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Dataset results
28 results for “open platforms”
NMRduino: A modular, open-source, low-field magnetic resonance platform
<p>The NMRduino is a compact, cost-effective, sub-MHz NMR spectrometer that utilizes readily available open-source hardware and software components. One of its aims is to simplify the processes of instrument setup and data acquisition control to make experimental NMR spectroscopy accessible to a broader audience. In this introductory paper, the key features and potential applications of NMRduino are described to highlight its versatility both for research and education.</p>
Dataset: An Open-hardware Platform for MPSoC Thermal Modeling
<p>This repository contains the experimental data for the paper</p> <p>"An Open-hardware Platform for MPSoC Thermal Modeling"</p> <p>published at 2019 samos conference</p> <p>http://samos-conference.com</p> <p>The data is released under a CC-BY Creative Commons license.<br> If you use this dataset, cite the following paper:<br> Federico Terraneo, Alberto Leva, William Fornaciari, "An Open-hardware Platform for MPSoC Thermal Modeling", 2019 IEEE International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation (SAMOS)</p>
Demonstration of the GOLDEN Artificial Intelligence (AI) GUI - Artificial Intelligence Platform for mine site monitoring (Open Pit Extraction, Valea Sesei and Roșia Poieni (Romania)).
<p>Demonstration of the GOLDEN Artificial Intelligence (AI) GUI - Artificial Intelligence Platform for mine site monitoring in the Open Pit Extraction (mine located at Valea Sesei and Roșia Poieni (Romania)) (3D view mode).</p> <p>Accessing the GOLDENAI GUI, please refer to the following link (<strong>login required</strong>): <a href="https://next-gui.goldenai.opt-net.eu/ ">https://next-gui.goldenai.opt-net.eu/ </a></p>
A survey of access to the digital collections of 195 UK GLAMs across internal and external platforms - Appendix 1 for A Culture of Copyright: A scoping study on open access to digital cultural heritage collections in the UK
<p>Created for the<a href="https://doi.org/10.5281/zenodo.6242611"> 'A Culture of Copyright: A scoping study on open access to digital cultural heritage collections in the UK' </a>report, this sample replicates and expands the Open galleries, libraries, archives and museums (GLAMs) Survey data extraction and methodology to include a range of GLAMs across the UK and new data points. The initial sample of 350 organisations included Independent Research Organisations (IROs) and Research Centre Institutes (RCIs), GLAMs associated with <a href="https://www.nationalcollection.org.uk/">Towards a National Collection</a> Foundation and Discovery projects, UK GLAMs in the Open GLAM Survey, and other UK GLAMs and related organisations. An initial review was performed to identify and remove organisations outside the scope of inquiry (<em>e.g.</em>, no permanent collections). The final sample included 195 organisations.</p> <p>From the final sample, 24 are IROs (all RCIs were removed). Another 32 are Universities (including GLAMs within universities). This brings the total number of organisations eligible for AHRC funding to 56 (or 28.6%). The remaining 140 include public and private GLAMs at national, regional and local levels (<em>e.g., </em>councils, historic buildings) and research initiatives or data aggregators (<em>e.g.,</em> Portable Antiquities Scheme, Culture Grid, Archaeology Data Service). Organisations are distributed across the UK as follows: Channel Islands (1 total); England (154 total); Isle of Man (1 total); Northern Ireland (5 total); Scotland (28 total); Wales (6 total).</p> <p>A survey of the copyright and open access policies of 63 GLAMs from the UK GLAM Sample is available on Zenodo at: <a href="https://doi.org/10.5281/zenodo.6242559">https://doi.org/10.5281/zenodo.6242559</a></p>
Description of the Features of the Open Research Knowledge Graph as a Crowdsourcing Platform based on the 4 Pillars of Crowdsourcing
<p>This dataset provides the description of the features of the <a href="https://www.orkg.org/orkg/">Open Research Knowledge Graph</a> (ORKG) based on the 4 pillars of crowdsourcing according to the reference model for crowdsourcing by Hosseini et al. [1]. This overview represents the features of the current implementation status of ORKG as a crowdsourcing platform.</p> <p>[1] M. Hosseini, K. Phalp, J. Taylor, and R. Ali, "<a href="https://ieeexplore.ieee.org/abstract/document/6861072?casa_token=zWTHNBHeH6kAAAAA:1n3EJjajqgSkSk154g4DlNFAmJs_7o3KY7LnobvP_W7AUIr-FvM5OyGP1FaRn68zUX-2oYHh7A">The Four Pillars of Crowdsourcing: A Reference Model</a>", in 2014 IEEE 8th International Conference on Research Challenges in Information Science (RCIS). IEEE, 2014, pp. 1–12.</p>
Low Emission Oil and Gas Open (LEOGO) platform specification
<p>This dataset describes the integrated energy system of a hypothetical but realistic offshore oil and gas platform referred to as the LEOGO reference platform. It reflects what would be considered a typical installation on the Norwegian Continental Shelf.</p> <p>Included with the dataset is</p> <ul> <li>input data for analysis with the open-source Oogeso (https://github.com/oogeso/oogeso) operational optimisation/simulation tool, including simplified links between electricity and heat demand and the gas/oil/water flow rates through the processing system.</li> <li>A detailed electrical model implemented in the Digsilent PowerFactory tool</li> </ul> <p> </p>
Dataset: A continuous open source data collection platform for architectural technical debt assessment
<p>The dataset and replication package of the study "A continuous open source data collection platform for architectural technical debt assessment".</p> <p> </p> <p>Abstract</p> <p>Architectural decisions are the most important source of technical debt. In recent years, researchers spent an increasing amount of effort investigating this specific category of technical debt, with quantitative methods, and in particular static analysis, being the most common approach to investigate such a topic.</p> <p> </p> <p>However, quantitative studies are susceptible, to varying degrees, to external validity threats, which hinder the generalisation of their findings.</p> <p>In response to this concern, researchers strive to expand the scope of their study by incorporating a larger number of projects into their analyses. This practice is typically executed on a case-by-case basis, necessitating substantial data collection efforts that have to be repeated for each new study.</p> <p> </p> <p>To address this issue, this paper presents our initial attempt at tackling this problem and enabling researchers to study architectural smells at large scale, a well-known indicator of architectural technical debt. Specifically, we introduce a novel approach to data collection pipeline that leverages Apache Airflow to continuously generate up-to-date, large-scale datasets using Arcan, a tool for architectural smells detection (or any other tool).</p> <p>Finally, we present the publicly-available dataset resulting from the first three months of execution of the pipeline, that includes over 30,000 analysed commits and releases from over 10,000 open source GitHub projects written in 5 different programming languages and amounting to over a billion of lines of code analysed.</p>
Video for "Outlining of the Open Digital Twin Platform"
<p>Complex simulations and machine-learning models increase in application in research, industry, and governance. However, applying these systems with reasonable accuracy and efficiency requires large-scale efforts of data collection, data transformation, data analysis, and data visualization. At the same time, maintaining the required infrastructure, software, and personnel skyrockets making these tools unavailable to many potential users. The paradigm of the digital twin offers a novel perspective on how to manage the data efficiently and make these systems available more steadily at a lower cost. We introduce the first prototype of the Open Digital Twin Platform (ODTP) that is designed to be openly available to all interested parties to enable a common framework and baseline for digital twin based research. ODTP uses containerization, loose coupling, and micro-services to provide dynamically composable digital twins.<br> ODTP also provides tools for licensing resolution, privacy and access control, and reproducibility. In its first iteration presented here, ODTP implements a common mobility research pipeline of the eqasim pipeline for MATSim. These kind of programs are usually difficult to assemble and use, thus leading to dangerous versions of ``never change a running system''. ODTP converts them into an easy-to-use version making it possible to initiate mobility simulations with one click. ODTP enables the quick adding of relevant data sources and analytical pipelines related to any topic and make them easily usable, accessible and shareable to research, industry, and governance. Thus, ODTP expands the FAIR principle from data to the complete data life cycle.</p>
Data on publication volumes for selected open access journals and platforms
<p>This dataset accompanies the report 'Scenario Modelling for Open Research Europe', prepared for the European Commission's Directorate-General for Research and Innovation by Rob Johnson of Research Consulting, acting in the capacity of an independent expert. The data was extracted from www.lens.org in May 2023 to asset historic patterns of publication growth for a sample of open access journals and platforms.</p>
Mobiliscope, an open platform to explore cities and social mix around the clock. www.mobiliscope.cnrs.fr
<p>Cities are not the same at night and during the day : people move daily and make changes in neighbourhoods densities and their social structures. <strong>Mobiliscope</strong> is a free and open-source web mapping platform to explore how cities, neighborhoods and social segregation change over a 24 hours period.</p> <p>58 city regions are included in this version (<strong>v4.3</strong>) of the Mobiliscope : 49 French cities, 6 Canadian cities and 3 Latin American cities.</p> <p><a href="https://mobiliscope.cnrs.fr/">https://mobiliscope.cnrs.fr/</a></p> <p>Data are <strong>made available under the Open Database License - ODbL</strong>. Users are free to use and adapt these data as long as they redistribute a version of their adapted database under the ODbL licence and that they attribute the original sources as indicated in the pdf files.</p>
Data from: The BumbleBox: An open-source platform for quantifying behavior in bumblebee colonies
Open the record for dataset details and reuse information.
Piveau: A Large-scale Open Data Management Platform based on Semantic Web Technologie
<p>This file contains the sources that were used to create the feature comparison in "Piveau: A Large-scale Open Data Management Platform based on Semantic Web Technologies".</p>
Analyzed papers in an open IoT platform systematic mapping study
<p>As part of our systematic mapping study related to Open IoT Platforms, here we present the overall included and analyzed papers for our study. As a process, the papers are classified into five categories, such as used, indicated, proposed, defined and no explanation studies.</p> <p>The result of the classification process is: -use: 134 papers, -indicate: 56 papers -propose: 28 papers, -define: 3 papers, and -no explanation: 59 papers</p>
FUNCERT - Registration dynamics and course certification rates on a Massive Open Online Course (MOOC) platform
<p>The FUNCERT data set describes 1 million course registration events collected over a 2-year period from the MOOC platform FUN (France Université Numérique, fun-mooc.fr). Each registration event is associated with a timestamp and an indication of whether a completion certificate was ultimately awarded. It was used in the referenced manuscript to model the impact of multiple course registrations on certificate rates.</p> <p>The data set is provided as a single file (FUNCERT.csv) with the following fields.</p> <p><strong>Time (min)</strong> The time of the registration event reported in minutes elapsed since the beginning of data collection. The time stamp is reported as a relative time only, not an exact calendar date, to enhance anonymization.</p> <p><strong>User ID</strong> A unique ID number for each user of the platform during this period. The number has been generated specifically for this data set and does not correspond to user ID numbers used within the FUN platform.</p> <p><strong>Course ID</strong> Each of the 140 offered courses is assigned a unique and anonymous ID code. In some cases courses were offered multiple times within the data collection period. The same Course ID is used across multiple instances of the same course.</p> <p><strong>Certificate</strong> A boolean variable set to 1 if the registration event is associated with a course completion certificate. Of 140 offered courses, 91 awarded certificates during the study period.</p> <p><strong>Age</strong> User age in years at the time of registration. Field may be left blank if data was not provided.</p> <p><strong>Gender</strong> User gender as selected from the options m and f. Field may be left blank if data was not provided.</p>
The eWaterCycle platform for Open and FAIR Hydrological collaboration Video Abstract
<p>In this video we introduce The eWaterCycle platform for Open and FAIR Hydrological collaboration. With the eWaterCycle platform we are providing the hydrological community with a platform to conduct their research fully compatible with the principles of Open Science as well as FAIR science.</p> <p>This is a video abstract with the publication "The eWaterCycle platform for Open and FAIR Hydrological collaboration." in the journal Geoscientific Model Development (GMD) (under review, link will be provided when available).</p> <p>For more information on the eWaterCycle platform see:</p> <ul> <li>the eWaterCycle package on Zenodo: https://doi.org/10.5281/zenodo.5119389</li> <li>the 5 use cases presented in the paper and video, on Zenodo: https://doi.org/10.5281/zenodo.5543899</li> <li>the eWaterCycle website at https://www.ewatercycle.org/</li> </ul>
An Open-Source Platform for Head-Fixed Operant and Consummatory Behavior
<p>This is a repository containing all data and analysis codes for Gordon-Fennell et al. 2023 from the lab of Dr. Garret Stuber.</p>
QUALITOP - Monitoring Multidimensional Aspects of QUAlity of Life After Cancer ImmunoTherapy, an Open Smart Digital Platform for Personalized Prevention and Patient Management
ClinicalTrials.gov study NCT05626764. IPD Sharing: UNDECIDED. Countries: 4. Publications: 1.
A Prospective, Multicenter, Open-label Study of the Beacon Platform for Holmium Laser Enucleation of the Prostate (HoLEP)
ClinicalTrials.gov study NCT06668142. IPD Sharing: NO. Countries: 2. Publications: 4.
Fedora4: The Open Linked Data Platform
<p>Presentation at Open Repositories 2015 (OR2015), the 10th International Conference on Open Repositories, Indianapolis, Indiana, in session P1A: Linked Open Data (LOD). Note that high quality video files for this talk were not obtainable, so some video quality problems may be noticed.</p> <p>Linked Open Data has moved from being a buzzword to a fundamental building block of modern repositories and information systems. Its explosion, taking in this domain the form of scholarly and scientific datasets, publications, annotations, cultural heritage descriptions and other repository-based content, offers unprecedented opportunity for scientific and societal advancement. It is the interconnections that integrate systems and resources, however, that turn disparate ideas into unanticipated solutions.</p> <p>The Open Repositories community largely understands the value of linked data. The trouble has been in answering the question of “how?” to do this together, rather than "why?" do it at all. In order to be effective, we need to have solid guidelines, common practices, and well specified toolsets and products. A confluence of developments has opened the door to exactly this.</p> <p>In October of 2012, the initial W3C working draft of the Linked Data Platform 1.0 (LDP) document was published[2]. In July of 2012, the demand for a next-generation Fedora platform was channeled into the Fedora 4 (F4) project, which at the time was termed Fedora Futures. The alignment of these two stars set in motion events that provided both requirements and solutions for the community.</p>
An Exploratory Empirical Study of Trust & Safety Engineering in Open-Source Social Media Platforms
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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.