A field of "statistics" has now a very high profile, in expectation that it's the fastest tool to bring the best answer to us, whereas not many of us understand how we should analyse what kind of data, as well as how we are to put them to practical use. I explain about randomized controlled experiment (randomized controlled trial), as well as a basic statistical principle on management advocated by Dr. Edwards Deming, a great statistician and the father of "Japan quality". I also mention the methodology of creating an ideal cycle of data analyzing which could directly applied to business, by making excellent use of "research design".

The results of government statistics are provided centrally in the "portal site of official statistics of japan (e-Stat)", mainly on files such as Excel. However, there are many Excel files based on traditional reports, which makes it difficult to extract data. To solve this problem, we have proceeded with database creation and also provided API function that can obtain data directly from the program. Furthermore, to make the utilization of statistical data even more advanced, we started offering Linked Open Data (LOD) which is said to be the best in open data in 2016. In this paper, we will explain the current state of data provision of government statistics and explain how to provide statistical data in LOD format as well as its design and the usage.

With use of modern computing power, advanced sensor networks and information technologies, a project is underway to establish a new system of real-time tsunami inundation forecasting, damage estimation, mapping and robust information dissemination to enhance society's resilience in the aftermath of major tsunami disaster. The system consists of fusion of real-time crustal deformation monitoring/fault model estimation, high-performance real-time tsunami propagation/inundation modeling with Tohoku University's vector supercomputer SX-ACE, damage/loss estimation model, geo-informatics and information technologies. The results are disseminated as mapping products to responders and stakeholders, e.g. national and regional municipalities, to be utilized for their emergency/response activities. In 2014, the system is verified through the case studies of 2011 Tohoku event and potential earthquake scenarios along Nankai Trough with regard to its capability and robustness.

Aozora Bunko (Open Air Library) is a volunteer-based online digital-text archive in Japan that uses text files (.txt) as a main format for archiving. This article explains Aozora Bunko's unique annotation styles for e-texts, its problems and solutions for digitalizing paper books, advantages of using plain texts, etc. along with historical details and future's visions. As a whole, the development of tools and documents for volunteer group-work was mainly due to the necessity for effective and economical use of JIS kanji code and annotations in formatting books.

Scientometrics based on large-scale bibliographic datasets has been actively investigated for an understanding of research activities and the establishment of science and technology policies. Thus, thesauri for science and technology information are increasingly used to search, classify and make clusters of articles, patents, and research data. Japan Science and Technology Agency (JST) constructed and is continuously maintaining such a thesaurus since 1975; then, this time, converted the JST thesaurus and the associated dictionary, including approximately 245,000 concepts to Linked Data of Resource Description Framework, a W3C standard format and made publicly available on the Web for a limited period. In this paper, we first describe the outline of the JST thesaurus and the associated dictionary followed by features and advantages of the Linked Data version. Then, we discuss the role of the JST thesaurus as the top-level ontology, which connects several domain-specific ontologies. We also introduce our activity for ontologically rearranging the relationship among concepts in a life-science category. Finally, semi-automatic maintenance of the thesaurus using natural language processing is proposed as future work.