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8,537 results for “Openness”
Open Data: FAIR, foul, and meta
<p><strong>Episode Summary: </strong></p> <p>In this episode we are discussing what metadata is, the obstacles to sharing research data, and how Open Science recommendations are being transformed into actions. Our interview guest will be Professor Eva Mendez from Universidad Carlos III in Madrid who is the Chair of the European Open Science Policy Platform.</p> <p><strong>Links:</strong></p> <p><a href="https://www.orion-openscience.eu/publications/training-materials/201808/factsheets">Factsheets (Open Data and Data Management)</a></p> <p><a href="https://uc3m.academia.edu/EvaM%C3%A9ndez/CurriculumVitae">Professor Eva Mendez</a></p> <p><a href="https://ec.europa.eu/research/openscience/index.cfm?pg=open-science-policy-platform">Open Science Policy Platform</a></p> <p><strong>Quotes:</strong></p> <p>'Open doesn't necessarily mean FAIR'</p>
Signing up to Open Science: Open Peer Review and Aligning Core Values
<p><strong>Episode Summary:</strong></p> <p>In this episode we are talking to Dr Guillaume Filion from the Center for Genomic Regulation (CRG), Barcelona about his decision to put his name on all his peer reviews, why he feels this makes him more accountable, and what choices researchers need to make about whether their values align with those who they will work with. </p> <p><strong>Resources and Links:</strong></p> <ul> <li><a href="https://www.orion-openscience.eu/node/201">Factsheets</a></li> <li><a href="https://www.crg.eu/en/programmes-groups/filion-lab">Dr Guillaume Filion</a> <ul> <li><a href="https://twitter.com/thegrandlocus">Twitter Page</a></li> </ul> </li> <li><a href="http://blog.thegrandlocus.com/2018/09/on-open-peer-review">Original Blog Post by Dr Guillaume Filion</a></li> <li><a href="https://www.fosteropenscience.eu/learning/open-peer-review/#/id/5a17e150c2af651d1e3b1bce">FOSTER+ Information on Open Peer Review </a></li> </ul> <p><strong>Episode Quotes:</strong></p> <p>“I had the feeling I would do a better job as a reviewer, if I put my name on it, if I put my name on the line then it would force me not to do a bad job”</p>
Three Golden Rules of Open Science Training
<p>Presentation and talk recorded for the Open Science Conference 2020 by Dr Emma A Harris about the lessons learned from Open Science training undertaken as part of the H2020 ORION Open Science Project.</p>
Open Source COVID-19
<p>Open Source COVID-19 collects open source projects during COVID-19. The projects are not necessarily hosted on GitHub, as long as it corporates in an open source way, that everyone can access, inspect and improve it.<br> The goal of this navigation site is to help people access data, contribute to the projects, and trigger new ideas.</p>
On Strong Scaling and Open Source Tools for Analyzing Atom Probe Tomography Data
<p>This repository contains supplemental results to the paper "On Strong Scaling and Open Source Tools<br> for Analyzing Atom Probe Tomography Data".</p> <p>Specifically, the input parameter and result files from all synthetic benchmark studies.<br> The results file for all synthetic specimen benchmark studies are available from the<br> authors upon serious request.</p> <p><strong>The repository content is as follows:</strong></p> <p><strong>Real world data:<br> Three triplets of *.tar.gz archive files document the settings and analysis files for the real world case studies</strong><br> 3013902 is the incipient specimen,<br> 2763207 the intermediate specimen, and<br> 3345501 the mature specimen.</p> <p><strong>Scripts.zip</strong><br> Contains all batch scripts we used for performing the analyses as a queue</p> <p><strong>Synthetic data:</strong></p> <p><strong>APTCrystallography.zip</strong><br> Contains all results from the benchmarking of the reimplemented Vicente Araullo-Peters et al. method</p> <p><strong>FullVolumeTessellation.zip</strong><br> Contains all results from the benchmarking of the Voro++ Voronoi volume tessellation method except for the HDF5/XDMF volume tessellation files of the 200 and 2000 million ion datasets</p> <p><strong>TwoPointStatistics.zip</strong><br> Contains all results from benchmarking the computing of 2-point spatial statistics</p> <p><strong>TipSurfaceDescrSpatialStatistics.zip</strong><br> Contains all results from benchmarking the alpha shape computation, descriptive spatial statistics, and clustering analyses</p> <p><strong>PARAPROBE.Results.2Mio.tar.gz<br> PARAPROBE.Results.20Mio.tar.gz</strong><br> <strong>PARAPROBE.Results.200Mio.tar.gz</strong><br> Contains all settings files and some results from benchmarking the hybrid implementation.</p> <p><strong>Unpack the individual repositories using tar through Linux console as follows:</strong><br> tar -xvf <archivename> <br> where <archivename> is a placeholder for the respective tar gz compressed archives within the ZIP file.<br> Alternatively WinRAR can be used on a Windows system.</p> <p><strong>We would kindly like to ask you to use the following repository<br> to access source code of PARAPROBE in the future:</strong></p> <p><strong>https://gitlab.mpcdf.mpg.de/mpie-aptfim-toolbox/paraprobe<br> https://paraprobe-toolbox.readthedocs.io/en/latest/</strong><br> <br> <strong>Only above repository will be updated in the future! </strong><br> <strong>Only there new code additions and bugfixes are posted!<br> The examples folder of this repository contains a folder examples/tasks/paper14 which shows how<br> to run a workflow of paraprobe tools from this above repository to run analyses akin as reported in this paper.</strong></p> <p>Recommendations and bug reports to M. Kühbach are appreciated! Happy APT analyzing!</p> <p>------------------------------------------------------------------------------------------------------------------------------------------------------------------------<br> <strong>The PARAPROBE source code version we used for analyzing the synthetic and real world APT<br> specimens in the paper used an earlier development version of the PARAPROBE tool, the source code</strong><br> <strong>is here:</strong></p> <p>PARAPROBE_20190117_VersionUsedForPaper.zip</p> <p>https://github.com/mkuehbach/PARAPROBE<br> https://paraprobe.readthedocs.io/en/latest/</p> <p> </p>
Open Peer Review Journal Data
<p>This csv file contains a descriptive dataset of <strong>617</strong> scholarly journals that make use of a form of Open Peer Review (OPR) based on Open Reports and/or Open Reviewer Identities. The data file contains the following fields:</p> <p>Journal Title</p> <p>Year of First Identified OPR Occurrence (2001-2019)</p> <p>High Level Discipline of the Journal (Humanities, Medical and Health Sciences, Multidisciplinary, Natural Sciences, Social Sciences, Technology)</p> <p>Journal URL</p> <p>Journal Publisher</p> <p>Publisher Country</p> <p>Use of Open Reports (Decided by Author, Decided by Editor, Mandated by Journal, None)</p> <p>Use of Open Reviewer Identities (Decided by Reviewer, Mandated, None)</p> <p>Notes that provide additional information about the journal</p>
Security vulnerabilities in open-source reused systems
<p>This dataset comprise 2017 Java projects. It contains information related to their external dependencies and its potential and disclosed security vulnerabilities.</p> <p>The potential vulnerabilities were detected with the use of the SpotBugs static analyzer tool, while the disclosed ones with the use of OWASP Dependency Check tool..</p> <p>This dataset was generated during a research effort to correlate software reuse to security vulnerabilities.</p> <p>The scripts for reproducing the dataset and analyzing it are available on GitHub under this link [https://github.com/AntonisGkortzis/Vulnerabilities-in-Reused-Software].</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>
Effectiveness of Open Science Policies at ESEC/FSE 2019
<p>This report summarizes how the ESEC/FSE 2019 open science policies came to life and how they resulted in openness for the conference. In particular, I provide how authors of 277 papers provided data at peer review time, and how authors of 74 published papers provided their papers and data openly. Finally, I discuss on the obtained results, and provide lessons learned for the development of SIGSOFT open science policies.</p> <p>See: <a href="https://ineed.coffee/5836/effectiveness-of-open-science-policies-at-esec-fse-2019/">https://ineed.coffee/5836/effectiveness-of-open-science-policies-at-esec-fse-2019/</a></p>
OpenPREDICT: Open and FAIR implementation of the PREDICT method for drug repurposing
<p>This dataset is used for Open and FAIR implementation of the PREDICT method. It is described in the paper titled "PREDICT: a method for inferring novel drug indications with application to personalized medicine.", Gottlieb A, Stein GY, Ruppin E, Sharan R. Mol Syst Biol. 2011;7:496. Published 2011 Jun 7. doi:10.1038/msb.2011.26</p>
COEMS EU2020 Open Data
<p>Open Data generated in the context of the COEMS H2020 project for the monitoring of execution traces. The Open Data includes the software source code, the instrumented binary files that we monitor, the execution traces and the output analysis that the TeSSLa specifications generated. The experiments are executed both in x86/ARM architectures. The x86 experiments corresponds to the offline monitoring of the execution traces; while the ARM experiments corresponds to the online monitoring via the COEMS hardware specific infrastructure. The Open Data includes 2 case of study from a COEMS industrial partner.</p>
Monitoring of cow location in barn by an open source low cost low energy Bluetooth tag system
<p>Supplementary materials for: Bloch, V., Pastell, M., 2020. Monitoring of Cow Location in a Barn by an Open-Source, Low-Cost, Low-Energy Bluetooth Tag System. Sensors 20, 3841. <a href="https://doi.org/10.3390/s20143841">https://doi.org/10.3390/s20143841</a></p>
State of open data in catalysis and contiguous fields
<p>This dataset comprises two sub-sets of data:</p> <ul> <li>Dataset_1: field-specific dataset to article ratio from 2011 to 2019</li> <li>Dataset_2: survey on datasets for hydrodeoxygenation</li> </ul> <p>These correspond to Figure 5 and Figure 4, respectively, of the following publication:</p> <p>P.S.F. Mendes, S. Siradze, L. Pirro, J.W. Thybaut, Open Data in Catalysis: From Today's Big Picture to the Future of Small Data, ChemCatChem, 2021, 13, 836-850, https://doi.org/10.1002/cctc.202001132</p> <p> </p>
An open dataset to study interlinkages triggered by energy transition in the transboundary Upper-Rhine within the WEFCL-Nexus
<p>This data set contains socio-economic and biophysical data describing the functioning of each of the five sectors the of Water – Energy – Climate – Land-Use – Food Nexus in the Upper Rhine. All data go from 2006-2050 at monthly time step. This data set was built as part of the SIM4Nexus H2020 project while aiming at putting into practice the Nexus approach and investigating conflicts and synergies triggered within the WEFCL-Nexus by energy transition in the Upper-Rhine, especially the development of bioenergy and renewables. This data set contains socio-economic and biophysical data describing the functioning of each of the five sectors the of Water – Energy – Climate – Land-Use – Food Nexus in the Upper Rhine. All data go from 2006-2050 at monthly time step. This data set was built as part of the SIM4Nexus H2020 project while aiming at putting into practice the Nexus approach and investigating conflicts and synergies triggered within the WEFCL-Nexus by energy transition in the Upper-Rhine, especially the development of bioenergy and renewables.</p>
Data from: Capturing open ocean biodiversity: comparing environmental DNA metabarcoding to the continuous plankton recorder
Environmental DNA (eDNA) metabarcoding is emerging as a novel, objective tool for monitoring marine metazoan biodiversity. Zooplankton biodiversity in the vast and important open ocean is currently monitored through continuous plankton recorder (CPR) surveys, using ship-based bulk plankton sampling and morphological identification. We assessed whether eDNA metabarcoding (2 L filtered seawater) could capture similar Southern Ocean biodiversity as conventional CPR bulk sampling (~1500 L filtered seawater per CPR sample). We directly compared eDNA metabarcoding with (i) conventional morphological CPR sampling and (ii) bulk DNA metabarcoding of CPR collected plankton (two transects for each comparison, 40 and 44 paired samples respectively). A metazoan‐targeted cytochrome c oxidase I (COI) marker was used to characterize species-level diversity. In the 2 L eDNA samples this marker amplified large amounts of non‐metazoan picoplanktonic algae, but eDNA metabarcoding still detected up to 1.6 times more zooplankton species than morphologically analysed bulk CPR samples. COI metabarcoding of bulk DNA samples mostly avoided non-metazoan amplifications and recovered more zooplankton species than eDNA metabarcoding. However, eDNA metabarcoding detected roughly two thirds of metazoan species and identified similar taxa contributing to community differentiation across the subtropical front separating transects. We observed a diurnal pattern in eDNA data for copepods which perform diel vertical migrations, indicating a surprisingly short temporal eDNA signal. Compared to COI, a eukaryote-targeted 18S ribosomal RNA marker detected a higher proportion, but lower diversity, of metazoans in eDNA. With refinement and standardization of methodology, eDNA metabarcoding could become an efficient tool for monitoring open ocean biodiversity.
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>
[Dataset] Expanding the Number of Reviewers in Open-Source Projects by Recommending Appropriate Developers
<p>A rich collection of review and development data, including information about reviewers, developers and their<br> commits within five large ASF projects and four Gerrit communities.</p>
Open database of small-scale solar PV installations: a Citizen Science initiative
<p>Presentation given at the European PV Solar Energy Conference 2020 about the development of a Citizen Science initiative related to PV installations, Generation Solar.</p>
Open and Closed Radicals: Local Geometry AroundUnpaired Electrons Governs MAS DNP Performance
<p>Raw NMR and EPR data for publication Open and Closed Radicals: Local Geometry AroundUnpaired Electrons Governs MAS DNP Performance with DOI.of 10.1021/jacs.0c04911</p>
Atticus Open Contract Dataset (AOK) (beta)
<p>Atticus Open Contract Dataset (AOK)(beta) is a corpus of 5,000+ labels in 200 commercial legal contracts that have been manually labeled by legal experts to identify 40 types of clauses that are important during contract review in connection with corporate transactions, such as mergers and acquisitions, IPO, and corporate financing.</p> <p>AOK Dataset is curated and maintained by The Atticus Project, Inc., a non-profit organization, to support NLP research and development in legal contract review.</p> <p>If you download this dataset, we'd love to know more about you and your project! Please fill out this short form: <a href="https://forms.gle/h47GUENTTbBqH39m7">https://forms.gle/h47GUENTTbBqH39m7</a>.</p> <p>Check out our website at <a href="https://www.atticusprojectai.org">atticusprojectai.org</a>.</p> <p> </p> <p><strong>Update:</strong> The expanded 1.0 version of the dataset is available here https://zenodo.org/record/4595826</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.