Abstract
A vast amount of data is being generated in a distributed manner, and data sharing among multiple related databases is becoming increasingly common. Data sharing can be expected to enable more appropriate data analysis and more efficient management. When it is difficult to grasp the overall picture of data for sharing and multiple data management entities are managing data in an autonomous and decentralized manner, it is desirable to be able to filter data to be imported or exported by setting conditions in order to share data based on local trust relationships and avoid unintentional data sharing or updating. Update exchange also needs to be discussed especially when each data management entity could update data imported from other data management entities, and then export that data. In this chapter, we discuss our SKY system, which is an autonomous and collaborative data personalization system with its implementation.
Original language | English |
---|---|
Title of host publication | Bidirectional Collaborative Data Management |
Subtitle of host publication | Collaboration Frameworks for Decentralized Systems |
Publisher | Springer Nature |
Pages | 139-154 |
Number of pages | 16 |
ISBN (Electronic) | 9789819764297 |
ISBN (Print) | 9789819764280 |
DOIs | |
Publication status | Published - Jan 1 2024 |
All Science Journal Classification (ASJC) codes
- General Computer Science