Demo Data from VLDB 2026 / reviewers in the wild / expert
Wolfgang H. Wohlleber
dblp:32/6152
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1979
—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 models and query languages · 50% Database theory · 50% | |
| Software engineering, system software, and programming languages
1 paper |
Programming languages and type systems · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Data models and query languages
data abstraction |
0.0 | 1 | 1979 | Data Abstractions for Database Systems · ACM Trans. Database Syst. 1979 |
Database theory
database schema |
0.0 | 1 | 1979 | Data Abstractions for Database Systems · ACM Trans. Database Syst. 1979 |
Programming languages and type systems
abstract data types |
0.0 | 1 | 1979 | Data Abstractions for Database Systems · ACM Trans. Database Syst. 1979 |
Methods — techniques the papers use, named apart from their topics
axiomatic specification · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1979 | Data Abstractions for Database SystemsabstractData abstractions were originally conceived as a specification tool in programming. They also appear to be useful for exploring and explaining the capabilities and shortcomings of the data definition and manipulation facilities of present-day database systems. Moreover they may lead to new approaches to the design of these facilities. In the first section the paper introduces an axiomatic method for specifying data abstractions and, on that basis, gives precise meaning to familiar notions such as data model, data type, and database schema. In a second step the various possibilities for specifying data types within a given data model are examined and illustrated. It is shown that data types prescribe the individual operations that are allowed within a database. Finally, some additions to the method are discussed which permit the formulation of interrelationships between arbitrary operations. Peter C. Lockemann, Heinrich C. Mayr, Wolfgang H. Weil, Wolfgang H. Wohlleber |
ACM Trans. Database Syst. | 4 |