Visual languages for supporting Big Data Analytics Development

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

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

4 Citations (Scopus)


We present BiDaML (Big Data Analytics Modeling Languages), an integrated suite of visual languages and supporting tool to help end-users with the engineering of big data analytics solutions. BiDaML, our visual notations suite, comprises six diagrammatic notations: brainstorming diagram, process diagram, technique diagrams, data diagrams, output diagrams and deployment diagram. BiDaML tool provides a platform for efficiently producing BiDaML visual models and facilitating their design, creation, code generation and integration with other tools. To demonstrate the utility of BiDaML, we illustrate our approach with a realworld example of traffic data analysis. We evaluate BiDaML using two types of evaluations, the physics of notations and a cognitive walkthrough with several target end-users e.g. data scientists and software engineers.

Original languageEnglish
Title of host publicationProceedings of the 15th International Conference on Evaluation of Novel Approaches to Software Engineering
EditorsRaian Ali, Hermann Kaindl, Leszek Maciaszek
Place of PublicationSetubal Portugal
Number of pages12
ISBN (Electronic)9789897584213
Publication statusPublished - 2020
EventInternational Conference on Evaluation of Novel Approaches to Software Engineering 2020 - Virtual, Prague, Czech Republic
Duration: 5 May 20206 May 2020
Conference number: 15th (Website) (Proceedings)


ConferenceInternational Conference on Evaluation of Novel Approaches to Software Engineering 2020
Abbreviated titleENASE 2020
Country/TerritoryCzech Republic
Internet address


  • Big Data Analytics
  • Big Data Modeling
  • Big Data Toolkits
  • Domain Specific Visual Languages
  • End-user Tools

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