| 1. |
- Kajko-Mattsson, Mira, et al.
(author)
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Refounding software engineering : The Semat initiative (Invited presentation)
- 2012
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In: Software Engineering (ICSE), 2012 34th International Conference on. - : IEEE Computer Society. - 9781467310673 ; , s. 1649-1650
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Conference paper (peer-reviewed)abstract
- The new software engineering initiative, Semat, is in the process of developing a kernel for software engineering that stands on a solid theoretical basis. So far, it has suggested a set of kernel elements for software engineering and basic language constructs for defining the elements and their usage. This paper describes a session during which Semat results and status will be presented. The presentation will be followed by a discussion panel.
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| 2. |
- Berre, A. -J, et al.
(author)
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Model driven service interoperability through use of semantic annotations
- 2009
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In: Proceedings - 2009 International Conference on Interoperability for Enterprise Software and Applications, IESA 2009. - : IEEE Computer Society. - 9780769536521 ; , s. 90-96
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Conference paper (peer-reviewed)abstract
- This paper presents an approach for comparing two architectures for ontology-based semantic annotation for service interoperability, the EMPOWER architecture using platform specific XML-based technologies and the MEMPOWER architecture extending this with platform independent Model Driven Architecture (MDA) based technologies. We will compare the two architectures with respect to pilot requirements and experienced advantages and challenges for model driven systems. The two approaches are being evaluated based on examples from interoperability between ERP-systems in a Buyer/Seller interaction context.
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| 3. |
- Roman, D., et al.
(author)
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Big Data Pipelines on the Computing Continuum : Ecosystem and Use Cases Overview
- 2021
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In: Proceedings - IEEE Symposium on Computers and Communications. - : Institute of Electrical and Electronics Engineers Inc..
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Conference paper (peer-reviewed)abstract
- Organisations possess and continuously generate huge amounts of static and stream data, especially with the proliferation of Internet of Things technologies. Collected but unused data, i.e., Dark Data, mean loss in value creation potential. In this respect, the concept of Computing Continuum extends the traditional more centralised Cloud Computing paradigm with Fog and Edge Computing in order to ensure low latency pre-processing and filtering close to the data sources. However, there are still major challenges to be addressed, in particular related to management of various phases of Big Data processing on the Computing Continuum. In this paper, we set forth an ecosystem for Big Data pipelines in the Computing Continuum and introduce five relevant real-life example use cases in the context of the proposed ecosystem.
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