Communications of the ACM
Models and issues in data stream systems
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Balancing energy efficiency and quality of aggregate data in sensor networks
The VLDB Journal — The International Journal on Very Large Data Bases
DBNotes: a post-it system for relational databases based on provenance
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
A survey of data provenance in e-science
ACM SIGMOD Record
MONDRIAN: Annotating and Querying Databases through Colors and Blocks
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
SPC: a distributed, scalable platform for data mining
Proceedings of the 4th international workshop on Data mining standards, services and platforms
The provenance of electronic data
Communications of the ACM - The psychology of security: why do good users make bad decisions?
OGC® Sensor Web Enablement: Overview and High Level Architecture
GeoSensor Networks
Supporting annotations on relations
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Representing Data Quality for Streaming and Static Data
ICDEW '07 Proceedings of the 2007 IEEE 23rd International Conference on Data Engineering Workshop
Infrastructure for Data Processing in Large-Scale Interconnected Sensor Networks
MDM '07 Proceedings of the 2007 International Conference on Mobile Data Management
Representing Data Quality in Sensor Data Streaming Environments
Journal of Data and Information Quality (JDIQ)
A letter soup for the quality of information in sensor networks
PERCOM '09 Proceedings of the 2009 IEEE International Conference on Pervasive Computing and Communications
Semantic middleware for e-science knowledge spaces
Proceedings of the 7th International Workshop on Middleware for Grids, Clouds and e-Science
PIKM 2010: ACM workshop for ph.d. students in information and knowledge management
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Emerging multidisciplinary research across database management systems
ACM SIGMOD Record
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In the field of e-science stream data processing is common place facilitating sensor networks, in particular for prediction and supporting decision making. However, sensor data may be erroneous, like e.g. due to measurement errors (outliers) or changes of the environment. While it can be foreseen that there will be outliers, there are a lot of environmental changes which are not foreseen by scientists and therefore are not considered in the data processing. However, these unforeseen semantic changes - represented as annotations - have to be propagated through the processing. Since the annotations represent an unforeseen, hence un-understandable, annotation, the propagation has to be independent of the annotation semantics. It nevertheless has to preserve the significance of the annotation on the data despite structural and temporal transformations. And should remain meaningful for a user at the end of the data processing. In this paper, we identify the relevant research questions.In particular, the propagation of annotations is based on structural, temporal, and significance contribution. While the consumption of the annotation by the user is focusing on clustering information to ease accessibility.