Data Compilation Procedure of the Nuclear Reaction Data on the Unified Research Management System Data compilation activity in the nuclear physics has been continued for over 40 years. In addition to neutron data for safe operation of nuclear reactors, utilization of charged particle nuclear reaction data has been promoted in various fields such as science, engineering and medical appellations. The complied data are classified into two categories. One is obtained from the experimental observation and the other is the evaluation deduced from the theoretical investigation combined with the model of reaction mechanism. The nuclear reaction data is compiled from the published scientific articles including the bibliographic information in addition to the experimental one, and the data is published on the website of the organization for the data compilation. In this work, we propose that the process of the data compilation is performed on a new environment for the scientific collaboration, which is called the Unified Research Management System (URMS), and aim to make the current compilation flow correspond to the services on URMS.

Exploring Metadata Search Essentials for Scientific Data Management Scientific experiments and observations store massive amounts of data in various scientific file formats. Metadata, which describes the characteristics of the data, is commonly used to sift through massive datasets in order to locate data of interest to scientists. Several indexing data structures (such as hash tables, trie, selfbalancing search trees, sparse array, etc.) have been developed as part of efforts to provide an efficient method for locating target data. However, efficient determination of an indexing data structure remains unclear in the context of scientific data management, due to the lack of investigation on metadata, metadata queries, and corresponding data structures. In this study, we perform a systematic study of the metadata search essentials in the context of scientific data management. We study a realworld astronomy observation dataset and explore the characteristics of the metadata in the dataset. We also study possible metadata queries based on the discovery of the metadata characteristics and evaluate different data structures for various types of metadata attributes. Our evaluation on realworld dataset suggests that trie is a suitable data structure when prefixsuffix query is required, otherwise hash table should be used. We conclude our study with a summary of our findings. These findings provide a guideline and offers insights in developing metadata indexing methodologies for scientific applications.