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289 results for “license”
LINC01235 regulate global histone modifications and enhances licensing factor accessibility
GEO Series GSE271799. Homo sapiens. 17 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Metabolic licensing of quiescent glioblastoma activation and immune evasion via astrocyte-mitochondria shuttle
GEO Series GSE294545. Homo sapiens. 20 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
αKG-driven RNA polymerase II transcription of cyclin D1 licenses malic enzyme 2 to promote cell cycle progression
GEO Series GSE221723. Homo sapiens. 6 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Dataset from "What do developers talk about open source software licensing? " - SEAA2020
<p>This is the dataset used in the respective research work. The abstract is available below.</p> <p>If you want to cite this work, please use:</p> <p> </p> <p>Georgia M. Kapitsaki, Maria Papoutsoglou, Daniel German and Lefteris Angelis, What do developers talk about open source software licensing?, to appear in the Proceedings of the Euromicro Conference on <a href="https://dsd-seaa2020.um.si/seaa/index.html">Software Engineering and Advanced Applications</a>, SEAA 2020.</p> <p>Free and open source software has gained a lot of momentum in the industry and the research community. Open source<br> licenses determine the rules, under which the open source software can be further used and distributed. Previous works<br> have examined the usage of open source licenses in the framework of specific projects or online social coding platforms, examining developers specific licensing views for specific software. However, the questions practitioners ask about licenses and licensing as captured in Question and Answer websites also constitute an important aspect toward understanding practitioners general licenses and licensing concerns. In this paper, we investigate open source license discussions using data from the Software Engineering, Open Source and Law Stack Exchange sites that contain relevant data. We describe the process used for the data collection and analysis, and discuss the main results. Our results indicate that clarifications about specific licenses and specific license terms are required. The results can be useful for developers, educators and license authors.</p>
CLARA Knowledge Graph of licensed educational resources (Singleton properties)
<p><span>/!\</span> This deposit is deprecated; a more complete version of the deposit can be found here: <a href="https://zenodo.org/records/8403142">8403142</a>. <span>/!\</span></p> <p><strong>CLARA</strong><br>This deposit is part of the <a href="https://project.inria.fr/clara/">CLARA project</a>. The CLARA project aims to empower teachers in the task of creating new educational resources. And in particular with the task of handling the licenses of reused educational resources.</p> <p>The present deposit contains the RDF files created using an RDF mapping (<a href="https://rml.io/">RML</a>) and a mapper (<a href="https://github.com/morph-kgc/morph-kgc">Morph-KGC</a>). The files used as inputs can be found <a href="http://10.5281/zenodo.8107150">here</a>. That pipeline can be found on <a href="https://gitlab.univ-nantes.fr/clara/pipeline">Gitlab</a>. The data used in that pipeline originate from <a href="https://www.x5gon.org/">X5GON</a>, a European project aiming to generate and gather open educational resources.</p> <p><strong>Content</strong><br>The present Knowledge Graph contains information about 45K educational resources and 135K subjects (extracted from DBpedia).<br>That information contains </p> <ul> <li>the author,</li> <li>its title and description</li> <li>the license,</li> <li>a URL to the resource itself,</li> <li>the language of the educational resource,</li> <li>its mimetype,</li> <li>and finally which subject it talks about, and to what extent.</li> </ul> <p><br>That extent is given by two scores, a PageRank score and a cosinus score (that were <strong>not</strong> calculated on our graph but during the X5GON project)</p> <p>A particularity of the Knowledge Graph is its heavy use of RDF reification, across large multi-valued properties.<br>Other versions of the same deposit can be found using different reification models:</p> <ul> <li><a href="https://zenodo.org/record/8108856">Standard reification</a></li> <li><a href="https://zenodo.org/record/8108948">Named graphs</a></li> <li><a href="https://zenodo.org/record/8108971">RDF-star</a></li> </ul> <p>The Knowledge Graph also contains <a href="https://databus.dbpedia.org/dbpedia/generic/categories">categories</a> originating from DBpedia. They help precise the subjects that are also extracted from DBpedia.</p> <p>The deposit contains five types of files:</p> <ul> <li><strong>Authors_[</strong>X<strong>].nt</strong> - Those contain the authors' nodes, their type, and name.</li> <li><strong>ER_[</strong>X<strong>].nt</strong> - Those contain the educational resources and their information using singleton properties.</li> <li><strong>categories_skos_[</strong>X<strong>].ttl</strong> - Those contain the hierarchy of DBpedia categories.</li> <li><strong>categories_labels.ttl </strong>- This file contains additional information about the categories.</li> <li><strong>categories_article.ttl</strong> - This file contains the RDF triples that link the DBpedia subjects to the DBpedia categories.</li> </ul>
CLARA Knowledge Graph of licensed educational resources (RDF-star)
<p><span>/!\</span> This deposit is deprecated; a more complete version of the deposit can be found here: <a href="https://zenodo.org/records/8403142">8403142</a>. <span>/!\</span></p> <p><strong>CLARA</strong><br>This deposit is part of the <a href="https://project.inria.fr/clara/">CLARA project</a>. The CLARA project aims to empower teachers in the task of creating new educational resources. And in particular with the task of handling the licenses of reused educational resources.</p> <p>The present deposit contains the RDF files created using an RDF mapping (<a href="https://ceur-ws.org/Vol-2980/paper374.pdf">RML-star</a>) and a mapper (<a href="https://github.com/morph-kgc/morph-kgc">Morph-KGC</a>). The files used as inputs can be found <a href="http://10.5281/zenodo.8107150">here</a>. That pipeline can be found on <a href="https://gitlab.univ-nantes.fr/clara/pipeline">Gitlab</a>. The data used in that pipeline originate from <a href="https://www.x5gon.org/">X5GON</a>, a European project aiming to generate and gather open educational resources.</p> <p><strong>Content</strong><br>The present Knowledge Graph contains information about 45K educational resources and 135K subjects (extracted from DBpedia).<br>That information contains </p> <ul> <li>the author,</li> <li>its title and description</li> <li>the license,</li> <li>a URL to the resource itself,</li> <li>the language of the educational resource,</li> <li>its mimetype,</li> <li>and finally which subject it talks about, and to what extent.</li> </ul> <p><br>That extent is given by two scores, a PageRank score and a cosinus score (that were <strong>not</strong> calculated on our graph but during the X5GON project)</p> <p>A particularity of the Knowledge Graph is its heavy use of RDF reification, across large multi-valued properties.<br>Other versions of the same deposit can be found using different reification models:</p> <ul> <li><a href="https://zenodo.org/record/8108856">Standard reification</a></li> <li><a href="https://zenodo.org/record/8108948">Named graphs</a></li> <li><a href="https://zenodo.org/record/8108963">Singleton properties</a></li> </ul> <p>The Knowledge Graph also contains <a href="https://databus.dbpedia.org/dbpedia/generic/categories">categories</a> originating from DBpedia. They help precise the subjects that are also extracted from DBpedia.</p> <p>The deposit contains five types of files:</p> <ul> <li><strong>Authors_[</strong>X<strong>].nt</strong> - Those contain the authors' nodes, their type, and name.</li> <li><strong>ER_[</strong>X<strong>].ttl</strong> - Those contain the educational resources and their information using RDF-star.</li> <li><strong>categories_skos_[</strong>X<strong>].ttl</strong> - Those contain the hierarchy of DBpedia categories.</li> <li><strong>categories_labels.ttl </strong>- This file contains additional information about the categories.</li> <li><strong>categories_article.ttl</strong> - This file contains the RDF triples that link the DBpedia subjects to the DBpedia categories.</li> </ul>
CLARA Knowledge Graph of licensed educational resources (Named graphs)
<p><span>/!\</span> This deposit is deprecated; a more complete version of the deposit can be found here: <a href="https://zenodo.org/records/8403142">8403142</a>. <span>/!\</span></p> <p><strong>CLARA</strong><br>This deposit is part of the <a href="https://project.inria.fr/clara/">CLARA project</a>. The CLARA project aims to empower teachers in the task of creating new educational resources. And in particular with the task of handling the licenses of reused educational resources.</p> <p>The present deposit contains the RDF files created using an RDF mapping (<a href="https://rml.io/">RML</a>) and a mapper (<a href="https://github.com/morph-kgc/morph-kgc">Morph-KGC</a>). The files used as inputs can be found <a href="http://10.5281/zenodo.8107150">here</a>. That pipeline can be found on <a href="https://gitlab.univ-nantes.fr/clara/pipeline">Gitlab</a>. The data used in that pipeline originate from <a href="https://www.x5gon.org/">X5GON</a>, a European project aiming to generate and gather open educational resources.</p> <p><strong>Content</strong><br>The present Knowledge Graph contains information about 45K educational resources and 135K subjects (extracted from DBpedia).<br>That information contains </p> <ul> <li>the author,</li> <li>its title and description</li> <li>the license,</li> <li>a URL to the resource itself,</li> <li>the language of the educational resource,</li> <li>its mimetype,</li> <li>and finally which subject it talks about, and to what extent.</li> </ul> <p><br>That extent is given by two scores, a PageRank score and a cosinus score (that were <strong>not</strong> calculated on our graph but during the X5GON project)</p> <p>A particularity of the Knowledge Graph is its heavy use of RDF reification, across large multi-valued properties.<br>Other versions of the same deposit can be found using different reification models:</p> <ul> <li><a href="https://zenodo.org/record/8108856">Standard reification</a></li> <li><a href="https://zenodo.org/record/8108963">Singleton properties</a></li> <li><a href="https://zenodo.org/record/8108971">RDF-star</a></li> </ul> <p>The Knowledge Graph also contains <a href="https://databus.dbpedia.org/dbpedia/generic/categories">categories</a> originating from DBpedia. They help precise the subjects that are also extracted from DBpedia.</p> <p>The deposit contains five types of files:</p> <ul> <li><strong>Authors_[</strong>X<strong>].nt</strong> - Those contain the authors' nodes, their type, and name.</li> <li><strong>ER_[</strong>X<strong>].nq</strong> - Those contain the educational resources and their information using named graphs.</li> <li><strong>categories_skos_[</strong>X<strong>].ttl</strong> - Those contain the hierarchy of DBpedia categories.</li> <li><strong>categories_labels.ttl </strong>- This file contains additional information about the categories.</li> <li><strong>categories_article.ttl</strong> - This file contains the RDF triples that link the DBpedia subjects to the DBpedia categories.</li> </ul>
CLARA Knowledge Graph of licensed educational resources (Standard reification)
<p><span>/!\</span> This deposit is deprecated; a more complete version of the deposit can be found here: <a href="https://zenodo.org/records/8403142">8403142</a>. <span>/!\</span></p> <p><strong>CLARA</strong><br>This deposit is part of the <a href="https://project.inria.fr/clara/">CLARA project</a>. The CLARA project aims to empower teachers in the task of creating new educational resources. And in particular with the task of handling the licenses of reused educational resources.</p> <p>The present deposit contains the RDF files created using an RDF mapping (<a href="https://rml.io/">RML</a>) and a mapper (<a href="https://github.com/morph-kgc/morph-kgc">Morph-KGC</a>). The files used as inputs can be found <a href="http://10.5281/zenodo.8107150">here</a>. That pipeline can be found on <a href="https://gitlab.univ-nantes.fr/clara/pipeline">Gitlab</a>. The data used in that pipeline originate from <a href="https://www.x5gon.org/">X5GON</a>, a European project aiming to generate and gather open educational resources.</p> <p><strong>Content</strong><br>The present Knowledge Graph contains information about 45K educational resources and 135K subjects (extracted from DBpedia).<br>That information contains </p> <ul> <li>the author,</li> <li>its title and description</li> <li>the license,</li> <li>a URL to the resource itself,</li> <li>the language of the educational resource,</li> <li>its mimetype,</li> <li>and finally which subject it talks about, and to what extent.</li> </ul> <p><br>That extent is given by two scores, a PageRank score and a cosinus score (that were <strong>not</strong> calculated on our graph but during the X5GON project)</p> <p>A particularity of the Knowledge Graph is its heavy use of RDF reification, across large multi-valued properties.<br>Other versions of the same deposit can be found using different reification models:</p> <ul> <li><a href="https://zenodo.org/record/8108948">Named graphs</a></li> <li><a href="https://zenodo.org/record/8108963">Singleton properties</a></li> <li><a href="https://zenodo.org/record/8108971">RDF-star</a></li> </ul> <p>The Knowledge Graph also contains <a href="https://databus.dbpedia.org/dbpedia/generic/categories">categories</a> originating from DBpedia. They help precise the subjects that are also extracted from DBpedia.</p> <p>The deposit contains five types of files:</p> <ul> <li><strong>Authors_[</strong>X<strong>].nt</strong> - Those contain the authors' nodes, their type, and name.</li> <li><strong>ER_[</strong>X<strong>].nt</strong> - Those contain the educational resources and their information using standard reification.</li> <li><strong>categories_skos_[</strong>X<strong>].ttl</strong> - Those contain the hierarchy of DBpedia categories.</li> <li><strong>categories_labels.ttl </strong>- This file contains additional information about the categories.</li> <li><strong>categories_article.ttl</strong> - This file contains the RDF triples that link the DBpedia subjects to the DBpedia categories.</li> </ul>
Unethical amnesia and the moral licensing effect in children. Is there a connection?
<p>We used an experimental procedure to explore the moral amnesia and licensing effects, and the connection between the two in a sample of 354 children aged 8 to 11. Results suggested that a) in the <em>recent </em>condition, children remembered more details about positive or moral behaviors; b) in the <em>distant </em>condition, children remembered more accurately details about generally moral behaviors; c) children who recalled recent negative behaviors scored higher on altruism compared to participants who recalled recent moral and immoral behaviors. Overall, we found a significant association between children's memory of recent positive behaviors and altruism.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.