ABSTRACT:Virtual Leodium is an interdisciplinary project aiming to develop an archaeological information system based on a city scale model. The first part of the paper describes current project's achievements; the general methodology and the workflow of the project, namely the production and the modelling of archaeological data; the prototype functions of the ad hoc developed archaeological information system. The second part of the paper presents our new Virtual Leodium archaeological information modelling approach, which aims at consider, in a more comprehensive way, the complexity of archaeological information.

Abstract. Museums are filled with hidden secrets. One of those secrets lies behind historical mock-ups whose signification goes far behind a simple representation of a city. We face the challenge of designing, storing and showing knowledge related to these mock-ups in order to explain their historical value. Over the last few years, several mock-up digitalisation projects have been realised. Two of them, Nantes 1900 and Virtual Leodium, propose innovative approaches that present a lot of similarities. This paper presents a framework to go one step further by analysing their data modelling processes and extracting what could be a generalized approach to build a numerical mock-up and the knowledge database associated. Geometry modelling and knowledge modelling influence each other and are conducted in a parallel process. Our generalized approach describes a global overview of what can be a data modelling process. Our next goal is obviously to apply this global approach on other historical mock-up, but we also think about applying it to other 3D objects that need to embed semantic data, and approaching historically enriched 3D city models.

The analysis of spectroscopic data to solve chemical structures requires practical skills and drills. In this context, we have developed ULg Spectra, a computer-based tool designed to improve the ability of learners to perform complex reasoning. The identification of organic chemical compounds involves gathering and interpreting complementary information from mass, infrared, Raman and nuclear magnetic resonance spectra. Here, special attention is paid to one-dimensional 1 H and 13 C NMR spectra and to two-dimensional NMR spectra because these techniques particularly require extensive interactive data manipulation. ULg Spectra offers tutorial-drill materials including spectra that are "authentic" in the sense that they contain solvent and impurity traces rather than being "idealized" spectra often found in textbook examples. A public version is accessible online free of charge. The exam results for two groups of students, one having used ULg Spectra for extra home-based training and the other not, were compared. Statistical data demonstrated higher performance for the "trained" students compared with the control group.

S The composition diagrams of the La Graufesenque, Banassac and Montans Terra Sigillata are given as well as a calculation method to improve the separation between the workshops with compositions which are very similar. This method can then be generalized.

Over the last decade, innovative computer technologies and the multiplication of geospatial data acquisition solutions have transformed the geographic information systems (GIS) landscape and opened up new opportunities to close the gap between GIS and the dynamics of geographic phenomena. There is a demand to further develop spatio-temporal conceptual models to comprehensively represent the nature of the evolution of geographic objects. The latter involves a set of considerations like those related to managing changes and object identities, modeling possible causal relations, and integrating multiple interpretations. While conventional literature generally presents these concepts separately and rarely approaches them from a holistic perspective, they are in fact interrelated. Therefore, we believe that the semantics of modeling would be improved by considering these concepts jointly. In this work, we propose to represent these interrelationships in the form of a hierarchical pyramidal framework and to further explore this set of concepts. The objective of this framework is to provide a guideline to orient the design of future generations of GIS data models, enabling them to achieve a better representation of available spatio-temporal data. In addition, this framework aims at providing keys for a new interpretation and classification of spatio-temporal conceptual models. This work can be beneficial for researchers, students, and developers interested in advanced spatio-temporal modeling.