Frontiers of Data and Computing ›› 2021, Vol. 3 ›› Issue (2): 39-49.doi: 10.11871/jfdc.issn.2096-742X.2021.02.005

• Special Issue: Management Decision and Intelligent Applications • Previous Articles     Next Articles

New ARP: A Data-Driven Exploration for Application Innovation on CAS Management System

YU Jianjun(),LIAO Fangyu(),ZHOU Xiaojun(),SUN Jianying()   

  1. Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China
  • Received:2021-02-28 Online:2021-04-20 Published:2021-05-18
  • Contact: YU Jianjun E-mail:yujj@cnic.ac.cn;fyliao@cnic.cn;xjzhou@cnic.cn;jysun@cnic.cn

Abstract:

[Background] Using big-data technologies to improve the modernization level of national governance is a very important strategy of China. CAS is continuously developing a data-driven management system to explore modern ways for technological innovation. [Methods] Since 2002, CAS has been working on development of the ARP (Academia Resource Planning) system, which is an cross-disciplinary effort between computer science and management science, and plays an important role in management innovation. [Results] The New ARP has covered the main functions of common business and applications for CAS institutions through re-factoring the whole system, especially during the span of the 13th Five-Year Plan. It combines the business-driven mode with the data-driven mode using the big-data technologies, and furthermore, it emphasizes data governance and application innovation, which can be characterized by the following features: (1) Besides usage by the management personnel, it does care about front-line researchers, and constructs a service-oriented architecture with “service-management-decision support”. (2) It simplifies the work flow and improves work efficiency. (3) The separation of front- and back-end services focuses on professional ability of business logic, and keeps the balance between the business complexity and ease of operation through work-flow governance. (4) Data assets becomes one of the core objects which would be widely used in decision-support, value-added services, big data analysis, and data sharing.

Key words: scientific research management system, data-driven, governance innovation, decision support system