Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data.

David G. Bell

dblp:73/6404 · DBLP profile ↗
← Back
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

TopicWeightPapersLastEvidence papers
Data integration and cleaning › enterprise information integration
enterprise data integration
0.112005
Lean middleware · SIGMOD Conference 2005
YearPublicationVenuePosition
2006 Business Intelligence in Large Organizations: Integrating Which Data?
David A. Maluf, David G. Bell, Naveen Ashish, Peter Putz, Yuri Gawdiak
ISMIS2
2005 Semi-Structured Data Management in the Enterprise: A Nimble, High-Throughput, and Scalable Approach
abstract
In 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
IDEAS2
2005 Lean middleware
abstract
This 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 Conference2