VLDB 2026 Research / reviewers in the wild / expert
David G. Bell
dblp:73/6404
· DBLP profile ↗
3ranked-venue papers
0as first author
0since 2021 · last 2006
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 2Artificial intelligence and machine learning · 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 · 100% |
Topics — the 1 heaviest of 1, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Data integration and cleaning › enterprise information integration
enterprise data integration |
0.1 | 1 | 2005 | Lean middleware · SIGMOD Conference 2005 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2006 | Business Intelligence in Large Organizations: Integrating Which Data?
David A. Maluf, David G. Bell, Naveen Ashish, Peter Putz, Yuri Gawdiak |
ISMIS | 2 |
| 2005 | Semi-Structured Data Management in the Enterprise: A Nimble, High-Throughput, and Scalable ApproachabstractIn this paper we describe an approach and system for managing enterprise semi-structured data that is high-throughput, nimble, and scalable. We present the NETMARK system, which provides for a "schemaless" way of managing semi-structured documents. We describe in particular detail the unique underlying data storage approach and efficient query processing mechanisms given this storage system. We present an extensive benchmark evaluation of the NETMARK system and also compare it with related XML management systems. At the heart of the approach is the philosophy of a focus on most common data management requirements in the enterprise, and not burdening users and application developers with unnecessary complexity and formal schemas. David A. Maluf, David G. Bell, Naveen Ashish, Christopher Knight 0001, Peter B. Tran |
IDEAS | 2 |
| 2005 | Lean middlewareabstractThis paper describes an approach to achieving data integration across multiple sources in an enterprise, in a manner that does not require heavy investment in database and middleware maintenance. This "lean" approach to integration leads to cost-effectiveness and scalability of data integration in the enterprise. David A. Maluf, David G. Bell, Naveen Ashish |
SIGMOD Conference | 2 |