BiDaML in practice: collaborative modeling of Big Data Analytics application requirements

Hourieh Khalajzadeh, Andrew J. Simmons, Tarun Verma, Mohamed Abdelrazek, John Grundy, John Hosking, Qiang He, Prasanna Ratnakanthan, Adil Zia, Meng Law

Research output: Chapter in Book/Report/Conference proceedingConference PaperOther

Abstract

Using data analytics to improve industrial planning and operations has become increasingly popular and data scientists are more and more in demand. However, complex data analytics-based software development is challenging. It involves many new roles lacking in traditional software engineering teams – e.g. data scientists and data engineers; use of sophisticated machine learning (ML) approaches replacing many programming tasks; uncertainty inherent in the models; as well as interfacing with models to fulfill software functionalities. These challenges make communication and collaboration within the team and with external stakeholders challenging. In this paper, we describe our experiences in applying our BiDaML (Big Data Analytics Modeling Languages) approach to several large-scale industrial projects. We used our BiDaML modeling toolset that brings all stakeholders around one tool to specify, model and document their big data applications. We report our experience in using and evaluating this tool on three real-world, large-scale applications with teams from: realas.com – a property price prediction website for home buyers; VicRoads – a project seeking to build a digital twin (simulated model) of Victoria’s transport network updated in real-time by a stream of sensor data from inductive loop detectors at traffic intersections; and the Alfred Hospital – Intracranial hemorrhage (ICH) prediction through Computed Tomography (CT) Scans. These show that our approach successfully supports complex data analytics software development in industrial settings.

Original languageEnglish
Title of host publicationEvaluation of Novel Approaches to Software Engineering
Subtitle of host publication15th International Conference, ENASE 2020 Prague, Czech Republic, May 5–6, 2020 Revised Selected Papers
EditorsRaian Ali, Hermann Kaindl, Leszek A. Maciaszek
Place of PublicationCham Switzerland
PublisherSpringer
Pages106-129
Number of pages24
ISBN (Electronic)9783030700065
ISBN (Print)9783030700058
DOIs
Publication statusPublished - 2021
EventInternational Conference on Evaluation of Novel Approaches to Software Engineering 2020 - Virtual, Prague, Czech Republic
Duration: 5 May 20206 May 2020
Conference number: 15th
https://web.archive.org/web/20191218164753/http://www.enase.org/ (Website)
https://www.scitepress.org/ProceedingsDetails.aspx?ID=58GseuYgkNA=&t=1 (Proceedings)
https://link.springer.com/book/10.1007/978-3-030-70006-5

Publication series

NameCommunications in Computer and Information Science
PublisherSpringer
Volume1375
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

ConferenceInternational Conference on Evaluation of Novel Approaches to Software Engineering 2020
Abbreviated titleENASE 2020
CountryCzech Republic
CityPrague
Period5/05/206/05/20
Internet address

Keywords

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

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