Data lineage describes the relationship between individual input and output data items of a
workflow, and has served as an integral ingredient for both traditional (eg, debugging …

Data processing pipelines that are designed to clean, transform and alter data in preparation
for learning predictive models, have an impact on those models' accuracy and performance …

Data provenance has evolved from a niche topic to a mainstream area of research in
databases and other research communities. This article gives a comprehensive introduction …

Query optimization remains one of the most challenging problems in data management
systems. Recent efforts to apply machine learning techniques to query optimization …

Successful data-driven science requires complex data engineering pipelines to clean,
transform, and alter data in preparation for machine learning, and robust results can only be …

We present an overview of GProM, a generic provenance middleware for relational
databases. The sys-tem supports diverse provenance and annotation management tasks …

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 …

The state-of-the-art approaches for tracking data provenance on high-performance
computing (HPC) systems are either supported by file systems or relational databases …

SQL declaratively specifies what the desired output of a query is. This work shows that a non-
standard interpretation of the SQL semantics can, instead, disclose where a piece of the …

Blockchain is an enabler of many emerging decentralized applications in areas of
cryptocurrency, Internet of Things, smart healthcare, among many others. Although various …