Demo Data from EDBT 2026 / reviewers in the wild / expert
Soonbo Han
dblp:233/6289
· DBLP profile ↗
2ranked-venue papers
1as first author
1since 2021 · last 2024
0009-0002-3039-5958ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 2 · 1 first-author · 1 since 2021
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 |
Query processing and optimization · 56% Graph data management · 44% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Graph data management
graph view |
0.8 | 1 | 2024 | Implementation Strategies for Views over Property Graphs · Proc. ACM Manag. Data 2024 |
Query processing and optimization
materialized view |
0.2 | 1 | 2024 | Implementation Strategies for Views over Property Graphs · Proc. ACM Manag. Data 2024 |
Methods — techniques the papers use, named apart from their topics
query rewriting · 0.8indexing structures · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Implementation Strategies for Views over Property GraphsabstractThe need to query complex interactions and relationships has motivated interest in property graph database platforms. For some graph applications, graph views are required to abstract the data, e.g., to capture individual-level vs. organization-level relationships; or show single computational steps vs. composite workflows. Emerging efforts to standardize graph query languages have developed semantics and language constructs for graph views. This paper considers the task of implementing such views using rewriting techniques --- both using existing property graph DBMSs and converting to relational RDBMSs. We consider both virtual and materialized views, ways of rewriting queries, and structures for indexing data. We also note a common use case of graph views, which involves preserving a graph except minor local transformations; we develop novel extensions and semantics for this. We evaluate and compare the performance of our techniques under a variety of workloads, and we compare existing graph and relational DBMS platforms. Soonbo Han, Zachary G. Ives |
Proc. ACM Manag. Data | 1 |
| 2019 | Dataset Relationship Management
Zachary G. Ives, Yi Zhang 0001, Soonbo Han |
CIDR | 3 |