VLDB 2026 Research / reviewers in the wild / expert
Andrew Sparkes
dblp:52/3697
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2012
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author
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.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Bioinformatics and computational biology · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
laboratory information management |
0.1 | 1 | 2012 | AutoLabDB: a substantial open source database schema to support a high-throughput automated laboratory · Bioinform. 2012 |
Bioinformatics and computational biology › drug discovery
high-throughput screening |
0.0 | 1 | 2012 | AutoLabDB: a substantial open source database schema to support a high-throughput automated laboratory · Bioinform. 2012 |
Methods — techniques the papers use, named apart from their topics
database design · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | AutoLabDB: a substantial open source database schema to support a high-throughput automated laboratoryabstractAbstract Motivation: Modern automated laboratories need substantial data management solutions to both store and make accessible the details of the experiments they perform. To be useful, a modern Laboratory Information Management System (LIMS) should be flexible and easily extensible to support evolving laboratory requirements, and should be based on the solid foundations of a robust, well-designed database. We have developed such a database schema to support an automated laboratory that performs experiments in systems biology and high-throughput screening. Results: We describe the design of the database schema (AutoLabDB), detailing the main features and describing why we believe it will be relevant to LIMS manufacturers or custom builders. This database has been developed to support two large automated Robot Scientist systems over the last 5 years, where it has been used as the basis of an LIMS that helps to manage both the laboratory and all the experiment data produced. Availability and implementation: The database schema has been made available as open source (BSD license), so that others may use, extend and improve it to meet their own needs. Example software interfaces to the database are also provided. http://autolabdb.sourceforge.net/ Contact: [email protected] Andrew Sparkes, Amanda Clare |
Bioinform. | 1 |