An end-to-end model-based approach to support big data analytics development

Hourieh Khalajzadeh, Andrew J. Simmons, Mohamed Almorsy Abdelrazek, John Grundy, John Hosking, Qiang He

Research output: Contribution to journalArticleResearchpeer-review


We present BiDaML 2.0, an integrated suite of visual languages and supporting tool to help multidisciplinary teams with the design of big data analytics solutions. BiDaML tool support provides a platform for efficiently producing BiDaML diagrams and facilitating their design, creation, report and code generation. We evaluated BiDaML using two types of evaluations, a theoretical analysis using the “physics of notations”, and an empirical study with 1) a group of 12 target end-users and 2) five individual end-users. Participants mostly agreed that BiDaML was straightforward to understand/learn, and prefer BiDaML for supporting complex data analytics solution modeling than other modeling languages.

Original languageEnglish
Article number100964
Number of pages20
JournalJournal of Computer Languages
Publication statusPublished - Jun 2020


  • Big data analytics
  • Big data modeling
  • Big data toolkits
  • Domain-specific visual languages
  • End-user tools
  • Multidisciplinary teams

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