Exploration and Practice of Big Data Introductory Courses for Big Data Management and Application Majors

As an introductory course for the emerging major of big data management and application,“Introduction to Big Data”has not yet formed a curriculum standard and implementation plan that is widely accepted and used by everyone.To this end,we discuss some of our explorations and attempts in the construction and teaching process of big data courses for the major of big data management and application from the perspective of course planning,course implementation,and course summary.After interviews with students and feedback from questionnaires,students are highly satisfied with some of the teaching measures and programs currently adopted.

Big data management in the mining industry

The mining industry faces a number of challenges that promote the adoption of new technologies.Big data,which is driven by the accelerating progress of information and communication technology,is one of the promising technologies that can reshape the entire mining landscape.Despite numerous attempts to apply big data in the mining industry,fundamental problems of big data,especially big data management(BDM),in the mining industry persist.This paper aims to fill the gap by presenting the basics of BDM.This work provides a brief introduction to big data and BDM,and it discusses the challenges encountered by the mining industry to indicate the necessity of implementing big data.It also summarizes data sources in the mining industry and presents the potential benefits of big data to the mining industry.This work also envisions a future in which a global database project is established and big data is used together with other technologies(i.e.,automation),supported by government policies and following international standards.This paper also outlines the precautions for the utilization of BDM in the mining industry.

Big spatial vector data management: a review

Spatial vector data with high-precision and wide-coverage has exploded globally,such as land cover,social media,and other data-sets,which provides a good opportunity to enhance the national macroscopic decision-making,social supervision,public services,and emergency capabilities.Simultaneously,it also brings great challenges in management technology for big spatial vector data(BSVD).In recent years,a large number of new concepts,parallel algorithms,processing tools,platforms,and applications have been proposed and developed to improve the value of BSVD from both academia and industry.To better understand BSVD and take advantage of its value effectively,this paper presents a review that surveys recent studies and research work in the data management field for BSVD.In this paper,we discuss and itemize this topic from three aspects according to different information technical levels of big spatial vector data management.It aims to help interested readers to learn about the latest research advances and choose the most suitable big data technologies and approaches depending on their system architectures.To support them more fully,firstly,we identify new concepts and ideas from numerous scholars about geographic information system to focus on BSVD scope in the big data era.Then,we conclude systematically not only the most recent published literatures but also a global view of main spatial technologies of BSVD,including data storage and organization,spatial index,processing methods,and spatial analysis.Finally,based on the above commentary and related work,several opportunities and challenges are listed as the future research interests and directions for reference.