VALUE CREATION FROM DATA

The research is generally constructive in nature, meaning that the research concerns:

• The invention of purposeful artifacts, such as frameworks, algorithms, data structures, indexes, languages, and techniques, as well as tools, systems, and solutions based on such components.
• The construction of prototype software, typically either for proof-of-concept or for the purpose of conducting studies of the properties of the artifacts.

SCOPE

The research spans foundational topics as well as advanced applications and aims to take advantage of opportunities for cross-fertilization between foundational and applied research activities. The research also embraces a data science approach, where solutions to specific domain challenges are invented.

DATA

The research focuses on spatio-temporal, multidimensional, timeseries, sensor and metric data, but also contributes in relation to graph, IoT, and electroencephalogram (EEG) data.

TOPICS

The research concerns data management and analytics, including query processing, data mining, and machine learning. Examples include:

• Data management: data integration and data lakes, data warehousing, and indexing
• Analytics: prediction and forecasting, pattern and outlier detection, similarity search, advanced routing, transfer learning, greenhouse gas emissions estimation, spatial keyword querying, clustering, why-not querying

APPLICATIONS

While key applications are in the general areas of intelligent transportation and digital energy, the group covers a wider range of data-intensive applications. Example applications include:

• Flexible energy grids that enable the ongoing transformation of the electricity grid and society-wide electrification.
• Smart services for energy efficient buildings
• IoT data-based diagnostics and prediction in the renewable energy sector
• Adaptability and failure prediction in power electronics
  Learning of travel times and travel-time based routing in dynamic and road networks
• Advanced spatial crowdsourcing in transportation and beyond
• Maritime analytics, including energy efficient routing and speed recommendation
• Personal data retention and GDPR compliance
• EGG based data analysis pipelines for neurorehabilitation, motion intent detection, and emotion and activity recognition
• Analysis of complex microbial community interactions

RESEARCH APPROACH

The research approach is primarily constructive: theoretically well-founded, purposeful artefacts such as frameworks, data structures, indexes, algorithms, languages, tools, and systems are designed, and proof-of-concept prototypes are constructed in order to carry out empirical studies of the properties of the underlying artifacts.

Further, the research is often driven by novel and challenging real-world applications, with primary applications in intelligent transportation and digital energy.

The research has impact on (at least) SDGs 3, 4, 6, 7, 11, 12, and 13.