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| 78 | + <h2>Project Tools</h2> |
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| 85 | + <h3>Autocodemeta</h3> |
| 86 | + <p>A web-based application designed to simplify the creation of standardized software descriptions by automatically pulling data |
| 87 | + from repository URLs to generate a codemeta.json file. It allows users to input a link from platforms like GitHub or GitLab |
| 88 | + and then uses that information to populate mandatory and optional fields, such as license details, funding sources, and author |
| 89 | + information.</p> |
| 90 | + <p><a href="https://autocodemeta.linkeddata.es/">Link to the tool</a></p> |
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| 95 | + <div class="user-frame" style="margin-bottom: 30px;"> |
| 96 | + <h3>sw-metadata-bot</h3> |
| 97 | + <p>This is the bot that complement the tool <a href="https://github.com/SoftwareUnderstanding/RsMetaCheck">RsMetaCheck</a>, it pushes issues |
| 98 | + to the repository with reports generated by RsMetaCheck with pitfalls like missing license details, alongside suggestions to |
| 99 | + let the creators know what needs to be updated. This keep the project's documentation clear and reliable so that it can be used |
| 100 | + without running into errors caused by outdated or missing information.</p> |
| 101 | + <p><a href="https://github.com/SoftwareUnderstanding/sw-metadata-bot">Link to the tool</a></p> |
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| 108 | + <div class="user-frame" style="margin-bottom: 30px;"> |
| 109 | + <h3>RSMetacheck</h3> |
| 110 | + <p> This project provides an automated tool for detecting common metadata quality issues (pitfalls & Warnings) in software repositories. |
| 111 | + The tool analyzes <a href="https://github.com/KnowledgeCaptureAndDiscovery/somef">SoMEF</a> (Software Metadata Extraction Framework) |
| 112 | + output files to identify 29 different types of metadata quality issues across multiple programming languages. </p> |
| 113 | + <p><a href="https://github.com/SoftwareUnderstanding/RsMetaCheck">Link to the tool</a></p> |
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| 116 | + |
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| 118 | + <div class="user-frame" style="margin-bottom: 30px;"> |
| 119 | + <h3>SoMEF</h3> |
| 120 | + <p>Command-line tool that uses machine learning and regular expressions to automatically extract extensive metadata from a project's |
| 121 | + documentation and configuration files. It scans files to identify technical details such as installation |
| 122 | + instructions, as well as metadata like citation preferences. |
| 123 | + It is designed to help build knowledge graphs of scientific software, making it easier to understand the |
| 124 | + requirements and functions of codebases.</p> |
| 125 | + <p><a href="https://github.com/KnowledgeCaptureAndDiscovery/somef">Link to the tool</a></p> |
| 126 | + </div> |
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| 151 | + <p class="acknowledgment"> |
| 152 | + The authors acknowledge the OSCARS project, which has received funding from the European Commission's Horizon Europe Research and Innovation programme under grant agreement No. 101129751 |
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