| Project/Area Number |
13630171
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Accounting
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| Research Institution | Waseda University |
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Principal Investigator |
TSUJI Masao Waseda University, School of Commerce, Professor, 商学部, 教授 (20063787)
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| Co-Investigator(Kenkyū-buntansha) |
MAENO Joji Waseda University, Media Network Center, Visiting Lecturer, メディアネットワークセンター, 講師 (30298210)
KATSURAYAMA Yasunori Waseda University, School of Social Sciences, Professor, 社会科学部, 教授 (10257222)
HAH Eitoku Waseda University, School of Commerce, Professor, 商学部, 教授 (70228378)
OSHIKA Tomoki Waseda University, Media Network Center, Research Associate, メディアネットワークセンター, 助手 (90329160)
大塚 宗春 早稲田大学, 商学部, 教授 (60063749)
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| Project Period (FY) |
2001 – 2002
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| Project Status |
Completed (Fiscal Year 2002)
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| Budget Amount *help |
¥3,500,000 (Direct Cost: ¥3,500,000)
Fiscal Year 2002: ¥1,100,000 (Direct Cost: ¥1,100,000)
Fiscal Year 2001: ¥2,400,000 (Direct Cost: ¥2,400,000)
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| Keywords | Financial Data / Financial Database / Financial Statement Analysis / Accounting Analysis / Corporate Analysis / XML / XBRL / Semantic Web / 企業財務情報 / データベース / NEEDS / インターフェース / セマンティックス |
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| Research Abstract |
In the first year, we compared "Nikkei NEEDS Database" with "Standards & Poor's Research Insight", in its contents, usage, and usability. Nikkei NEEDS database has a relatively simple interface, with its search criteria limited to some important variables. Research Insight offers a variety of methods, and its search method is categorized with customers' purposes. They offer a "portal", featuring four types of search methods: (1) research, (2) report, (3) graph, and (4) company information. In the meanwhile, we studied the theoretical background of implementation. In the implementation phase, we have to remind the usability. Usability consists of interface and semantics. We adopted XML technology and Relational Database Management System to solve these two challenges. In expressing accounting data with XML, we have to analyze account items carefully. We broke Nikkei NEEDS financial file data into tree structure.
In the second year, we deployed accounting items into XBRL (Extensive Business Reporting Language) and put those data into the relational database. We also implemented necessary interface (front-end) for this database, and offered to the users at Waseda University.
Performance of this database is quite fast. Usual usage, such as searching 10 variables for 2,000 companies ends within 10 seconds. We also used this system for several empirical studies. We are continuing to work to improve the system with the feed back from users.
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