Towards Semantic Data Management Plans for Efficient Review Processing and Automation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F24%3A00375870" target="_blank" >RIV/68407700:21240/24:00375870 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.5220/0012837900003756" target="_blank" >https://doi.org/10.5220/0012837900003756</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5220/0012837900003756" target="_blank" >10.5220/0012837900003756</a>
Alternative languages
Result language
angličtina
Original language name
Towards Semantic Data Management Plans for Efficient Review Processing and Automation
Original language description
In recent times, Data Management Planning has become increasingly crucial. Effective practices in data management ensure more precise data collection, secure storage, proper handling, and utilization beyond the primary project. However, existing DMPs often suffer from complex structures that impede accessibility for humans and machines. This project aims to address these challenges by converting DMPs into formats that are both machine-actionable and human-readable. Leveraging established DMP templates and relevant ontologies, our methodology involves analyzing diverse approaches to achieve this dual functionality. We assess machine-actionability through comparative evaluations using AI and NLP tools. Furthermore, we identify gaps in ontologies, laying the groundwork for future enhancements in this critical area of research.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 13th International Conference on Data Science, Technology and Applications
ISBN
978-989-758-707-8
ISSN
2184-285X
e-ISSN
2184-285X
Number of pages
8
Pages from-to
543-550
Publisher name
SciTePress
Place of publication
Madeira
Event location
Dijon
Event date
Jul 9, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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