End-user-oriented tool support for modeling data analytics requirements

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

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


Big data and analytics are increasingly used in different domains to gain insights and to improve decision-making. Developing big data analytics solutions is a complex task involving multidisciplinary teams and users-with no data science and programming background-to professional data scientists and software engineers. Different stakeholders work with a variety of data types, tasks and concepts in different languages from high-level domain concepts to low level programming languages and technical concepts. In order to advance the level of abstraction beyond low-level data analysis technical details, we demonstrate our BiDaML tool. BiDaML brings all stakeholders around one tool to specify, model and document their big data applications using a novel set of domain-specific visual languages (DSVLs).

Original languageEnglish
Title of host publicationProceedings - 2020 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), VL/HCC 2020
EditorsMichael Homer, Felienne Hermans, Steven Tanimoto, Craig Anslow
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages4
ISBN (Electronic)9781728169019
ISBN (Print)9781728169026
Publication statusPublished - 2020
EventIEEE Symposium on Visual Languages and Human-Centric Computing 2020 - Virtual, Dunedin, New Zealand
Duration: 10 Aug 202014 Aug 2020
https://ieeexplore-ieee-org.ezproxy.lib.monash.edu.au/xpl/conhome/9124617/proceeding (Proceedings)
https://conf.researchr.org/home/vlhcc2020 (Website)

Publication series

NameProceedings of IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC
PublisherInstitute of Electrical and Electronics Engineers, Inc.
ISSN (Print)1943-6092
ISSN (Electronic)1943-6106


ConferenceIEEE Symposium on Visual Languages and Human-Centric Computing 2020
Abbreviated titleVL/HCC 2020
CountryNew Zealand
Internet address


  • BiDaML
  • big data analytics
  • domain-specific visual languages

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