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End-User-Oriented Tool Support for Modeling Data Analytics Requirements

Version 2 2024-06-04, 13:05
Version 1 2020-09-04, 12:53
conference contribution
posted on 2024-06-04, 13:05 authored by Hourieh KhalajzadehHourieh Khalajzadeh, Andrew J Simmons, Mohamed AbdelrazekMohamed Abdelrazek, John Grundy, John Hosking, Qiang He
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).

History

Pagination

1-4

Location

Online

Start date

2020-08-10

End date

2020-08-14

ISBN-13

978-1-7281-6901-9

Language

eng

Publication classification

E1 Full written paper - refereed

Title of proceedings

VL/HCC 2020 : Proceedings of the IEEE Symposium on Visual Languages and Human-Centric Computing

Event

2020 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)

Publisher

IEEE

Place of publication

Piscataway, N.J.

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