Abstract
Information overload is a severe problem for operators of
large-scale control systems, as such systems typically provide a vast amount of information about a large number of
real-world objects. Systems supporting situation awareness
have recently gained attention as way to help operators to
grasp the overall meaning of available information. To fulfill
this task, data quality has to be ensured by assessment and
improvement strategies. In this paper, a vision towards a
methodology for data quality assessment and improvement
for situation awareness systems is presented.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 8th International Workshop on Quality in Databases, QDB 2010 |
| Number of pages | 5 |
| Publication status | Published - 2010 |
Fields of science
- 101004 Biomathematics
- 101027 Dynamical systems
- 101028 Mathematical modelling
- 101029 Mathematical statistics
- 101014 Numerical mathematics
- 101015 Operations research
- 101016 Optimisation
- 101017 Game theory
- 101018 Statistics
- 101019 Stochastics
- 101024 Probability theory
- 101026 Time series analysis
- 102 Computer Sciences
- 102001 Artificial intelligence
- 102003 Image processing
- 102004 Bioinformatics
- 102013 Human-computer interaction
- 102018 Artificial neural networks
- 102019 Machine learning
- 103029 Statistical physics
- 106005 Bioinformatics
- 106007 Biostatistics
- 202017 Embedded systems
- 202035 Robotics
- 202036 Sensor systems
- 202037 Signal processing
- 305901 Computer-aided diagnosis and therapy
- 305905 Medical informatics
- 305907 Medical statistics
- 102032 Computational intelligence
- 102033 Data mining
- 101031 Approximation theory
- 102002 Augmented reality
- 102006 Computer supported cooperative work (CSCW)
- 102015 Information systems
- 102021 Pervasive computing
- 102025 Distributed systems
- 102027 Web engineering
- 202038 Telecommunications