Abstract
A new method based on Domain Specific Language (DSL) approach to Deep Learning (DL) lifecycle data management tool support is presented: a very simple DL lifecycle data management tool, which however is usable in practice (it will be called Core tool) and a very advanced extension mechanism which in fact converts the Core tool into domain specific tool (DSL tool) building framework for DL lifecycle data management tasks. The extension mechanism will be based on the metamodel specialization approach to DSL modeling tools introduced by authors. The main idea of metamodel specialization is that we, at first, define the Universal Metamodel (UMM) for a domain and then for each use case define a Specialized Metamodel. But for use in our new domain the specialization concept will be extended: we add a functional specialization where invoking an additional custom program at appropriate points of Core tool is supported.
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Acknowledgements
The research was supported by ERDF project 1.1.1.1/18/A/045 at Institute of Mathematics and Computer Science, University of Latvia.
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Celms, E. et al. (2020). Towards DSL for DL Lifecycle Data Management. In: Robal, T., Haav, HM., Penjam, J., Matulevičius, R. (eds) Databases and Information Systems. DB&IS 2020. Communications in Computer and Information Science, vol 1243. Springer, Cham. https://doi.org/10.1007/978-3-030-57672-1_16
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