7 citations · 10 across the 6 of their papers we have counts for
4 papers · 1 filter
Logica-TGD: Transforming Graph Databases Logically
Evgeny Skvortsov, Yilin Xia, Bertram Ludäscher +1
Graph transformations are a powerful computational model for manipulating complex networks, but handling temporal aspects and scalability remain significant challenges. We present…
Approximate Summaries for Why and Why-not Provenance (Extended Version)
Seokki Lee, Bertram Ludaescher, Boris Glavic
Why and why-not provenance have been studied extensively in recent years. However, why-not provenance, and to a lesser degree why provenance, can be very large resulting in severe…
PUG: A Framework and Practical Implementation for Why & Why-Not Provenance (extended version)
Seokki Lee, Bertram Ludaescher, Boris Glavic
Explaining why an answer is (or is not) returned by a query is important for many applications including auditing, debugging data and queries, and answering hypothetical questions…
Validation and Inference of Schema-Level Workflow Data-Dependency Annotations
Shawn Bowers, Timothy McPhillips, Bertram Ludäscher
An advantage of scientific workflow systems is their ability to collect runtime provenance information as an execution trace. Traces include the computation steps invoked as part o…