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.

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Dealing with historical knowledge implies specific approaches. Then, modeling it and the different know-hows involved is a complex task. Indeed, patrimonial objects are historical witnesses whose life cycle is hard to handle. In this paper, we discuss possibilities of managing such heterogeneous content through a PLM system dedicated to historical knowledge and museum. Based on previous research in the field of ancient advanced archaeology, we demonstrate our process through an industrial research and development project with a history museum.

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International audienceAlong the product life-cycle, industrial processes generate massive digital assets containing precious information. Besides structured databases, written reports hold unstructured information hardly exploitable due to the lack of vocabulary and syntax standardization. In this paper we present a methodology and natural language processing approach to exploit these documents. Our method consists in providing connections based on supervised retrieval of domain-specific expressions. No prior document analysis are required to drive the algorithm. It underlines a scale of specificity in pattern visualization. This allows relevant and specific information extraction for feedback (e.g. design stage, after-sales service)

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In this article we present a multidisciplinary experimentation realized between a mechanical laboratory, a computer scientist laboratory and a museum. Our goal is to provide automatic tools for non-expert people who want to use 3D digitized elements. After scanning an objet, we obtain a huge amount of points. In order to manipulate it, it is necessary to decimate it. However, when doing this operation, we can optimize the algorithms for creating semantic topology; obviously we can do it automatically. Consequently, we are going to do what we name segmentation: we extract meaning from 3D points and meshes. Our experimentation deals with a physical mock-up of Nantes city that have been designed in 1900. After digitalization, we have created a software that can: 1. use the whole 3D cloud of points as an input; 2. fill a knowledge database with an intelligent segmentation of the 3D virtual models: ground, walls, roofs… This use case is the first step of our research. At the end, we aim to deploy our method to complex mechanical parts. Nowadays, when designing CAD parts we use as well as volume parts than surface parts or meshes. We know is it not necessary to reconstruct all the triangles. It is a lost of time and we can directly use cloud of points for CAD design. However, the design tree will not be updated. So, with our method, imagine that one day we can digitalize a motor and a system could automatically create the 3D mock-up and the design tree.

In this article we propose a new way for enriching technical models that drive contemporary enterprise. Our proposition is to take into account a new stage in the object lifecycle: at its end, it enters into a new phase that we call “heritage lifecycle”. Indeed, many old technical objects fall in ruins and are destroyed after their uses. After capitalization, we propose to conserve them virtually. Thanks to virtual tools coupled to database, it will help us to define a new information system for driving the long life cycle of objects: it is the Digital Heritage Reference Model, DHRM. This information system will be implemented in a new PLM dedicated to museum, place where know-how and mankind’s knowledge is stored and promoted when possible. Museum-related PLM would eventually interact with enterprises PLM as a bijective enrichment.