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9 results for “discoverability”
45 Vulnerability Discoverability Timelines from the 2019 Collegiate Penetration Testing Competition
<p><em><strong>Description</strong></em></p> <p>This is a collection of manually curated timelines from the 2019 Collegiate Penetration Testing Competition (CPTC). Collection and annotation are described in detail in this publication:</p> <ul> <li>Benjamin S. Meyers, Sultan Fahad Almassari, Brandon N. Keller, and Andrew Meneely. Examining Penetration Tester Behavior in the Collegiate Penetration Testing Competition. Forthcoming at Transactions on Software Engineering and Methodology. https://dl.acm.org/doi/10.1145/3514040</li> </ul> <p><em><strong>Included Files</strong></em></p> <ul> <li><strong><em>2019_cptc_timelines.csv</em>:</strong> Completed timelines for ten teams from the 2019 CPTC nationals competition.</li> <li><strong><em>2019_cptc_timeline_columns.csv</em>:</strong> Descriptions of the columns in <strong><em>2019_cptc_</em></strong><em><strong>timelines.csv</strong></em>.</li> <li><strong><em>2019_cptc_vulnerabilities.csv</em>:</strong> Brief vulnerability descriptions and CWE mappings.</li> </ul> <p><em><strong>Other Resources</strong></em></p> <ul> <li>Complete Splunk log data dumps are available <a href="http://mirrors.rit.edu/cptc/2019/mirrors/nationals/">here</a>. These must be ingested and viewed with a Splunk instance.</li> <li>To request access to the CPTC team reports, please contact Brock Wagehoft (<a href="mailto:bew1127@rit.edu">email</a>).</li> </ul> <p><em><strong>Contact</strong></em></p> <p>Please contact Benjamin S. Meyers (<a href="mailto:bsm9339@rit.edu">email</a>) with questions about this data and its collection.</p> <p><em><strong>Acknowledgments</strong></em></p> <p>Collection of this data has been sponsored in part by the National Science Foundation grant 1922169, and by a Department of Defense DARPA SBIR program (grant 140D63-19-C-0018).</p>
Supporting dataset for: Repository optimisation & techniques to improve discoverability and web impact : an evaluation
<p>This dataset supports the working paper, "Repository optimisation & techniques to improve discoverability and web impact : an evaluation", currently under review for publication and available as a preprint at: <a href="https://doi.org/10.17868/65389/">https://doi.org/10.17868/65389/</a>. </p> <ul> <li>Macgregor, G. (2018). <em>Repository optimisation techniques to improve discoverability and web impact: an evaluation</em>. (pp. 1-13). Glasgow: University of Strathclyde [Strathprints repository]. Available: <a href="https://doi.org/10.17868/65389/">https://doi.org/10.17868/65389/</a></li> </ul> <p>The dataset comprises a single OpenDocument Spreadsheet (.ods) format file containing seven data sheets of data pertaining to COUNTER compliant usage statistics, search query traffic from Google Search Console, web traffic data for Google Analytics and Google Scholar, and usage statistics from IRStats2. All data relate to the EPrints repository, Strathprints, based at the University of Strathclyde.</p>
Demonstration record for discoverable IPCC WGIII data
<p>This is a record used to demonstrate the concept of discoverable data for IPCC AR7 WGIII.</p>
Supporting dataset for: Reviewing repository discoverability: approaches to improving repository visibility and web impact
<p>This dataset supports the conference poster, "<a href="http://strathprints.strath.ac.uk/61333/">Reviewing repository discoverability: approaches to improving repository visibility and web impact</a>", presented at the Repository Fringe 2017 conference at the University of Edinburgh.</p> <p>The dataset comprises a single OpenDocument Spreadsheet (.ods) format file containing six data sheets of data pertaining to COUNTER compliant usage statistics, search query traffic from Google Search Console, web traffic data for Google Analytics and usage statistics from IRStats2. All data relate to the EPrints repository, <a href="http://strathprints.strath.ac.uk/">Strathprints</a>, based at the University of Strathclyde.</p> <p></p>
Don't mention it: challenges to using software mentions to investigate citation and discoverability - Data and Notebooks
<p>This deposit contains the data and Jupyter notebooks used for sampling and annotation analysis of our submission to the PeerJ Computer Science special issue <em>Software Citation, Indexing, and Discoverability </em>(<a href="https://peerj.com/collections/84-software">https://peerj.com/collections/84-software</a>):</p> <blockquote> <p>Stephan Druskat, Neil P. Chue Hong, Sammie Buzzard, Olexandr Konovalov, and Patrick Kornek. Don’t mention it: challenges to using software mentions to investigate citation and discoverability.</p> </blockquote> <p>See the README in this deposit.</p> <p>The contents of this deposit can also be browsed at <a href="https://github.com/softwaresaved/habeas-corpus/tree/main/replication-package">https://github.com/softwaresaved/habeas-corpus/tree/main/replication-package</a>.</p>
Proteome Discoverer IR E. coli, D. radiodurans, and H. Sapiens result files
<p>File containing all of the Proteome Discoverer result files available with the publication "<strong>Ionizing radiation-induced proteomic oxidation in <em>Escherichia coli."</em></strong></p>
Artifact: VISON: An Ontology-Based Approach for Software Visualization Tool Discoverability
<p>VISON an ontology that captures the semantics of software visualizations through concepts and relationships. The artifact has been submitted to VISSOFT'19 to support the results reported on our full paper "VISON: An Ontology-Based Approach for Software Visualization Tool Discoverability".</p>
Trait selection strategy in multi-trait GWAS: Boosting SNPs discoverability
<p>Dataset used during the study "Trait selection strategy in multi-trait GWAS: Boosting SNPs discoverability"</p>
On the Discoverability of npm Vulnerabilities in Node.js Projects
<p>This package contains the material used in the manuscript.</p> <p>For more information on how to understand the package structure, please read the README.md.</p> <p> </p>
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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.