A Data Streams Processing Platform for Matching Information Demand and Data Supply

Information Systems Engineering in Responsible Information Systems: CAiSE Forum 2019: Proceedings. Lecture Notes in Business Information Processing. Vol.350 2019
Jānis Grabis, Jānis Kampars, Krišjānis Pinka, Jānis Pekša

Data-driven applications are adapted according to their execution context, and a variety of live data is available to evaluate this contextual information. The BaSeCaaS platform described in this demo paper provides data streaming and adaption services to the data driven applications. The main features of the plat-form are separation of information requirements from data supply, model-driven configuration of data streaming services and horizontal scalable infrastructure. The paper describes conceptual foundations of the platform as well as design of data stream processing solutions where matching between information demand and data supply takes please. Light-weight open-source technologies are used to implement the platform. Application of the platform is demonstrated using a win-ter road maintenance case. The case is characterized by variety of data sources and the need for quick reaction to changes in context.

Keywords
Data stream, adaptation, context, model-driven
DOI
10.1007/978-3-030-21290-2
Hyperlink
https://link.springer.com/book/10.1007%2F978-3-030-21290-2

Grabis, J., Kampars, J., Pinka, K., Pekša, J. A Data Streams Processing Platform for Matching Information Demand and Data Supply. In: Information Systems Engineering in Responsible Information Systems: CAiSE Forum 2019: Proceedings. Lecture Notes in Business Information Processing. Vol.350, Italy, Rome, 3-7 June, 2019. Cham: Springer, 2019, pp.111-119. ISBN 978-3-030-21296-4. e-ISBN 978-3-030-21297-1. Available from: doi:10.1007/978-3-030-21290-2

Publication language
English (en)