Demo Data from VLDB 2026 / reviewers in the wild / expert
B. Nick Rossiter
dblp:r/BNickRossiter
· DBLP profile ↗
7ranked-venue papers
2as first author
0since 2021 · last 2013
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 3 · 1 first-authorDatabases, data management, data science and information retrieval · 3 · 2 first-authorSoftware engineering, systems software and programming languages · 2Graphics, computer vision, multimedia, augmented reality and games · 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.
| Computer graphics and multimedia
1 paper |
Visualization and visual analytics · 100% | |
| Databases, data mining, and information retrieval
1 paper |
Database system architecture and tuning · 77% Information retrieval · 23% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Visualization and visual analytics
visualization theory |
0.2 | 1 | 2013 | Understanding Visualization: A Formal Approach Using Category Theory and Semiotics · IEEE Trans. Vis. Comput. Graph. 2013 |
Database system architecture and tuning › text databases
hypertext database |
0.0 | 1 | 1989 | Database Support for Hypertext · VLDB 1989 |
Information retrieval › document organization
hypertext |
0.0 | 1 | 1989 | Database Support for Hypertext · VLDB 1989 |
Methods — techniques the papers use, named apart from their topics
semiotics · 0.2category theory · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2013 | Understanding Visualization: A Formal Approach Using Category Theory and SemioticsabstractThis paper combines the vocabulary of semiotics and category theory to provide a formal analysis of visualization. It shows how familiar processes of visualization fit the semiotic frameworks of both Saussure and Peirce, and extends these structures using the tools of category theory to provide a general framework for understanding visualization in practice, including: Relationships between systems, data collected from those systems, renderings of those data in the form of representations, the reading of those representations to create visualizations, and the use of those visualizations to create knowledge and understanding of the system under inspection. The resulting framework is validated by demonstrating how familiar information visualization concepts (such as literalness, sensitivity, redundancy, ambiguity, generalizability, and chart junk) arise naturally from it and can be defined formally and precisely. This paper generalizes previous work on the formal characterization of visualization by, inter alia, Ziemkiewicz and Kosara and allows us to formally distinguish properties of the visualization process that previous work does not. Paul Vickers, Joe Faith, B. Nick Rossiter |
IEEE Trans. Vis. Comput. Graph. | 3 |
| 2011 | Parsed use case descriptions as a basis for object-oriented class model generation
Mosa Elbendak, Paul Vickers, B. Nick Rossiter |
J. Syst. Softw. | 3 |
| 2008 | Relational Database Migration: A Perspective
Abdelsalam M. Maatuk, Muhammad Akhtar Ali, B. Nick Rossiter |
DEXA | 3 |
| 1998 | Constructing Standards For Cross-Platform Operation
Michael A. Heather, B. Nick Rossiter |
Softw. Qual. J. | 2 |
| 1990 | Database Models for Textual Documents: User Needs and System Capabilities
B. Nick Rossiter, Michael A. Heather |
DEXA | 1 |
| 1990 | Semantic pattern matching in netbases
Michael A. Heather, B. Nick Rossiter |
Neurocomputing | 2 |
| 1989 | Database Support for Hypertext
B. Nick Rossiter |
VLDB | 1 |