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RELATIONAL DATABASE MANAGEMENT SYSTEM FOR THE EARLY METALLURGY OF COPPER AND BRONZE IN TRANSYLVANIA, ROMANIA Manuella Kadar1, Valentin Bucur 1, Emilian Ceuca1 “1 Decembrie 1918” University of Alba Iulia, Department of Mathematics- Computer Science Nicolae Iorga street 11-13, 2500 Alba Iulia [email protected], [email protected], [email protected] Abstract. In order to approach the problems of bronze metallurgy in their full complexity, we have considered that the design of a relational database management system is required. Regarding the database design we have given a special attention to the problems concerning the relational model and the query system of the database in order to obtain complex reports. This application is designed to be a fundamental tool for organizing and developing a complex archaeological study. Thus, the database has a bibliographical collection, a collection of properties, a geological distribution with image facilities, an archaeological repertoire, etc. The metal finds belonging to Neolithic, Eneolithic and Early Bronze Age cultures of Transylvania have been classified, on the bases of metallographic analyses and chemical composition. Typological classification of artefacts is correlated with the results obtained by analytical methods, in order to discuss the provenience of raw materials, the metalworking techniques in this region, and their relationships to other early metallurgical centers from Central and South-Eastern Europe. An interdisciplinary, methodological approach has been adopted, which uses the latest analytical techniques, integrating various methodological and theoretical means of design, dissemination and validation. Keywords; relational database, copper, bronze, metallurgy, Transylvania, chemical composition, metallographic analyses INTRODUCTION DESIGN AND MODELING This application has been designed as a tool serving an interdisciplinary project focused on the early metallurgy of copper and bronze in Transylvania. Situated within the Carpathian Arch, Transylvania is important for its natural resources and strategic geographical position starting from prehistoric times. Design was based on the traditional theory consisting of three steps: analysis, design and implementation. The conceptual model, which is independent of the target technology has been created in the first phase, then the logical data model and the physical model are ready for implementation. Starting from the relational model the physical implementation had to fulfill some performance requirements imposed by index configuration, data placement, storage allocation, space optimization. The theory of the independent metallurgical canters which were developed in the Balkans versus the origins of metallurgy in the Near East and its spread through intensive cultural exchanges from Anatolia or from the Aegean area is the key issue discussed in this project. Our analyses would like to complement the analyses of metal artifacts from Serbia, Bulgaria, Greece and Anatolia in order to be provide a basis for the interregional comparisons. Reconstruction of production and exchange systems in Eneolithic and Bronze Age Europe and the identification of geological sources for raw materials available in Eneolithic and Bronze Age are the questions to be answered by this study. Typological classifications of artefacts correlated with classifications based on chemical composition and microstructure analyses provide key information on the specific features of metalworking techniques in this region and comparison with other early metallurgical centres from Central and South- Eastern Europe. A data warehouse has been created by using the basic principles of data modelling and database design, including new techniques of dimensional data modelling (star schema) and normalized dimension tables (snowflake schemas) have been introduced to support design. One of the most important problems for the implementation of RDBMS (Relational Database Management System) is the selection of indexes. An index that improves data retrieval performance may degrade performance for all kinds of updates, because the maintenance cost for the index has to be paid for each update. Selecting the optimal indexes for a given set of tables (an index configuration) is a laborious process that requires trade-offs between the different kinds of database operations (retrieval operations, update transactions, and utilities). Given an index, one must determine its properties, such as the column ordering for multi-column indexes, and whether or not the index should be clustered, or partitioned ordered. Space optimisation had to be taken into account when designing relational databases. Allocating enough space to maintain the clustering properties, without wasting too much space along index selection and data placement provide the structural stability of the relational model. The relational model is presented in figure 1. Figure 1. Relationships Considering the advantages of the star schema for dimensional modelling (e.g. easy to understand; hierarchies are easy to define; one can reduce the number of physical table joins; low maintenance; the meta data is very simple) the method has been used in this application. Some goals we have kept in mind were: • • • • To maintain data at the conceptual level To transform a valid, complete model to a relational design To design an optimal database To reuse data definitions or relational designs. As general design methodology an interdisciplinary approach has been adopted that uses the latest analytical techniques and integrates various methods of assessment such as artificial neural networks in statistics. The database is designed as a support for organizing and developing of this archaeometallurgical study. Artefacts are considered in their complex archaeological and social context in order to describe as accurately as possible the technological level of the communities who have created those artefacts. Some of the features we have taken into consideration with regard the design of the database were: • Detailed, accurate, up to date documentation of the metallic artefacts • • • • Easy access, processing and filtering of data, facilitating research in the field of human culture and development of technology Objective storage of data, enabling all interested researchers to get acquainted with it and with various interpretations made by scholars Interpretative observations resulted from the subjective view of the individual researcher, such as cultural or functional attributes, have been entered into special fields labelled ”Notes” in order to provide maximum level of objectivity. Connections to other reference databases and bibliography has been provided in order to offer all the existing information on a specific issue. DATABASE STRUCTURE The database was created in Access 2000 which provides userfriendly programming, easy upgradability, and the likelihood of continued upgrades in the future. The base is still in the experimental phases and it has been tested on three counties of Transylvania: Alba, Hunedoara and Cluj. The main access frame is a clickable map representing all counties from Romania, being active within the Carpathian Arch.A language option has been implemented in order to make the information available to foreign researchers as well (figure 2). All tables are presented both in English and Romanian and searching is available in both languages. Figure 2. Main interface of the database A central concern in creating the interface was to create a simple clean set of forms which give access to a complex set of tables. Data entry could have been achieved only through a “high level“ knowledge of the database system and a more in depth knowledge of archaeological recording systems. This restricted the casual user but meant that data entry became more of an intelligent process required in creating archaeological archives. The documentation system starts with a General Form comprising all the scannings and measurable data with special fields for personal observation and interpretation. General data about place and type of storage, general description of the piece can be seen in the main form. Within the main form one can choose links to other sub-forms in order to get a more comprehensive information. These sub-forms are presenting the archaeological data, technological data, metallographic data , chemical composition, micro-radiography and micro-photography, general and specific bibliography connected with each sub-form. Archaeological data includes information on the excavation, site description, location of finds, circumstances of the unearthing, horizontal and vertical stratigraphy, cultural attribution and fields for observations and bibliography. Technological data refers to functional attributions, macrostructural examination, technological and ornamental description, signs of wear, various possible treatments to which the objects has been submitted after its recovery, state of preservation, etc. This description include also dimensional characterization, type of material and photograph of the object, drawings (figure 3). Metallographic data presents the identification of the microstructure and methods of investigation applied to each object. Comparisons with previous analyses achieved by other research teams are available. This sub-form is connected with a collection of digital images representing different magnifications of the microstructure. Chemical composition includes various methods of investigation, which have been applied to each object. Results are available in tables and comparisons between methods applied during the last centuries in order to investigate the composition of early metallic objects are provided in the observations and notes section (figure 4). The search in the database is possible on two levels, through the commands FIND and FILTER. FIND has been applied to the graphical search connected to the map showing counties and localities where artefacts have been discovered. In each chosen locality from the map, a list of artefacts will appear on the right side of the window, allowing the user to obtain more complete information in a printable report. FILTER command is working similarly but with the facility of filtering data using one or more criteria. The criteria options for filtering that are included in the main starting frame are: historical period, locality, object’s name, object’s category, object’s type, type of material, type of archaeological site. Figure 3. Technical description of the artefact Figure 4. Chemical composition sub-form FUTURE DEVELOPMENT Systematic construction of the data base in a powerful relational structure seems to be the key issue for usability and modifiability in the future. We are continuing to invest considerable effort and student training in developing this database and to extend it to other regions of Romania, as well. Another direction of development will be the implementation of a three-dimensional reconstruction of sites with all features consisted in, by using data on the elevations. After the testing and monitoring of this archaeometallurgical database will be finalized, we intend to inter-link it with other independent bases and archives in a graphic environment set up on the INTERNET in order to permit access to various levels of research and to increase the consulting and management possibility with regard to the cultural heritage of Romania.