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6,782 results for “project”
Dataset supporting publication: "Geofit Project Creating the Opportunity of Geographical – BIM (GEOBIM) Platform to Manage Geothermal Systems"
<p>Dataset supporting publication: “Geofit Project Creating the Opportunity of Geographical – BIM (GEOBIM) Platform to Manage Geothermal Systems” (publication available in <a href="https://zenodo.org/record/7274056#.Y2Jml3bMJPY">GEOFIT Zenodo</a>)</p> <p>Within the GEOFIT project (Smart Geothermal Systems1), BIM environment has been defined as GeoBIM platform. This term refers to those specific geothermal applications which are included in a tailormade BIM platform to manage the geothermal systems, building, site and assets information from models, sensors installed and simulations. In GEOFIT project, the demo-sites location is enriched up to the holistic view of the retrofitted buildings with all the geothermal facilities designed, simulated, installed, commissioned, and monitored, from inception onward, during the lifecycle of a facility and includes all stakeholders who need facility information – from the designers to the occupants with the building in operation. This holistic view includes the execution control and the permanent geographical reference because the simulation, monitoring and design processes happen in a specific geographical context. The definition and implementation of a GEOBIM platform is paramount for the project and it is one of the main outcomes of<br> GEOFIT project. While BIM implementation is ubiquitous in the architectural issues of the project, relying mostly on CAD designs, geographical information has a limited role particularly in construction projects, it is often restricted to some specific tasks or seen as a potential redundancy to BIM. Considering the geographical dependent tasks in GEOFIT, GIS can bring a valuable complementary contribution to the BIM process by providing spatial input and geospatial visualization, adding information on the retrofitting demo-site’s surrounding environment and underground thermal information that is essential for design decisions and the approval processes regarding building integrity and geothermal energy availability. In this paper, an interdisciplinary cooperation, data exchange, and data transfer occurs among the different professionals and disciplines involved for the successful retrofitting project planning and energy efficiency demonstration throughout the GEOBIM platform. This is implemented to assemble this set of powerful assessment, inspection and ground research, testing, and real time monitoring tools.</p>
Seawater velocities measured by autonomous sailbuoy Adcp in the Barents Sea from May to July 2021 on campaign the PolarFront project
<p>This dataset contains ocean currents measured by sailing autonomous surface vehicle <em>Adcp</em>, while on campaign at 70–77N in the Barents Sea for the <a href="https://github.com/akvaplan-niva/polarfront">PolarFront</a> research project, from 16 May to 25 July 2021 (Daase 2021). The <em>Adcp</em> is equipped with a <a href="https://www.aanderaa.com/">Aanderaa</a> DCPS 5400 operating at 600 kHz, mounted in the keel at –0.2 m.</p> <p><strong>Space/time coverage</strong></p> <ul> <li>Time: 2021-05-16T13:45:00Z/2021-07-25T13:15:00Z</li> <li>Space: [20.5,70.0,33.0,76.8] ([W,S,E,N])</li> </ul> <p><strong>Data distributions</strong></p> <p><em>Datalogger (text files)</em></p> <p>The primary distribution consists of 2 datalogger text files retrieved post-mission from sailbuoy internal storage. The files are the original full scale original data records, as captured by the internal sofware of manufacturer <a href="http://www.sailbuoy.no/">Offshore Sensing</a>.</p> <ul> <li>DATA.TXT: Position and sensor metadata</li> <li>DCPS.TXT: Ocean currents</li> </ul> <p><em>GeoJSON</em></p> <p>For increased data interoperability, a <a href="https://www.rfc-editor.org/info/rfc7946"><strong>GeoJSON</strong></a> file is also included, consisting of Point features like the following:</p> <p>{ "geometry": { "coordinates": [30.11165, 76.438894], "type": "Point" }, "properties": { "time": "2021-05-19T22:45:00Z", "TTFF": 11, "Count": 24, "Commands": 0, "TxTries": 1, "ONT": 635, "DiskUsed": 0.783123, "Files": 0, "I": 0.01564, "V": 13.195122, "Temperature": 4.06502, "DCPSStatus": 0, "DCPSOnMin": 10, "DCPSSpeed": 0.329999, "DCPSDirection": 233.233643 }, "type": "Feature" }</p> <p>The GeoJSON file is derived from DATA.TXT and contains the full position and DCPS metadata log in a standard/machine-parsable format, including coordinated universal time following <a href="https://datatracker.ietf.org/doc/html/rfc3339">RFC 3339</a>/<a href="https://www.iso.org/obp/ui#iso:std:iso:8601:-1:ed-1:v1:en">ISO 8601</a>.</p> <p><strong>Data formats and interoperability</strong></p> <p>Both of the datalogger text files are in non-standard vendor formats. The DCPS text format is described in the <a href="https://www.aanderaa.com/media/pdfs/td304-manual-dcps.pdf">vendor manual.</a></p> <p><strong>Related publications</strong></p> <p>For a recent discussion on measuring ocean currents from sailbuoys compared to other platforms, see <a href="https://doi.org/10.3390/s22155553">Wullenweber et al., 2022</a>.</p> <p>See also <a href="https://doi.org/10.1029/2019GL086649">Swart et al.,2020</a>; <a href="https://doi.org/10.3390/s21206752">Camus et al., 2021</a> for further discussion on near-surface data collection with sailbuoys and other autonomous vehicles.</p> <p><strong>References</strong></p> <p>Camus L, Andrade H, Aniceto AS, Aune M, Bandara K, Basedow SL, Christensen KH, Cook J, Daase M, Dunlop K, Falk-Petersen S, Fietzek P, Fonnes G, Ghaffari P, Gramvik G, Graves I, Hayes D, Langeland T, Lura H, Kristiansen T, Nøst OA, Peddie D, Pederick J, Pedersen G, Sperrevik AK, Sørensen K, Tassara L, Tjøstheim S, Tverberg V, Dahle S (2021). Autonomous Surface and Underwater Vehicles as Effective Ecosystem Monitoring and Research Platforms in the Arctic—The Glider Project. Sensors 21(20):6752. <a href="https://doi.org/10.3390/s21206752">https://doi.org/10.3390/s21206752</a></p> <p>Daase M (ed.). (2021). ARCTOS Barents Sea Polar Front May 2021 Cruise Report (1.1.0). Zenodo. <a href="https://doi.org/10.5281/zenodo.7384076">https://doi.org/10.5281/zenodo.7384076</a></p> <p>Edholm J. (2022). Sailbuoy DCPS. Zenodo. <a href="https://doi.org/10.5281/zenodo.6798056">https://doi.org/10.5281/zenodo.6798056</a></p> <p>Swart S, du Plessis MD, Thompson AF, Biddle LC, Giddy I, Linders T, Mohrmann M, Nicholson S (2020). Submesoscale fronts in the Antarctic marginal ice zone and their response to wind forcing. Geophysical Research Letters, 47, e2019GL086649. <a href="https://doi.org/10.1029/2019GL086649">https://doi.org/10.1029/2019GL086649</a></p> <p>Wullenweber N, Hole LR, Ghaffari P, Graves I, Tholo H, Camus L (2022). SailBuoy Ocean Currents: Low-Cost Upper-Layer Ocean Current Measurements. Sensors. 22(15):5553. <a href="https://doi.org/10.3390/s22155553">https://doi.org/10.3390/s22155553</a></p>
Data set for EMPIR project MeDDII Paper FMI 73 2020 101729
<p>Data set for EMPIR project MeDDII Paper</p> <p>https://doi.org/10.1016/j.flowmeasinst.2020.101729</p>
Data set for EMPIR project MeDDII Report A2.2.2
<p>Data set for EMPIR project MeDDII Report A2.2.2</p> <p>In-line calibration of in-line pressure sensors</p>
Synthetic electricity distribution networks from UK for flexibility analysis - ATTEST project
<p>The dataset contains information about two realistic 6.6 kV weakly meshed synthetic UK distribution networks with 38 buses and 38 lines, and with 124 buses and 124 lines. The network files (MatPower format) include a “snapshot” or “steady-state” at a given time. The systems are ideal for testing flexible resources integration. The first network has buses with high demand (lower voltages) and distributed generation (higher voltages). In the second network there are potential voltage issues and congestions. Both systems can also be used for analysing network reconfiguration effects.</p>
Are automated static analysis tools worth it? An investigation into relative warning density and external software quality on the example of Apache open source projects
<p>This is the dataset for the publication "Are automated static analysis tools worth it? An investigation into relative warning density and external software quality on the example of Apache open source projects".</p> <p>It contains just-in-time defect-prediction style data in jit_data2.tar.gz as well as warnings generated by PMD 6.31.0 in warnings_data3.tar.gz.</p> <p>Further information and scripts for generating the plots and tables can be found in the <a href="https://github.com/atrautsch/emse2021a_replication">replication kit</a>.</p>
Investigating How Companies Get Involved in Open Source Software Projects
<p>Dataset derived from <a href="https://zenodo.org/record/3653878#.Y8pIA_7MJro">Enterprise-Driven Open Source Software | Zenodo</a></p>
Supplemental Material for the paper "Tropical Cyclones and Climate Change: Global Landfall Frequency Projections Derived from Knutson et al 2020"
<p>As described in the paper.</p> <p> </p>
2020_04_08_Percentages_of_MA_projects
Dataset related to WP1 'Knowledge mapping and co-creating best practices' INTERVIEWS with multi-actor projects (MAPs)
Injection-induced microseismic events CO2CRC Otway Project Stage 3
<p>This repository contains the seismograms of fluid-induced microseismic events during CO2CRC Otway Project Stage 3 (https://co2crc.com.au/otway-stage-3). The data was recorded by enhanced distributed acoustic sensing systems in five ~1,600 m deep wells. The data is in a standard SEGY format that should be readable by most seismic processing libraries/software. See attached SEGY_trace_headers_outline.csv for the outline of the trace headers for event_5, channel 121, recorded in CRC-7 at a depth of 1565 m below the ground </p>
Fig. 8 in Taxonomic revision of Saxicolella (Podostemaceae), African waterfall plants highly threatened by Hydro-Electric projects
Fig. 8. Saxicolella futa. Habit of the dead plant at the end of the dry season-start of the wet season. June 2013, chute de Sal'aa. PHOTO: M. cHEEK.
Fig. 1. Saxicolella flabellata. A in Taxonomic revision of Saxicolella (Podostemaceae), African waterfall plants highly threatened by Hydro-Electric projects
Fig. 1. Saxicolella flabellata. A habit, flowering plant; B leafy, flowering shoot; C portion of root with young spathellae and shoots; D group of spathellae each terminal in a leaf rosette; E developing flower inside spathellum; F mature flower (spathellum opened); G stamen; H dyad pollen; J dehisced unilocular capsule showing seed; K transverse section of ovary (diagrammatic). From Keay in FHI 28240. ALL DRAWN BY E. MARGARET STONES (Originally published in Taylor (1953: 54) reproduced with permission of the estate of Margaret Stones and the Natural History Museum, London) © the estate of Margaret Stones.
H2020 RESCUER project
<p>Introduction video for the project</p>
Dual contribution of ASIC1a channels in the spinal processing of pain information by deep projection neurons revealed by computational modeling
<p>Experimental data used in the figures of the manuscript</p>
Fig. 2 in The German Myriapod Literature Project (GerMyLit)
Fig. 2. Example of a duplicate search over three databases, provided by the programme Reference Manager®. The activated folder shows the possible duplicates, some identical, others only similar.
Discrete Samples of Particulate Phosphorus from R/V Melville MV1015 in the S. Pacific from Arica, Chile to Easter Island, 2010 (C-MORE project)
<p>“The South East Pacific (SEP) is characterized by very high nutrient concentrations in the waters adjacent to the Chilean coast, but very low nutrient concentrations (oligotrophic) in the mid- South Pacific Subtropical Gyre (SPSG), near Easter Island. The steep gradient in nutrient concentrations across the region affects the level of marine production, the composition of the microbial community, and the operation of major biogeochemical cycles in ways that are not fully understood. Despite the remarkable diversity of trophic conditions, strong gradients and even some unique singularities, the SEP is still the most sparsely sampled oceanic region of the global ocean from hydrodynamic, biological and biogeochemical points of view. The SPSG is also the most oligotrophic of all sub-tropical gyres. Previous expeditions and remote sensing studies have described the nutrient and chlorophyll field, but there have been few simultaneous measurements of chemical properties with microbial community structure and function. This expedition is designed to investigate the impact of elemental nutrient (nitrogen, phosphorus, iron, silicon, carbon) ratios on marine productivity and microbial community composition. Samples for PP (particulate phosphorus) were collected on acid washed combusted 25mm glass fiber filters (GF/F) and stored in a -80 freezer until analysis. Samples were further analyzed using a CARY UV-VIS Spectrophotometer following the combustion and acid hydrolysis method of Karl, et al. (1991).” One sample entry contained no depth value or sample data so it was deleted for visualization purposes. </p> <p>This description has been reproduced using the following source: </p> <p>http://dmoserv3.bco-dmo.org/jg/info/BCO-DMO/CMORE/bigrapa/PP%7Bdir=dmoserv3.bco-dmo.org:80/jg/dir,data=dmoserv3.bco-dmo.org:80/jg/serv/BCO-DMO/CMORE/bigrapa/PP.html1%7D?</p>
Source code of projects
<p>This dataset contains the source code of projects for evaluation experiments.</p>
LightningSim Benchmark Projects
<p>This dataset consists of 33 High-Level Synthesis projects for AMD/Xilinx Vitis HLS 2021.1, which were used in the evaluation of <a href="https://github.com/sharc-lab/LightningSim">LightningSim: Fast and Accurate Trace-Based Simulation for High-Level Synthesis.</a></p> <p>These benchmark projects come from several sources:</p> <ul> <li>Projects whose names contain “basic_examples_vhls” are derived from <a href="https://github.com/Xilinx/Vitis-HLS-Introductory-Examples/tree/2021.1">Xilinx Vitis HLS Introductory Examples, version 2021.1.</a></li> <li>Projects whose names contain “pp4fpgas” are derived from <a href="https://github.com/KastnerRG/pp4fpgas/tree/d8fc5fa560e1b5e365ddaafd6fec1894a17cc698/examples">the examples from Kastner et al.’s <em>Parallel Programming for FPGAs</em> book.</a></li> <li>Projects whose names contain “flowgnn” are derived from <a href="https://github.com/sharc-lab/FlowGNN/tree/v1.0.0">Sarkar et al.’s “FlowGNN: A Dataflow Architecture for Universal Graph Neural Network Inference via Multi-Queue Streaming.”</a></li> </ul> <p>All projects were modified to ensure that the “setup.tcl” script inside each project directory can be used to setup a Vitis HLS project with name “project” containing a solution with name “solution1” which is able to be synthesized and co-simulated under AMD/Xilinx Vitis HLS 2021.1.</p>
Data Table for PhD Project 'Domesticity and Suffragism in Middlebrow English and Irish Magazines, 1897-1914'
<p>This table explains my plans for managing my project's data, including publication drafts, reading notes, outlines, and digitized primary sources. </p>
Data from Meta-IBD Project, metabarcoding for the diatom trophic indices evaluation, South West France
<p>These data were generated within the framework of the Meta-IBD project, led by the Laboratoires des Pyrénées et des Landes and financially supported by the Adour Garonne Water Agency, including two scientific partners, Scimabio Interface and Artemis.</p> <p>The objective of the project was to compare the evaluation of diatom trophic indices obtained by the reference method (microscopy) versus the metabarcoding method, at the local scale. This comparison is based on biofilm sampling in southwest France, in the Adour, Nives and Gaves regions, in 2021 and 2022. The project ran from May 2021 to September 2023.</p> <p>The directory contains the following files:</p> <p>756 (378 x 2 replicates) samples fastq files (file intituled MetaIBD_Biofilm2021et22_LPL.rar) - contains the 756 fastq files from the Laboratoires des Pyrénées et des Landes sequencing.</p> <p>Metadonnees_MetaIBD_20212022.csv - contains all the data available for each sample corresponding to the names of the sequencing fastq files.</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.