The Web of Data has emerged as a means to expose, share, reuse, and connect information on the Web identified by URIs using RDF as a data model, following Linked Data Principles. However, the reuse of third party data can be compromised without proper data quality assessments. In this context, important questions emerge: how can one trust on published data and links? Which manipulation, modification and integration operations have been applied to the data before its publication? What is the nature of comparisons or transformations applied to data during the interlinking process? In this scenario, provenance becomes a fundamental element. In this paper, we describe an approach for generating and capturing Linked Open Provenance (LOP) to support data quality and trustworthiness assessments, which covers preparation and format transformation of traditional data sources, up to dataset publication and interlinking. The proposed architecture takes advantage of provenance agents, orchestrated by an ETL workflow approach, to collect provenance at any specified level and also link it with its corresponding data. We also describe a real use case scenario where the architecture was implemented to evaluate the proposal.

Most modern aircraft engines rely on the use of high Bypass Ratios (BPR) turbofans to achieve both high thrust and low specific fuel consumption. However, such configurations are prone to the formation of ground vortices during low-speed operations. This phenomenon arises under specific combinations of wind direction, velocity or inlet air speed, generating engine vibrations and leading to the suction of damaging abrasive particles. Its characterization in early design stages is crucial. In this work, a joint experimental and numerical exploration of operating conditions leading to ground vortex presence is carried out on a scaled wind tunnel configuration. Flow details are investigated for several working points obtained from a specific set of input parameters (intake speed, wind speed, ground clearance). A methodology suitable for both experimental and Computational Fluid Dynamics (CFD) works is developed to extract vortex characteristic quantities, based on a local pressure minimum and Q-criterion contours topology. A very good agreement is obtained when comparing vortex predictions stemming from CFD and experiments. This database shall be used to transpose experimental data probed outside of the nacelle to data within the nacelle using data analytics techniques, paving the way for future data driven predictive models.