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Towards dsl for dl lifecycle data management

  • Edgars Celms*
  • , Jānis Visvaldis Bārzdiņš
  • , Audris Kalniņš
  • , Artūrs Sproģis
  • , Mikus Grasmanis
  • , Sergejs Rikačovs
  • , Paulis Barzdins
  • *Corresponding author for this work
  • Innovation Labs LETA
  • University of Latvia

Research output: Chapter in Book/Report/Conference proceedingConference paperResearchpeer-review

2 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationDatabases and Information Systems - 14th International Baltic Conference, DB and IS 2020, Proceedings
EditorsTarmo Robal, Hele-Mai Haav, Jaan Penjam, Raimundas Matulevicius
Pages205-218
Volume1243 CCIS
DOIs
Publication statusPublished - 2020

Publication series

NameCommunications in Computer and Information Science
Volume1243 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Keywords

  • DL
  • DL lifecycle data management
  • DSL
  • Metamodel specialization

OECD Field of Science

  • 1.2 Computer and Information Sciences

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