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

被引:2
|
作者
Khalajzadeh, Hourieh [1 ]
Simmons, Andrew J. [2 ]
Abdelrazek, Mohamed [3 ]
Grundy, John [1 ]
Hosking, John [4 ]
He, Qiang [5 ]
机构
[1] Monash Univ, Fac Informat Technol, Melbourne, Vic, Australia
[2] Deakin Univ, Appl Artificial Intelligence Inst A2I2, Melbourne, Vic, Australia
[3] Deakin Univ, Sch Informat Technol, Melbourne, Vic, Australia
[4] Univ Auckland, Fac Sci, Auckland, New Zealand
[5] Swinburne Univ, Sch Software & Elect Engn, Melbourne, Vic, Australia
基金
澳大利亚研究理事会;
关键词
big data analytics; domain-specific visual languages; BiDaML;
D O I
10.1109/vl/hcc50065.2020.9127196
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
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).
引用
收藏
页数:4
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