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070123 KU Knowledge representation and management (2017W)
Continuous assessment of course work
Labels
Registration/Deregistration
- Registration is open from Fr 01.09.2017 00:00 to We 20.09.2017 12:00
- Registration is open from Mo 09.10.2017 00:00 to We 11.10.2017 12:00
- Deregistration possible until Tu 31.10.2017 23:59
Details
max. 25 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
Monday
02.10.
09:45 - 13:00
Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Monday
09.10.
09:45 - 13:00
Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Monday
16.10.
09:45 - 13:00
Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Monday
23.10.
09:45 - 13:00
Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Monday
30.10.
09:45 - 13:00
Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Monday
06.11.
09:45 - 13:00
Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Monday
13.11.
09:45 - 13:00
Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Monday
20.11.
09:45 - 13:00
Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Monday
27.11.
09:45 - 13:00
Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Monday
04.12.
09:45 - 13:00
Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Monday
11.12.
09:45 - 13:00
Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Information
Aims, contents and method of the course
Assessment and permitted materials
Course attendance and presentation of an individual or group (max 4 students) project.
Minimum requirements and assessment criteria
Examination topics
Reading list
Antoniou, G. & van Harmelen, F. (2004), A Semantic Web Primer , MIT Press .DuCharme, B. St. Laurent, S. & Perez, J., ed. (2011), Learning SPARQL .Hyvönen, E. (2012), Publishing and Using Cultural Heritage Linked Data on the Semantic Web , Morgan & Claypool PublishersRademaker, A. (2012), A Proof Theory for Description Logics. , Springer .Specific references will be indicated during the seminar.
Association in the course directory
PM4: Digital Humanities
Last modified: Mo 07.09.2020 15:30
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.OUTLINEData 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.