**2.3 GIS for archaeology**

What does a GIS do? Basically providing a definition of GIS and referring to its abilities to capture and manipulate spatial data doesn't provide much insight into its functionality. The basic tasks of a GIS system can be broken down into five groups, data acquisition, spatial data management, database management, data visualization and spatial data analysis (Jones, 1997). Most archaeological data such as artifacts, features, buildings, sites or landscapes, have spatial and aspatial attributes that can be explored by GIS. These attributes include the spatial location that informs about the local or global context concerning the pieces of information, and the morphology that defines the shape and the size of an object.

The acquisition of spatial data is undertaken with the help of existing digitizing functionalities within the application software providing them. They are responsible for the acquisition of data and integrating it to the existing spatial sets. Spatial data include, but are not limited to, topographic maps, site locations and morphology, archaeological plans, artifacts distribution, aerial photography, geophysical data and satellite imagery.

The spatial data management process uses sophisticated database management systems in order to store and retrieve spatial data and their attributes. Data collected from different sources have to be transformed in the same coordinate system in order to integrate them.

160 Semantics – Advances in Theories and Mathematical Models

What does a GIS do? Basically providing a definition of GIS and referring to its abilities to capture and manipulate spatial data doesn't provide much insight into its functionality. The basic tasks of a GIS system can be broken down into five groups, data acquisition, spatial data management, database management, data visualization and spatial data analysis (Jones, 1997). Most archaeological data such as artifacts, features, buildings, sites or landscapes, have spatial and aspatial attributes that can be explored by GIS. These attributes include the spatial location that informs about the local or global context concerning the pieces of information, and the morphology that defines the shape and the size of an object. The acquisition of spatial data is undertaken with the help of existing digitizing functionalities within the application software providing them. They are responsible for the acquisition of data and integrating it to the existing spatial sets. Spatial data include, but are not limited to, topographic maps, site locations and morphology, archaeological plans,

artifacts distribution, aerial photography, geophysical data and satellite imagery.

The spatial data management process uses sophisticated database management systems in order to store and retrieve spatial data and their attributes. Data collected from different sources have to be transformed in the same coordinate system in order to integrate them.

Fig. 1. The main excavation area Site.

Kreuzhaus

**2.3 GIS for archaeology**

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 linked.

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

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

Spatialization of the Semantic Web 163

The project ArchaeoKM plans to complement the principle of knowledge management by implementing it in the application through formulating the knowledge rules that can be used by archaeologists on the excavated data. The knowledge stored in machine readable format is inferred to bring result which could be well understood by human. Moreover, it moves beyond managing the concepts defined to annotate documents, which most of the research projects currently focusing on, to the instances of concepts with their own property values. In this manner, an object found in a point cloud can be linked, with the help of an instance in the ontology to other documents (a part in an image or a section of archive document)

One of the main focuses on ArchaeoKM project is to determine an approach of integrating the spatial data within its overall framework of data integration. The integration process did not only serve for the data integration but also has taken a step forward in data analysis and

The challenges possessed to document the artifacts in such a site could be handled through utilizing the knowledge of responsible archaeologists. The platform ArchaeoKM focuses on the use of the knowledge of archaeologists to document the objects with respect to the surrounding. In the process a tool based on the Semantic Web technology and its underlying knowledge technology was develop to provide the archaeologists to share their knowledge and document the information collected during the excavation process. One of the challenges is to bring all the datasets previously presented in one common platform. As a knowledge representation format, the top level ontology acts as the global schema for data integration in the platform. The application tool provides a common platform for

The GIS technology performs a group of five tasks to execute the result. These tasks as already been mentioned are acquisition of spatial data, spatial data management, database management, spatial data analysis and the spatial data visualization. The ArchaeoKM project attempts to complement the five major processing steps of a GIS through its four processing activities which it calls the processing steps of 4Ks: knowledge acquisition,

The knowledge acquisition task consists in general term defines metadata on data acquired during the survey process. The spatial data acquisition process is still involved during the process, but in addition metadata on these data are defined using a knowledge representation language. Actually, an ontology, which defines the semantic of the recovered features, is defined to capture and capitalized the knowledge of archeologists on the archaeological site. Hence the schema of the ontology is defined at this level. This is done by the help of a specialist on ontologies. The relationships and their semantics are stored into the ontology. This semantic could be provided through an example of the relation of "insideOf" which is transitive relationship. In mathematics, a binary relation R over a set X is transitive if whenever an element a is related to an element b, and b is in turn related to an

management through the knowledge management techniques.

archaeologists to share their experience and knowledge.

knowledge management, knowledge visualization, knowledge analysis.

**2.4 Towards knowledge processing**

that contains the same object.

**2.4.1 The web platform ArchaeoKM**

**2.4.2 The ArchaeoKM architecture**

for their representations, but the interoperability of these systems and the knowledge sharing remains a gap.

In addition, the sharing of knowledge in archaeology and disseminate it to the general public through wiki has been discussed in (Costa & Zanini, 2008). Likewise the use of knowledge to build up a common semantic framework has been discussed in (Kansa, 2008). Research works in data interoperability exist in the field of archaeology, but most of the research is carried out in other related fields. However, it could be applied in archaeology as well. The existing researches focus more on using the common language for efficient interoperability. The research project (Kollias, 2008) concerns the achieving syntactic and semantic interoperability through ontologies and the RDF framework to build a common standard. Data integration through ontologies and their relationships is discussed in (Doerr, 2008). Although the work on the Semantic Web and knowledge management in the field of Information System in Archaeology or related fields is stepping up with these research works, the fact is they are in very preliminary phases. Additionally, these projects concentrate more on how to achieve interoperability with semantic frameworks and ontologies. However, none of them focuses on the knowledge generation process and more specifically on rules defined by archaeologists in order to build up the system which should use, evaluate and represent the knowledge of the archaeologists.

Knowledge contained in documents has been traditionally managed through the use of metadata. Before going on details about knowledge management, let us first understand the perspective about the whole idea. Every activity begins with data. However data is meaningless until they are put in context of space or an event. Additionally, unless the relationship between different pieces of data is defined, simply data do not have any significance. Once the data are defined in terms of space or events and are defined through relationships, they become Information. Information understands the nature of the data but they do not provide the reasons behind the existence of data and are relatively static and linear by nature. Information is a relationship between data and, quite simply, is what it is, with great dependence on context for its meaning and with little implication for the future (Bellinger, 2004). Beyond every relationship, arises a pattern which has capacity to embody completeness and consistency of the relations to an extent of creating its own context (Bateson, 1979). Such patterns represent knowledge on the information and consequently on data. The term Knowledge Management has wide implications. However, very precisely Knowledge Management is about the capture and reuse of knowledge at different knowledge level. In order to access the knowledge, data are annotated and indexed in the knowledge base. This is in line to the concept proposed by Web Semantic where it proposes to annotate the document content using semantic information from domain ontologies (Berners-Lee et al., 2001). The goal is to create annotations with well-defined semantics so they can be interpreted efficiently. Today, in the context of Semantic Web, the contents of a document can be described and annotated using RDF and OWL. The result is a set of Web documents interpretable by machine with the help of mark-ups. With such Semantic Web annotation, the efficiency of information retrieval is enhanced and the interoperability is improved. The information retrieval is improved by the ability to perform searches, which exploit the ontology in order to make inferences about data from heterogeneous resources (Welty & Ide, 1999).

162 Semantics – Advances in Theories and Mathematical Models

for their representations, but the interoperability of these systems and the knowledge

In addition, the sharing of knowledge in archaeology and disseminate it to the general public through wiki has been discussed in (Costa & Zanini, 2008). Likewise the use of knowledge to build up a common semantic framework has been discussed in (Kansa, 2008). Research works in data interoperability exist in the field of archaeology, but most of the research is carried out in other related fields. However, it could be applied in archaeology as well. The existing researches focus more on using the common language for efficient interoperability. The research project (Kollias, 2008) concerns the achieving syntactic and semantic interoperability through ontologies and the RDF framework to build a common standard. Data integration through ontologies and their relationships is discussed in (Doerr, 2008). Although the work on the Semantic Web and knowledge management in the field of Information System in Archaeology or related fields is stepping up with these research works, the fact is they are in very preliminary phases. Additionally, these projects concentrate more on how to achieve interoperability with semantic frameworks and ontologies. However, none of them focuses on the knowledge generation process and more specifically on rules defined by archaeologists in order to build up the system which should

Knowledge contained in documents has been traditionally managed through the use of metadata. Before going on details about knowledge management, let us first understand the perspective about the whole idea. Every activity begins with data. However data is meaningless until they are put in context of space or an event. Additionally, unless the relationship between different pieces of data is defined, simply data do not have any significance. Once the data are defined in terms of space or events and are defined through relationships, they become Information. Information understands the nature of the data but they do not provide the reasons behind the existence of data and are relatively static and linear by nature. Information is a relationship between data and, quite simply, is what it is, with great dependence on context for its meaning and with little implication for the future (Bellinger, 2004). Beyond every relationship, arises a pattern which has capacity to embody completeness and consistency of the relations to an extent of creating its own context (Bateson, 1979). Such patterns represent knowledge on the information and consequently on data. The term Knowledge Management has wide implications. However, very precisely Knowledge Management is about the capture and reuse of knowledge at different knowledge level. In order to access the knowledge, data are annotated and indexed in the knowledge base. This is in line to the concept proposed by Web Semantic where it proposes to annotate the document content using semantic information from domain ontologies (Berners-Lee et al., 2001). The goal is to create annotations with well-defined semantics so they can be interpreted efficiently. Today, in the context of Semantic Web, the contents of a document can be described and annotated using RDF and OWL. The result is a set of Web documents interpretable by machine with the help of mark-ups. With such Semantic Web annotation, the efficiency of information retrieval is enhanced and the interoperability is improved. The information retrieval is improved by the ability to perform searches, which exploit the ontology in order to make inferences about data from heterogeneous resources

use, evaluate and represent the knowledge of the archaeologists.

sharing remains a gap.

(Welty & Ide, 1999).

## **2.4 Towards knowledge processing**

The project ArchaeoKM plans to complement the principle of knowledge management by implementing it in the application through formulating the knowledge rules that can be used by archaeologists on the excavated data. The knowledge stored in machine readable format is inferred to bring result which could be well understood by human. Moreover, it moves beyond managing the concepts defined to annotate documents, which most of the research projects currently focusing on, to the instances of concepts with their own property values. In this manner, an object found in a point cloud can be linked, with the help of an instance in the ontology to other documents (a part in an image or a section of archive document) that contains the same object.

One of the main focuses on ArchaeoKM project is to determine an approach of integrating the spatial data within its overall framework of data integration. The integration process did not only serve for the data integration but also has taken a step forward in data analysis and management through the knowledge management techniques.
