Demo Data from VLDB 2026 / reviewers in the wild / expert
Maher Manoubi
dblp:66/8510
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2010
—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 |
Data integration and cleaning · 77% Database system architecture and tuning · 23% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Distributed systems · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Data integration and cleaning › data integration system
peer data management system |
0.1 | 1 | 2010 | Peer coordination through distributed triggers · Proc. VLDB Endow. 2010 |
Database system architecture and tuning › active database
trigger processing |
0.0 | 1 | 2010 | Peer coordination through distributed triggers · Proc. VLDB Endow. 2010 |
Distributed systems
distributed coordination |
0.0 | 1 | 2010 | Peer coordination through distributed triggers · Proc. VLDB Endow. 2010 |
Methods — techniques the papers use, named apart from their topics
declarative trigger language · 0.2active DBMS extension · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2010 | Peer coordination through distributed triggersabstractThis is a demonstration of data coordination in a peer data management system through the employment of distributed triggers. The latter express in a declarative manner individual security and consistency requirements of peers, that cannot be ensured by default in the P2P environment. Peers achieve to handle in a transparent way data changes that come from local and remote actions and events. The distributed triggers are implemented as an extension of the active functionality of a centralized commercial DBMS. The language and execution semantics of distributed triggers are integrated in the kernel of the DBMS such that the latter handles transparently and simultaneously both centralized and distributed triggers. Moreover, the management of distributed triggers is associated with a set of peer acquaintance and termination protocols which are incorporated in the centralized DBMS. Verena Kantere, Maher Manoubi, Iluju Kiringa, Timos K. Sellis, John Mylopoulos |
Proc. VLDB Endow. | 2 |