**10. Conclusion**

It is important to describe quality indicators that have no ambiguity of interpretation and to calculate their values accurately in a coherent way. To this end, we introduce a representation system of quality indicators, which consists of (i) an ontology of medical services, (ii) objective graphs to represent the objectives of quantification and an interpretation of objective graphs as sets, and (iii) quantifying concepts. We also briefly explain the whole image of our theoretical framework to define quality indicators and to calculate their values. Moreover, we explain a way to calculate the values of quality indicators based on the medical databases through an example of a quality indicator.

**9** 

*1France 2Germany*

**From Unstructured 3D Point Clouds to** 

*1Laboratoire Le2i, UFR Sciences et Techniques* 

*amFachbereichGeoinformatik und Vermessung, Mainz,* 

*2Fachhochschule Mainz, Institut i3mainz,* 

*Université de Bourgogne, Dijon,* 

**Structured Knowledge - A Semantics Approach** 

Helmi Ben Hmida, Christophe Cruz, Frank Boochs and Christophe Nicolle

Over the last few years, formal ontologies has been suggested as a solution for several engineer problems, since it can efficiently replace standard data bases and relational one with more flexibility and reliability. In fact, well designed ontologies own lots of positive aspects, like those related to defining a controlled vocabulary of terms, inheriting and extending existing terms, declaring a relationship between terms, and inferring relationships by reasoning on existent ones. Ontologies are used to represent formally the knowledge of a domain where the basic idea was to present knowledge using graphs and logical structure to make computers able to understand and process it, (Boochs, et al., 2011). As most recent works, the tendency related to the use of semantic has been explored, (Ben Hmida, et al., 2010) (Hajian, et al., 2009) (Whiting, 2006) where the automatic data extraction from 3D point clouds presents one of the new challenges, especially for map updating, passenger safety and security improvements. However such domain is characterized by a specific vocabulary containing different type of object. In fact, the assumption that knowledge will help the improvement of the automation, the accuracy and the result quality is shared by

As a matter of fact, surveying with 3D scanners is spreading all domains. Terrestrial laser scanners have been established as a workhorse for topographic and building survey from the archaeology (Balzani, et al., 2004) to the architecture (Vale, et al., 2009). Actually, with every new scanner model on the market, the instruments become faster, more accurate and can scan objects at longer distances. Such technology presents a powerful tool for many applications and has partially replaced traditional surveying methods since it can speed up field work significantly. Actually, this powerful method allows the creation of 3D point clouds from objects or landscapes. However, the huge amount of data generated during the process proved to be costly in post-processing. The field time is very height since in most cases; processing techniques are still mainly affected by manual interaction of the user. Typical operations consist to clean point clouds, to delete unnecessary areas, to navigate in an often huge and complicated 3D structure, to select set of points, to extract and model

**1. Introduction** 

specialists of the point cloud processing.

The proposed representation system plays a central role in the framework explained in Section 2, which enables medical staffs and patients, who desire to evaluate medical services, to define quality indicators and to calculate their values based on medical databases, without knowing the structure of the data models of them. Moreover, the representation system helps medical stuffs and system engineers, who develop or manage medical databases, collaborate in developing useful vocabularies to establish and standardize quality indicators.

## **11. References**

Abiteboul, S.; Hull, R. B. & Vianu, V. (1995). *Foundations of Databases*, Addison-Wesley.


http://www.internationalqip.com/index.aspx.

