|Nombre del curso:||Semantic Knowledge engineering and Applications|
|Course Name:||Semantic Knowledge engineering and Applications|
|Profesor:||PhD. Salvatore Flavio Pileggi – The University of Queensland (Brisbane, Australia)|
|PhD. María del Pilar Villamil – Universidad de los Andes|
|Válido como:||Estudiantes MINE: Curso de Profundización|
|Estudiantes de Otras maestrías: Curso Electivo|
|Estudiantes ISIS: Electiva profesional|
- Validez del curso
- Objetivos Curriculares
- Contenido del curso
- Conocimientos previos
- Salvatore Flavio Pileggi
|Programa del DISC:||Válido por:|
|MINE||Curso de profundización|
|Otras maestrías||Curso electivo|
During the past years large-scale systems have experienced a constant evolution, addressing data ecosystems of an increasing scale and complexity. The persistent demand for advanced interoperability models has pushed the progressive development of the semantic technology. Such a technology, as the name itself suggests, aims at the specification of formal semantics that are adopted in order to give meanings to disparate raw data, information and knowledge, enabling in fact ecosystems suitable to advanced reasoning.
The core difference between the semantic technology and other data technologies, for instance the relational database, is its focus on the meaning of the data rather than on its structure only. The most relevant branch of the semantic technology is the Semantic Web technology, which uniquely identifies concepts and builds relationships among them through the Web infrastructure, enabling a global mechanism for linking data with each other.
This course is aimed at providing the principles underpinning the current Web semantic technology, as well as the skills required to enable that technology in real environments, eventually within complex systems. Bridging the gap between theory and application requires a contextual understanding of the semantic technology, in which the different aspects of knowledge and software engineering converge according to an integrated methodology.
We will establish such a methodology holistically and step-by-step, involving progressively all the assets required (languages, tools, software APIs) to build complete semantic ecosystems. An overview of the most popular applications, both with the empirical evaluation of the performance, will be an added value for the course which will end exploring the possible evolution of the semantic technology as well as some research open issues.
At the end of the course students will able to:
- Define and conceptualise data, information and knowledge adopting concept maps
- Build and process ecosystem based on linked data by using RDF /SPARQL
- Develop Ontology in OWL-DL
- Use reasoners (Jena/Pellet) to interact with semantic infrastructures: software
- Evaluate performances of Semantic Technology and design solutions accordingly
- Get familiar with the most popular applications of Web Semantics
- Understand Semantic Technology and its evolution from a research perspective
Course Structure (tentative)
Part 1: Principles of semantic knowledge engineering (5%, Laboratory: NO)
Part 2: Linked Data and Semantic Web (35-40%, Laboratory: YES)
Part 3: Ontology Engineering and Semantic Reasoning (45-50%, Laboratory: YES)
Part 4: Performance Evaluation (5%, Laboratory: YES)
Part 5: Evolution of the technology and open research issues (10%, Laboratory: NO)
Language: Spanish or English. Slides in English.
Pre-requisites: JAVA (mandatory); basic understanding of markup languages, XML for
instance (mandatory); experience in data engineering, such as relational databases
or XML databases (optional); experience on query languages, e.g. SQL/XMLPath-
Dr. Salvatore Flavio Pileggi
He is a Research Fellow in the School of Information Technology and Electrical Engineering (ITEE) at the University of Queensland (Australia). His research is currently focusing on different aspects of Computational Science and eResearch, including, among others, Knowledge Representation, Data Engineering and Analytics. Previously, after a short experience as a Software Engineer in 2007, he has held research-focused positions at top-level institutions in Spain (Polytechnic University of Valencia, 2007-2012), in New Zealand (University of Auckland, 2013-2014) and in France (INRIA & UPMCLIP6, 2014-2016). In those years he has been working across multiple research areas including (but not limitedto) Cyber-Physical Systems, Semantic Technologies and Cloud Computing. He received a M.Sc. in Computer Engineering from the University of Calabria (Italy) in 2005 and a Ph.D. (Cum Laude) in Communications from the Polytechnic University of Valencia (Spain) in 2011. He have authored/co-authored well over 40 peer-reviewed research papers, as well as he has been involved in more than 10 collaborative research projects. Extensive information and full CV available at: www.flaviopileggi.net