UBIWARE project, Deliverable 3


Deliverable 3.2

Industrial Cases

The objective of this workpackage is to trial UBIWARE on real industrial cases. This has two major goals for such case studies. The first goal is to evaluate the scientific concepts behind UBIWARE and to find problems and issues in UBIWARE that would otherwise be overlooked. The second goal is to facilitate the further utilization of UBIWARE in the industry. Several specific cases, proposed by the industrial partners, are analyzed, designed and prototyped based on the UBIWARE platform. The reasons for prototyping are the same: to identify issues in UBIWARE that would get overlooked if the work was only theoretical and thus abstract, and to demonstrate the benefits of UBIWARE in a tangible way so to facilitate future industrial adoption. There are three industrial cases, those of Fingrid, Inno-W and Metso Automation.

Fingrid case:

With respect to the UBIWARE approach and platform, Fingrid’s main area of interest is in organizing smart data management related to the events/alarms which company gets from their control systems. Existing systems do not provide many possibilities for managing this data beyond storing it to a time-series log, and browsing it with some filtering possibilities. A wish is to that the data should get flexibly accessible, integrated with other related data, and possibilities should be provided for producing generalizing reports to the power system operation and asset management persons.

Inno-W case:

The plan for the implementation of industrial cases for Inno-W Company was to elaborate adapter for a real RDF data storage of proposals to be browsed through 4I (FOR EYE) Browser in the context of close/similar resources. This case is a test bed for a research and development within the WP5.

Metso Automation case:

Metso industrial case was selected to be a test bed for a research and development within the WP2 (Distributed Querying and Integration) because of its “distributed nature” and big amounts of data in storages, that can not be collected in one place. We integrate event flow data (events from monitoring and diagnostic systems) together with the structural and design data to provide a convenient assistant tool for an expert in diagnostics. In the new version of the prototype we have made a manager for the components/Ontonuts developed. The manager provides functionality for editing and making test runs for the newly updated component descriptions.


Deliverable 3.2, Technical Report
Deliverable 3.2, Presentation