| Project/Area Number |
18K11315
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Multi-year Fund |
|---|
| Section | 一般 |
|---|
| Review Section |
Basic Section 60080:Database-related
|
|---|
| Research Institution | Kyushu University (2021-2022)
Kyoto University (2018-2020) |
|---|
Principal Investigator |
|
|---|
| Project Period (FY) |
2018-04-01 – 2023-03-31
|
| Project Status |
Completed (Fiscal Year 2022)
|
| Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2020: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2019: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2018: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
|
|---|
| Keywords | データベース / 問合せ / データクリーニング / データ共有 / 理解支援 |
|---|
| Outline of Final Research Achievements |
We considered how data managers can efficiently manage data while deepening their understanding of the data, and specifically worked on research related to data cleaning and data sharing. As for the study on data cleaning, we proposed a method for detecting candidates of inconsistent values, and also a method for showing partial data containing the candidates of inconsistent values to data managers using a view-based approach using queries. As for the study on data sharing, we devised a mechanism for appropriately sharing and updating partial data expressed by queries in a situation where multiple data management entities are managing data in an autonomous and decentralized manner, and proposed an implementation method for this mechanism.
|
| Academic Significance and Societal Importance of the Research Achievements |
近年、機械学習を用いたデータ分析が盛んに行われているが、適切な分析のためにはデータを整備し、理解して手法を適用することが重要だと思われる。分散的にデータが生成され、管理されている場合など、一人のデータ管理者が関連するデータの全体像を把握するのが困難な状況も多いと思われる。本研究では、問合せを用いて部分データを切り出して扱うことで、データ管理者によるデータの理解を助けながらデータ管理を行うことを考え、そのための手法の提案と実装を行った。
|
