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In column-oriented query processing, a materialization strategy determines when lightweight positions (row IDs) are translated into tuples. It is an important part of column-store architecture, since it defines the class of supported query…
Memristive in-memory sorting has been proposed recently to improve hardware sorting efficiency. Using iterative in-memory min computations, data movements between memory and external processing units can be eliminated for improved latency…
Main memory column-stores have proven to be efficient for processing analytical queries. Still, there has been much less work in the context of clusters. Using only a single machine poses several restrictions: Processing power and data…
Process Mining is a branch of Data Science that aims to extract process-related information from event data contained in information systems, that is steadily increasing in amount. Many algorithms, and a general-purpose open source…
The unit commitment problem is an important optimization problem in the energy industry used to compute the most economical operating schedules of power plants. Typically, this problem has to be solved repeatedly with different data but…
Many organisations have a large network of connected computers, which at times may be idle. These could be used to run larger data processing problems were it not for the difficulty of organising and managing the deployment of such…
Developers perform online sensemaking on a daily basis, such as researching and choosing libraries and APIs. Prior research has introduced tools that help developers capture information from various sources and organize it into structures…
Database system architectures are undergoing revolutionary changes. Algorithms and data are being unified by integrating programming languages with the database system. This gives an extensible object-relational system where non-procedural…
At high energy physics experiments, processing billions of records of structured numerical data from collider events to a few statistical summaries is a common task. The data processing is typically more complex than standard query…
Physical data layout is an important performance factor for modern databases. Clustering, i.e., storing similar values in proximity, can lead to performance gains in several ways. We present an automated model to determine beneficial…
Skyline computation is an essential database operation that has many applications in multi-criteria decision making scenarios such as recommender systems. Existing algorithms have focused on checking point domination, which lack efficiency…
Tables, typically two-dimensional and structured to store large amounts of data, are essential in daily activities like database queries, spreadsheet manipulations, web table question answering, and image table information extraction.…
Modern in-memory databases are typically used for high-performance workloads, therefore they have to be optimized for small memory footprint and high query speed at the same time. Data compression has the potential to reduce memory…
A number of popular systems, most notably Google's TensorFlow, have been implemented from the ground up to support machine learning tasks. We consider how to make a very small set of changes to a modern relational database management system…
Anyone in need of a data system today is confronted with numerous complex options in terms of system architectures, such as traditional relational databases, NoSQL and NewSQL solutions as well as several sub-categories like column-stores,…
While clustering is one of the most popular methods for data mining, analysts lack adequate tools for quick, iterative clustering analysis, which is essential for hypothesis generation and data reasoning. We introduce Clustrophile, an…
In the past few decades, the life sciences have experienced an unprecedented accumulation of data, ranging from genomic sequences and proteomic profiles to heavy-content imaging, clinical assays, and commercial biological products for…
We present the design of a structured search engine which returns a multi-column table in response to a query consisting of keywords describing each of its columns. We answer such queries by exploiting the millions of tables on the Web…
Data compression schemes have exhibited their importance in column databases by contributing to the high-performance OLAP (Online Analytical Processing) query processing. Existing works mainly concentrate on evaluating compression schemes…
As an emerging field, MS-based proteomics still requires software tools for efficiently storing and accessing experimental data. In this work, we focus on the management of LC-MS data, which are typically made available in standard…