>Parkinson’s disease (PD) involves genetic and<span> </span>environmental risk factors. Increasing research efforts have been made to understand how they interact<span> </span>to<span> </span>impair<span> </span>homeostasis<span> </span>and<span> </span>elevate<span> </span>risk. Inflammation could be one unifying factor. In this study, <em>wild-type</em> (WT) and overexpressing human </span><span>α</span><span>-synuclein (<em>Snca</em><sup>+/+</sup>) rats <span>were intraperitoneally injected with a single dose of </span>lipopolysaccharide<span> </span>(LPS) or with saline (SAL). In these animals we assessed </span><span>the development of PD-like symptoms by immunohistology, high-dimensional flow cytometry, electrophysiology, and behavioral analyses. A single injection of LPS to both WT and <em>Snca<sup>+/+</sup> </em>rats triggered long-lasting increased activation of pro-inflammatory microglial markers, infiltrating monocytes and T-lymphocytes. However, only LPS <em>Snca</em><sup>+/+</sup> rats displayed dopaminergic neuronal loss in the <em>substantia<span> </span>nigra pars compacta<span> </span></em>(SNpc), associated with a reduction of evoked dopamine<span> release </span>in the striatum. No significant<span> </span>changes were observed in the behavioral domain. </span></p> <p><span> </span></p>
Earth System Model-based Life Cycle Assessment of Ocean Alkalinity Enhancement
<ol> <li>“Fig2data.xlsx”, “Fig5data.xlsx” and “Fig4data.xlsx” are the original data to create Fig.2, Fig.3 and Fig.5. The data are calculated from UVic results.</li> <li>“Fig4.txt” is the code to create Fig.4 by Pyferret from UVic results.</li> <li>“X.f” are the update codes in our UVic model.</li> </ol>
Official Code and Dataset of Table Tennis Coaching System Based on a Multimodal Large Language Model with Knowledge Base
<p>Official Code and Dataset of Table Tennis Coaching System Based on a Multimodal Large Language Model with Knowledge Base</p>
Seismic Azimuthal Anisotropy Model for the Juan de Fuca ‐ Gorda Plate System
<p>This dataset is supplementary to:</p> <p>Liu, C., et al. (2024) Seismic Azimuthal Anisotropy Within the Juan de Fuca ‐ Gorda Plate System, GRL</p> <div> <p>DOI: 10.1029/2024GL111835</p> <p>Azimuthal anisotropy model from 10-100 km</p> <p> </p> <p>Model 1: <code>JdFG_Azi_anisotropy_model.nc</code>: contains</p> <ul> <li>Anisotropic lithospheric layer: base of sediments to 20km below the Moho</li> <li>Anisotropic asthenospheric zone: 50 km thick layer beneath the lithosphere layer</li> <li>A complementary deeper asthenosphere layer </li> </ul> <p>Model 2:<code>JdFG_Azi_anisotropy_model_ios_crust.nc</code>: </p> <ul> <li>Anisotropic lithospheric layer: the Moho to 30km below the Moho</li> <li>Anisotropic asthenospheric zone: 50 km thick layer beneath the lithosphere layer</li> <li>A complementary deeper asthenosphere layer </li> </ul> </div> <p>The uploaded file uses NetCDF4 format.</p> <p>File format:</p> <p><code>Longitude</code>, <code>Latitude</code>, <code>Depth</code>, <code>fa</code>,<code>unc_fa</code>,<code>amp</code>,<code>unc_amp</code></p> <ul> <li> <p>Dimensions:</p> <ul> <li><code>Longitude</code>: -130.2° to -125.0° with 0.4° interval.</li> <li><code>Latitude</code>: 40.6° to 49.0° with 0.4° interval.</li> <li><code>Depth</code>: 10 to 100 with 10 km interval</li> </ul> </li> <li>Model variables: <ul> <li><code>fa</code>: depth-dependent fast azimuth (deg)</li> <li><code>unc_fa</code>: uncertainty for depth-dependent fast azimuth (deg)</li> <li><code>amp</code>: depth-dependent anisotropy amplitude (%)</li> <li><code>unc_amp</code>: uncertainty for depth-dependent anisotropy amplitude (%)</li> </ul> </li> </ul>
Dataset: Process Mining for Reliability Modeling of Smart Manufacturing Systems with Reduced Data Requirements
<p>Operational state logs from the Industry 4.0 Lab, University of Southern Denmark.</p> <p>"I4.0Lab_state_log.csv" -> without failures</p> <p>I4.0Lab_state_log_failures.csv -> with failures</p>
Code and data for publication "pyGRETA, pyCLARA, pyPRIMA: A pre-processing suite to generate flexible model regions for energy system models"
<p>This dataset contains the code of the three pre-processing tools <a href="https://github.com/tum-ens/pyGRETA">pyGRETA</a>, <a href="https://github.com/tum-ens/pyPRIMA">pyPRIMA</a> and <a href="https://github.com/tum-ens/pyCLARA">pyCLARA</a> and an examplary database for the scope of Austria.</p> <p>To run the code with full functionality additional data is needed. Check the documentation of the tools for further information.</p> <p> </p> <p>Sources for data can be found here: </p> <p>pyGRETA: https://pygreta.readthedocs.io/en/stable/user_manual.html#recommended-input-sources</p> <p>pyPRIMA: https://pyprima.readthedocs.io/en/stable/user_manual.html#recommended-input-sources</p> <p>pyCLARA: https://pyclara.readthedocs.io/en/stable/user_manual.html#recommended-input-sources</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.