Lithium-ion batteries are promising energy storage devices for electric vehicles and
renewable energy systems. However, due to complex electrochemical processes, potential …

Data quality management, especially data cleansing, has been extensively studied for many
years in the areas of data management and visual analytics. In the paper, we first review and …

Data cleaning is an important problem and data quality rules are the most promising way to
face it with a declarative approach. Previous work has focused on specific formalisms, such …

This paper presents the design of a read-optimized relational DBMS that contrasts sharply
with most current systems, which are write-optimized. Among the many differences in its …

Data quality is one of the most important problems in data management. A database system
typically aims to support the creation, maintenance and use of large amount of data …

In previous papers [SC05, SBC+ 07], some of us predicted the end of" one size fits all" as a
commercial relational DBMS paradigm. These papers presented reasons and experimental …

We introduce a few-shot learning framework for error detection. We show that data
augmentation (a form of weak supervision) is key to training high-quality, ML-based error …

The last 25 years of commercial DBMS development can be summed up in a single phrase:"
One size fits all". This phrase refers to the fact that the traditional DBMS architecture …

Online Transaction Processing (OLTP) databases include a suite of features---disk-resident
B-trees and heap files, locking-based concurrency control, support for multi-threading---that …

The currently operational (March 1976) version of the INGRES database management
system is described. This multiuser system gives a relational view of data, supports two high …