060084 UE Basics of data management in archaeology (2019W)

Practically any archaeological work produces (large quantities of) different types of data. To archive, reuse, understand and interpret the collected data, a well-thought data management system is necessary. This course focuses on the theory and practical implementation of the main stages of this process from data modelling, data retrieval, and data archival.
The first part introduces the different data types and management systems usually applied in archaeology. The students will learn how to properly store archaeological data with special attention given to tabular data, controlled vocabularies and guidance on how to omit data redundancy. It discusses applications with different questions and addresses the needs of different data types, e.g. for quantitative analyses and spatial operations.
Afterwards, the issue of necessary metadata to document this process for ensuring data reusability will be addressed. Because archaeologists often have to work with existing data that might not comply with best practice and do, therefore, not allow for functional data retrieval, this introduction will also cover practical advice on how to work with and clean such data.
In the next stage, students will create a relational database. First, they will learn how to design a data model suitable for the specific nature of archaeological data and how such a model affects the process of data retrieval. Second, they will learn how to compose simple queries to gain information from the designed database. In a further step, the special data type and model necessities for spatial data are explained and presented using examples.
In the last part of this lecture series, ontologies will be introduced. Using the example of the CIDOC Conceptual Reference Model for cultural heritage, it will be shown how an ontology differs from a database, what are its advantages, limits and technical possibilities.
Besides a variety of different theoretical concepts, this course will provide students with a basic but practical knowledge of working with OpenRefine, Microsoft Excel and Access and simple geospatial file types to be imported into a Geographic Information System.