Spring Boot based REST API to Improve Data Quality Report Generation for Big Scientific Data: ARM Data Center Example

被引:0
|
作者
Guntupally, Kavya [1 ]
Devarakonda, Ranjeet [1 ]
Kehoe, Kenneth [2 ]
机构
[1] Oak Ridge Natl Lab, Div Environm Sci, Oak Ridge, TN 37830 USA
[2] Univ Oklahoma, Norman, OK 73019 USA
关键词
auto configuration; CRUD; !text type='java']java[!/text] framework; service; oriented architecture; REST; spring boot;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Web application technologies are growing rapidly with continuous innovation and improvements. This paper focuses on the popular Spring Boot [1] java-based framework for building web and enterprise applications and how it provides the flexibility for service-oriented architecture (SOA). One challenge with any Spring-based applications is its level of complexity with configurations. Spring Boot makes it easy to create and deploy stand-alone, production-grade Spring applications with very little Spring configuration. Example, if we consider Spring Model-View-Controller (MVC) framework [2], we need to configure dispatcher servlet, web jars, a view resolver, and component scan among other things. To solve this, Spring Boot provides several Auto Configuration options to setup the application with any needed dependencies. Another challenge is to identify the framework dependencies and associated library versions required to develop a web application. Spring Boot offers simpler dependency management by using a comprehensive, but flexible, framework and the associated libraries in one single dependency, which provides all the Spring related technology that you need for starter projects as compared to CRUD web applications. This framework provides a range of additional features that are common across many projects such as embedded server, security, metrics, health checks, and externalized configuration. Web applications are generally packaged as war and deployed to a web server, but Spring Boot application can be packaged either as war or jar file, which allows to run the application without the need to install and/or configure on the application server. In this paper, we discuss how Atmospheric Radiation Measurement (ARM) Data Center (ADC) at Oak Ridge National Laboratory, is using Spring Boot to create a SOA based REST [4] service API, that bridges the gap between frontend user interfaces and backend database. Using this REST service API, ARM scientists are now able to submit reports via a user form or a command line interface, which captures the same data quality or other important information about ARM data.
引用
收藏
页码:5328 / 5329
页数:2
相关论文
共 50 条
  • [1] Next-Gen Tools for Big Scientific Data: ARM Data Center Example
    Devarakonda, Ranjeet
    Dumas, Kyle
    Beus, Sheman
    Rush, Everett
    Krishna, Bhargavi
    Records, Rob
    Prakash, Giri
    2016 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2016, : 3968 - 3970
  • [2] Big Federal Data Centers Implementing FAIR Data Principles: ARM Data Center Example
    Devarakonda, Ranjeet
    Prakash, Girl
    Guntupally, Kavya
    Kumar, Jitendra
    2019 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2019, : 6033 - 6036
  • [3] The geospatial data quality REST API for primary biodiversity data
    Otegui, Javier
    Guralnick, Robert P.
    BIOINFORMATICS, 2016, 32 (11) : 1755 - 1757
  • [4] Can big data improve firm decision quality? The role of data quality and data diagnosticity
    Ghasemaghaei, Maryam
    Calic, Goran
    DECISION SUPPORT SYSTEMS, 2019, 120 : 38 - 49
  • [5] An Improve The Quality Of Data Considering Big Data Aspect Based On Sensitive Of Cost Time
    Mohammad, Banan
    Alzyadat, Wael
    Al-Fayoumi, Mohammad
    Hawi, Ruba E. L.
    AyshAlhroob
    2021 7TH INTERNATIONAL CONFERENCE ON ENGINEERING AND EMERGING TECHNOLOGIES (ICEET 2021), 2021, : 329 - 334
  • [6] An Approach to Improve Data Quality from Big Data Aspect by Sensitive Cost and Time
    Mohammad, Banan
    Alzyadat, Wael
    Al-Fayoumi, Mohammad
    El Hawi, Ruba
    Alhroob, Aysh
    2020 11TH INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION SYSTEMS (ICICS), 2020, : 022 - 026
  • [7] Air quality data analysis and forecasting platform based on big data
    Wang, Jinghan
    Zhang, Jinnan
    Yuan, XueGuang
    Tang, Yu
    Hao, Hongyu
    Zuo, Yong
    Tan, Zebin
    Qiao, Min
    Cao, Yang Hua
    Ai, Lingmei
    Wan, Yihang
    Chen, Hao
    2019 CHINESE AUTOMATION CONGRESS (CAC2019), 2019, : 2042 - 2046
  • [8] Data Mining on the Flight Quality of an Airline based on QAR Big Data
    Wang, Xin
    Zhao, Xinbin
    Yu, Liling
    PROCEEDINGS OF 2020 IEEE 2ND INTERNATIONAL CONFERENCE ON CIVIL AVIATION SAFETY AND INFORMATION TECHNOLOGY (ICCASIT), 2020, : 955 - 958
  • [9] Big Data Market Optimization Pricing Model Based on Data Quality
    Yang, Jian
    Zhao, Chongchong
    Xing, Chunxiao
    COMPLEXITY, 2019, 2019
  • [10] A Big Data Security Architecture Based on Blockchain and Trusted Data Cloud Center
    Qin, Peng
    Li, Wei
    Ding, Ke
    WIRELESS COMMUNICATIONS & MOBILE COMPUTING, 2022, 2022