The Data Semantics course provides an introduction to the most challenging issues in knowledge and data representation and semantics, with particular emphasis on languages and technologies for the semantic web.
Students will learn key elements in data protection and privacy: data privacy and anonymity, metrics and techniques; macro and microdata protection; data protection in outsourcing scenarios; privacy on the web; advanced access control. Students will be involved in project activities.
After the course students will be able to design and implement an ontology and to understand, present and discuss in a critical way the most challenging issues in ontology development and in Natural Language Processing.
Traditional: frontal lessons and laboratories
Contents:
Ontology languages and tools:
Semantic Data Management:
Computational linguistic:
Ontology development:
Applications
S. Abiteboul, I. Manolescu, F. Rigaux, M.C. Roust, P. Senellart. Web Data Management. Cambridge University Press. 2011
Ricevimento: Appointment by email Office: Valle Puggia – third floor
VIVIANA MASCARDI (Presidente)
BARBARA CATANIA
GIOVANNA GUERRINI
The exam will consist in a written part (traditional open/closed questions, exercises) plus an individual project (requiring about 1 man/week to be completed).
Each student will choose her/his most preferred project type and topic: as an example, a project might consist in writing a report on issues that have not been discussed in details during the course, or developing a SW component using one of the tools studied during the course, or experimenting with some new SW library/application and reporting the results of the experimentation to the teachers in a written document. In case of SW development, a short report accompanying the developed component is required.
The acquisition of the skills foreseen by this course are assessed via the written exam + the project which have been carefully designed to allow the teachers to verify whether a student is actually able to design and implement an ontology and to understand, present and discuss in a critical way the most challenging issues in ontology development and in Natural Language Processing.
