070123 KU Knowledge representation and management (2017W)

The course will provide an in-depth treatment of one of the sub-fields from digital humanities concerning the KNOWLEDGE REPRESENTATION AND MANAGEMENT. It will contain both theoretical lessons and practical exercise providing a hands-on introduction to modelling the knowledge in humanities using computational methods.
In order to understand the evolution of data management and the importance of computational analysis in humanities the first part of the course will be dedicated to the analysis of the evolution of knowledge management in humanities ( from RDBMS to repositories) with a special focus on semantic web technologies i.e metadata, ontologies, linked data and resource discovery i.e inferences, reasoning and SPARQL syntax.
The second part will be characterized by a special focus on knowledge representation in history and archaeology. Starting from a set of digital archives or repositories during the classes will be analyzed how the knowledge can be represented in history and archaeology and how the knowledge can be enriched using the “Semantic Web Paradigm”.
The objective of the course is to provide students with a deep understanding of the possibilities and limitations of modelling and representing the knowledge and to teach them the basics of semantic knowledge management i.e mapping process, reasoning and inference, enabling them to create new knowledge environment for their own research purpose.

At the end of the course, students will be able to:

1) Understand the role of knowledge representation and conceptualization in “modern” humanities.
2)Identify and translate implicit, conceptual models (scientific hypotheses formulated in natural language) into formal explicit models i.e mappings.
3)Build an ontology using description logic formalism.
4)Visualize the knowledge graph derived from the conceptualization process.

OUTLINE

Data collection and tools Analysis of standard methods of recording cultural data; definition of the possibilities and critical aspects of the different types of data; different standards and processing of data.

Data Management In this module will be treated the different solutions and infrastructures adopted in humanities about data management i.e RDBMS, repository etc. Here will be considered the importance of preservation to ensure the authenticity, reliability and logical integrity of data, the use of open standards and open formats, metadata, and ontologies for knowledge modelling.

Search techniques and the use of data from the internet Compatibility between different infrastructures, SPARQL end-point and triple store.

Data visualisation and communication Analysis of different solutions and tools useful for knowledge visualization.