In these years, we co-designed and developed tools for responding to the main needs that arise during all the phases of archaeological (interdisciplinary) work. The tools we co-designed and developed so far can be categorized according to the archaeological activity that they are meant to support: excavation data management, stratigraphic analysis, 3D reconstruction of tombs, geographic analysis, and decipherment of non-verbal markings. In what follows, we present the tools following this categorization.
4.1 Excavations’ Data Management
In archeological knowledge creation and dissemination the information overload plays one of the most critical roles. At the beginning, the collaboration between the departments of Computer Science and Cultural Heritage and Environment of Università degli Studi di Milano, took the first steps towards the digitizing of their archaeological collections. Before that, the main problem was that archaeologists acquired data in manual way, without any strategies based on computer databases for storing, making future research difficult. Undocumented changes in data and loss of original organizational strategies could further compromise accessibility and integrity. Based on our experiences in research analysis, we proposed specific methods to make archaeological data management as flexible and useful as possible.
Another problem was that the large quantity of digital material generated by each team (archaeologists, architects, geologists, chemists) was incomplete, inconsistent and often hard to access. Moreover, very often, the teams are geographically distributed and the communication among all the stakeholders becomes challenging. As a possible solution to these problems, we identified a strategy based on a holistic approach for knowledge representation, designed according to widely held community understanding.
We designed and developed an application called “Tarchna DB” (See Fig. 1.) that is meant to collect the categories of evidences predetermined by the archaeologists in order to classify the multifaceted aspects of the findings that are almost always fragmentary (e.g., architectural structures, layers of ground, pottery, different kinds of equipment) . Several problems arise from the integration of different archives, and one of the most important issues is the need of establishing a common knowledge representation to be used to exchange data among all the stakeholders involved in the collaboration. Specifically, our model allows to organize archeological data in a way that is more natural for archaeologists to use. It relies on an ontology (i.e., “a description of the concepts and relationships that can exist for an agent or community of agents” [18, 19]) organized into two levels, and on specialized services for managing it. The top level of the ontology presents a view that is suitable for non-computer experts while the bottom level is suitable for interacting with the computing infrastructure. The top-level ontology exploits the concept of a standard ontology of cultural heritage (CIDOC-CRM ) for producing a representation of concepts and relationships suitable for archaeologists. The information core also supports the ability to perform information retrieval and to browse the existing knowledge. This approach uses the knowledge base as a semantic access point to the information that can then be retrieved from databases federated by means of the ontology schema. The knowledge representation model at the base of our framework uses an ontological schema, representing a specific cultural context, as a semantic access point to different types of data sources using suitable mapping strategies.
4.2 Stratigraphic Analysis
Beyond archiving, managing and studying the findings collected during archaeological excavations there is a wide research area that is focused on information visualization. The way in which the information is represented can deeply impact how it is understood and used .
In particular, in Archaeology graph visualization systems can face the problem of facilitating the exploration and analysis of a vast amount of data by means of visual methods and tools able to support needs of a wide range of different research communities involved in the study of an excavation such as archaeologists, architects, geologists, chemists, and biologists. Information visualization strategies are applied for assisting domain experts in the examination and interpretation of the stratigraphy of excavation sites, and identifying both natural and cultural strata.
The British archaeologist Edward Cecil Harris in 1973 invented the Harris Matrix method that is used to graphically represent stratigraphic sequences in a graph-based form . Before the design and development of a dedicated interactive system, Harris’ method was used to realize the graphs on paper with the following procedure.
During the excavation phase, each time that a stratigraphic unit is detected, the archaeologists filled in a proper paper form to keep track of its characteristics. A type identifies each unit: layer stratigraphic unit (US) – of natural origins – or structural stratigraphic unit (USS) – a manufactured artifact (e.g., a wall). After this first categorization, the number of the box in which the findings retrieved in the unit were recorded, together with the maximum and minimum altitude of the unit and a description of the unit itself. In the rest of the form, the relationships among the unit and other units were made explicit.
Three types of relationship could exist: active, passive, and neutral. Active relationships are (a) covers, (b) fills, (c) leans, and (d) cuts; passive relationships are (a) is covered, (b) is filled, (c) relies on, (d) is cut; neutral relationships are (a) is equal to, and (b) binds. Once the form was completely filled in, the archaeologists represent the stratigraphic unit in a drawing on paper that was then used in successive data analysis. At the end of the excavation campaign, all this material was collected and studied for creating the correspondent Harris Matrix. The resultant Harris Matrix enabled the archaeologists to determine the chronology of the various units (an example is shown in Fig. 2. The rectangles represented the stratigraphic units, while lines are used to indicate the existing relationships among them (e.g., “copre” means “covers”, “taglia” means “cuts”, “riempie” means “fills”). After the drawing was complete, the archaeologists tried to determine the historical age to which the stratigraphic units belong to. After this, the next activity is the detection of the overlays, i.e., logical levels that are constituted by the stratigraphic units that belong to the same historical period.
This entire procedure was performed using paper documents and therefore the quantity of the material related to an excavation site tended to grow very fast and its consultation became extremely difficult. Moreover, the more stratigraphic units are added, the more the Harris Matrix to be drawn became big and exponentially complicated to be modified and extended. Given these difficulties, the main disadvantages that came from the use of a non-digital approach was the impossibility of properly diffuse the knowledge that was gathered through the archaeologists’ activity performed on the field and the difficulty of keeping the Harris Matrix documents up to date. In fact, to give permissions to modify the Matrix to more than one person is not so simple, and new problems arise when many people have access and modification permission to the same resource.
Our work aimed to design and development an innovative visualization tool named ArchMatrix [6, 40] able to efficiently store and manage excavation site knowledge so that the data may be visualized and queried in a graph-based environment, and to offer a visual representation of archaeological assets and their relationships in order to support intuitive and useful explorations. To support real-world knowledge construction and decision making by means of a Harris Matrix, the most important challenge was to realize a system able to meet real needs of domain experts in handling content and structures that fit their domain-specific interests and practices. In this context, the paradigm of the map as a support for knowledge organization has been used. This is based on the principle that maps can also be used to spatially represent knowledge about systems and subjects. In fact, the Harris Matrix system uses a map-based representation to show the stratigraphic units, the relationships between them and other related information. ArchMatrix is implemented as a Web application which uses a graph visualization as tool for knowledge assessment. Through a Harris Matrix and its nodes, relationships and conceptual structure, ArchMatrix offers a solution for collaborative managing shared knowledge among experts of different domains. A screenshot of ArchMatrix is given in Fig. 3.
4.3 3D Reconstruction of Tombs
During the last decade, Virtual Reality (VR) technologies have been the focus of intense developments and applications, mainly because of the increased availability of dedicated cheaper hardware platforms and display technologies. These are some of the domains with respect to which VR techniques have an important potential for the deployment and manipulation of 3D materials, images, sounds, and datasets in order to provide a richer and visually-appealing content presentations. Consider as an example the Archaeological domain. Using VR techniques, heritage which no longer exists, or which must be handled with special care in order to be preserved, can be virtually reconstructed and presented to an audience from perspectives which go beyond what it is possible in the real world. Not only, VR can be used to provide innovative strategies for studying and analyzing features of existing monuments or ancient populations, or for visiting and exploring collections, which elements are physically located at different museums or cultural institutions, and so forth. Although those solutions are very appealing and today many museums and cultural institutions have started investing in such direction, VR solutions are still not widely adopted as a mean for archaeological study and dissemination. The main reason is the high cost of content production and the low reusability and poor portability of infrastructures. In addition, researchers and users are quite sophisticated and have high expectations; therefore, they are not interested in simple walk-through applications. Instead, they ask for formative and interactive experiences that they can personalize on the basis of their preferences.
We adopted this innovative strategy in the field of the VR applied at the Archaeology in the design of the virtual reality simulation of the Etruscan Necropolis of Tarquinia (UNESCO site since 2004) that has been realized not only for dissemination purpose but also for supporting archaeological analysis . The site is an outstanding testimonial of the Etruscan culture, in which so far more than 6200 tombs carved in the rock were discovered. Among them, around 140 are extraordinarily painted, and many hundreds more present traces of paintings . The earliest tomb dates from the 7th century B.C. Most of them are constituted by a room only, while others are more articulated. Currently, 64 tombs are accessible: some of them are protected by glass and always visible, some others are open for visits in rotation, whereas many others are kept closed. Most of the painted tombs were discovered in the second half of 19th century. Across the centuries, many paintings were detached from the walls and then lost or destroyed, while others are currently not visible due to the fading of the original colors. In these cases, our knowledge of those paintings is mainly based on descriptions and paintings made by artists and scholars in 17th, 18th, and 19th centuries. Cultural Heritage experts rely in a relevant way on digital images acquired inside the tombs: natural light is not present (or it is limited to some parts of a small number of tombs whose entrances are adequately oriented), while artificial light is often not adequate to achieve a full and detailed observation of the full painted walls. Therefore, many samples of each area that compose the inner parts of the tombs are collected through several accurate sessions of photographic acquisition. The images are then processed to enhance details, merged using adequate techniques in order to allow an ensemble analysis of the painted walls, and eventually stored in a multimedia database for supplemental studies and for dissemination.
3D models allow to investigate the morphology of the architecture in its completeness and to analyze all the parts of the architecture in detail and as a whole. The VR reconstruction of the Necropolis is based on a modular approach, in order to handle a site composed by a large number of independent tombs. The 3D visualization of the tombs is based on a first-person point of view approach, and the users can rotate their view and eventually move inside the environments. Moreover, we have introduced the possibility to visualize the already mentioned drawings and paintings as superimposed on the original walls (See Fig. 4).
4.4 Geographic Analysis
Over the last two centuries, several more or less scientific archaeological and restoration projects have been carried out, and their merits and defects are still visible today. Given the complexity, the extent and the prolonged use of an excavation site, researchers need innovative tools for deeper understanding the site and for comparison with archaeological sites in the vicinity. Three-dimensional tools are useful solutions for facilitating the investigation of the sites in their landscape setting, for example on a large scale, exploiting the possibilities offered by LiDAR  (Light Detection and Ranging) survey. The cartographic results thus obtained can be used as metrically correct basis for the positioning of all the archaeological sites, thus enabling their comparison and analysis. Precisely because of the prolonged use of sites and their extent, the creation of reconstructive models can be crucial for our understanding and dissemination of the results to non-specialist as well as professional audiences.
A LiDAR survey, by means of an aerial recognition, has been carried out in the area of the Civita of Tarquinia in 2010 (see Fig. 5). The Figure shows how it is possible to pre-process the LIDAR image on the left for identifying buildings/structures, terrain skin, and vegetation, in order to identify only archaeological evidences such as ruins, territorial presence/absence, candidate archaeological items (LIDAR image on the right).
The application of laser scanning and LiDAR technology in an archaeological environment has rapidly established abroad and recently in Italy.
The first output of the aerial survey appears as a dense cloud of points (defined by planimetric coordinates, elevations, intensity, number of returns and other parameters) arranged along the scanning pattern of the instrument. From such raw data, it is possible to reconstruct the territorial conformation and the related elements (vegetation, ground, structures, etc.…). Subsequent digital processing produces different elaborations: Digital Elevation Model (DEM), Digital Terrain Model (DTM), high-resolution orthophotos, and elaborations based on intensity and number of returns. These elaborations are recorded in a Geographical Information System to catalog and to systematize the existing documentation about historical cartography and scientific and literary information, in order to grasp persistence and consistence of meaningful traces of the ancient territorial occupation. Therefore, an exhaustive georeferenced documentation, gathered in a diachronic and synchronic atlas endowed with each punctual or areal data, is available in order to compare and contrast the palimpsest of settlement. After the analysis, through the use of metric models previously created, a 2D-3D cartographic archive is improved to permit the geo-referenced localization of every data set on the territory, giving the possibility to interface information through a shared platform. Such work results useful tools to identify and analyze settlements and to assess cause-effect relationship between their architectural and urbanistic features and the terrain morphology. The GIS cartographic database, with all its interfaces (geological, historical, archaeological), makes it possible to read permanent signs and assess the land use in historical cartography.
4.5 Non-verbal Markings Collaborative Decipherment
In the frame of IESP (International Etruscan Sigla) Project, we co-designed and developed a system aimed at supporting the collaborative decipherment of Etruscan sigla (non-verbal markings) found on objects discovered in different digging sites distributed in the Mediterranean area. The project involved archaeologists from Università degli Studi di Milano and Florida State University, giving us the possibility of studying the two different approaches to archaeological practice, both in terms of methodology and terminology used. A screenshot of IESP system is given in Fig. 6.
Unlike what happens in deciphering verbal languages, in the case of non-verbal signs it is possible to study their elements from a graphical point of view and to apply similarity techniques to support the human interpretation activity. As to Etruscan language, thousands of examples of non-verbal markings exist. Typically, they are referred to as graffiti, a term that is found to be inadequate. Instead, the Latin word siglum (pl. sigla) – corresponding to the Greek one sema (pl. semata) – should be used. Etruscan sigla, composed by one or more symbols, numbers or letters, are dated from around 700 BCE to the first century BCE. They are incised, painted or stamped on different types of objects; e.g., pottery weights, spindle whorls, sarcophagi, burial urns, roof tiles, architectural terracotta, boundary stones, stone walls, and a wide variety of artefacts in bronze (axes, fibulas, helmets, knives, razors, sickles). The contexts in which the objects have been found include cemeteries, sanctuaries, ports, artisans’ quarters and habitations – all spheres of Etruscan life and afterlife. The study of Etruscan sigla is aimed at assessing the real consistency of archaeological indicators according to a deductive method that takes into account a dialectic comparison between the ideas of function and role [2, 20]. The function of an object could be in fact be deduced by its shape. On the other hand, the role of the same kind of object can be determined differently on the basis of the conditions of their discovery and from the comparison of iconographic sources. This means that the meaning of sigla can change widely according to the context in which they have been discovered. An example is the case of V-shape siglum that can be interpreted as a number 5 or letter U. The same uncertainty exists in interpreting a siglum formed by a cross inscribed in a circle: it could mean the Greek letter theta or could be the graphic representation of a sacred space [1, 4]. The experience we developed in the frame of IESP Project led to the design and development of an approach and its software implementation for:
Analyzing cases of recurrent sigla as cultural indicators of non-verbal communication within their different archaeological contexts.
Supporting questions about function and role in the field of sigla and according to a multifaceted perspective that takes into account archaeological data to a larger extent.
The main goal of the approach and the final system is to assess sigla with reference to their geographical range and chronology, to the nature of the objects and contexts to which they belong and to the layout of the graphic design. The enormous amount of data, the variety of the cultural background of archaeological experts involved the wide span of different hypotheses about the interpretation of each siglum type and their relationships led to the design of a tool that supports collaborative activities and dialectic comparisons. In our case, the goal is to interpret the meaning of non-verbal markings by means of the comparison of images, the sharing of descriptions, and the collaborative contribution by whole interdisciplinary team.