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Information Technology


Master Projects
Amos II

SSPI: Scalable search of product life cycle information

This work is funded by SSF.

The goal of the SSPI project is to develop software systems for efficient and scalable search of product data and meta-knowledge produced during the entire product life cycle. It is intended to develop such software systems based on Data Stream Management Systems (DSMS) and the semantic web model.

The project is expected to produce (1) novel methods for scalable search in high volume data streams, (2) novel scalable methods to verify systems based on DSMS technology, (3) novel searchable semantic web based models to preserve product data, and (4) novel ways to verify the functioning of products in use.  The proposed project is further expected to produce software prototypes which demonstrate the feasibility of the developed approaches, software which in the hands of industrial partners may significantly improve their possibility of developing and selling functional products with increased service content.

Searching product data

As the volume of streaming data from products in use may be large, there is need for highly scalable DSMS technology to provide fast search in these streams. Furthermore, finding the relevant data streams require suitable meta-data representations and it is expected that semantic web representations such as RDF and RDF-Schema as very promising future knowledge representation languages for such data stream identification.  

Product Modelling and Simulation

The use of simulations in product development is continuously increasing, leading to an increased need of validation activities. In order to validate simulation models, measured real world data is needed. In the SSPI project it will be investigated how simulation models can be continuously verified by using a DSMS. The verification is made by continuously comparing measurement streams from products in use with the predicted behaviour generated by the simulation models. In case of deviations, the deviations may either indicate faulty behaviour of the product or incomplete or erroneous simulation models. In the latter case the simulation model needs to be further developed.  

Semantic Web Model Approach

Product models document product information along with the knowledge used by the people developing the product (for example design rationale). Knowledge about why something is designed a certain way (knowledge about knowledge) is called meta-knowledge. Efficient and scalable preservation, reuse, and search in meta-knowledge is of utmost importance in product developments. 

Long term preservation of product meta-knowledge and data requires representation languages that can describe information from regular databases, from product models, and from (archived) streams produced by products in use.

In the SSPI project it will be investigated how to preserve and search all different kinds of product information based on semantic web based meta-knowledge.

Project organization

Responsible for this project is Tore Risch. It is a collaboration with Lennart Karlsson at Lule University of Technology.

© 2009 Uppsala Universitet, Department of Information Technology, Box 337, 751 05 Uppsala, Sweden | This page is maintained by Tore Risch