64817

Автор(ы): 

Автор(ов): 

2

Параметры публикации

Тип публикации: 

Доклад

Название: 

On Big Data-Driven Digital Ecosystem Framework for Railway Reporting

ISBN/ISSN: 

978-3-902734-29-7, 1726-9679

DOI: 

10.2507/31st.daaam.proceedings.070

Наименование конференции: 

  • 31st DAAAM International Symposium on Intelligent Manufacturing and Automayion

Наименование источника: 

  • Proceedings of the 31st DAAAM International Symposium on Intelligent Manufacturing and Automayion

Город: 

  • Vienna, Austria

Издательство: 

  • ACCESS

Год издания: 

2020

Страницы: 

0499-0509, https://www.daaam.info/Downloads/Pdfs/proceedings/proceedings_2020/070.pdf
Аннотация
In our application research, we propose a Digital Ecosystem approach to overcome data integration, orchestration and quality challenges in railway reporting system using Big Data technologies. We are building a Digital Ecosystem Framework consisting of different Agents, where each Agent is an essential part of the Railway Reporting Management System. In this work, we address different problems in building digital ecosystem including integration problems, orchestration problems and data quality problems. We present a proprietary solution called the Digital Ecosystem Reporting Framework (DERF) for building robust, reliable, fault-tolerant, scalable and high-loaded data pipelines of the Railway Reporting Management System based on Big Data technologies. DERF integrates different Digital Agents such as main ETL-pipeline Agents, technical data quality Agents, business data quality Agents, BI-services integration Agents and high-level data orchestration Agent. A test implementation of DERF has been performed for Railway Reporting Management System using KPI reporting data of the real Railway company.

Библиографическая ссылка: 

Сулейкин А.С., Панфилов П. On Big Data-Driven Digital Ecosystem Framework for Railway Reporting / Proceedings of the 31st DAAAM International Symposium on Intelligent Manufacturing and Automayion. Vienna, Austria: ACCESS, 2020. С. 0499-0509, https://www.daaam.info/Downloads/Pdfs/proceedings/proceedings_2020/070.pdf.