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747 results for “Open Data”
Documenting And Assessing Open Innovation: Co-creation Of An Open Data Model For Surgical Training (Additional materials, tables 2 & 3)
<p>Challenge competitions have recently resurged for promoting open innovation in areas where markets fail to provide incentives, such as the Sustainable Development Goals (SDGs). Challenges call for the general public to contribute novel solutions to a well-defined problem, in exchange for prizes, credentials and the promise of further development of selected solutions. The aim of this paper is to report on the development of an open and collaborative data model to document and evaluate innovations in the context of a challenge competition, while also being compatible with the work of other open source communities to validate and improve them. By reusing open documentation standards and embedding them into a semantic collaborative platform, the model aimed to be flexible enough to respond to the evaluation needs of the project organisers and self-assessment for participants. We expect our experience provides insights on the potential of semantic, collaborative platforms and standards for increasing the impact of innovations towards the SDGs.</p> <p>The developer team defined the goal and scope of the ontology in collaboration with the GSTC organisers. This was done by agreeing on scenarios where the ontology will be used and establishing competency questions that the ontology has to be able to respond to. Table 2 describes the four motivating scenarios, including actors involved, requirements, sequence of actions and main problems identified. Table 3 details the competency questions for each scenario.</p>
Data for blog post on dfm.io: "An experiment in open science: exoplanet population inference"
<p>The data set used be the blog post "An experiment in open science: exoplanet population inference" published at https://dfm.io/posts/exopop/</p>
Funding Covid-19 research: Insights from an exploratory analysis using open data infrastructures - Supplementary material
<p>This dataset contains supplementary material for the paper 'Funding Covid-19 research: Insights from an exploratory analysis using open data infrastructures' by Alexis-Michel Mugabushaka, Nees Jan van Eck, and Ludo Waltman.</p> <ul> <li>supplementary_material_1_dataset.ods: Dataset of Covid-19 publications.</li> <li>supplementary_material_2_sample.ods: Samples of publications used to assess the accuracy of funding data in the different databases.</li> <li>supplementary_material_3_tables_and_figures.ods: Statistics underlying the tables and figures presented in the paper.</li> </ul>
TrainRuns.jl: an Open-Source Tool for Running Time Estimation - Supplement Data
<p>This additional data contains the initial data and the calculated results for comparing FBS and TrainRuns.jl.</p> <p><strong>File description</strong></p> <ul> <li><em>local.yaml</em>: input parameters for the local train</li> <li><em>freight.yaml</em>: input parameters for the freight train</li> <li><em>running_path.yaml</em>: input parameters for the path</li> <li><em>freight_FBS.csv</em>: export of calculation from FBS for the freight train</li> <li><em>freight_TrainRuns.csv</em>: export of calculation from TrainRun.jl converted in FBS units for the freight train</li> <li><em>freight_diff.csv</em>: the calculated difference between FBS.csv and TrainRuns.csv for the freight train</li> <li><em>local_FBS.csv</em>: export of calculation from FBS for the local train</li> <li><em>local_TrainRuns.csv</em>: export of calculation from TrainRun.jl converted in FBS units for the local train</li> <li><em>local_diff.csv</em>: the calculated difference between FBS.csv and TrainRuns.csv for the local train</li> <li><em>running_path.csv</em>: converted running_path.yaml for displaying</li> <li><em>comparison.tex</em>: LaTeX code for the graph in comparison.pdf</li> </ul> <p><strong>Sources</strong></p> <p>The calculations in FBS were done with the file 'Ostsachsen_V220.railml'. FBS needs a commercial license, which can be purchased. License for 'Ostsachsen_V220.railml' is Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0).<br> The file 'Ostsachsen_V220.railml' can be found at:<br> https://www.railml.org/en/user/exampledata.html (last accessed 2022-06-06 with login) -> "Real world railway examples from professional tools" -> "East Saxony railway network by FBS" -> "Ostsachsen_V220.railml"</p> <p>Other sources are mentioned in the files.</p>
Data for manuscript sumitted to Open Research Europe, entitled "Low-resistivity, high-resolution W-C electrical contacts fabricated by direct-write focused electron beam induced deposition"
<p>These are the data obtained experimentally and used to draw the figures in the article submitted to Open Research Europe</p>
Data for: Open COVID Trials (OCT) Project
<p><span>The COVID-19 pandemic has brought substantial attention to the systems used to communicate biomedical research. In particular, the need to rapidly and credibly communicate research findings has led many stakeholders to encourage researchers to adopt open science practices such as posting preprints and sharing data. To examine the degree to which this has led to the actual adoption of such practices, we examined the "openness" of a sample of 539 published papers describing the results of randomized controlled trials testing interventions to prevent or treat COVID-19. The majority (56%) of the papers in this sample were free to read at the time of our investigation and 23.56% were preceded by preprints. However, there is no guarantee that the papers without an open license will be available without a subscription in the future, and only 49.61% of the preprints we identified were linked to the subsequent peer-reviewed version. Of the 331 papers in our sample with statements identifying if (and how) related datasets were available, only a paucity indicated that data was available in a repository that facilitates rapid verification and reuse. Our results demonstrate that, while progress has been made, there is still a significant mismatch between aspiration and actual practice in the adoption of open science in an important area of the COVID-19 literature.</span></p>
Supplementary data: "Open modeling of electricity and heat demand curves for all residential buildings in Germany"
<p>This repository contains supplementary data for the paper <a href="https://doi.org/10.1186/s42162-022-00201-y"><em> "Open modeling of electricity and heat demand curves for all residential buildings in Germany"</em></a>.</p> <p>See <em>README.md</em> / <em>README.pdf</em> for further details.</p> <p><strong>Citing</strong></p> <p>Please cite as:</p> <p><em>Büttner, C., Amme, J., Endres, J. et al. Open modeling of electricity and heat demand curves for all residential buildings in Germany. Energy Inform 5 (Suppl 1), 21 (2022).</em></p> <p><strong>Funding</strong></p> <p>The authors thank the Federal Ministry for Economic Affairs and Climate Action for funding the research project eGon (funding code: 03EI1002).</p> <p> </p>
Linked Open Data for the maritime domain
<p>Linked Data in this data set have been compiled from diverse data sources providing information about Trade and Transport locations, protected areas, surveillance data of vessels and vessel characteristics. Data have been transformed into triples according to the vesselAI ontology, using <a href="http://core.ac.uk/download/pdf/212138612.pdf">RDF-Gen</a> . All geometries are provided using <a href="http://www.opengis.net/ont/geosparql">OGC</a> terms. The vesselAI ontology documentation is available<a href="http://83.212.101.70/vesselAI_ontology.html"> here</a> .</p> <p>In a nutshell, this data set comprises data from the following sources:</p> <p>1. AIS messages of moving objects retrieved from <a href="https://ais-public.kystverket.no/ais-download/">Norwegian Coastal Administration's SafeSeaNet</a> solution, combined with data provided by the <a href="http://web.ais.dk/aisdata/">Danish Maritime Authority</a>. Each record contains the coordinates of the vessel, a timestamp, an identifier for the vessel, its speed and heading. Typically, each vessel reports this information by sending an AIS message every few seconds. Each reported position is also annotated with the corresponding weather conditions according to Copernicus Climate Change Service (C3S) (files: reconstructed_traj.7z, ais202101_part1.7z, ais202101_part2.7z)</p> <p><br> . The weather variables currently considered as relative to the movement of vessels are:</p> <ul> <li> '10m_u_component_of_wind',</li> <li> '10m_v_component_of_wind',</li> <li> '2m_dewpoint_temperature',</li> <li> '2m_temperature',</li> <li> 'mean_sea_level_pressure',</li> <li> 'mean_wave_direction',</li> <li> 'mean_wave_period',</li> <li> 'precipitation_type',</li> <li> 'sea_surface_temperature',</li> <li> 'total_precipitation'</li> </ul> <p>2. Vessel characteristics retrieved from online sources, combined with information about departure and destination seaports. United Nations Code for Trade and Transport Locations (UN/LOCODE), has been also used, to annotate the seaports with their longitude, latitude and Well Known Text (WKT) information, as well as features and facilities available according to online sources (files: vesselsCharacteristics.7z, worldPorts.7z ).</p> <p>3. Regions of interest in the maritime domain include fishing areas, endangered species habitat areas, exclusive economic zones (EEZ), Natura2000 protected areas. In this snapshot we provide Natura2000 regions (file: natura2000.7z) as well as <a href="https://www.protectedplanet.net/en">World Protected Areas data set</a> (file: wdpa2022.ttl.7z )</p> <p>Updates and additional data sets can be found <a href="http://83.212.101.70/vesselAI_ontology.html">here</a> .</p> <p>The surveillance and weather data in this data set, are for January 2021 and within the region defined by the degrees:</p> <p>#west: 2.53<br> #south: 51.50<br> #north: 60.50<br> #east: 17.50</p>
Supplementary Data for "Adoption of Transparency and Openness Promotion (TOP) guidelines across journals"
<p>Supplementary data for: https://zenodo.org/record/7129250</p>
Data for "The APC-Barrier and its effect on stratification in open access publishing"
<p>Dataset to reproduce the analysis of the paper "The APC-Barrier and its effect on stratification in open access publishing". An earlier version of the manuscript with the title "The APC-Effect: Stratification in Open Access Publishing" is available at <a href="https://doi.org/10.31222/osf.io/w5szk">https://doi.org/10.31222/osf.io/w5szk</a>.</p> <p>Data is licensed under CC-BY-SA International (4.0), see the file LICENSE.</p> <p>A full description of the dataset is provided in the README.md.</p>
Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 9 April 2010
<p>Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 9 April 2010</p>
Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 14 January 2016
<p>Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 14 January 2016</p>
Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 2 August 2017
<p>Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 2 August 2017.</p>
Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 26 August 2014
<p>Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 26 August 2014</p>
Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 30 January 2018.
<p>Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 30 January 2018.</p>
Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 31 August 2016
<p>Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 31 August 2016</p>
Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 15 July 2016
<p>Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 15 July 2016</p>
Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 11 August 2011
<p>Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 11 August 2011</p>
Linked Open Data at cervantesvirtual.com
<p>The catalogue of the Biblioteca Virtual Miguel de Cervantes contains about 200,000 records which were originally created in compliance with the MARC21 standard. The entries in the catalogue have been recently migrated to a new relational database whose data model adheres to the conceptual models promoted by the International Federation of Library Associations and Institutions (IFLA), in particular, to the FRBR and FRAD specifications.</p> <p>The database content has been later mapped, by means of an automated procedure, to RDF triples which employ mainly the RDA vocabulary (Resource Description and Access) to describe the entities, as well as their properties and relationships. In contrast to a direct transformation, the intermediate relational model provides tighter control over the process for example through referential integrity, and therefore enhanced validation of the output. This RDF-based semantic description of the catalogue is now accessible online.</p>
Open Source Software in Data Science
<p>This upload includes an anonymized data set of a survey first launched in 2022. The survey has been revised since. The data set. however, contains answers of the first launch.</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.