The Fifth Electronics Research Institute of the Ministry of Industry and Information Technology, Guangzhou, China

Transcription

1 2016 International Conference on Humanities Science, Management and Education Technology (HSMET 2016) ISBN: Research on Science and Technology Project Management Based on Data Knowledge Keqiang Cheng 1,2, Pengnan Zhang 1, Yao Li 1,3,a, Xiaoyin Liu 1,3, Qingyun Dai 4 1 The Fifth Electronics Research Institute of the Ministry of Industry and Information Technology, Guangzhou, China 2 School of Information Engineering, Guangdong University of Technology, Guangzhou, China 3 Ceprei Certification Body, Guangzhou, China 4 Guangdong Polytechnic Normal University, Guangzhou, China a ckqjiayou@163.com Keywords: Data Knowledge, Science and Technology Project, Knowledge Base, Decision-making Model Abstract. In the background of big data, the problems existing in the current science and technology project management were analyzed in this paper, and the information technology (IT) such as the internet of things (IOTs) and cloud computing were combined to introduce the characteristics of the science and technology project management. The knowledge base of science and technology project management was put forward by describing the principle of the hierarchical structure of it based on big data. Finally, the paper proposes the model that using the data knowledge to serve decision of science and technology project management from the perspective of the undertaking enterprise of the project, which may be helpful for the innovation of science and technology project management model. 1. Introduction With the improvement of comprehensive national strength, scientific research funding invested by governments is increasing year by year. At the same time, more and more science and technology projects are undertaken by the research institutes and large enterprises. In order to spend the money in the most effective way, governments continuously increase the strength of the supervision on the project lifecycle [1]. As the scientific research management department directed by the undertaking enterprise of the project, it needs to develop a series of scientific research management measures to make researchers concentrate on the research work and complete the project with quality. With the coming of big data period, and the rapid development of IT represented by the IOTs and cloud computing, science and technology project management faces new challenges and opportunities. Therefore, we must change the traditional idea of management, innovate the managerial model by taking full advantage of the valuable wealth of big data. 2. Analysis of the current situation of science and technology project management Science and technology project is generally in order to solve a specific technical problems or a common problem for the industry, with a certain degree of innovation and risk, while also clearly targeted [2]. And science and technology project management refers to the management of the manpower, material and financial resources in the whole process of research and application of innovative technologies, including the management of the process of project research, the supervise and management of equipment and researchers, the monitor and control of research funds, and the promotion of research results and so on. Traditional science and technology project management mainly has the following problems. Firstly, the preceding planning of the project is not enough, such as the analysis of feasibility and risk evaluation of the project does not reach the designated position, and the projects are completed for the sake of money instead of the pursuit of science. Secondly, the lack of effective supervision 161

2 mechanism in the whole project process, and failed to establish effective project tracking and evaluation means of dynamic monitoring in the use of the funds, equipment procurement and project progress. Thirdly, the project application was money oriented, rather than develop science and technology research according to the actual situation. At last, the deficiency of self-financing ability. Most of major projects and technological transformation projects need co-financing with the undertaking enterprises of the projects. Some enterprises overlook the importance of self-raised funds in order to obtain goverment-matching funds. Therefore, the projects would be delayed or discontinued because of the shortage of funds. The above problems, mostly due to the lack of scientific supervision mechanism and means, seriously affect the process of science and technology projects, but also affect the function and status of scientific and technological work in social development. In addition, the traditional methods of project communication influenced and restricted by many factors, for instance as time, distance, researchers and other aspects, leading to the lower efficiency of science and technology project management. The project management through the network based on a unified data application platform, could break the limitation of geographical, time, personnel, and to achieve the sharing of information, it will effectively improve the efficiency of science and technology project management. 3. The characteristics of science and technology project management in the era of big data With the development of the IOTs, cloud computing and sensor technology, large amounts of data generated in the whole life cycle of science and technology research project [3]. Among it, there are a lot of unstructured data in addition to a large number of structured data, such as streaming media, pictures, intellectual property, space information, etc. Compared with traditional data, the big data has features such as volume, variety, value, velocity and variety and so on [4]. Research shows that big data is a valuable resource which contains a wealth of rules and knowledge. Therefore, it is worthy to pay attention to mining and application of data knowledge, which would helpful for science and technology project management. The science and technology project management in the era of big data has a lot of characteristics. Firstly, not only the experimental data, but also non-experimental data seems disorganized will become an increasingly important resources. With the development of machine learning, deep learning and visualization technology, rules and knowledge could be found in the complex data with the help of intelligent mining and analysis technology. So, the data protection has become more and more impotant. Secondly, the amount of data is huge and complexity of data is increasing, this creates more work for science and technology project management staff. In the whole process of project, multi-type of data generating continuously with the development of sensor technology and communication technology. With no doubt, this creates more workload, such as collection, storage, processing and analysis of the data. Thirdly, the investment of laboratory will gradually increasing. In the era of big data, sampling experiment has been replaced by large quantities of simulation experiments, which requires much more laboratory resources. At the same time, this may also be an obstacle to some undertaking enterprises of the projects which has insufficient funds. Fourthly, the personnel arrangement and financial management of science and technology project will become more transparent and more reasonable through data collection and analysis. Because the data are more revealing than subjective feelings. The era of big data brings opportunity for science and technology project management, but also brought a big challenge. At the same time, the science and technology management is also endowed with a new meaning, that is using scientific managements to store, integrate, analysis and utilize the manpower, material and financial resources involved in the whole process of science and technology project management in the form of data. At present, there are some problems existing in science and technology project management, such as the rate of data resource sharing is low, short of high-quality talents, lack of standards and norms, and the data protection system is not perfect and the 162

3 stability of open source system needs to be improved. However, innovation of the science and technology project management model based on big data is the development trend of the future. 4. Analysis of a hierarchical structure of science and technology project management based on big data The driving force of storage and processing big data is the precious wealth it contains [5]. And we should clearly recognize that science and technology project management will be paid more and more attention to data in the information technology revolution. Because big data generated from IOTs and cloud computing provides a platform for its applications. The development of the IOTs, cloud computing and big data is driving innovation in science and technology project management model. We first discuss the hierarchical structure of project management based on big data, before exploring how to use big data serves project management. Figure 1. A hierarchical structure of science and technology project management based on big data. Using Big data serves science and technology project management mainly divided into data processing and analysis of application. The purpose of data processing is to discovery some valuable knowledge from large amounts of data generated in science and technology project management process. In this paper, we put forward a hierarchical structure of science and technology project management based on big data, as shown in Figure 1. We carry out three stages of processing and analysis for personnel data, research funds, equipment resources and other data information, which are related with the process of the management of science and technology project. The first stage is data collection and preprocessing. At this stage, the data collecting through sensor technology, artificial statistics, experimental calculation will be cleaned, sorted and stored. Followed by processing stage, discovery data knowledge through data mining, integration and analysis. The top stage is the application, applications of big data in science and technology project management is very broad, including analysis of development situation, decision support, establish personalized management programs for science and technology project, etc. We could discory the knowledge of big data through machine learning, deep learning, intelligent analysis, visualization technology and so on, then forming a base of data knowledge. The following text, we will discuss how to use data knowledge to serve science and technology project management. 5. Using data knowledge serves for science and technology project management Within problems existing in the current science and technology project management, we discovery the data knowledge by analyzing the characteristics of the data in the process of project management and using IOTs, cloud computing, big data and other cutting-edge technology. Then forming a base of 163

4 data knowledge. Finally, we put forward using data knowledge to optimize the model of the science and technology project management process. Start a project Make a plan The knowledge base of science and technology project management based on big data Call experience knowledge Call data knowledge Make a preliminary plan Plan matching Decision contrast Program optimization Add to the knowledge base Make a final decision and continue to monitor Figure 2. The decision-making model of data knowledge serves for science and technology project management. In this paper, we put forward a model of the service-decision making of the data knowledge based on the science and technology project management process, as shown in figure 2. This service-decision making model runs through the whole life cycle of the project, from project planning and reporting, implementation process and evaluation to the project summary and acceptance [6]. Once the project task arrives, the science and technology project management department will issue a plan, which involving arrangements of researchers, budgets, equipments procurement, supervision of funds, management of results, etc [7]. Traditional science and technology project management tend to pay more attention to the knowledge of experience, is too subjective because generally we use information based on recent or current state as references. Now, we have built a knowledge base of science and technology project management based on big data, when the project task arrives, contrasting with the project already in the knowledge base through the model matching, it may greatly optimize the program. After that, we could add the program to the knowledge base, to provide an alternative for subsequent science and technology project management. 6. Summary Science and technology project management is a complicated task, involving the management of manpower, materials, financial resources and other resource. With the rapid development of national economy, the pace of technological development accelerates and a corresponding increase of workload of science and technology project management staff year by year. Respond the new requirements of science and technology project management reasonably and quickly demands not only the constant evolution and innovation of the management mode, but also the contents, methods 164

5 and means of innovation management. The paper firstly analyzes the status of the science and technology project management. Then, analyzing the principle of the hierarchical structure of project management based on big data, combined with the IOTs, cloud computing, big data, and other information technology, the construction of science and technology project management knowledge base based on big data is proposed. Finally, a decision-making model is presented, which serves the science and technology project management by using the data knowledge. Big data of science and technology project management contains the valuable wealth. Although in terms of the current situation, the data sharing and data processing technology are facing great challenge, it is an unpreventable tendency to use them to guide the project management of science and technology. Acknowledgements This work was financially supported by the National Key Technology Support Program (2015BAH26F00). References [1] Information on [2] Chen SP, Li ZH, Liu T: Science and Technology, Guangzhou, Sun Yat-sen University Press 2007: [3] H. Li: Research on Construction of the Science and Technology Management Innovation Platform in the Background of Big Data, Scientific management research. 2014, 32(3): [4] Hilbert M., Lopez P. The world s technological capacity to store, communicate, and compute information. Science, 2011, 332(6025): [5] Cheng X.Q., jin X.L., Wang Y.Z., Guo J.F., Zhang T.Y., Li G.J. Survey on Big Data System and Analytic Technology. Ruan Jian Xue Bao/Journal of Software, 2014, 25(9): [6] W.F. Hu: Life cycle view of technical project management, science and technology progress and policy, 2004(5): [7] Z.P Wang: Research on the application of modern project management in science and technology project, Forum on Science and Technology in China, 2006(6):