BiDaML: a suite of visual languages for supporting end-user data analytics

Hourieh Khalajzadeh, Mohamed Abdelrazek, John Grundy, John Hosking, Qiang He

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

16 Citations (Scopus)


We introduce Big Data Analytics Modeling Languages (BiDaML), a novel integrated suite of visual languages aimed at supporting end users during the process of designing big data analytics solutions. BiDaML comprises five diagrammatic notations: A data analytics brainstorming diagram; a process diagram; technique diagrams; data diagrams; and output diagrams. Tool support in the form of an integrated design environment for creating BiDaML diagrams has also been developed. To demonstrate the utility of BiDaML, we illustrate our approach with a real-world example of property price prediction and evaluate BiDaML using the physics of notations and cognitive walkthroughs with target end users-data scientists and software engineers.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE International Congress on Big Data
EditorsElisa Bertino, Carl K. Chang, Peter Chen, Ernesto Damiani, Michael Goul, Katsunori Oyama
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages5
ISBN (Electronic)9781728127729
Publication statusPublished - 2019
EventIEEE International Congress on Big Data 2019 - Milan, Italy
Duration: 8 Jul 201913 Jul 2019!/toc/7 (Proceedings)


ConferenceIEEE International Congress on Big Data 2019
Abbreviated titleBigData Congress 2019
Internet address


  • big data analytics
  • big data modeling
  • big data toolkits
  • domain specific visual languages
  • end user tools

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