**2.1 The domain of the industrial archaeology: a case study**

The domain of the Industrial archaeology is the recording, study, interpretation and preservation of the physical remains of the industrially related artifacts, sites and systems within their social and historical contexts (Clouse, 1995). During the period of 18th and 19th century the industrial revolution started from the United Kingdom and spread across the world marking a major turn of the human civilization. In the course of time the industries established during the period were abandoned and replaced by new installments. These abandoned sites however hide many important histories of modern developments which need to be preserved as historical facts. Today, the domain of the industrial archaeology has occupied its position in the archaeological community as a mainstream branch of archaeology which deals with the history of constructions, the development architecture, the history of technologies, socio-economic and cultural history (Boochs, 2009). The domain of the industrial archaeology has its own challenges. It does not involve the excavation process and just documents the standing artefacts in contrast to the conventional archaeology, so the discipline was initially considered as hobby archaeology and not a mainstream archaeology. Though the branch has now been taken more seriously by its contemporary branches, it still needs acceptance by the wider community as the awareness about the importance of this field in archaeology is still minimal. The lack of acceptance has its own impact here as there is no reliable tool to document the artifact as the classical archaeology and hence large scale of existing relicts get lost forever. Usually the industrial archaeological sites are available for limited amount of time as they are not mostly conserved for continuous excavation and they are most often the sites for new constructions. Adding on, the advancement of current data capturing technologies made it possible to capture huge and heterogeneous datasets in this limited duration. It is absolutely not possible to manage this nature of datasets in such a limited amount of time without the intervention of machine to assist human. It thus requires human machine collaboration to manage them which is not possible through the conventional technologies.

The project points out these limitations and provides a prospective solution to handle the dataset through the knowledge possessed by the archaeologists and facilitated by knowledge management tools within Semantic Web technology. This section presents the case study site used within this research work discussing the diversity and amount of data acquired through the modern technologies.

#### **2.2 The main excavation area**

The main excavation area lies in Krupp area in Essen belt, Germany. The 200 hectares area was used for steel production during early 19th century. The work on steel production has a critical impact on the settlement development of Essen. In this way the history of Essen is 158 Semantics – Advances in Theories and Mathematical Models

data collected during the excavation process. It then reviews the current Information Systems that are either being implemented or researched in this domain. It includes the usages of Geographic Information Systems (GIS) in this field. Then after, the chapter continues with the introduction of the ArchaeoKM project through discussion on the principle and how it is different from the existing systems. It concludes with a discussion on

The domain of the Industrial archaeology is the recording, study, interpretation and preservation of the physical remains of the industrially related artifacts, sites and systems within their social and historical contexts (Clouse, 1995). During the period of 18th and 19th century the industrial revolution started from the United Kingdom and spread across the world marking a major turn of the human civilization. In the course of time the industries established during the period were abandoned and replaced by new installments. These abandoned sites however hide many important histories of modern developments which need to be preserved as historical facts. Today, the domain of the industrial archaeology has occupied its position in the archaeological community as a mainstream branch of archaeology which deals with the history of constructions, the development architecture, the history of technologies, socio-economic and cultural history (Boochs, 2009). The domain of the industrial archaeology has its own challenges. It does not involve the excavation process and just documents the standing artefacts in contrast to the conventional archaeology, so the discipline was initially considered as hobby archaeology and not a mainstream archaeology. Though the branch has now been taken more seriously by its contemporary branches, it still needs acceptance by the wider community as the awareness about the importance of this field in archaeology is still minimal. The lack of acceptance has its own impact here as there is no reliable tool to document the artifact as the classical archaeology and hence large scale of existing relicts get lost forever. Usually the industrial archaeological sites are available for limited amount of time as they are not mostly conserved for continuous excavation and they are most often the sites for new constructions. Adding on, the advancement of current data capturing technologies made it possible to capture huge and heterogeneous datasets in this limited duration. It is absolutely not possible to manage this nature of datasets in such a limited amount of time without the intervention of machine to assist human. It thus requires human machine collaboration to manage them which is not possible through the

The project points out these limitations and provides a prospective solution to handle the dataset through the knowledge possessed by the archaeologists and facilitated by knowledge management tools within Semantic Web technology. This section presents the case study site used within this research work discussing the diversity and amount of data

The main excavation area lies in Krupp area in Essen belt, Germany. The 200 hectares area was used for steel production during early 19th century. The work on steel production has a critical impact on the settlement development of Essen. In this way the history of Essen is

the future prospective of the work.

conventional technologies.

**2.2 The main excavation area**

acquired through the modern technologies.

**2.1 The domain of the industrial archaeology: a case study**

closely related to the activities of steel production in Krupp. The site grew over the decades and formed a so-called Krupp Belt. The site was destroyed during the Second World War. Most of the area is never rebuilt. In between 1945 to 2007, the area was basically a wasteland making it an ideal site for an industrial archaeological excavation. However, the ThyssenKrupp is returning to build its new headquarters in the site by then 2010. This has raised the problem of limitation of time period for a proper management of the recovered objects. The objects are recorded as soon as they are recovered and these records are stored in a repository in their respective data formats. Hence, there is a clear lack of well-defined structure for data management. Moreover, in contrast to the conventional archaeology where the data collection and data analysis goes side by side so in that case the data structure could be designed at the beginning, the data analysis is carried out at the end in industrial archaeology so it is not possible to perceive the structure of the data at the beginning. The first challenge consists of creating a proper data structure which helps in retrieving those data efficiently. As there was not enough time to filter the collected data concurrently, the amount of data that are collected is huge. Hence, the system that has to handle the collection of data should be able to handle this huge set.

Archaeologists with assistance of photogrammetric specialists were involved in data acquisition process. They were responsible to decide the methods of measurements. The findings were scanned through terrestrial laser scanning instruments. Two scanners were used to acquire the scanned data. They were the Zöller and Fröhlich scanner (ZF) and the Riegl scanner. Those two scanners were used according to their requirement. Large objects scanning were carried out with the help of the Riegl scanner whereas the ZF scanner is used whenever some important findings are recovered. The Riegl scanner was installed on the roof of the Kreuzhaus (the building marked at the bottom of the site in figure 1) so that the scanner gets a good overview of the area. The findings were scanned with a resolution of 0.036 degrees (6 mm on 10 m) hence the point cloud is very dense. All the data were stored in the Gauß Krüger zone II (GK II) coordinate system.

An orthophoto was orthorectified from the aerial images (that were taken during the course of research work). The orthophoto has 10 cm resolution and is in GK II coordinate system. Huge numbers of digital pictures were taken during the research activities and they were stored in their original formats. These photos were taken with non-calibrated digital cameras. However, certain knowledge can be extracted from them by the archaeologists. Besides, photographs documents like the site plan of the area and some documents with relevant information of the site or the objects recovered were collected during data acquisition process. These data and documents were digitized and stored for proper mapping with the relevant objects. Archaeological notes taken by archaeologists during these excavation processes are of high importance. Hence, these notes are digitized and stored in the repository. Similarly, the site plan of the area was digitized and stored as .shp format in ArcGIS.

The nature of the dataset that was collected during the research work is varied. There are four distinct kinds of data which ranges from textual documents as the archaeological notes to multimedia documents as images. The heterogeneity of dataset is evident through the nature of each type of dataset varying completely from others in terms of their storages, presentations and implementations.

Spatialization of the Semantic Web 161

The database management system, involving conceptual and logical data modeling is an important part of GIS because it ensures that the construction and the maintenance of database is done and that the spatial and aspatial datasets and components are correctly

Some limitations appear visible in currents GIS system in the context of the Industrial Archaeology. The lack of GIS platforms that uses data like point cloud is one of such visible limitations. It however is a fact that conventionally an Information System for archaeologists is a Geographic Information System or 3D object modelling system. The statement has been supported by the current commercial applications for the archaeologists. Applications like ArchaeoCAD from ArcTron and PointCloud from Kubit rely heavily on the geometry of the objects excavated. The applications are thus used primarily to represent objects excavated in a 3D space. Similarly, GIS vendors like ESRI uses the spatial information of the objects to analyze them spatially. Meanwhile, the data collection process has seen a tremendous change in the last few years. Today, it is not only the amount of data that needs consideration, the diversity of data should also be taken into account. It is becoming increasingly difficult to manage them solely with the current database system due to the size and diversity of the data. In addition, information systems in archaeological projects or cultural heritage projects lacks from a complete package. There have been lots of researches going on but they are on the independent components. However, research projects like 3D MURALE (Cosmas et al., 2001) and GIS DILAS (Wüst et al., 2004) contains most of the elements needed for a complete package and hence could be considered as comprehensive Information System. The 3D MURALE system is composed of a recording component, a reconstruction component, a visualization component and database components. The findings are managed through a database management system. Once the findings are stored in the database with a proper data structure, the objects are reconstructed through the reconstruction component. This is done by modeling the objects in the 3D space. These 3D models are displayed in the visualization component. The DILAS is generic software, fully object oriented model for 3D geo-objects. The 3D geometry model is based on a topological boundary representation and supports most basic geometry types. It also incorporates the concept of multiple levels of detail (LOD) (Balletti et al., 2005) as well as texture information. It is thus clear that the existing systems rely heavily on the geometries of excavated objects

Fig. 2. The five main groups of tasks performed by GIS.

linked.

Fig. 1. The main excavation area Site.
