A Review of the Status and Development Strategies of Computer Science and Technology Under the Background of Big Data

This article discusses the current status and development strategies of computer science and technology in the context of big data.Firstly,it explains the relationship between big data and computer science and technology,focusing on analyzing the current application status of computer science and technology in big data,including data storage,data processing,and data analysis.Then,it proposes development strategies for big data processing.Computer science and technology play a vital role in big data processing by providing strong technical support.

Big Data and Data Science:Opportunities and Challenges of iSchools

Due to the recent explosion of big data, our society has been rapidly going through digital transformation and entering a new world with numerous eye-opening developments. These new trends impact the society and future jobs, and thus student careers. At the heart of this digital transformation is data science, the discipline that makes sense of big data. With many rapidly emerging digital challenges ahead of us, this article discusses perspectives on iSchools＇ opportunities and suggestions in data science education. We argue that iSchools should empower their students with ＂information computing＂ disciplines, which we define as the ability to solve problems and create values, information, and knowledge using tools in application domains. As specific approaches to enforcing information computing disciplines in data science education, we suggest the three foci of user-based, tool-based, and application- based. These three loci will serve to differentiate the data science education of iSchools from that of computer science or business schools. We present a layered Data Science Education Framework （DSEF） with building blocks that include the three pillars of data science （people, technology, and data）, computational thinking, data-driven paradigms, and data science lifecycles. Data science courses built on the top of this framework should thus be executed with user-based, tool-based, and application-based approaches. This framework will help our students think about data science problems from the big picture perspective and foster appropriate problem-solving skills in conjunction with broad perspectives of data science lifecycles. We hope the DSEF discussed in this article will help fellow iSchools in their design of new data science curricula.

Big Metadata,Smart Metadata,and Metadata Capital:Toward Greater Synergy Between Data Science and Metadata

Purpose： The purpose of the paper is to provide a framework for addressing the disconnect between metadata and data science. Data science cannot progress without metadata research.This paper takes steps toward advancing the synergy between metadata and data science, and identifies pathways for developing a more cohesive metadata research agenda in data science. Design/methodology/approach： This paper identifies factors that challenge metadata research in the digital ecosystem, defines metadata and data science, and presents the concepts big metadata, smart metadata, and metadata capital as part of a metadata lingua franca connecting to data science. Findings： The ＂utilitarian nature＂ and ＂historical and traditional views＂ of metadata are identified as two intersecting factors that have inhibited metadata research. Big metadata, smart metadata, and metadata capital are presented as part ofa metadata linguafranca to help frame research in the data science research space. Research limitations： There are additional, intersecting factors to consider that likely inhibit metadata research, and other significant metadata concepts to explore. Practical implications： The immediate contribution of this work is that it may elicit response, critique, revision, or, more significantly, motivate research. The work presented can encourage more researchers to consider the significance of metadata as a research worthy topic within data science and the larger digital ecosystem. Originality/value： Although metadata research has not kept pace with other data science topics, there is little attention directed to this problem. This is surprising, given that metadata is essential for data science endeavors. This examination synthesizes original and prior scholarship to provide new grounding for metadata research in data science.

Demonstration and Radiation Extension mode of Agricultural Technology——A Case of the Science and Technology Project of High Yield in Hebei Province

Firstly,relying on the science and technology project of high yield in Hebei Province,connotation of agricultural technology demonstration and extension mode and the high yield grain project in Hebei Province is introduced.Extension mode of agricultural technology demonstration and radiation is constructed.Agricultural technology demonstration and radiation mode includes the radiation center,primary irradiation and secondary irradiation.Secondly,management system and operational mechanism of agricultural technology demonstration and radiation mode are discussed,mainly expressed in establishing leading group in each demonstration county(city),carrying out leader contract responsibility system,establishing expert advisor steering group and setting up core experts group for subject,establishing technical experts group for subject,setting up leading group in the radiation area,carrying out chief expert responsibility system and technician matrix responsibility system,establishing the operating mechanism of "open,flow,competition and collaboration" with "test area-expert two-way selection" as the core content.Finally,countermeasures to improve the agricultural technology demonstration and radiation mode is put forward,such as establishing the rural technology demonstration base,strengthening cooperation with enterprises,and adopting flexible technical training,so as to promote the spread of agricultural high-tech,to increase the contribution rate of agricultural technology,and to offer ideas for agricultural technology extension model at the new era.

Study on Growth Laws of Marine Science and Technology Talents Based on the Perspective of Big Data

Based on the perspective of big data,the growth characteristics of marine science and technology talents were analyzed,and the growth of marine science and technology talents was divided into five periods:study period,adaptation period,growth period,promotion period and stability period.Moreover,some suggestions for the training of marine science and technology talents were proposed from the aspects of students,families,schools and society.

Performance Evaluation Management and Meta-norm Execution Cost of Major Science and Technology Project

Major science and technology project generally got high social expectations as a result of harge investment.To ensure that the science and technology teams follow the norms of S&T research and make full use of the investment,the effective norms maintenance mechanism must be established which includes punishment for violators and burnout of teams of supervisors,namely setting up the meta-norm execution mechanism.It is very important to establish the effective major science and technology project evaluation system to reduce the norm and metanorm execution cost.In this paper,the principles,methods and implementation system guarantee of evaluation system building are studied as well.

人工智能背景下Materials Project数据库在计算材料学课程教学中的应用

该文探讨了在人工智能背景下,Materials Project数据库在计算材料学课程教学中的应用和影响。Materials Project数据库是一个集成了AI和大数据技术的开放获取的材料库,能为学生提供海量的材料晶体结构和物性数据,使教学内容更为丰富,让学生能通过亲自操作获取和分析数据,深入理解微观结构与物性之间的关系。这一新兴的教学模式不仅提升了学生的科研能力和创新思维能力,还有助于培养具备计算材料专业知识和多学科交叉的复合型人才。总体来说,人工智能时代下,大数据的引入为计算材料学课程带来新的活力,并对未来教育改革和实践产生了积极影响。

Construction and Practice of Cloud-based Experiment and Innovation Project Supporting Platform for Computer Science Education

Higher and more requirements on experiments and innovation projects of computer science courses is brought forward to promote the "Double First Class". For these requirements, the cloud-based experiment and innovation project supporting platform is introduced in this paper. On the one hand, the platform could satisfy the diversified resource requirements of both teachers and students in course experiments and innovation projects. On the other hand, the feature of "construct once and access anywhere" could achieve higher resource utilization rate and lower costs than the traditional "lab-based" experiment mode. The supporting platform has been applied to practice and gains a lot of positive feedbacks.

The Impact of Online Networks and Big Data in Life Sciences

Advances in Information Technology (IT) have enhanced our ability to gather, collect and analyze information from individuals and specific groups of people online. The emergence of online networks has facilitated connections between individuals by leveraging data exchange in a variety of fields. Online networking in life sciences transforms data collection into actionable information that will improve individual and population health, deliver effective therapies and, consequently, reduce the cost of healthcare. These novel tools might also have a direct impact in personalized medicine programs, since the adoption of new products by health care professionals in life sciences and peer-to-peer learning could be improved using social networks and big data analytics. However, one of the main concerns of information exchange online is data privacy. In this article, we will review how online networks and big data analytics are impacting the life sciences sector.

Designing a Citizen Science Project for Forest Landscapes: A Case from Hofmann Forest in Eastern North Carolina

Citizen science is a participatory research design that utilizes both non-professional researchers and professional researchers to collect, analyze, and disperse data. Citizen scientists seek to discover answers and draw solutions to scientific questions. The Hofmann Open Water Laboratory (HOWL) project, established in 2016, focuses its collaborative-based efforts in eastern North Carolina. HOWL citizen scientists monitor water quality, and quantity, that flows on and off the Hofmann Forest. HOWL provides opportunities to citizen scientists and gathers data to meet the project outcomes, which include understanding the importance of Hofmann Forest in the inner coastal plain of North Carolina, building science education skills for citizen science participants, and enhancing community relationships between the forest and citizens. This article outlines several approaches for developing citizen science projects in a forest context, drawing on experiences from HOWL. The paradigm can be used to meet the needs of any forest landscape’s research and management goals, while employing a participatory research approach. The guidelines present suggestions for productive and enduring processes for citizen engagement and project sustainability. Each project will need participants to set goals, build a diverse collaboration, and establish on-going evaluation processes to determine successful and failed components that ensures the project moves forward effectively. The citizen science efforts near the Hofmann Forest in Eastern North Carolina provided an excellent case study of the development of citizen science on the forest and adjacent lands. HOWL attempts to meet participant and socio-ecological outcomes, such as encouraging public action in natural resource and forest management, as well as enhancing scientific knowledge and skills. The project helps synthesize our experiences in this effort and the social science literature, providing reasonable guidelines for those seeking to establish their own citizen science efforts within a forest context.

International Cooperation Projects in Research Center for Eco-Environmental Sciences Chinese Academy of Sciences

1. CERP The Cooperative Ecological Research Programme (CERP) is a joint plan to study the Man and Biosphere (MAB) ecosystem in our country, founded by Germany through UNESCO. The second-stage projects of CERP had been undertaken in 1991, including: (1) Study on the Ecological Strategy for the Urban Development of Tianjin City Exemplifying the large industrial city, it is to study the succession mechanism, cybernetic characteristics, and systems analytic methods of identification, simulation and planning, of the Social-Economic-Natural Com-

Big Data 4.0: The Era of Big Intelligence

Big data has had significant impacts on our lives,economies,academia and industries over the past decade.The current equations are:What is the future of big data?What era do we live in?This article addresses these questions by looking at meta as an operation and argues that we are living in the era of big intelligence through analyzing from meta(big data)to big intelligence.More specifically,this article will analyze big data from an evolutionary perspective.The article overviews data,information,knowledge,and intelligence(DIKI)and reveals their relationships.After analyzing meta as an operation,this article explores Meta(DIKE)and its relationship.It reveals 5 Bigs consisting of big data,big information,big knowledge,big intelligence and big analytics.Applying meta on 5 Bigs,this article infers that 4 Big Data 4.0=meta(big data)=big intelligence.This article analyzes how intelligent big analytics support big intelligence.The proposed approach in this research might facilitate the research and development of big data,big data analytics,business intelligence,artificial intelligence,and data science.

LIRR's Project of “Study on Spalling Mechanism Mechanism of Dense Refractory Castables by Rapid Heating-up” Being Obtained the Support from National Natural Natural Science Foundation of China

LIRR＇s Priject of ＂Research on Spalling Mechanism Due to Rapid Heating-up of Dense Refractory Castables＂ declared by Wang Zhanmin,vice-president of LIRR,will gain the fund support from National Natural Science Foundation of China in 2011.

Research on the Teaching Reform of “Big Data Analysis and Visualization” Course for College Students

Under the background of the big data era,the education of big data majors is undergoing a profound teaching reform and innovation.With the increasing role of big data technology in analysis and decision-making,updating and expanding the teaching content of big data majors has become particularly important.In the era of big data,modern enterprises have put forward new and higher demands for big data talents,which not only include traditional data analysis skills but also knowledge of data visualization and information technology.To address these challenges,big data education needs to reform and innovate in the development and utilization of teaching content,methods,and resources.This paper proposes teaching models and reform methods for big data majors and analyzes corresponding teaching reforms and innovations to meet the requirements of the new development of big data majors.The traditional classroom teaching method is no longer sufficient to meet the learning needs of students,and more dynamic and interactive teaching methods,such as case studies,flipped classrooms,and project-based learning,are becoming increasingly essential.These innovative teaching methods can more effectively cultivate students’practical operation skills and independent thinking while allowing them to better learn advanced knowledge in a real big-data environment.In addition,the paper also discusses the construction of big data processing and analysis platforms,as well as innovative teaching management and evaluation systems to improve teaching quality.

Business Invitation in Science and Technology for China Nonferrous Metal Projects

1. The production of high grade ferrite permanent magnet device (Beijing General Research Institute of Metallurgy) 2. Beijing Jinlong Science and Trade Comprehensive Building (A,B) (Beijing General Research Institute of Nonferrous Metals)

PROJECTS WON 1998 CAS AWARDS FOR NATURAL SCIENCES (II)

The CAS Award for Natural Sciences is a major award issued by the Chinese Academy of Sciences to recognize the scientific findings and research results by which CAS scientists bring to light natural phenomena, laws and properties in their basic and applied basic research. In 1998, 73 research projects won the CAS Awards for Natural Sciences. The following are profiles of some of the prize-wining projects.

Research on the Construction of Application-Oriented Undergraduate Data Science and Big Data Technology Courses

In order to conduct research and analysis on the construction of application-oriented undergraduate data science and big data technology courses,the professional development characteristics of universities and enterprises should be taken into consideration,the development trend of the big data industry should be scrutinized,and professional application-oriented talents should be cultivated in line with job requirements.This paper expounds the demand for capacity-building professional development in application-oriented undergraduate data science and big data technology courses,conducts research and analysis on the current situation of professional development,and puts forward strategies in hope to provide reference for capacity-building professional development.