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8,537 results for “Openness”
Quality Evaluation Models or Frameworks for Open Source Software: A Systematic Literature Review (Matching articles with categories)
<p>This document includes which primary study falls into which category with respect to the RQs in the following study: “Quality Evaluation Models or Frameworks for Open Source Software: A Systematic Literature Review”</p>
Open Access Publishing
<p><strong>Open Access Publishing. </strong>Prepared for the Diploma in Education Technology Management (A Distance Education Programme) of NAAM, Hyderabad. DETM 524 – Ethical Issues in Educational Technology (3+0 credits) by Sridhar Gutam (<a href="mailto:sridhar.gutam@icar.gov.in">sridhar.gutam@icar.gov.in</a>) 2021</p> <p><strong>Video</strong>: <a href="https://youtu.be/A9Gxa6Z_0D8">https://youtu.be/A9Gxa6Z_0D8</a></p> <p><strong>Slide</strong> <strong>Deck</strong>: <a href="https://bit.ly/OAPSG">https://bit.ly/OAPSG</a></p>
An Empirical Study on the Usage and Availability of Machine Learning Libraries in Open-Source Python Projects - Dataset
<p>This repository contains the dataset of the manuscript:</p> <p>"An Empirical Study on the Usage and Availability of Machine Learning Libraries in Open-Source Python Projects"</p>
Modeling to determine when to re-open HIV services during COVID-19 pandemic
<p><b>The Risks and Benefits of Providing HIV Services during the COVID-19 Pandemic</b></p> <p><b>Introduction</b></p> <p>The COVID-19 pandemic has caused widespread disruptions including to health services. In the early response to the pandemic many countries restricted population movements and some health services were suspended or limited. In late 2020 and early 2021 some countries re-imposed restrictions. Health authorities need to balance the potential harms of additional SARS-CoV-2 transmission due to contacts associated with health services against the benefits of those services, including fewer new HIV infections and deaths. This paper examines these trade-offs for select HIV services. </p> <p><b>Methods</b></p> <p>We used four HIV simulation models (Goals, HIV Synthesis, Optima HIV and EMOD) to estimate the benefits of continuing HIV services in terms of fewer new HIV infections and deaths. We used three COVID-19 transmission models (Covasim, Cooper/Smith and a simple contact model) to estimate the additional deaths due to SARS-CoV-2 transmission among health workers and clients. We examined four HIV services: voluntary medical male circumcision, HIV diagnostic testing, viral load testing and programs to prevent mother-to-child transmission. We compared COVID-19 deaths in 2020 and 2021 with HIV deaths occurring now and over the next 50 years discounted to present value. The models were applied to countries with a range of HIV and COVID-19 epidemics.</p> <p><b>Results</b></p> <p>Maintaining these HIV services could lead to additional COVID-19 deaths of 0.002 to 0.15 per 10,000 clients. HIV-related deaths averted are estimated to be much larger, 19 - 146 discounted deaths per 10,000 clients.</p> <p><b>Discussion</b></p> <p>While there is some additional short-term risk of SARS-CoV-2 transmission associated with providing HIV services, the risk of additional COVID-19 deaths is at least 100 times less than the HIV deaths averted by those services. Ministries of Health need to take into account many factors in deciding when and how to offer essential health services during the COVID-19 pandemic. This work shows that the benefits of continuing key HIV services are far larger than the risks of additional SARS-CoV-2 transmission.</p>
Inputs and results of "A qualitative and quantitative analysis of open citations to retracted articles: the Wakefield 1998 et al.'s case"
<p>This repository contains the datasets and visualizations generated in our work: <strong>"A qualitative and quantitative analysis of open citations to retracted articles: the Wakefield 1998 et al.’s case"</strong>.</p> <p><strong>Note:</strong> the data are all contained inside the <strong><em>data.zip</em> </strong>file. You need to unzip the container to get access to all the files and directories listed below.</p> <p>The data (citations) gathered accompanied by their annotated characteristics are stored in <strong><em>data/</em>:</strong></p> <ul> <li><em><strong>"cits_features.csv": </strong></em>a dataset containing all the entities (rows in the CSV) which have cited the Wakefield et al. retracted article, and a set of features characterizing each citing entity (columns in the CSV). The features included are: DOI ("doi"), year of publication ("year"), the title ("title"), the venue identifier ("source_id"), the title of the venue ("source_title"), yes/no value in case the entity is retracted as well ("retracted"), the subject area ("area"), the subject category ("category"), the sections of the in-text citations ("intext_citation.section"), the value of the reference pointer ("intext_citation.pointer"), the in-text citation function ("intext_citation.intent"), the in-text citation perceived sentiment ("intext_citation.sentiment"), and a yes/no value to denote whether the in-text citation context mentions the retraction of the cited entity ("intext_citation.section.ret_mention").<br> <strong>Note: </strong>this dataset is licensed under a <a href="https://creativecommons.org/publicdomain/zero/1.0/legalcode">Creative Commons public domain dedication (CC0)</a>.</li> <li><em><strong>"cits_text.csv": </strong>this dataset stores the abstract ("abstract") and the in-text citations context ("intext_citation.context") </em>for each citing entity identified using the DOI value ("doi").<br> <strong>Note: </strong>the data keep their original license (the one provided by their publisher). This dataset is provided in order to favor the reproducibility of the results obtained in our work.</li> </ul> <p><strong>Topic modeling</strong></p> <p>We run a topic modeling analysis on the textual features gathered (i.e. abstracts and citation contexts). The results are stored inside the <em><strong>topic_modeling/</strong></em> directory. The topic modeling has been done using MITAO, a tool for mashing up automatic text analysis tools and creating a completely customizable visual workflow [1]. The topic modeling results for each textual feature are separated into two different folders, <em><strong>abstract/</strong></em> for the abstracts, and <em><strong>intext_cit/</strong></em> for the in-text citation contexts. Both the directories contain the datasets and visualizations generated using MITAO. </p> <p> </p> <p><strong>References</strong></p> <p>[1] Ferri, P., Heibi, I., Pareschi, L., & Peroni, S. (2020). MITAO: A User Friendly and Modular Software for Topic Modelling [JD]. PuntOorg International Journal, 5(2), 135–149. <a href="https://doi.org/10.19245/25.05.pij.5.2.3">https://doi.org/10.19245/25.05.pij.5.2.3</a></p>
Materials for Design Open Repository. Polymer Derived Ceramics
<p>The current dataset is composed of a collection of Polymer Derived Ceramics (PDCs). It contains the number of chemical elements (NoE), PDC composition, used precursor, Pyrolysis temperature <em>T</em><sub>p</sub>, Pyrolysis time <em>t</em><sub>p</sub>, gas atmosphere, a set of columns containing the chemical elements and their corresponding fraction, and the references. This dataset was developed in the framework of the European project ACHIEF for the discovery of novel materials to be used in industrial processes.</p>
open_MODEX base dataset
<p>The dataset includes the scenario data for the base scenario in the open_MODEX project.</p> <p>Licence note: All data is subject to the CC-BY 4.0 licence, unless otherwise declared. You are free to share and adapt.</p> <p> </p> <p> </p>
How are Solidity smart contracts tested in open source projects? An exploratory study
<p>A dataset with 139 Github Solidity projects containing information about testing files, testing tools, and testnets that each project uses.</p>
Global Socio-Economic and Environmental data for PyPSA-Earth: An Open Optimisation Model of the Earth Energy System.
<p><strong>PyPSA-Earth </strong>is an open model dataset of the global power system at different network levels that cover our Earth. The African model can be built using the code provided at <a href="https://github.com/pypsa-meets-africa/pypsa-africa">https://github.com/pypsa-meets-africa/pypsa-africa</a>. Other regions follow soon under the same code base.</p> <p>Since the GitHub codebase is not suited for handling large changing files, we provide here separate <strong>data bundles and cutouts</strong> to be downloaded and extracted as noted in the <a href="https://pypsa-meets-africa.readthedocs.io/en/latest/index.html">documentation</a></p> <p>The below-provided<strong> data files </strong>contain various open data for improving energy system modelling decisions. A thorough description with license restrictions will follow soon.</p>
Open Source Software Sustainability
<p>The reproducible code and dataset along with the paper submission.</p>
Comparative and predictive phylogeography in the South American diagonal of open formations: Unravelling the biological and environmental influences on multitaxon demography
<p><span><span>Phylogeography investigates historical drivers of species' geographic distribution. Special attention has been given to ecological, climatic, and geological processes in the diversification of the Neotropical biota. Several species sampled across the dry diagonal of South America (DDSA, comprising the Caatinga, Cerrado, and Chaco biomes) experienced range shifts coincident with Quaternary climatic changes. However, studies across different spatial, temporal, and biological scales on species from South America's dry biomes are still poorly represented. Here, we combine phylogeographic model selection and machine learning predictive frameworks to investigate the influence of Pleistocene climatic changes on both plant and animal species from the DDSA. We assembled mitochondrial/chloroplastic DNA sequences in public repositories and inferred the historical demographic responses of 70 lineages. We then built a random forest model using both biotic and abiotic information to identify potential traits for predicting whether species underwent population expansion, contraction, or stasis during the Pleistocene. Finally, we estimated the temporal synchrony of species demographic responses using hierarchical approximate Bayesian computation (hABC). Biotic variables largely predicted how species responded to Pleistocene climatic changes, and demographic changes were mostly synchronous during the Middle Pleistocene. Although many DDSA species underwent demographic expansion, presumably associated with the spread of aridity during glacial Pleistocene periods, our findings suggest that some species exhibited the opposite response and that species-specific attributes might have been related to these differences.</span></span></p>
Ecological traits drive genetic structuring in two open-habitat birds from the morphologically cryptic genus Elaenia (Aves: Tyrannidae)
<p>Understanding the relative contributions of the many factors that shape population genetic structuring is a central theme in evolutionary and conservation biology. Historically, abiotic or extrinsic factors (such as geographic barriers or climatic shifts) have received greater attention than biotic or intrinsic factors (such as dispersal or migration). This focus stems in part from the logistical difficulties in taking a comparative phylogeographic approach that contrasts species that have experienced similar abiotic conditions during their evolution yet differ in the intrinsic attributes that might shape their genetic structure. To explore the effects of intratropical migration on the genetic structuring of Neotropical birds, we chose two congeneric species, the Lesser Elaenia (<em>Elaenia chiriquensis</em>) and the Plain-crested Elaenia (<em>E. cristata</em>), that are largely sympatric, and which have similar plumage, habitat preferences, and breeding phenology. Despite these many commonalities, they differ in migratory behavior: <em>E. chiriquensis</em> is an intratropical migratory species while <em>E. cristata</em> is sedentary. We used a reduced representation genomic approach to test whether migratory behavior is associated with increased gene flow and therefore lower genetic population structure. As predicted, we found notably stronger genetic structuring in the sedentary species than in the migratory ones. <em>E. cristata</em> comprises genetic clusters with geographic correspondence throughout its distribution, while there are no geographic groups within Brazil for <em>E. chiriquensis</em>. This comparison adds to the growing evidence about how intrinsic traits like migration can shape the genetic structuring of birds, and advances our understanding of the diversification patterns of the understudied, open habitat species from South America.</p>
Even when you know it is a placebo, you experience less sadness: First evidence from an experimental open-label placebo investigation (Open Data and Open Materials)
<p><strong>Open Data and Open Materials of: Even when you know it is a placebo, you experience less sadness: First evidence from an experimental open-label placebo investigation. <em>Journal of Affective Disorders</em>. </strong></p> <p><em>Background:</em> Recent studies demonstrate substantial effects of deceptive placebo on experimentally induced sadness,<br> even on autonomic activity. Whether deception is necessary, remains to be elucidated. We investigated the<br> effect of an open-label placebo (OLP) treatment, i.e. an openly administered placebo delivered with a convincing<br> rationale for its sadness-protecting effect.<br> <em>Methods:</em> Eighty-four healthy females were randomized to an OLP group or a no-treatment control group. All<br> participants received the same detailed information about the OLP effect, only the OLP group received an OLP<br> nasal spray. Before and after the OLP intervention, participants underwent a sad mood induction procedure<br> combining self-deprecating statements (Velten's method) and sad music. Sadness was assessed by the Positive<br> and Negative Affect Schedule (PANAS-X). Autonomic activity was measured continuously.<br> <em>Results:</em> Participants in the OLP group reported a significantly attenuated increase in sadness upon mood induction<br> and less sadness after induction compared to the control group (d = 0.79). Regardless of intervention,<br> heart rate decreased during mood inductions with a more pronounced deceleration in the second mood induction.<br> <em>Limitations:</em> Generalizability is limited due to the selective sample and the reliance on an experimentally controlled<br> mood induction.<br> <em>Conclusion:</em> OLP treatment had a beneficial effect on perceived sadness, at least at the subjective level. Hence,<br> deception may not necessarily be required for placebos to modulate experienced sad mood. Investigating the<br> beneficial effects of OLP in (sub-)clinical samples would seem a promising and required next step towards a<br> clinical use of placebo-associated positive treatment expectations.</p>
Open data for spatial public health research
<p><strong>Background</strong></p> <p>Preventive and health-promoting policies can guide (place and space-specific) factors influencing human health, such as the physical and social environment. Required is data that can lead to a more nuanced decision-making process and identify both, existing and future challenges. Along with the rise of new technologies, and thus the multiple opportunities to use and process data, new options have emerged to measure and monitor factors that affect health. Thus, in recent years, several gateways for open data (including governmental and geospatial data) became available. At present, an increasing number of research institutions as well as (state and private) companies and citizens' initiatives provide data. However, there is a lack of overviews covering the range of such offerings regarding health. In particular, for geographically differentiated analyses, there are challenges related to data availability at different spatial levels and the growing number of data providers.</p> <p><strong>Objectives</strong></p> <p>To provide an overview of open data resources available in the context of space and health to date. It also describes the technical and legal conditions for using open data</p> <p><strong>Results</strong></p> <p>An up-to-date summary of results including information on relevant data access and terms of use is provided along with a web visualization. All data is available for further use under an open license.</p>
CamoEvo: an open access toolbox for artificial camouflage evolution experiments
<p>Camouflage research has long shaped our understanding of evolution by natural selection, and elucidating the mechanisms by which camouflage operates remains a key question in visual ecology. However, the vast diversity of colour patterns found in animals and their backgrounds, combined with the scope for complex interactions with receiver vision presents a fundamental challenge for investigating optimal camouflage strategies. Genetic algorithms have provided a potential method for accounting for these interactions, but with limited accessibility. Here, we present CamoEvo, an open-access toolbox for investigating camouflage pattern optimisation by using tailored genetic algorithms, animal and egg maculation theory and artificial predation experiments. This system allows for camouflage evolution within the span of just 10-30 generations (~1-2 min per generation), producing patterns that are both significantly harder to detect and that are optimised to their background. CamoEvo was built in ImageJ to allow for integration with an array of existing open access camouflage analysis tools. We provide guides for editing and adjusting the predation experiment and genetic algorithm as well as an example experiment. The speed and flexibility of this toolbox makes it adaptable for a wide range of computer based phenotype optimisation experiments.</p>
Dvoice : An open source dataset for Automatic Speech Recognition on African Languages and Dialects
<p>DVoice is a community initiative that aims to provide African languages and dialects with data and models to facilitate their use of voice technologies. The lack of data on these languages makes it necessary to collect data using methods that are specific to each language. Two different approaches are currently used: the DVoice platform, which is based on Mozilla Common Voice, for collecting authentic recordings from the community, and transfer learning techniques for automatically labeling the recordings. The DVoice platform currently manages 7 languages including Darija (Moroccan Arabic dialect) whose dataset appears on this version, Wolof, Mandingo, Serere, Pular, Diola and Soninke. The Swahili-labeled data present in this version was obtained after automatic labeling via the learning transfer of the Voxlingua107 dataset. For a first time, we also advocate for the increase of data given their small size that we currently have. Thus this version of the dataset contains easily identifiable augmented data.</p>
TRINITY open access data repository data set 2 by Budapest University of Technology and Economics
<p>Horizon 2020 programme supports access to and reuse of research data generated by Horizon 2020 projects through the Open Research Data Pilot (ORDP). To support the validation of scientific results, the pilot focuses on providing access to data needed to validate the scientific results. There are several types of such data, e.g. machine learning data sets, models, measurements, statistical results of experiments, survey outcomes, etc.</p> <p>This deliverable summarizes the data that are expected to be collected in the course of the project and where and how they are stored. The aspect of providing open access to research data (as required by the European Commission’s Open Research Data Pilot, <a href="https://www.openaire.eu/what-is-the-open-research-data-pilot">https://www.openaire.eu/what-is-the-open-research-data-pilot</a>) is addressed in Section 3. Finally, in Section 4 we describe the data sets that were or are expected to be generated within the TRINITY projects and made freely available.</p>
TRINITY open access data repository by Budapest University of Technology and Economics
<p>Horizon 2020 programme supports access to and reuse of research data generated by Horizon 2020 projects through the Open Research Data Pilot (ORDP). To support the validation of scientific results, the pilot focuses on providing access to data needed to validate the scientific results. There are several types of such data, e.g. machine learning data sets, models, measurements, statistical results of experiments, survey outcomes, etc.</p> <p>This deliverable summarizes the data that are expected to be collected in the course of the project and where and how they are stored. The aspect of providing open access to research data (as required by the European Commission’s Open Research Data Pilot, <a href="https://www.openaire.eu/what-is-the-open-research-data-pilot">https://www.openaire.eu/what-is-the-open-research-data-pilot</a>) is addressed in Section 3. Finally, in Section 4 we describe the data sets that were or are expected to be generated within the TRINITY projects and made freely available.</p>
Figures 2 and 3 in HighRes for Springer book chapter "Online Infrastructures For Open Educational Resources"
<p>Figure 2 and Figure 3 in high resolution for the book chapter:</p> <p>Marín, V. I., & Villar-Onrubia, D. (in press, 2022). Online Infrastructures For Open Educational Resources. In I. Jung & O. Zawacki-Richter (Eds.), <em>Handbook of Open, Distance and Digital Education</em> (Global Perspectives and Internationalization). Springer. <a href="https://doi.org/10.1007/978-981-19-0351-9_18-1">https://doi.org/10.1007/978-981-19-0351-9_18-1</a></p> <p>----</p> <p>Details for the figures:</p> <p>Fig. 2 Examples of national and regional digital infrastructures in Europe. (Note: The original figure of the Europe map was created by Commons user Alexrk2, CC BY-SA 3.0, shared via Wikimedia Commons)</p> <p>Figure 3. Examples of national and regional digital infrastructures in South America. (Note: The original figure of the South America map was created by TUBS, CC BY-SA 3.0, shared via Wikimedia Commons)</p>
Open data repository, An et al., Deep learning-based automated lesion segmentation on mouse stroke magnetic resonance images
<p>Open data repository of journal article "Deep learning-based automated lesion segmentation on mouse stroke magnetic resonance images" by Jeehye An <em>et al. </em>At time of publication of this dataset, the manuscript is still under revision.</p> <p>This dataset contains mouse T2 weighted MRI data, and manually and automated segmented ischemic stroke lesion masks for developing and evaluating a deep learning-based automated lesion segmentation. All files are in NIFTI format.<br> </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.