Demo Data from VLDB 2026 / reviewers in the wild / expert
Chih-Shing Yu
dblp:59/3809
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1995
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Databases, data mining, and information retrieval
1 paper |
Distributed and cloud data management · 50% Data integration and cleaning · 50% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Data integration and cleaning
heterogeneous data integration |
0.0 | 1 | 1995 | The Design and Implementation of a Full-Fledged Multiple DBMS · ICDE 1995 |
Distributed and cloud data management
multidatabase systems |
0.0 | 1 | 1995 | The Design and Implementation of a Full-Fledged Multiple DBMS · ICDE 1995 |
Methods — techniques the papers use, named apart from their topics
core storage manager · 0.0access manager · 0.0ODBC driver · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1995 | The Design and Implementation of a Full-Fledged Multiple DBMSabstractWe have described our design of the multiple DBMS (MDBMS). This MDBMS enables users to access data controlled by different DBMSs as if data were managed by a single DBMS. It supports facilities for SQL queries and transactions, and considers security functions. In addition, an ODBC driver at the client site has been realized to ease the development of MDBMS applications. Several popular commercial DBMSs, including Oracle, Informix and Sybase, have been successfully integrated. The MDBMS is in operation now. However, we found the performance to be unsatisfactory. It took about several seconds to process an SQL query with single join on two relations of hundreds of tuples. We have identified the performance bottleneck to be on the retrieval of meta data. The current MDBMS Server employs a commercial DBMS to store meta data, which is necessary for processing a global query. The processing of a query is slow because it needs to retrieve the schema information via an external DBMS several times. We are currently designing a core storage manager and an access manager specifically for maintaining the meta data and the intermediate results of a global query. We expect this design to significantly improve the performance.> Shu-Chin Su Chen, Chih-Shing Yu, Yen-Yao Yao, San-Yih Hwang, B. Paul Lin |
ICDE | 2 |