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Source data for "Inhibitory top-down projections from zona incerta mediate neocortical memory"
<p>These files contain the data that are presented in the figures in the article: "Inhibitory top-down projections from zona incerta mediate neocortical memory".</p>
MILAN project: raw images of deep sky objects captured with a Stellina observation station -- [2022-11]
<p>During the MILAN research project (MachIne Learning for AstroNomy), the research team uses Stellina observation stations to collect raw images of deep sky objects. </p> <p>The Stellina observation station has an apochromatic ED doublet with an aperture of 80 mm and a focal length of 400 mm - focal ratio of f/5. It is equipped with a Sony IMX 178 CMOS sensor with a resolution of 6.4 million pixels (3096 x 2080 pixels). An anti-pollution filter is placed in front of the camera sensor. The station also has a fully automated alt-azimuth mount: setup, object tracking and focusing are also automatic. Stellina also has an integrated field rotator that adapts to the target.</p> <p>Thus, the research team built a dataset that faithfully represents what can be obtained during classical Electronically Assisted Astronomy sessions in the Luxembourg Greater Region:<br> - targets: representative set of deep sky objects from the Messier / NGC / IC / Barnard catalogs during the period.<br> - type of targets: nebulaes, planetary nebula, galaxies, globular clusters, open clusters<br> - for each observation session: sub-frames of 10 seconds exposure time and total cumulative duration of ~15/30 minutes (depending of the target) -- bad sub-frames were not filtered.</p> <p>The dataset is composed of ZIP files -- and each zip file contain raw images in FITS format (Flexible Image Transport System): data come directly from the Sony IMX178 sensor of the Stellina observation station (no debayerisation and no post processing).</p> <p>This research was funded by the Luxembourg National Research Fund (FNR), grant reference 15872557.</p> <p>To refer to or to cite this work, please use: "Parisot, O., Hitzelberger, P., Bruneau, P., Krebs, G., Destruel, C., & Vandame, B. (2023). MILAN Sky Survey, a dataset of raw deep sky images captured during one year with a Stellina automated telescope. Data in Brief, 48, 109133."</p> <p> </p> <p>MILAN project team members: Olivier Parisot (LIST), Patrik Hitzelberger (LIST), Pierrick Bruneau (LIST), Gilles Krebs (VAONIS, Christophe Destruel (VAONIS), Benoît Vandame (VAONIS).</p> <p>More information about the MILAN project: https://www.fnr.lu/results-2021-1-bridges-call/.</p> <p>More information about VAONIS instruments: https://vaonis.com</p> <p>More information about Luxembourg of Science and Technology (LIST): https://www.list.lu</p> <p>Data license for files: Attribution-NonCommercial-NoDerivatives 4.0 International</p>
Project logo
<p>Project logo</p>
Dataset supporting publication: "Environmental sustainability and Energy Efficiency in Historical Buildings: GeoFit Project Implementation in the Case Study of a medieval fortress in Perugia"
<p>Dataset supporting publication:“Environmental sustainability and Energy Efficiency in Historical Buildings: GeoFit Project Implementation in the Case Study of a medieval fortress in Perugia” (publication available for download: <a href="https://zenodo.org/record/7435513">GEOFIT Zenodo</a>)</p> <p>Italian cities are mainly constituted by buildings constructed until the mid-20th century by pre-industrial construction techniques. A HVAC system for the energy retrofit of historical buildings is evaluated when applied in the case study of Sant’Apollinare. It consists of a ground source heat pump a water tank for thermal energy storage connected to a low-temperature radiant system and air handling unit. The building thermal-energy behavior, typically influenced by thermal inertia in historical buildings, and the novel HVAC system performance interactions are comparatively assessed together with more traditional scenarios. Energy demand decreases by about one third compared to the pre-retrofit situation.</p>
Critical Success Factors of Agile Transformation Initiatives from a Project Management Perspective
<p>Context: Agile methods have been adopted as an alternative to<br> meet the frequent changes in the IT industry and to address is-<br> sues of quality, cost, speed, and efficiency in systems development<br> processes. Problem: Managers are responsible for the appropriate<br> application of knowledge, skills, tools, and techniques that can<br> impact the success or failure of an agile transformation initiative.<br> However, there is not much visibility into the critical success factors<br> (CSF) associated with it. Solution: We aim to identify the CSFs that<br> affect agile transformation initiatives from a project management<br> perspective. IS Theory: The General Systems Theory provides the<br> basis for this study, since the different organizational aspects in-<br> volved in the agile transformation are interrelated and influenced<br> by factors such as environment, culture, information technology,<br> internal management systems, and other elements that may hinder<br> its adoption. Method: We performed a systematic mapping study<br> in the following digital databases: EI Compendex, IEEE, ISI Web<br> of Science, and SCOPUS. Sumary of Results: We selected 12 stud-<br> ies that allowed us to identify 12 CSF. The most cited ones were<br> top management support, team empowerment, adapting the pro-<br> cess toagile, and customer focus. Adoption of management style,<br> good communication, and strong teams are among the least cited<br> CSF. Contributions and Impact in the IS area: Our results can help<br> organizations in new agile transformation initiatives. Such CSF<br> are interrelated and, if taken into consideration, have an impor-<br> tant effect on the success of the agile transformation. Moreover,<br> management should consider the business through a systemic and<br> holistic view because those CSFs can positively impact the agile<br> transformation.</p>
Data set for EMPIR project MeDDII Paper bmt-2022-0040
<p>Data set for EMPIR project MeDDII Paper</p> <p>https://doi.org/10.1515/bmt-2022-0040</p>
Data set for EMPIR project MeDDII Report A2.3.4 D4
<p>Data set for EMPIR project MeDDII Report A2.3.4 D4</p> <p>Report on the use of a calibrated microfluidic multi-parameter chip for the in-line measurement of pressure, viscosity and temperature</p>
Data set for EMPIR project MeDDII Report A2.1.4
<p>Data set for EMPIR project MeDDII Report A2.1.4</p> <p>Validation of the pipe viscometers (primary standards) for the in-line measurement of the dynamic viscosity of Newtonian liquids</p>
Data set for EMPIR project MeDDII Paper FLOMEKO 2022 ID90
<p>Data set for EMPIR project MeDDII Paper FLOMEKO 2022 ID90</p> <p>Dynamic vs constant liquid flow calibrations down to 20 nL/min</p>
Data set for EMPIR project MeDDII Paper FLOMEKO 2022 ID88
<p>Data set for EMPIR project MeDDII Paper FLOMEKO 2022 ID88</p> <p>First comparison of inline measurements of dynamic viscosity</p>
Data set for EMPIR project MeDDII Report A2.3.3
<p>Data set for EMPIR project MeDDII Report A2.3.3</p> <p>Characterization of devices for the in-line measurement of the dynamic viscosity and the density of Newtonian liquids</p>
Material from a collaborative analysis with young people. Insights into the analysis process of R&I Action #2 Youth Employment of the CoAct project
<p>The collaborative data analysis presented in this document was undertaken in the context of the research project CoAct (Co-designing Citizen Social Science for Collective Action) as part of the R&I Action #2 on Youth Employment. In this R&I Action, using Citizen Social Science as a research approach, young people aged between 15 and 21 years in employment measures in Vienna/Austria participated in collaborative social research activities. The visualisation of data analysis in the form of posters, is a selection of the collaborative analysis of qualitative expert interviews using the the “Stop and Go” (Harrasser, 2017) method. Following this method, audio recording of interviews, done by the young co-researchers themselves, are listened to and summarized as well as connected to the co-researchers’ own experience.</p> <p>The Creative Commons license and a recommendation regarding the citation of the material are provided in the document.</p> <p>For more information please contact veronika.woehrer@univie.ac.at</p>
Final project E.Glazacheva
<p>Computational Literacy final project</p>
ECFAS Mapping products, Deliverable 5.5 – Mapping products – ECFAS Project (GA 101004211), www.ecfas.eu
<p>The European Copernicus Coastal Flood Awareness System (ECFAS) project aimed at contributing to the evolution of the Copernicus Emergency Management Service (https://emergency.copernicus.eu/) by demonstrating the technical and operational feasibility of a European Coastal Flood Awareness System. Specifically, ECFAS provides a much-needed solution to bolster coastal resilience to climate risk and reduce population and infrastructure exposure by monitoring and supporting disaster preparedness, two factors that are fundamental to damage prevention and recovery if a storm hits.</p><p>The ECFAS Proof-of-Concept development ran from January 2021 to December 2022. The ECFAS project was a collaboration between Scuola Universitaria Superiore IUSS di Pavia (Italy, ECFAS Coordinator), Mercator Ocean International (France), Planetek Hellas (Greece), Collecte Localisation Satellites (France), Consorzio Futuro in Ricerca (Italy), Universitat Politecnica de Valencia (Spain), University of the Aegean (Greece), and EurOcean (Portugal), and was funded by the <strong>European Commission H2020 Framework Programme</strong> within the call LC-SPACE-18-EO-2020 - Copernicus evolution: research activities in support of the evolution of the Copernicus services. </p><p><i><strong>Description of the product</strong></i></p><p>The deliverable includes a document and a compressed directory with ready-to-print maps, the associated geospatial datasets and symbology files. All products were developed under Task 5.5 – Mapping products.<br>The document reports on the activities conducted during Task 5.5 – Mapping products that aimed at demonstrating the added value of the ECFAS products and propose adequate representation for communication and integration into the Copernicus Emergency Management Services. Five Demonstration cases, corresponding each to one recent coastal event and one location, were selected to highlight the ECFAS products resulting of the coastal Flood, Impacts and Shoreline position tools developed previously during the ECFAS activities. The Mapping products prepared for each demonstration case are provided along the document in cartographic formats (ready-to-print maps), along with the symbology files and geospatial datasets that were used to create the products.</p><p>This <strong>dataset</strong> is made available under the <strong>Open Database License</strong>: <a href="http://opendatacommons.org/licenses/odbl/1.0/">http://opendatacommons.org/licenses/odbl/1.0/</a>. Any rights in individual contents of this dataset are licensed under the <strong>Open Database License</strong>: <a href="http://opendatacommons.org/licenses/dbcl/1.0/">http://opendatacommons.org/licenses/dbcl/1.0/</a>.</p><p>This <strong>Report</strong> is made available under the <strong>Creative Commons Attribution 4.0 International License</strong>.</p><p><i><strong>Disclaimer:</strong></i></p><p>ECFAS partners provide the data "as is" and "as available" without warranty of any kind. The ECFAS partners shall not be held liable resulting from the use of the information and data provided.</p><p>This project has received funding from the Horizon 2020 research and innovation programme under grant agreement No. 101004211</p><p> </p><p> </p>
Identification of local thresholds of TWL for triggering the European coastal flood awareness system, Deliverable 4.3 – Report on the identification of local thresholds of TWL for triggering coastal flooding - ECFAS project (GA 101004211). www.ecfas.eu
<p>The European Copernicus Coastal Flood Awareness System (ECFAS) project aimed at contributing to the evolution of the Copernicus Emergency Management Service (https://emergency.copernicus.eu/) by demonstrating the technical and operational feasibility of a European Coastal Flood Awareness System. Specifically, ECFAS provides a much-needed solution to bolster coastal resilience to climate risk and reduce population and infrastructure exposure by monitoring and supporting disaster preparedness, two factors that are fundamental to damage prevention and recovery if a storm hits.</p><p>The ECFAS Proof-of-Concept development ran from January 2021 to December 2022. The ECFAS project was a collaboration between Scuola Universitaria Superiore IUSS di Pavia (Italy, ECFAS Coordinator), Mercator Ocean International (France), Planetek Hellas (Greece), Collecte Localisation Satellites (France), Consorzio Futuro in Ricerca (Italy), Universitat Politecnica de Valencia (Spain), University of the Aegean (Greece), and EurOcean (Portugal), and was funded by the <strong>European Commission H2020 Framework Programme</strong> within the call LC-SPACE-18-EO-2020 - Copernicus evolution: research activities in support of the evolution of the Copernicus services. </p><p><i><strong>Description of the product</strong></i></p><p>The ECFAS Deliverable 4.3 - Report on the identification of local thresholds of TWL for triggering coastal flooding aims to describe the methodology developed to identify local thresholds that will trigger the coastal flood mapping activity. To this end, it was necessary to identify both a total water level triggering threshold, used as a local reference to trigger the system in case of forecasted TWL exceedence, and a duration threshold, used to set the storm duration. In order to compute both thresholds, an Extreme Value Analysis (EVA) and a Duration Analysis (DA) were performed on the ECFAS combined hindcast. As the local TWL thresholds (triggering and duration) were identified using the ECFAS combined hindcast, and the system will instead be operative with the input of CMEMS forecast, a methodology was developed to establish a correction to be applied before integrating the thresholds into the warning system. The document also describes some limitations and possible future improvements of the employed methodology.</p><p>The Deliverable 4.3 - Report on the identification of local thresholds of TWL for triggering coastal flooding is accompanied by an accessory data file. This file, named "ThresholdsFile.csv", contains the values of the triggering and duration thresholds for all the ECFAS combined hindcast of TWL points and their coordinates.</p><p>This <strong>ECFAS Thresholds Dataset</strong> is made available under the <strong>Open Database License</strong>: <a href="http://opendatacommons.org/licenses/odbl/1.0/">http://opendatacommons.org/licenses/odbl/1.0/</a>. Any rights in individual contents of the ECFAS Thresholds Dataset are licensed under the Database Contents License: <a href="http://opendatacommons.org/licenses/dbcl/1.0/">http://opendatacommons.org/licenses/dbcl/1.0/</a>.</p><p>This <strong>Report</strong> on the identification of thresholds is made available under the <strong>Creative Commons Attribution 4.0 International License</strong>.</p><p><i><strong>Disclaimer:</strong></i></p><p>ECFAS partners provide the data "as is" and "as available" without warranty of any kind. The ECFAS partners shall not be held liable resulting from the use of the information and data provided.</p><p>This project has received funding from the Horizon 2020 research and innovation programme under grant agreement No. 101004211</p><p> </p>
Shorelines dataset. Deliverable 3.2 - Algorithms for satellite derived shoreline mapping and shorelines dataset, ECFAS project (GA 101004211), www.ecfas.eu.
<p>The European Copernicus Coastal Flood Awareness System (ECFAS) project aimed at contributing to the evolution of the Copernicus Emergency Management Service (https://emergency.copernicus.eu/) by demonstrating the technical and operational feasibility of a European Coastal Flood Awareness System. Specifically, ECFAS provides a much-needed solution to bolster coastal resilience to climate risk and reduce population and infrastructure exposure by monitoring and supporting disaster preparedness, two factors that are fundamental to damage prevention and recovery if a storm hits.</p> <p>The ECFAS Proof-of-Concept development ran from January 2021 to December 2022. The ECFAS project was a collaboration between Scuola Universitaria Superiore IUSS di Pavia (Italy, ECFAS Coordinator), Mercator Ocean International (France), Planetek Hellas (Greece), Collecte Localisation Satellites (France), Consorzio Futuro in Ricerca (Italy), Universitat Politecnica de Valencia (Spain), University of the Aegean (Greece), and EurOcean (Portugal), and was funded by the <strong>European Commission H2020 Framework Programme</strong> within the call LC-SPACE-18-EO-2020 - Copernicus evolution: research activities in support of the evolution of the Copernicus services. </p> <p><em><strong>Reference literature:</strong></em></p> <p><em><strong>Palomar-Vázquez, J.; Pardo-Pascual, J.E.; Almonacid-Caballer, J.; Cabezas-Rabadán, C. Shoreline Analysis and Extraction Tool (SAET): A New Tool for the Automatic Extraction of Satellite-Derived Shorelines with Subpixel Accuracy. Remote Sens. 2023, 15, 3198. <a href="https://doi.org/10.3390/rs15123198">https://doi.org/10.3390/rs15123198</a></strong></em></p> <p><em><strong>J.E. Pardo-Pascual, J. Almonacid-Caballer, C. Cabezas-Rabadán, A. Fernández-Sarría, C. Armaroli, P. Ciavola, J. Montes, P.E. Souto-Ceccon, J. Palomar-Vázquez: Assessment of satellite-derived shorelines automatically extracted from Sentinel-2 imagery using SAET. Coastal Engineering, 2023, 104426, ISSN 0378-3839, <a href="https://doi.org/10.1016/j.coastaleng.2023.104426">https://doi.org/10.1016/j.coastaleng.2023.104426</a>.</strong></em></p> <p><em>Pardo-Pascual, J. E., Cabezas-Rabadán, C., Palomar-Vázquez, J., Fernández-Sarría, A., Almonacid-Caballer, J., Souto-Ceccon, P. E., Montes, J., Armaroli, C., and Ciavola, P.: Satellite-derived shorelines extracted using SAET for characterizing the effect of Storm Gloria in the Ebro Delta (W Mediterranean), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9856, <a href="https://doi.org/10.5194/egusphere-egu22-9856">https://doi.org/10.5194/egusphere-egu22-9856</a>, 2022.</em></p> <p>In relation to <strong>SAET</strong>, additional information, instructions and the <strong>open-source code</strong> are available here <a href="https://doi.org/10.5281/zenodo.5807710"><strong>https://zenodo.org/records/10256957</strong></a> and also in <strong>GitHub </strong>here<strong> <a href="https://github.com/jpalomav/SAET_master">https://github.com/jpalomav/SAET_master</a></strong></p> <p> </p> <p><strong>Description of the containing files inside the Dataset</strong></p> <p>The deliverable includes two different files: the dataset of shorelines and the accompanying report.</p> <p>The report describes the structure of the dataset of shorelines produced in Task 3.2 - Shoreline mapping validation and calibration and described in Deliverable 3.2 - Algorithms for satellite derived shoreline mapping and shorelines dataset (DOI: 10.5281/zenodo.5807711).</p> <p>The dataset is composed of three folders.</p> <ol> <li>The first folder ("SDS_vs_VHR_shoreline") contains the SDSs extracted at each test site by the different algorithms tested in ECFAS (SHOREX, Cabezas-Rabadán et al., 2021; Sánchez-García et al., 2020; CoastSat, Vos et al., 2019a,b and SAET, Palomar-Vázquez et al., 2021; Pardo-Pascual et al., 2021) to assess their performance through the comparison with shorelines photo-interpreted on coincident VHR satellite images. The SDSs obtained at all the test sites using SAET and CoastSAT are included, as well the SDSs obtained using SHOREX at the Spanish test sites. The photo-interpreted shorelines are also provided. For all the test sites it is provided the line separating the instantaneous shoreline (water/land boundary), obtained by photo-interpretation. For the sites in the Netherlands, also the wet/dry line is provided.</li> <li>The second folder ("SDS_vs_video-monitored_shorelines") presents for each of the three test sites the SDSs obtained using the different algorithms and video-derived shorelines. The SDSs at the beaches of la Victoria and Cala Millor were obtained using SAET, SHOREX and CoastSAT. In the case of Gerakas Beach, the shorelines were obtained using SAET and CoastSAT.</li> <li>The third folder ("SDS_SAET_Storm_cases") includes eight examples in different European coasts in which the SDSs before and after a storm have been obtained.</li> </ol> <p>This <strong>ECFAS dataset of shorelines</strong> is made available under the <strong>Open Database License</strong>: <a href="http://opendatacommons.org/licenses/odbl/1.0/">http://opendatacommons.org/licenses/odbl/1.0/</a>. Any rights in individual contents of the ECFAS dataset of shorelines are licensed under the <strong>Open Database License</strong>: <a href="http://opendatacommons.org/licenses/dbcl/1.0/">http://opendatacommons.org/licenses/dbcl/1.0/</a>.</p> <p>This <strong>Report</strong> is made available under the <strong>Creative Commons Attribution 4.0 International License</strong>.</p> <p> </p> <p><em><strong>Disclaimer:</strong></em></p> <p>ECFAS partners provide the data "as is" and "as available" without warranty of any kind. The ECFAS partners shall not be held liable resulting from the use of the information and data provided.</p> <p>This project has received funding from the Horizon 2020 research and innovation programme under grant agreement No. 101004211</p> <p> </p>
ECFAS Pan-EU Flood Catalogue, D5.4 – Pan-EU flood maps catalogue - ECFAS project (GA 101004211), https://www.ecfas.eu/
<p>The European Copernicus Coastal Flood Awareness System (ECFAS) project aimed at contributing to the evolution of the Copernicus Emergency Management Service (https://emergency.copernicus.eu/) by demonstrating the technical and operational feasibility of a European Coastal Flood Awareness System. Specifically, ECFAS provides a much-needed solution to bolster coastal resilience to climate risk and reduce population and infrastructure exposure by monitoring and supporting disaster preparedness, two factors that are fundamental to damage prevention and recovery if a storm hits.</p> <p>The ECFAS Proof-of-Concept development ran from January 2021 to December 2022. The ECFAS project was a collaboration between Scuola Universitaria Superiore IUSS di Pavia (Italy, ECFAS Coordinator), Mercator Ocean International (France), Planetek Hellas (Greece), Collecte Localisation Satellites (France), Consorzio Futuro in Ricerca (Italy), Universitat Politecnica de Valencia (Spain), University of the Aegean (Greece), and EurOcean (Portugal), and was funded by the <strong>European Commission H2020 Framework Programme</strong> within the call LC-SPACE-18-EO-2020 - Copernicus evolution: research activities in support of the evolution of the Copernicus services. </p> <p><em><strong>Reference literature:</strong></em></p> <p><em><strong>Le Gal, M., Fernández-Montblanc, T., Duo, E., Montes Perez, J., Cabrita, P., Souto Ceccon, P., Gastal, V., Ciavola, P., and Armaroli, C.: A new European coastal flood database for low–medium intensity events, Nat. Hazards Earth Syst. Sci., 23, 3585–3602, <a href="https://doi.org/10.5194/nhess-23-3585-2023">https://doi.org/10.5194/nhess-23-3585-2023</a>, 2023.</strong></em></p> <p><strong>Description of the Dataset</strong></p> <p>The present database gathers flood and velocity maps for the European Union coast as well as their associated forcing parameters. The coast is divided into geographic regions embracing similar oceanographic conditions and subsequently into coastal sectors. The coastal sectors can be identified by its region index RXXX and its own index CSYYY. For each coastal sector, flood models were developed using the LISFLOOD-FP model with a grid resolution of 100 m. The flood model configuration follows the recommendation highlighted in ECFAS Deliverable D5.2 - Validated LISFLOOD-FP model for coastal areas. The flood and velocity maps are associated with synthetic storms that are characterised by a specific extreme water level and storm duration. These parameters were derived from Extreme Value Analyses performed on the ECFAS ANYEU-SSL hindcast (ECFAS D4.1 - Report on the calibration and validation of hindcasts and forecasts of TWL and D4.3 - Report on the identification of local thresholds of TWL for triggering coastal flooding). Five extreme water level values for each coastal point of the hindcast, and three durations (12, 24 and 36 h) were identified leading to 15 scenarios for each coastal sector. The flood and velocity maps are gathered into a NetCDF file for each coastal sector indicating the scenario parameters as attributes. In addition, the extreme water level values used for each coastal sector are contained in a complementary NetCDF file.</p> <p>The shapefile of the polygons defining the coastal sectors as defined for the catalogue implementation is included in the database.</p> <p><strong>- The ECFAS Flood Catalogue was used to produce the associated ECFAS Pan-EU Impact Catalogue:</strong></p> <p><strong>Impact Catalogue in Zenodo</strong>: Duo, E., Montes Pérez, J., Le Gal, M., Souto Ceccon, P.E., Cabrita, P., Fernández Montblanc, T., and Ciavola, P., 2022. ECFAS Pan-EU Impact Catalogue, D5.4 – Pan-EU flood maps catalogue - ECFAS project (GA 101004211). <a href="http://www.ecfas.eu/">www.ecfas.eu</a> [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.6778864">https://doi.org/10.5281/zenodo.677865</a></p> <p><em><strong>Impact Catalogue Reference literature</strong>: Duo, E., Montes, J., Le Gal, M., Fernández-Montblanc, T., Ciavola, P., and Armaroli, C.: Validated probabilistic approach to estimate flood direct impacts on the population and assets on European coastlines, Nat. Hazards Earth Syst. Sci., 25, 13–39, <a href="https://doi.org/10.5194/nhess-25-13-2025">https://doi.org/10.5194/nhess-25-13-2025</a>, 2025.</em></p> <p> </p> <p>The Flood Catalogue is accompanied by a technical document describing methods, datasets, structure, format and content of the ECFAS Flood and Impact Catalogues:</p> <p>Duo, E., Le Gal, M., Souto Ceccon, P.E., Montes Pérez, J., 2022. <a href="https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5ee287a5d&appId=PPGMS">Technical document</a> on the ECFAS Flood and Impact Catalogue, D5.4 – Pan-EU flood maps catalogue - ECFAS project (GA 101004211). <a href="http://www.ecfas.eu/">www.ecfas.eu</a></p> <p> </p> <p>This ECFAS <strong>Flood Catalogue</strong> is made available under the <strong>Open Database License</strong>: <a href="http://opendatacommons.org/licenses/odbl/1.0/">http://opendatacommons.org/licenses/odbl/1.0/</a>. Any rights in individual contents of the Flood Catalogue are licensed under the <strong>Open Database License</strong>: <a href="http://opendatacommons.org/licenses/dbcl/1.0/">http://opendatacommons.org/licenses/dbcl/1.0/</a>.</p> <p>This <strong>technical document</strong> describing methods, datasets, structure, format and content of the ECFAS Flood and Impact Catalogues is made available under the <strong>Creative Commons Attribution 4.0 International License</strong>.</p> <p>*The size of the uncompressed dataset is 124 GB.</p> <p> </p> <p><em><strong>Disclaimer:</strong></em></p> <p>ECFAS partners provide the data "as is" and "as available" without warranty of any kind. The ECFAS partners shall not be held liable resulting from the use of the information and data provided.</p> <p>This project has received funding from the Horizon 2020 research and innovation programme under grant agreement No. 101004211</p> <p> </p>
MILAN project: raw images of deep sky objects captured with a Stellina observation station -- [2022-12]
<p>During the MILAN research project (MachIne Learning for AstroNomy), the research team uses Stellina observation stations to collect raw images of deep sky objects. </p> <p>The Stellina observation station has an apochromatic ED doublet with an aperture of 80 mm and a focal length of 400 mm - focal ratio of f/5. It is equipped with a Sony IMX 178 CMOS sensor with a resolution of 6.4 million pixels (3096 x 2080 pixels). An anti-pollution filter is placed in front of the camera sensor. The station also has a fully automated alt-azimuth mount: setup, object tracking and focusing are also automatic. Stellina also has an integrated field rotator that adapts to the target.</p> <p>Thus, the research team built a dataset that faithfully represents what can be obtained during classical Electronically Assisted Astronomy sessions in the Luxembourg Greater Region:<br> - targets: representative set of deep sky objects from the Messier / NGC / IC catalogs during the period.<br> - type of targets: nebulaes, planetary nebula, galaxies, globular clusters, open clusters<br> - for each observation session: sub-frames of 10 seconds exposure time and total cumulative duration of ~15/30 minutes (depending of the target) -- bad sub-frames were not filtered.</p> <p>The dataset is composed of ZIP files -- and each zip file contain raw images in FITS format (Flexible Image Transport System): data come directly from the Sony IMX178 sensor of the Stellina observation station (no debayerisation and no post processing).</p> <p>This research was funded by the Luxembourg National Research Fund (FNR), grant reference 15872557.</p> <p>To refer to or to cite this work, please use: "Parisot, O., Hitzelberger, P., Bruneau, P., Krebs, G., Destruel, C., & Vandame, B. (2023). MILAN Sky Survey, a dataset of raw deep sky images captured during one year with a Stellina automated telescope. Data in Brief, 48, 109133."</p> <p> </p> <p>MILAN project team members: Olivier Parisot (LIST), Patrik Hitzelberger (LIST), Pierrick Bruneau (LIST), Gilles Krebs (VAONIS, Christophe Destruel (VAONIS), Benoît Vandame (VAONIS).</p> <p>More information about the MILAN project: https://www.fnr.lu/results-2021-1-bridges-call/.</p> <p>More information about VAONIS instruments: https://vaonis.com</p> <p>More information about Luxembourg of Science and Technology (LIST): https://www.list.lu</p> <p>Data license for files: Attribution-NonCommercial-NoDerivatives 4.0 International</p> <p> </p>
CP_OdU (Climate Projections for Odesa, Ukraine): Climate indices and daily meteorological variables for Odesa (Ukraine) in 2021-2050 by different RCM simulations from Euro-CORDEX
<ol> <li>ODS-UA_RCM_outputs_day_20210101-20501231.zip file contains outputs from Euro-CORDEX RCM’s simulation for a land-located point closest to the Odesa meteorological site (46.44N, 30.77E).</li> <li>The RCM grids define the coordinates for this point (the gridpoint is mostly located in the city center (Kateryninska^Troitska) or near the 7-km market.</li> <li>The nomenclature of files and variables in these files are defined in http://is-enes-data.github.io/cordex_archive_specifications.pdf.</li> <li>Other files contain the so-called climate indices as described in <a href="https://knmi-ecad-assets-prd.s3.amazonaws.com/documents/atbd.pdf">https://knmi-ecad-assets-prd.s3.amazonaws.com/documents/atbd.pdf</a> and table in 0readme.pdf.</li> </ol>
IMMERSE H2020 PROJECT - WP8 - downstream service UNIBO
<p>The archive contains the following datasets:</p> <p>- Daily mean Temperature of CMEMS reanalysis product (IBI_REANALYSIS_PHYS_005_002 product) with 1/12° horizontal resolution [form 13 to 19 November 2002] in the Galicia Coastal area.</p> <p>- Hourly mean Temperature from a downscaling experiment with NEMO4.2 with horizontal resolution of 1/48° [form 13 to 19 November 2002] in the Galicia Coastal area.</p> <p>- Daily gap-free (L4) Satellite sea surface temperatures (SST) dataset at (0.0417° x 0.0417°) horizontal resolution representative of night SST values (00:00 UTC).</p>
ScienceDex guides
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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.