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International audience; The long-term objective of the paper aims to provide decision aid support to a technical smart buildings manager to potentially reduce the emission of data produced by sensors inside a building and, more generally, to acquire knowledge on the data produced in the facility. As the first step, the paper proposes to characterize the smart-building ecosystem's Internetof-things (IoT) data sets. The description and the construction of learning models over data sets are crucial in engineering studies to advance critical analysis and serve diverse researchers' communities, such as architects or data scientists. We examine two data sets deployed in one location in the Grenoble area in France. We assume that the building is an autonomic computing system. Thus, the underlying model we deal with is the wellknown MAPE-K methodology introduced by IBM. The paper mainly addresses the analysis component and the adjacent connector component of the MAPE-K model. The content of this layer, and its organization, constitutes the methodological point we put forward. Consequently, we automatically provide a complete set of practices and methods to pass to the planning component of the MAPE-K model. We also sketch a semiautomatic way of reducing the number of measures done by sensors. In the background of our study, we aim to reduce the operational cost of making measures with a much more sober approach than the current one. We also discuss in profound the main findings of our work. Finally, we provide insights and open questions for future outcomes based on our experience.

Today, the Network Slicing technology is massively addressed by the research community. However, Network Slice (NS) modelling details from Standards Developing Organizations (SDOs) are not yet well considered for End-to-End (E2E) NS implementations. In addition, each SDO develops standards targeting only a specific part of the NS architecture. Therefore, based on a profound analysis of the major existing works, this article explains first (i) a general architecture that clarifies the basic E2E network slicing functionality before diving deep into domain-specific visions. Then, (ii) it focuses at providing a survey stitching together the NS modelling works in Radio Access Networks (RAN), Core Networks (CN) and also Transport Networks (TN). The end goal is to clarify the E2E Network Slicing process from the service order request to the NS deployment and life-cycle management. Last, as there is no consensus on a specific information model in the Transport network domains (iii) we provide our vision on how several data models, developed by IETF working groups, can be integrated together in the context of the ACTN architecture in order to provision and manage Transport NSs.