In the current era of data science, data quality has a significant and critical impact on business operations. This is no different for the meteorological data encountered in the field of meteorology. However, the conventional methods of meteorological data quality control mainly focus on error detection and null-value detection; that is, they only consider the results of the data output but ignore the quality problems that may also arise in the workflow. To rectify this issue, this paper proposes the Total Meteorological Data Quality (TMDQ) framework based on the Total Quality Management (TQM) perspective, especially considering the systematic nature of data warehousing and process focus needs. In practical applications, this paper uses the proposed framework as the basis for the development of a system to help meteorological observers improve and maintain the quality of meteorological data in a timely and efficient manner. To verify the feasibility of the proposed framework and demonstrate its capabilities and usage, it was implemented in the Tamsui Meteorological Observatory (TMO) in Taiwan. The four quality dimension indicators established through the proposed framework will help meteorological observers grasp the various characteristics of meteorological data from different aspects. The application and research limitations of the proposed framework are discussed and possible directions for future research are presented.

Assurance improvement is the most challenging task both in railway and space areas, even though their required technologies are different. It can be said that the railways have been achieving the extremely high assurance level through their long history and experience, while the space area has not accumulated enough experience in addition to their requirement of highly advanced technology. As a result, the latter places more emphasis on theoretical analyses for ensuring the assurance. This paper introduces the two different approaches of railway and space areas toward assurance, and compares the two methods.

There are three viewpoints involved in software project management: process management, quality management and cost management. Software projects must be managed on the basis of these three viewpoints. However, in many cases process management, quality management and cost management systems are built separately as individual systems respectively. Construction of software project management systems which these three functions are integrated has been rare. Therefore, in order to construct a system integrating these functions, the authors clarify the significance of integration of application systems. And then the authors unveil the structure of a software project management system that process management system, quality management system and cost management system are integrated by using an object oriented database.

We propose a new concept of network dimensioning, which is based not only on the grade of service but also on profit. In traditional network dimensioning methodology, the number of circuits on links is designed under a cost-minimization concept with grade of service constraints. Recently, telecommunication markets have become very large and competitive; therefore, we believe that a profit viewpoint is now essential. However, it is difficult to calculate profit in almost all the dimensioning methods currently used, because they mainly employ peak-hour traffic data, while profit depends on all the hourly traffic data which contain both peak and off-peak data. In this paper, we propose using all the hourly traffic data in network dimensioning. From these data and telephone charges for each hour, revenues will be estimated. On the other hand, facility costs will be estimated from the number of circuits. Finally, we can estimate profit from the difference between revenues and facility costs. Focusing on both quality and profits in network dimensioning leads to more advanced quality management and quality control in telecommunications networks than with traditional methodology. This paper outlines a dimensioning method based on profit, and describes its properties, some applications of it, and summarizes further studies.