Conference
Challenges in Data Preservation for AI and ML Systems
| العنوان: | Challenges in Data Preservation for AI and ML Systems |
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| المؤلفون: | Tonkin, Emma L., Tourte, Gregory J. L. |
| المساهمون: | Klein, Maike, Krupka, Daniel, Winter, Cornelia, Gergeleit, Martin, Martin, Ludger |
| بيانات النشر: | Gesellschaft für Informatik e.V. |
| سنة النشر: | 2024 |
| مصطلحات موضوعية: | data preservation, data management, artificial intelligence, machine learning, best practices |
| الوصف: | The management and preservation of machine learning (ML) and artificial intelligence (AI) data is increasingly a concern for research institutions, as well as for institutions and industry organisations making use of this type of data and method. This paper summarises key issues in this area, presenting the case that there are significant benefits to the industry in developing best practices and joint standards in this area, and identifying the benefits of this approach, as well as highlighting risks and a current paucity of best practice in the area. |
| نوع الوثيقة: | conference object |
| وصف الملف: | application/pdf |
| اللغة: | English |
| Relation: | INFORMATIK 2024; Lecture Notes in Informatics (LNI) - Proceedings, Volume P-352; https://dl.gi.de/handle/20.500.12116/45197 |
| DOI: | 10.18420/inf2024_38 |
| الاتاحة: | https://dl.gi.de/handle/20.500.12116/45197 https://hdl.handle.net/20.500.12116/45197 https://doi.org/10.18420/inf2024_38 |
| رقم الانضمام: | edsbas.5F08575D |
| قاعدة البيانات: | BASE |
| DOI: | 10.18420/inf2024_38 |
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